This paper was converted on www.awesomepapers.org from LaTeX by an anonymous user.
Want to know more? Visit the Converter page.

Toric non-archimedean μ\mu-entropy and thermodynamical structure

Eiji Inoue RIKEN, iTHEMS, 2-1 Hirosawa, Wako, Saitama, 351-0198, Japan [email protected]
Abstract.

We study non-archimedean μ\mu-entropy for toric variety as a further exploration of μ\muK-stability. We show the existence of optimizer of toric non-archimedean μλ\mu^{\lambda}-entropy for λ\lambda\in\mathbb{R} and the uniqueness for λ0\lambda\leq 0. For the proof of existence, we establish a Rellich type compactness result for convex functions on simple polytope. We also reveal a thermodynamical structure on toric non-archimedean μ\mu-entropy. This observation allows us to interpret the enigmatic parameter T=λ2πT=-\frac{\lambda}{2\pi} as temperature and non-archimedean μ\mu-entropy as entropy of an infinite dimensional composite system.

1. Introduction

1.1. Main Results on existence

Canonical metric and K-stability are primary interests in Kähler geometry. There is a series of studies [21, 22, 23, 24, 25] exploring these topics from a unique perspective which motivates a minimization problem we study in this article. Compared to the general case [25], the problem in the toric case we discuss here can be described in a quite simple way by convex functions on convex polytope, for which we only need a few things to prepare. It would be simpler to begin with our convex setup and main existence result of this article, and explain its esoteric background and motivation for the problem afterwards.

1.1.1. Setup

We prepare some terminologies convenient for our arguments. Let VV be an nn-dimensional affine space over \mathbb{R}. A half space of VV is a subset of the form 1([0,))\ell^{-1}([0,\infty)) for some non-zero affine function :V\ell:V\to\mathbb{R}. The face of a half space 1([0,))\ell^{-1}([0,\infty)) is the hyperplane 1(0)\ell^{-1}(0).

We call a subset PVP\subset V a polytope if it is a compact subset with non-empty interior and can be expressed as the intersection of finitely many half spaces. A subset FPF\subset P is called a face of PP if it is the intersection of PP and the face of a half space which contains PP. A face is again a polytope of a lower dimensional affine subspace WVW\subset V. The relative interior of a face is the interior in such WW. A facet of PP is a face of PP which gives a polytope of a codimension one affine subspace. A vertex of PP is a face of PP with one element. A simple polytope is a polytope for which every vertex can be written as the intersection of precisely nn-facets. In this article, we restrict our main interest to simple polytopes. In toric geometry, such (rational) polytopes represent toric orbifolds.

It is well-known that a complete parallel translation invariant measure on VV (with the usual σ\sigma-algebra) which puts positive finite mass on relatively compact open sets is a constant multiple of the Lebesgue measure under an affine identification VnV\cong\mathbb{R}^{n}. A flat measure on a polytope (resp. a face of a polytope) is the restriction of such translation invariant measure on VV (resp. such measure on the affine subspace WW which contains the face as a polytope). We note the topological boundary P=PP\partial P=P\setminus P^{\circ} is the union of facets. A flat measure on P\partial P is a measure whose restriction to each facet is flat.

For a polytope PP and p1p\geq 1, we consider the following spaces:

(1.1) NAexp,p(P)\displaystyle\mathcal{E}_{\mathrm{NA}}^{\exp,p}(P) :={ lsc convex q:P(,]|Pepq𝑑μ<},\displaystyle:=\{\text{ lsc convex }q:P\to(-\infty,\infty]~{}|~{}\int_{P}e^{pq}d\mu<\infty\},
(1.2) NAexp,p(P)\displaystyle\mathcal{M}_{\mathrm{NA}}^{\exp,p}(P) :={ lsc lc u:P(0,]|Pu𝑑μ=P𝑑μ,Pup𝑑μ<},\displaystyle:=\{\text{ lsc lc }u:P\to(0,\infty]~{}|~{}\int_{P}ud\mu=\int_{P}d\mu,\int_{P}u^{p}d\mu<\infty\},

which are independent of the choice of the flat measure dμd\mu on PP. Here lsc lc is short for lower semi-continuous log convex. Namely, we have lim infu(xi)u(x)\liminf u(x_{i})\geq u(x_{\infty}) for xixPx_{i}\to x_{\infty}\in P and u((1t)x0+tx1)u1t(x0)ut(x1)u((1-t)x_{0}+tx_{1})\leq u^{1-t}(x_{0})u^{t}(x_{1}). For two lsc convex functions q,qq,q^{\prime}, the condition q=qq=q^{\prime} almost everywhere with respect to dμd\mu is equivalent to the condition q=qq=q^{\prime} everywhere. In particular, the boundary value q|Pq|_{\partial P} can be recovered from interior values q|Pq|_{P^{\circ}}.

We endow NAexp,p(P)\mathcal{M}_{\mathrm{NA}}^{\exp,p}(P) with the LpL^{p}-topology and call its element (nonequilibrium) state. For qNAexp,p(P)q\in\mathcal{E}_{\mathrm{NA}}^{\exp,p}(P), we can assign a state

(1.3) u(q):=P𝑑μPeq𝑑μeqNAexp,p(P).\displaystyle u(q):=\frac{\int_{P}d\mu}{\int_{P}e^{q}d\mu}e^{q}\in\mathcal{M}_{\mathrm{NA}}^{\exp,p}(P).

For qNAexp,1(P)q\in\mathcal{E}_{\mathrm{NA}}^{\exp,1}(P), we have qNAexp,p(P)q\in\mathcal{E}_{\mathrm{NA}}^{\exp,p}(P) if and only if u(q)NAexp,p(P)u(q)\in\mathcal{M}_{\mathrm{NA}}^{\exp,p}(P). Later we explain a Kähler geometric background of the space NAexp,p(P)\mathcal{E}_{\mathrm{NA}}^{\exp,p}(P).

Now let us consider a triple 𝒫=(P,dμ,dσ)\mathcal{P}=(P,d\mu,d\sigma) of a simple polytope PP, a flat measure dμd\mu on PP and a flat measure dσd\sigma on P\partial P, which we call a simple non-archimedean Hamiltonian system or just a system. When we refer to 𝒫\mathcal{P} with general non-simple polytope PP, we call it a general system.

For uNAexp,1(P)u\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(P), we introduce

(1.4) S𝒫(u)\displaystyle S_{\mathcal{P}}(u) :=1P𝑑μPulogudμ[,0],\displaystyle:=-\frac{1}{\int_{P}d\mu}\int_{P}u\log ud\mu\in[-\infty,0],
(1.5) U𝒫(u)\displaystyle U_{\mathcal{P}}(u) :=1P𝑑μPu𝑑σ(0,],\displaystyle:=\frac{1}{\int_{P}d\mu}\int_{\partial P}ud\sigma\in(0,\infty],

which we call the (nonequilibrium) entropy and (non-archimedean nonequilibrium) internal μ\mu-energy, respectively. For TT\in\mathbb{R}, which we call temperature, we further introduce

(1.6) F𝒫(T,u):={U𝒫(u)TS𝒫(u)S𝒫(u)>S𝒫(u)=.\displaystyle F_{\mathcal{P}}(T,u):=\begin{cases}U_{\mathcal{P}}(u)-TS_{\mathcal{P}}(u)&S_{\mathcal{P}}(u)>-\infty\\ \infty&S_{\mathcal{P}}(u)=-\infty\end{cases}.

We call this functional (non-archimedean nonequilibrium) free μ\mu-energy. We will see S𝒫(u)=S_{\mathcal{P}}(u)=-\infty implies U𝒫(u)=U_{\mathcal{P}}(u)=\infty and this definition makes the functional F𝒫(T,u(q))F_{\mathcal{P}}(T,u(q)) continuous along increasing sequence qiqq_{i}\nearrow q. As we explain later, there is a Kähler geometric background for these functionals.

In section 4, we newly unveil there is a stochastic thermodynamical interpretation of these functionals, which gives us a strong motivation to our terminologies of thermodynamical flavor. We note some references (cf. [3]) in the same field use similar terminologies like entropy and free energy, but these are not directly related to ours. We are mostly interested in K-unstable case, while the reference focuses on K-stable case.

1.1.2. Main results

Now we state our main result. Its output to Kähler geometry is explained later.

Theorem 1.1.

Let 𝒫=(P,dμ,dσ)\mathcal{P}=(P,d\mu,d\sigma) be an nn-dimensional system. Then for every TT\in\mathbb{R}, there exists uNAexp,nn1(P)u\in\mathcal{M}_{\mathrm{NA}}^{\exp,\frac{n}{n-1}}(P) which minimizes F𝒫(T,):NAexp,1(P)(,]F_{\mathcal{P}}(T,\bullet):\mathcal{M}_{\mathrm{NA}}^{\exp,1}(P)\to(-\infty,\infty].

Moreover,

  1. (1)

    (Uniqueness) if T>0T>0, minimizer of F𝒫(T,)F_{\mathcal{P}}(T,\bullet) is unique.

  2. (2)

    (Conditional uniqueness) if T=0T=0, there exists a unique minimizer of F𝒫(0,)=U𝒫()F_{\mathcal{P}}(0,\bullet)=U_{\mathcal{P}}(\bullet) which maximizes S𝒫S_{\mathcal{P}} among all minimizers.

  3. (3)

    (Regularity) if T=0T=0 and n=2n=2, any minimizer of F𝒫(0,)=U𝒫()F_{\mathcal{P}}(0,\bullet)=U_{\mathcal{P}}(\bullet) is bounded and continuous.

We call the unique minimizer in the above (1) and (2) the μ\mu-canonical distribution of temperature TT. In Kähler geometric context, q=loguNAexp,1(P)q=\log u\in\mathcal{E}_{\mathrm{NA}}^{\exp,1}(P) is also called the optimizer or optimal destabilizer of 𝝁ˇNAλ\bm{\check{\mu}}_{\mathrm{NA}}^{\lambda}.

This main theorem summarizes Theorem 3.3, Theorem 3.5 and Theorem 3.18. To show the existence, we establish the following compactness result, which is proved in section 2.2. The proof works not only for lsc lc functions but for general non-negative convex functions.

Theorem 1.2.

Let {ui:P[0,]}i\{u_{i}:P\to[0,\infty]\}_{i\in\mathbb{N}} be a sequence of non-negative convex functions with a uniform bound

Pui𝑑σC.\int_{\partial P}u_{i}d\sigma\leq C.

Then all uiu_{i} are in Lnn1(P)L^{\frac{n}{n-1}}(P) and after taking a subsequence, there exists a unique non-negative lsc convex function u:P[0,]u:P\to[0,\infty] in Lnn1(P)L^{\frac{n}{n-1}}(P) such that uiu_{i} converges to uu in LpL^{p}-topology for every p[0,nn1)p\in[0,\frac{n}{n-1}).

Remark 1.3.

The above theorem is reminiscent of Rellich’s compactness theorem. It is well-known by Sobolev embedding and trace theorem that we have

L1(P)|PW1,1(P)Lnn1(P),L^{1}(\partial P)\xleftarrow{|_{\partial P}}W^{1,1}(P)\hookrightarrow L^{\frac{n}{n-1}}(P),

while what we prove is

Conv(P)L1(P)Lnn1(P).\mathrm{Conv}(P)\cap L^{1}(\partial P)\subset L^{\frac{n}{n-1}}(P).

It is natural to expect Conv(P)L1(P)=Conv(P)W1,1(P)\mathrm{Conv}(P)\cap L^{1}(\partial P)=\mathrm{Conv}(P)\cap W^{1,1}(P), but we do not pursue it in this article.

As an interest in Kähler geometry, we also prove the following. It summarizes Theorem 3.11 and Theorem 3.13. We explain terminologies in the next section.

Theorem 1.4.

Let (X,L)T(X,L)\circlearrowleft T be a toric variety and 𝒫\mathcal{P} be the associated system we explain later. Let |ξ:P:μμ,ξ\ket{\xi}:P\to\mathbb{R}:\mu\mapsto\langle\mu,\xi\rangle denote the linear map associated to ξ𝔱\xi\in\mathfrak{t}. For T0T\geq 0, we have the following.

  • The toric variety (X,L)(X,L) is toric μξ2πT\mu^{-2\pi T}_{\xi}K-semistable if and only if u=u(|ξ)u=u(\ket{\xi}) minimizes F𝒫(T,)F_{\mathcal{P}}(T,\bullet).

  • If a toric manifold (X,L)(X,L) admits a μξ2πT\mu^{-2\pi T}_{\xi}-cscK metric with ξLie(Tcpt)\xi\in\mathrm{Lie}(T_{\mathrm{cpt}}), then u=u(|ξ)u=u(\ket{\xi}) is the μ\mu-canonical distribution of temperature TT.

We further prove some results in section 4 motivated by thermodynamics, using our existence result. To appreciate the results, we must recall the origin of μ\mu-cscK metric and the enigmatic way our parameter TT is introduced in the theory. We explain these in section 4. Though we present our main result as the existence and uniqueness of minimizer for the free μ\mu-energy F𝒫(T,)F_{\mathcal{P}}(T,\bullet), the observation in section 4 would be much deeper. It should be explored further in future study.

1.2. Why does it matter in Kähler geometry?

1.2.1. Toric variety and polytope

Let T𝔾m×nT\cong\mathbb{G}_{m}^{\times n} be an algebraic torus and TcptTT_{\mathrm{cpt}}\subset T be the maximal compact torus. For the character lattice M=Hom(T,𝔾m)=Hom(Tcpt,U(1))M=\mathrm{Hom}(T,\mathbb{G}_{m})=\mathrm{Hom}(T_{\mathrm{cpt}},U(1)), we put 𝔱:=M\mathfrak{t}^{\vee}:=M\otimes_{\mathbb{Z}}\mathbb{R}. We denote the dual vector space by 𝔱\mathfrak{t} and identify it with the Lie algebra of TcptT_{\mathrm{cpt}}.

Ler (X,L)T(X,L)\circlearrowleft T be a polarized toric variety of dimension nn. As usual in toric geometry, we assign a general system 𝒫=(P,dμ,dσ)\mathcal{P}=(P,d\mu,d\sigma) as follows. We put

(1.7) P=Conv({μM|H0(X,L)μ0})𝔱.\displaystyle P=\mathrm{Conv}(\{\mu\in M~{}|~{}H^{0}(X,L)_{\mu}\neq 0\})\subset\mathfrak{t}^{\vee}.

Here H0(X,L)μH^{0}(X,L)_{\mu} denotes the eigenspace {sH0(X,L)|s.t=μ(t)stT}\{s\in H^{0}(X,L)~{}|~{}s.t=\mu(t)s~{}\forall t\in T\}. The lattice MM defines a unique flat measure on 𝔱\mathfrak{t}^{\vee} by setting μ(B(m1,,mn))=1\mu(B(m_{1},\ldots,m_{n}))=1 for the box

B(m1,,mn)={i=1mtimi|0ti1}B(m_{1},\ldots,m_{n})=\{\sum_{i=1}^{m}t_{i}m_{i}~{}|~{}0\leq t_{i}\leq 1\}

generated by a \mathbb{Z}-basis m1,,mnMm_{1},\ldots,m_{n}\in M. Since |detA|=1|\det A|=1 for AGL(M)A\in GL(M), the flat measure is independent of the choice of m1,,mnm_{1},\ldots,m_{n}. We denote its restriction to PP by dμd\mu. On the other hand, since the affine subspace W𝔱W\subset\mathfrak{t}^{\vee} spanned by a facet QQ of PP is a rational subspace, the intersection WMW\cap M gives a lattice spanning WW. Then we similarly define a unique flat measure on each facet QQ compatible with the lattice WMW\cap M and a flat measure dσd\sigma on P\partial P.

The flat measure dσd\sigma on P\partial P represents the anti-canonical divisor KX-K_{X}. In general, flat signed measures on P\partial P are in one to one correspondence with TT-invariant \mathbb{R}-Weil divisors: each facet QPQ\subset\partial P represents a TT-invariant prime divisor EQE_{Q} and a flat signed measure dσd\sigma^{\prime} on P\partial P represents the divisor Qdσ(Q)dσ(Q)EQ\sum_{Q}\frac{d\sigma^{\prime}(Q)}{d\sigma(Q)}E_{Q}. For the flat signed measure dσd\sigma^{\prime} representing a TT-invariant \mathbb{R}-Weil divisor Δ=QaQEQ\Delta=\sum_{Q}a_{Q}E_{Q} on XX, we put

(1.8) dσΔ:=dσdσ=Q(1aQ)dσ,\displaystyle d\sigma_{\Delta}:=d\sigma-d\sigma^{\prime}=\sum_{Q}(1-a_{Q})d\sigma,

which represents the \mathbb{R}-divisor (KX+Δ)-(K_{X}+\Delta). From thermodynamical perspective, the measure dσd\sigma plays the role of Hamiltonian of the system and its variation can be interpreted as thermodynamical work.

A triple (X,Δ,L)(X,\Delta,L) of a toric variety XX, a TT-invariant \mathbb{R}-divisor Δ\Delta with coefficient aQ[0,1)a_{Q}\in[0,1) and a TT-equivariant polarization LL is called a polarized log toric variety. By the above construction, we can assign a general system 𝒫=(P,dμ,dσΔ)\mathcal{P}=(P,d\mu,d\sigma_{\Delta}) for a polarized log toric variety.

The associated polytope PP is known to be simple if and only if XX has at most orbifold singularity. See [13, Theorem 3.1.19].

1.2.2. μ\mu-cscK metric

Let XX be a compact Kähler manifold and LH2(X,)L\in H^{2}(X,\mathbb{R}) be a Kähler class. We consider a pair (ω,f)(\omega,f) of a Kähler metric (form) ω\omega in LL and a smooth real valued function ff on XX. For λ\lambda\in\mathbb{R}, a pair (ω,f)(\omega,f) is called μλ\mu^{\lambda}-cscK metric if it satisfies the following two conditions:

  1. (1)

    The complex vector field ωf=gij¯f,j¯i\partial^{\sharp}_{\omega}f=g^{i\bar{j}}f_{,\bar{j}}\partial_{i} is holomorphic.

  2. (2)

    The μλ\mu^{\lambda}-scalar curvature sλ(ω,f):=s(ω)+Δωf|ωf|2λfs^{\lambda}(\omega,f):=s(\omega)+\Delta_{\omega}f-|\partial_{\omega}^{\sharp}f|^{2}-\lambda f is constant.

When the imaginary part ξ=2Imωf\xi=-2\mathrm{Im}\partial^{\sharp}_{\omega}f is specified, we call the metric ω\omega μξλ\mu^{\lambda}_{\xi}-cscK metric. Since iξω=2Imiωfω=2Img(Jωf,)=dfi_{\xi}\omega=-2\mathrm{Im}i_{\partial^{\sharp}_{\omega}f}\omega=-2\mathrm{Im}g(J\partial^{\sharp}_{\omega}f,\cdot)=-df, ff is the Hamiltonian potential of ξ\xi. The imaginary part ξ\xi preserves the metric gg, so it is a Killing vector field. This implies we can always take a closed torus TcptT_{\mathrm{cpt}} acting on (X,L)(X,L) so that ξ𝔱=Lie(Tcpt)\xi\in\mathfrak{t}=\mathrm{Lie}(T_{\mathrm{cpt}}). We note there is a subtle but an important difference between μλ\mu^{\lambda}-cscK metric and μξλ\mu^{\lambda}_{\xi}-cscK metric: when we refer to μλ\mu^{\lambda}-cscK metric, the vector ξ\xi is not fixed.

Remark 1.5.

The above definition of μξλ\mu^{\lambda}_{\xi}-cscK metric is equivalent to what we call μˇξλ1{{}^{1}\check{\mu}}^{\lambda}_{\xi}-cscK metric in [23].

The notion unifies two frameworks of canonical metrics: constant scalar curvature Kähler (cscK) metric and Kähler–Ricci soliton. Indeed, when XX is a Fano manifold (i.e. the anti-canonical class KX=c1(X)-K_{X}=c_{1}(X) is positive), a Kähler metric ω\omega in the anti-canonical Kähler class T1KXT^{-1}K_{X} (T<0T<0) is μ2πT\mu^{-2\pi T}-cscK metric if and only if it is Kähler–Ricci soliton: Ric(ω)fω=2πTω\mathrm{Ric}(\omega)-\mathscr{L}_{\partial^{\sharp}f}\omega=-2\pi T\omega. Kähler–Ricci soliton is defined only for Fano manifolds due to the a priori constraint

2πλ[ω]=[Ric(ω)fω]=2πc1(X),2\pi\lambda[\omega]=[\mathrm{Ric}(\omega)-\mathscr{L}_{\partial^{\sharp}f}\omega]=2\pi c_{1}(X),

while μλ\mu^{\lambda}-cscK metric makes sense for general polarized manifold.

A fundamental question on μλ\mu^{\lambda}-cscK metric is the existence and uniqueness modulo translation by automorphisms. When we fix ξ\xi, the theory of μξλ\mu^{\lambda}_{\xi}-cscK metric is enclosed in the theory of weighted cscK metric. It is then proved by [28] that μξλ\mu^{\lambda}_{\xi}-cscK metric is unique modulo translation by aumorphisms preserving ξ\xi. As for the uniqueness of μλ\mu^{\lambda}-cscK metric, we must show the uniqueness of ξ\xi (modulo translation) which admits a μξλ\mu^{\lambda}_{\xi}-cscK metric. We confirm this uniqueness for toric manifolds with λ0\lambda\leq 0.

Theorem 1.6.

Assume λ0\lambda\leq 0. On a toric manifold, μλ\mu^{\lambda}-cscK metrics are unique modulo the action of automorphism group.

On the other hand, fixing ξ\xi, the existence of μξλ\mu^{\lambda}_{\xi}-cscK metric implies an algebro-geometric condition of (X,L)(X,L) called μξλ\mu^{\lambda}_{\xi}K-stability.

1.2.3. μ\muK-stability

The notion can be defined for general polarized scheme, but here for simplicity we only explain a toric version of the notion. It can be simply described in terms of convex functions.

Definition 1.7 (Toric μ\muK-stability).

Let (X,Δ,L)T(X,\Delta,L)\circlearrowleft T be a polarized log toric variety and 𝒫=(P,dμ,dσΔ)\mathcal{P}=(P,d\mu,d\sigma_{\Delta}) be the associated general system.

Let qq be a rational piecewise affine convex function on PP. Namely, qq is of the form q=maxi=1,,miq=\max_{i=1,\ldots,m}\ell_{i} for finitely many rational affine function i\ell_{i} on 𝔱=M\mathfrak{t}^{\vee}=M\otimes_{\mathbb{Z}}\mathbb{R}. Then for λ\lambda\in\mathbb{R} and ξ𝔱=Lie(Tcpt)\xi\in\mathfrak{t}=\mathrm{Lie}(T_{\mathrm{cpt}}), we define the μξλ\mu^{\lambda}_{\xi}-Futaki invariant Futξλ(q)\mathrm{Fut}^{\lambda}_{\xi}(q) by

(1.9) Futξλ(q)\displaystyle\mathrm{Fut}^{\lambda}_{\xi}(q) :=2πPqe|ξ𝑑σΔλPq|ξe|ξ𝑑μPe|ξ𝑑μs¯ξλPqe|ξ𝑑μPe|ξ𝑑μ,\displaystyle:=\frac{2\pi\int_{\partial P}qe^{\ket{\xi}}d\sigma_{\Delta}-\lambda\int_{P}q\ket{\xi}e^{\ket{\xi}}d\mu}{\int_{P}e^{\ket{\xi}}d\mu}-\bar{s}^{\lambda}_{\xi}\frac{\int_{P}qe^{\ket{\xi}}d\mu}{\int_{P}e^{\ket{\xi}}d\mu},

using the linear map |ξ:P:μμ,ξ\ket{\xi}:P\to\mathbb{R}:\mu\mapsto\langle\mu,\xi\rangle. Here we put

s¯ξλ:=2πPe|ξ𝑑σΔλP|ξe|ξ𝑑μPe|ξ𝑑μ.\bar{s}^{\lambda}_{\xi}:=\frac{2\pi\int_{\partial P}e^{\ket{\xi}}d\sigma_{\Delta}-\lambda\int_{P}\ket{\xi}e^{\ket{\xi}}d\mu}{\int_{P}e^{\ket{\xi}}d\mu}.

We call (X,Δ,L)(X,\Delta,L) toric μξλ\mu^{\lambda}_{\xi}K-semistable if Futξλ(q)0\mathrm{Fut}^{\lambda}_{\xi}(q)\geq 0 for every rational piecewise affine function qq and toric μξλ\mu^{\lambda}_{\xi}K-polystable if moreover Futξλ(q)>0\mathrm{Fut}^{\lambda}_{\xi}(q)>0 for non-affine qq.

Remark 1.8.

The above definition of μξλ\mu^{\lambda}_{\xi}-Futaki invariant is equivalent to what we call μˇξλ1{{}^{1}\check{\mu}}^{\lambda}_{\xi}-Futaki invariant in [23]. Using the Cartan model of equivariant cohomology as in [22, 23], we can check

s¯ξλ=Xsξλ(ω)eμξvolωXeμξvolω\bar{s}^{\lambda}_{\xi}=\frac{\int_{X}s^{\lambda}_{\xi}(\omega)e^{\mu_{\xi}}\mathrm{vol}_{\omega}}{\int_{X}e^{\mu_{\xi}}\mathrm{vol}_{\omega}}

for volω=ωn/n!\mathrm{vol}_{\omega}=\omega^{n}/n!. For q=|ηq=\ket{\eta}, we have

Futξλ(|η)=X(sξλ(ω)s¯ξλ)μηeμξvolωXeμξvolω.\mathrm{Fut}^{\lambda}_{\xi}(\ket{\eta})=\frac{\int_{X}(s^{\lambda}_{\xi}(\omega)-\bar{s}^{\lambda}_{\xi})\mu_{\eta}e^{\mu_{\xi}}\mathrm{vol}_{\omega}}{\int_{X}e^{\mu_{\xi}}\mathrm{vol}_{\omega}}.

When ξ=0\xi=0, the invariant is independent of λ\lambda:

(1.10) DF(q):=Fut0λ(q)=2πP𝑑μ(Pq𝑑σΔP𝑑σΔP𝑑μPq𝑑μ)\displaystyle\mathrm{DF}(q):=\mathrm{Fut}^{\lambda}_{0}(q)=\frac{2\pi}{\int_{P}d\mu}(\int_{\partial P}qd\sigma_{\Delta}-\frac{\int_{\partial P}d\sigma_{\Delta}}{\int_{P}d\mu}\int_{P}qd\mu)

It is called the Donaldson–Futaki invariant.

We note the μξλ\mu^{\lambda}_{\xi}-Futaki invariant is well-defined for general integrable convex function qq on general system 𝒫\mathcal{P}. For a set 𝒬\mathcal{Q} of convex functions, we call 𝒫\mathcal{P} toric μξλ\mu^{\lambda}_{\xi}K-semistable (resp. μξλ\mu^{\lambda}_{\xi}K-polystable) with respect to 𝒬\mathcal{Q} if Futξλ(q)0\mathrm{Fut}^{\lambda}_{\xi}(q)\geq 0 for every q𝒬q\in\mathcal{Q} (resp. if further Futξλ(q)>0\mathrm{Fut}^{\lambda}_{\xi}(q)>0 for non-affine qq). We call 𝒫\mathcal{P} K-unstable if it is not μ0\mu_{0}K-semistable. We note even if XX is K-unstable, it may be μξλ\mu^{\lambda}_{\xi}K-semistable with respect to some λ\lambda and non-trivial ξ0\xi\neq 0.

Remark 1.9.

We define μξλ\mu^{\lambda}_{\xi}K-stability by rational piecewise affine convex functions because these convex functions correspond to toric test configurations. A (compactified ample) toric test configuration is a T×𝔾mT\times\mathbb{G}_{m}-equivariant flat family of polarized schemes (𝒳¯,¯)(\bar{\mathcal{X}},\bar{\mathcal{L}}) over 1\mathbb{P}^{1} which is endowed with a T×𝔾mT\times\mathbb{G}_{m}-equivariant isomorphism from X×𝔸1X\times\mathbb{A}^{1} to 𝒳¯𝒳0\bar{\mathcal{X}}\setminus\mathcal{X}_{0} over 𝔸1=1{(0:1)}:w=(1:w)\mathbb{A}^{1}=\mathbb{P}^{1}\setminus\{(0:1)\}:w=(1:w). Here T×𝔾mT\times\mathbb{G}_{m} acts on 1\mathbb{P}^{1} by (z:w).(t,u)=(uz:w)(z:w).(t,u)=(uz:w) and ¯\bar{\mathcal{L}} is an ample \mathbb{Q}-line bundle over 𝒳¯\bar{\mathcal{X}}. We may assume 𝒳¯\bar{\mathcal{X}} is normal for our interest. Since (𝒳¯,¯)T×𝔾m(\bar{\mathcal{X}},\bar{\mathcal{L}})\circlearrowleft T\times\mathbb{G}_{m} is an n+1n+1-dimensional polarized toric variety, we can consider the associated polytope Q𝔱×Q\subset\mathfrak{t}^{\vee}\times\mathbb{R}. We can show the polytope QQ can be written as Q={(x,τ)|xP,0τq(x)}Q=\{(x,\tau)~{}|~{}x\in P,~{}0\leq\tau\leq-q(x)\} using a convex function qq on PP. Since QQ is a rational polytope, qq is rational piecewise affine convex function.

For a polarized variety (X,L)(X,L), we denote by NA(X,L)\mathcal{H}_{\mathrm{NA}}(X,L) the set of all (not necessarily TT-equivariant) test configurations of (X,L)(X,L). Similarly for a rational polytope PP, we denote by NA(P)\mathcal{H}_{\mathrm{NA}}(P) the set of all rational piecewise affine convex functions on PP. Convex functions in NA(P)\mathcal{H}_{\mathrm{NA}}(P) represent TT-equivariant test configurations, which form a proper subset NAT(X,L)NA(X,L)\mathcal{H}_{\mathrm{NA}}^{T}(X,L)\subset\mathcal{H}_{\mathrm{NA}}(X,L). We note every lower semi-continuous convex function qq has an increasing net qiNA(P)q_{i}\in\mathcal{H}_{\mathrm{NA}}(P) which pointwisely converges to qq, thanks to Fenchel–Moreau theorem.

By the result of [1] (see also [27, 23]), it is known that a polarized manifold (X,L)(X,L) is μξλ\mu^{\lambda}_{\xi}K-polystable if it admits a μξλ\mu^{\lambda}_{\xi}-cscK metric. When ξ=0\xi=0, the case of cscK metric, it is also known that a uniform version of toric K-polystability implies the existence of cscK metric for toric manifold by [19, 10, 29]. As far as the author knows, this implication for general ξ0\xi\neq 0 is still unkown. It is natural to expect the same method for ξ=0\xi=0 would work. For general polarized manifold, it is still a conjecture even for cscK metric, which is known as YTD conjecture, but recently there are great progress (cf. [9, 29, 30, 7]). We do not pursue this direction in this article as we are rather interested in K-instability.

1.2.4. Perelman entropy

Now we return to μ\mu-cscK metric. Originally, μ\mu-cscK metric is introduced in [22] based on a moment map picture on Kähler–Ricci soliton observed in [21]. The moment map picture heuristically explains why the existence of μξλ\mu^{\lambda}_{\xi}-cscK metric is related to μξλ\mu^{\lambda}_{\xi}K-stability and moduli problem, so this perspective is important in stability aspect. We review this later in order to explain how the parameter λ\lambda appears.

On the other hand, it turns out later in [24] that μλ\mu^{\lambda}-cscK metric is also characterized by Perelman’s entropy. This perspective illuminates “instability aspect” of the theory of μ\mu-cscK metric and μ\muK-stability, which is the main interest of this article.

Now we introduce Perelman’s functionals. For a Kähler metric ω\omega and a real valued function ff normalized as Xefvolω=Xvolω\int_{X}e^{f}\mathrm{vol}_{\omega}=\int_{X}\mathrm{vol}_{\omega} for volω:=ωn/n!\mathrm{vol}_{\omega}:=\omega^{n}/n!, we put

(1.11) 𝒲λ(ω,f)\displaystyle\mathcal{W}^{\lambda}(\omega,f) :=1XvolωX(s(ω)+|ωf|2λf)efvolωλlogXenvolω,\displaystyle:=-\frac{1}{\int_{X}\mathrm{vol}_{\omega}}\int_{X}(s(\omega)+|\partial_{\omega}^{\sharp}f|^{2}-\lambda f)e^{f}\mathrm{vol}_{\omega}-\lambda\log\int_{X}e^{-n}\mathrm{vol}_{\omega},
(1.12) 𝝁Perλ(ω)\displaystyle\bm{\mu}^{\lambda}_{\mathrm{Per}}(\omega) :=supf𝒲λ(ω,f),\displaystyle:=\sup_{f}\mathcal{W}^{\lambda}(\omega,f),

which we call Perelman’s 𝒲\mathcal{W}-entropy and μ\mu-entropy, respectively. We note the above convention differs from Perelman’s original one by sign and multiplication of constants, which is off course not essential. Perelman considered general Riemannian metric for 𝒲λ\mathcal{W}^{\lambda}, but we restrict our interest to Kähler metric in the context of μλ\mu^{\lambda}-cscK metric, which is in turn essential for our variational result.

It is proved in [24] that we can characterize μλ\mu^{\lambda}-cscK metrics (ω,f)(\omega,f) as the critical points of 𝒲λ\mathcal{W}^{\lambda}. We note here we must restrict metrics to the space (X,L)\mathcal{H}(X,L) of Kähler metrics in LL. Moreover, for λ0\lambda\leq 0, we can also characterize ω\omega of μλ\mu^{\lambda}-cscK metrics (ω,f)(\omega,f) as minimizers of 𝝁Perλ\bm{\mu}^{\lambda}_{\mathrm{Per}}. This characterization is nice as our differential geometric interest is in the metric ω\omega and not so much in the function ff or the vector field ξ=2Imωf\xi=-2\mathrm{Im}\partial_{\omega}f.

Recall we fix vector ξ\xi to define μξλ\mu^{\lambda}_{\xi}K-stability, while now we have a vector-free characterization of μλ\mu^{\lambda}-cscK metric. To match up, it is better to have an algebro-geometric criterion for ξ\xi which tells if (X,L)(X,L) could be μξλ\mu^{\lambda}_{\xi}K-semistable. However, in general, there may be no such vector. In such case, we are interested in finding “most destabilizing qq” in a suitable sense. It is revealed in [25] that the nature of these two questions are actually the same. We can formalize and solve both questions in terms of toric non-archimedean μ\mu-entropy, which is essentially the functional F𝒫(T,)F_{\mathcal{P}}(T,\bullet) in our main theorem.

1.2.5. Toric non-archimedean μ\mu-entropy

Let 𝒫\mathcal{P} be the general system associated to a polarized toric variety (X,L)(X,L). For a lsc convex function qNAexp,1(P)q\in\mathcal{E}_{\mathrm{NA}}^{\exp,1}(P), we put

(1.13) 𝝈(q)\displaystyle\bm{\sigma}(q) :=P(n+q)eq𝑑μPeq𝑑μlogPeq𝑑μ,\displaystyle:=\frac{\int_{P}(n+q)e^{q}d\mu}{\int_{P}e^{q}d\mu}-\log\int_{P}e^{q}d\mu,
(1.14) 𝝁ˇNA(q)\displaystyle\bm{\check{\mu}}_{\mathrm{NA}}(q) :=2πPeq𝑑σPeq𝑑μ.\displaystyle:=-2\pi\frac{\int_{\partial P}e^{q}d\sigma}{\int_{P}e^{q}d\mu}.

For λ\lambda\in\mathbb{R}, we consider

(1.15) 𝝁ˇNAλ(q):={𝝁ˇNA(q)+λ𝝈(q)𝝈(q)<𝝈(q)=\displaystyle\bm{\check{\mu}}_{\mathrm{NA}}^{\lambda}(q):=\begin{cases}\bm{\check{\mu}}_{\mathrm{NA}}(q)+\lambda\bm{\sigma}(q)&\bm{\sigma}(q)<\infty\\ -\infty&\bm{\sigma}(q)=\infty\end{cases}

and call it the toric non-archimedean μ\mu-entropy.

These are essentially the functionals we already introduced:

𝝁ˇNA(q)\displaystyle\bm{\check{\mu}}_{\mathrm{NA}}(q) =2πU𝒫(u(q)),\displaystyle=-2\pi U_{\mathcal{P}}(u(q)),
𝝈(q)\displaystyle\bm{\sigma}(q) =S𝒫(u(q))logPen𝑑μ,\displaystyle=-S_{\mathcal{P}}(u(q))-\log\int_{P}e^{-n}d\mu,
𝝁ˇNAλ(q)\displaystyle\bm{\check{\mu}}_{\mathrm{NA}}^{\lambda}(q) =2πF𝒫(λ2π,u(q))λlogPen𝑑μ.\displaystyle=-2\pi F_{\mathcal{P}}(-\frac{\lambda}{2\pi},u(q))-\lambda\log\int_{P}e^{-n}d\mu.

The differential of toric non-archimedean μ\mu-entropy 𝝁ˇNAλ\bm{\check{\mu}}_{\mathrm{NA}}^{\lambda} gives the minus of μξλ\mu^{\lambda}_{\xi}-Futaki invariant:

(1.16) ddt|t=0𝝁ˇNAλ(|ξ+tq)=Futξλ(q).\displaystyle\frac{d}{dt}\Big{|}_{t=0}\bm{\check{\mu}}_{\mathrm{NA}}^{\lambda}(\ket{\xi}+tq)=-\mathrm{Fut}^{\lambda}_{\xi}(q).

This implies that if 𝝁ˇNAλ\bm{\check{\mu}}_{\mathrm{NA}}^{\lambda} is maximized at a vector |ξ\ket{\xi}, then (X,L)(X,L) is toric μξλ\mu^{\lambda}_{\xi}K-semistable.

It is proved in [24] that there is an inequality between 𝝁ˇNAλ\bm{\check{\mu}}_{\mathrm{NA}}^{\lambda} and 𝝁Perλ\bm{\mu}_{\mathrm{Per}}^{\lambda} for λ\lambda\in\mathbb{R}:

(1.17) supqNA(X,L)𝝁ˇNAλ(q)infω(X,L)𝝁Perλ(ω).\displaystyle\sup_{q\in\mathcal{H}_{\mathrm{NA}}(X,L)}\bm{\check{\mu}}_{\mathrm{NA}}^{\lambda}(q)\leq\inf_{\omega\in\mathcal{H}(X,L)}\bm{\mu}_{\mathrm{Per}}^{\lambda}(\omega).

Moreover if λ0\lambda\leq 0 and there exists a μξλ\mu^{\lambda}_{\xi}-cscK metric ω\omega, then the above equality is achieved by 𝝁ˇNAλ(|ξ)=𝝁Perλ(ω)\bm{\check{\mu}}_{\mathrm{NA}}^{\lambda}(\ket{\xi})=\bm{\mu}_{\mathrm{Per}}^{\lambda}(\omega). This implies if there exists a μξλ\mu^{\lambda}_{\xi}-cscK metric for λ0\lambda\leq 0, then |ξ\ket{\xi} maximizes 𝝁ˇNAλ\bm{\check{\mu}}_{\mathrm{NA}}^{\lambda}, which in particular gives another proof for the μξλ\mu^{\lambda}_{\xi}K-semistability of μξλ\mu^{\lambda}_{\xi}-cscK manifold with λ0\lambda\leq 0. It is conjectured the equality holds for λ0\lambda\leq 0 even when there is no μλ\mu^{\lambda}-cscK metric.

The non-archimedean μ\mu-entropy 𝝁ˇNAλ\bm{\check{\mu}}_{\mathrm{NA}}^{\lambda} is essentially introduced in [23] for qNA(P)q\in\mathcal{H}_{\mathrm{NA}}(P) and more generally for a test configuration (𝒳,)NA(X,L)(\mathcal{X},\mathcal{L})\in\mathcal{H}_{\mathrm{NA}}(X,L) of a non-toric polarized variety (X,L)(X,L). The paper [25] introduces a completion NAexp(X,L)\mathcal{E}_{\mathrm{NA}}^{\exp}(X,L) of the space NA(X,L)\mathcal{H}_{\mathrm{NA}}(X,L) of test configuraitons in terms of non-archimedean pluripotential theory developed in [5]. The space NAexp(X,L)\mathcal{E}_{\mathrm{NA}}^{\exp}(X,L) consists of functions on the Berkovich analytification of XX, which is the reason for the word “non-archimedean”. In the toric setup, the TT-invariant part of the space NAexp(X,L)\mathcal{E}_{\mathrm{NA}}^{\exp}(X,L) corresponds to the intersection p1NAexp,p(P)\bigcap_{p\geq 1}\mathcal{E}_{\mathrm{NA}}^{\exp,p}(P). It takes considerable pages to extend the non-archimedean μ\mu-entropy to NAexp(X,L)\mathcal{E}_{\mathrm{NA}}^{\exp}(X,L) as an upper semi-continuous functional, which in our toric case turns extremely easy to show. In the toric case, 𝝁ˇNAλ(q)\bm{\check{\mu}}_{\mathrm{NA}}^{\lambda}(q) is continuous along increasing sequence by the monotone convergence theorem, so we may replace supqNA(X,L)𝝁ˇNAλ(q)\sup_{q\in\mathcal{H}_{\mathrm{NA}}(X,L)}\bm{\check{\mu}}_{\mathrm{NA}}^{\lambda}(q) in (1.17) with supqNAexp,1(P)𝝁ˇNAλ(q)\sup_{q\in\mathcal{E}_{\mathrm{NA}}^{\exp,1}(P)}\bm{\check{\mu}}_{\mathrm{NA}}^{\lambda}(q).

Theorem 1.1 confirms that there always exists a maximizer qNAexp,nn1(P)q\in\mathcal{E}_{\mathrm{NA}}^{\exp,\frac{n}{n-1}}(P) of 𝝁ˇNAλ\bm{\check{\mu}}_{\mathrm{NA}}^{\lambda}, even when the toric variety (X,L)(X,L) is μλ\mu^{\lambda}K-unstable. If qq is a bounded convex function, we can assign a filtration q=φq\mathcal{F}_{q}=\mathcal{F}_{\varphi_{q}} on the graded ring R(X,L)=mH0(X,Lm)R(X,L)=\bigoplus_{m}H^{0}(X,L^{\otimes m}) as in [25]. If further the filtration is finitely generated, which is the case for instance when qNA(P)q\in\mathcal{H}_{\mathrm{NA}}(P), it produces an algebro-geometric degeneration (𝒳,)/Bσ(\mathcal{X},\mathcal{L})/B_{\sigma} of (X,L)(X,L) called polyhedral configuration in [25]. Then we can show that the central fibre (𝒳0,0)(\mathcal{X}_{0},\mathcal{L}_{0}) of such degeneration is μξλ\mu^{\lambda}_{\xi}K-semistable with respect to the vector ξ\xi generated by the degeneration. See [25] for further detail.

1.2.6. Other works in the same spirit

One ultimate goal of our study is to construct a degeneration of μ\muK-unstable polarized variety to a μ\muK-semistable “space” (see Remark 3.17), which is often referred to as optimal degeneration. The non-archimedean μ\mu-entropy is not the unique quantity measuring K-instability. We briefly review other works on K-instability as reference.

\bullet Optimal degeneration in the context of Kähler–Ricci soliton

The first pioneering work on optimal degeneration in the context of Kähler–Ricci soliton on Fano manifold would be Chen–Wang’s work [12]. They constructed a metric geometric degeneration along Kähler–Ricci flow. Chen–Sun–Wang [11] gives an algebro-geometric description of the degeneration, in which the idea of using filtration and two step degeneration is utilized. Dervan–Székelyhidi [14] introduced a quantity called HH-invariant and showed Chen–Sun–Wang’s filtration minimizes the HH-invariant. Han–Li [18] pursued an algebro-geometric aspect of HH-invariant and proved the uniqueness of Chen–Sun–Wang’s degeneration. Finally, Blum–Liu–Xu–Zhuang [4] constructed Chen–Sun–Wang’s degeneration in a purely algebro-geometric way, which allows them to extend the result to Fano variety with singularity. It is known by Wang–Zhu’s work [34] that every toric Fano manifold admits Kähler–Ricci soliton. This result can also be regarded as the explicit description of optimizer in toric case: the optimizer for HH-invariant is given by the vector associated to Kähler–Ricci soliton. In [25], it turns out that the non-archimedean μ\mu-entropy also characterizes Chen–Sun–Wang’s degeneration.

\bullet Optimal degeneration in the context of extremal metric

Optimal degeneration problem of polarized variety would be firstly considered by Donaldson [16] in the context of extremal metric. The quantity for K-instability in this context is called normalized Donaldson–Futaki invariant. In toric case, Székelyhidi [33] proved the existence of optimal destabilizing L2L^{2}-integrable convex function. Xia [35] pursued the problem from pluripotential theoretic perspective and proved the existence of an optimal destabilizing geodesic ray in a suitable completion 2(X,L)\mathcal{E}^{2}(X,L) of the space of Kähler metrics. It turns out by Li’s analysis [29] that the geodesic ray can be interpreted as a non-archimedean metric. Compared to Kähler–Ricci soliton, much less is known on the regularity of optimal destabilizer. We speculate this context can be treated as the limit λ\lambda\to-\infty of our framework.

\bullet Optimal degeneration in the context of Mabuchi soliton:

Optimal destabilization problem for Mabuchi soliton would be firstly considered by Hisamoto [20]. The quantity for K-instability in this context is called normalized Ding invariant. In toric case, Yao [36] constructed an optimal destabilizing convex function for normalized Ding invariant. He also proved the crucial regularity result: the optimizer is piecewise affine. This is much better than the current knowledge on the optimizer for normalized Donaldson–Futaki invariant and non-archimedean μ\mu-entropy.

\bullet Still many other works…

There are still many other works on optimal degeneration. Among all, the structure of the above three frameworks is closest to that of our framework. For instance, we have Donaldson type inequality (cf. [16, 14, 20, 35, 24]) which can be interpreted as minimax theorem on some functional (cf. [24, 25]). Thus here we do not give further comments on those other works in the context of δ\delta-invariant and the normalized volume.

Acknowledgments

This work is supported by RIKEN iTHEMS Program. We used Wolfram Mathematica to create some graphs.

2. Convex analysis on simple polytope

2.1. Local estimates

Here we prepare some estimates we use in the next section.

2.1.1. Mean value estimate

Proposition 2.1.

Let u:i=1n[ai,bi][0,]u:\prod_{i=1}^{n}[a_{i},b_{i}]\to[0,\infty] be a convex function. Then we have

u(x)i=1n[ai,bi]u𝑑𝒙1i=1nmin{xiai,bixi}u(x)\leq\int_{\prod_{i=1}^{n}[a_{i},b_{i}]}ud\bm{x}\cdot\frac{1}{\prod_{i=1}^{n}\min\{x_{i}-a_{i},b_{i}-x_{i}\}}

for every xi=1n[ai,bi]x\in\prod_{i=1}^{n}[a_{i},b_{i}]. Here d𝒙d\bm{x} denotes the nn-dimensional Lebesgue measure.

Proof.

The claim is trivial if xi=aix_{i}=a_{i} or xi=bix_{i}=b_{i} for some ii. By supporting hyperplane theorem, for xi=1n(ai,bi)x\in\prod_{i=1}^{n}(a_{i},b_{i}), we can take an affine function x(y)=i=1nxi(yixi)+h\ell_{x}(y)=\sum_{i=1}^{n}\ell^{i}_{x}(y_{i}-x_{i})+h so that xu\ell_{x}\leq u on i=1n[ai,bi]\prod_{i=1}^{n}[a_{i},b_{i}] and x(x)=h=u(x)\ell_{x}(x)=h=u(x). If we put

i:={[ai,xi]xi<0[xi,bi]xi0,\Box_{i}:=\begin{cases}[a_{i},x_{i}]&\ell_{x}^{i}<0\\ [x_{i},b_{i}]&\ell^{i}_{x}\geq 0\end{cases},

we have xu(x)\ell_{x}\geq u(x) on i=1nii=1n[ai,bi]\prod_{i=1}^{n}\Box_{i}\subset\prod_{i=1}^{n}[a_{i},b_{i}]. Since uu is non-negative, we have umax{x,0}u\geq\max\{\ell_{x},0\}, so that

i=1n[ai,bi]u𝑑𝒙i=1n[ai,bi]max{x,0}𝑑𝒙i=1ni𝑑𝒙u(x).\int_{\prod_{i=1}^{n}[a_{i},b_{i}]}ud\bm{x}\geq\int_{\prod_{i=1}^{n}[a_{i},b_{i}]}\max\{\ell_{x},0\}d\bm{x}\geq\int_{\prod_{i=1}^{n}\Box_{i}}d\bm{x}\cdot u(x).

Thus we get

u(x)i=1n[ai,bi]u𝑑𝒙1i=1nvoli.u(x)\leq\int_{\prod_{i=1}^{n}[a_{i},b_{i}]}ud\bm{x}\cdot\frac{1}{\prod_{i=1}^{n}\mathrm{vol}\Box_{i}}.

Since volimin{xiai,bixi}\mathrm{vol}\Box_{i}\geq\min\{x_{i}-a_{i},b_{i}-x_{i}\}, we get the desired inequality. ∎

We put

(2.1) Δpn(r):={x[0,)p×(r,r)np|i=1pxi<r}.\displaystyle\Delta^{n}_{p}(r):=\{x\in[0,\infty)^{p}\times(-r,r)^{n-p}~{}|~{}\sum_{i=1}^{p}x_{i}<r\}.
Corollary 2.2.

Let u:Δpn(r)[0,]u:\Delta^{n}_{p}(r)\to[0,\infty] be a convex function. For 12rr<r\frac{1}{2}r\leq r^{\prime}<r and for every xΔpn(r)x\in\Delta^{n}_{p}(r^{\prime}), we have

u(x)(r)p(rr)nΔpn(r)u𝑑𝒙1i=1pxi.u(x)\leq\frac{(r^{\prime})^{p}}{(r-r^{\prime})^{n}}\int_{\Delta^{n}_{p}(r)}ud\bm{x}\cdot\frac{1}{\prod_{i=1}^{p}x_{i}}.
Proof.

For xΔpn(r)x\in\Delta^{n}_{p}(r^{\prime}), we have B(x):=i=1p[0,rrxi]×j=p+1n(r,r)Δpn(r)B(x):=\prod_{i=1}^{p}[0,\frac{r}{r^{\prime}}x_{i}]\times\prod_{j=p+1}^{n}(-r,r)\subset\Delta^{n}_{p}(r), so that

u(x)\displaystyle u(x) B(x)u𝑑𝒙1i=1pmin{xi,(rr1)xi}(rr)np\displaystyle\leq\int_{B(x)}ud\bm{x}\cdot\frac{1}{\prod_{i=1}^{p}\min\{x_{i},(\frac{r}{r^{\prime}}-1)x_{i}\}\cdot(r-r^{\prime})^{n-p}}
(r)p(rr)nΔpn(r)u𝑑𝒙1i=1pxi\displaystyle\leq\frac{(r^{\prime})^{p}}{(r-r^{\prime})^{n}}\int_{\Delta^{n}_{p}(r)}ud\bm{x}\cdot\frac{1}{\prod_{i=1}^{p}x_{i}}

by the above proposition. Here we note min{xi,(rr1)xi}=1r(rr)xi\min\{x_{i},(\frac{r}{r^{\prime}}-1)x_{i}\}=\frac{1}{r^{\prime}}(r-r^{\prime})x_{i} when 12rr\frac{1}{2}r\leq r^{\prime}. ∎

2.1.2. Boundary mean value estimate

For i=1,,pi=1,\ldots,p, we put

(2.2) iΔpn(r):={xΔpn(r)|xi=0}Δp1n1(r)\displaystyle\partial_{i}\Delta^{n}_{p}(r):=\{x\in\Delta^{n}_{p}(r)~{}|~{}x_{i}=0\}\cong\Delta^{n-1}_{p-1}(r)

and consider the (n1)(n-1)-dimensional Lebesgue measure d𝒙d\bm{x}^{\prime}.

Proposition 2.3.

Suppose p2p\geq 2. Let u:Δpn(r)[0,]u:\Delta^{n}_{p}(r)\to[0,\infty] be a convex function. Then for ij{1,,p}i\neq j\in\{1,\ldots,p\}, we have

(r2)npu(x)iΔpn(r)u𝑑𝒙xj(xi+xj)2ki,jxk+jΔpn(r)u𝑑𝒙xi(xi+xj)2ki,jxk\Big{(}\frac{r}{2}\Big{)}^{n-p}u(x)\leq\int_{\partial_{i}\Delta^{n}_{p}(r)}ud\bm{x}^{\prime}\cdot\frac{x_{j}}{(x_{i}+x_{j})^{2}\prod_{k\neq i,j}x_{k}}+\int_{\partial_{j}\Delta^{n}_{p}(r)}ud\bm{x}^{\prime}\cdot\frac{x_{i}}{(x_{i}+x_{j})^{2}\prod_{k\neq i,j}x_{k}}

for every xΔpn(r2)x\in\Delta^{n}_{p}(\frac{r}{2}). Here kk in \prod runs over 1,,p1,\ldots,p, excluding i,ji,j.

Proof.

The claim is trivial on {xi=xj=0}\{x_{i}=x_{j}=0\}. We assume (xi,xj)(0,0)(x_{i},x_{j})\neq(0,0). For

𝒙i\displaystyle\bm{x}^{i} :=(x1,,xi1,xi+xj,xi+1,,xj1,0,xj+1,,xn)iΔpn(r),\displaystyle:=(x_{1},\ldots,x_{i-1},x_{i}+x_{j},x_{i+1},\ldots,x_{j-1},0,x_{j+1},\ldots,x_{n})\in\partial_{i}\Delta^{n}_{p}(r),
𝒙j\displaystyle\bm{x}^{j} :=(x1,,xi1,0,xi+1,,xj1,xi+xj,xj+1,,xn)jΔpn(r),\displaystyle:=(x_{1},\ldots,x_{i-1},0,x_{i+1},\ldots,x_{j-1},x_{i}+x_{j},x_{j+1},\ldots,x_{n})\in\partial_{j}\Delta^{n}_{p}(r),

we have

(x1,,xn)=xixi+xj𝒙j+xjxi+xj𝒙i.(x_{1},\ldots,x_{n})=\frac{x_{i}}{x_{i}+x_{j}}\bm{x}^{j}+\frac{x_{j}}{x_{i}+x_{j}}\bm{x}^{i}.

Then by convexity,

u(x)xixi+xju(𝒙j)+xjxi+xju(𝒙i).u(x)\leq\frac{x_{i}}{x_{i}+x_{j}}u(\bm{x}^{j})+\frac{x_{j}}{x_{i}+x_{j}}u(\bm{x}^{i}).

When xΔpn(r2)x\in\Delta^{n}_{p}(\frac{r}{2}), we have 𝒙iiΔpn(r2)Δp1n1(r2)\bm{x}^{i}\in\partial_{i}\Delta^{n}_{p}(\frac{r}{2})\cong\Delta^{n-1}_{p-1}(\frac{r}{2}), so that the claim follows by Corollary 2.2 applied to u(𝒙i),u(𝒙j)u(\bm{x}^{i}),u(\bm{x}^{j}) on Δp1n1(r2)\Delta^{n-1}_{p-1}(\frac{r}{2}). ∎

Corollary 2.4.

Suppose p2p\geq 2. There exists a function U:Δpn(r)[0,]U:\Delta^{n}_{p}(r)\to[0,\infty] such that ULq(Δpn(r))U\in L^{q}(\Delta^{n}_{p}(r)) for every q[1,pp1)q\in[1,\frac{p}{p-1}) and

u(x)i=1piΔpn(r)u𝑑𝒙U(x)u(x)\leq\sum_{i=1}^{p}\int_{\partial_{i}\Delta^{n}_{p}(r)}ud\bm{x}^{\prime}\cdot U(x)

for every convex function u:Δpn(r)[0,]u:\Delta^{n}_{p}(r)\to[0,\infty] and xΔpn(r2)x\in\Delta^{n}_{p}(\frac{r}{2}).

Proof.

By the above proposition, we have

u(x)(2r)npi=1piΔpn(r)u𝑑𝒙min{1(xi+xj)ki,jxk|ij{1,,p}}.u(x)\leq\Big{(}\frac{2}{r}\Big{)}^{n-p}\sum_{i=1}^{p}\int_{\partial_{i}\Delta^{n}_{p}(r)}ud\bm{x}^{\prime}\cdot\min\Big{\{}\frac{1}{(x_{i}+x_{j})\prod_{k\neq i,j}x_{k}}~{}\Big{|}~{}i\neq j\in\{1,\ldots,p\}\Big{\}}.

Here kk in \prod runs over 1,,p1,\ldots,p except for i,ji,j. We compute

max{(xi+xj)ki,jxk|ij}\displaystyle\max\{(x_{i}+x_{j})\prod_{k\neq i,j}x_{k}~{}|~{}i\neq j\} (p2)1i,j:i<j(xi+xj)ki,jxk\displaystyle\geq\binom{p}{2}^{-1}\sum_{i,j:i<j}(x_{i}+x_{j})\prod_{k\neq i,j}x_{k}
=2pj=1pkjxk\displaystyle=\frac{2}{p}\sum_{j=1}^{p}\prod_{k\neq j}x_{k}
2j=1pkjxkp=2j=1pxjp1p.\displaystyle\geq 2\sqrt[p]{\prod_{j=1}^{p}\prod_{k\neq j}x_{k}}=2\prod_{j=1}^{p}x_{j}^{\frac{p-1}{p}}.

It follows that

u(x)i=1piΔpn(r)u𝑑𝒙(2r)np12j=1pxjp1p.u(x)\leq\sum_{i=1}^{p}\int_{\partial_{i}\Delta^{n}_{p}(r)}ud\bm{x}^{\prime}\cdot\Big{(}\frac{2}{r}\Big{)}^{n-p}\frac{1}{2\prod_{j=1}^{p}x_{j}^{\frac{p-1}{p}}}.

We can easily check the function

U(x)=(2r)np12j=1pxjp1pU(x)=\Big{(}\frac{2}{r}\Big{)}^{n-p}\frac{1}{2\prod_{j=1}^{p}x_{j}^{\frac{p-1}{p}}}

enjoys the desired convexity and integrability. ∎

Proposition 2.5.

Suppose p2p\geq 2. Let u:Δpn(r)[0,]u:\Delta^{n}_{p}(r)\to[0,\infty] be a convex function. Then we have

Δpn(r2)upp1𝑑𝒙(p1)(2r)npp1i=1p(iΔpn(r)u𝑑𝒙)pp1.\int_{\Delta^{n}_{p}(\frac{r}{2})}u^{\frac{p}{p-1}}d\bm{x}\leq(p-1)\Big{(}\frac{2}{r}\Big{)}^{\frac{n-p}{p-1}}\sum_{i=1}^{p}\Big{(}\int_{\partial_{i}\Delta^{n}_{p}(r)}ud\bm{x}^{\prime}\Big{)}^{\frac{p}{p-1}}.
Proof.

For i,j{1,,p}i,j\in\{1,\ldots,p\}, we put

(2.3) Δp,ijn(r):={(x1,,xn)Δpn(r)|xi,xjminki,jxk}.\displaystyle\Delta^{n}_{p,ij}(r):=\{(x_{1},\ldots,x_{n})\in\Delta^{n}_{p}(r)~{}|~{}x_{i},x_{j}\leq\min_{k\neq i,j}x_{k}\}.

Then we have

Δpn(r)=i<jΔp,ijn(r).\Delta^{n}_{p}(r)=\bigcup_{i<j}\Delta^{n}_{p,ij}(r).

Now we consider

Pij(r):={(tij;rij,𝒙ij)[0,1]×Δp1n1(r)|tijrij,(1tij)rijminki,jxk},P_{ij}(r):=\{(t_{ij};r_{ij},\bm{x}^{ij})\in[0,1]\times\Delta^{n-1}_{p-1}(r)~{}|~{}t_{ij}r_{ij},(1-t_{ij})r_{ij}\leq\min_{k\neq i,j}x_{k}\},

where kk in min\min runs over 1,,p1,\ldots,p except for i,ji,j and we put

𝒙ij\displaystyle\bm{x}^{ij} :=(x1,,xi1,xi+1,,xj1,xj+1,,xn).\displaystyle:=(x_{1},\ldots,x_{i-1},x_{i+1},\ldots,x_{j-1},x_{j+1},\ldots,x_{n}).

By

(tij;rij,𝒙ij)(x1,,xi1,tijrij,xi+1,,xj1,(1tij)rij,xj+1,,xn),(t_{ij};r_{ij},\bm{x}^{ij})\mapsto(x_{1},\ldots,x_{i-1},t_{ij}r_{ij},x_{i+1},\ldots,x_{j-1},(1-t_{ij})r_{ij},x_{j+1},\ldots,x_{n}),

we get a map from Pij(r)P_{ij}(r) onto Δp,ijn(r)\Delta^{n}_{p,ij}(r), which gives a homeomorphism outside the zero set {xi=xj=0}Δp,ijn(r)\{x_{i}=x_{j}=0\}\subset\Delta^{n}_{p,ij}(r). The Lebesgue measure d𝒙=dx1dxnd\bm{x}=dx_{1}\dotsb dx_{n} is transformed into

dtijrijdrijd𝒙ij=dtijrijdrijdx1dxi1dxi+1dxj1dxj+1dxn.dt_{ij}r_{ij}dr_{ij}d\bm{x}^{ij}=dt_{ij}r_{ij}dr_{ij}dx_{1}\dotsb dx_{i-1}dx_{i+1}\dotsb dx_{j-1}dx_{j+1}\dotsb dx_{n}.

A convex function ff on Δp,ijn\Delta^{n}_{p,ij} gives a convex function ftij(rij,𝒙ij):=f(tij;rij,𝒙ij)f_{t_{ij}}(r_{ij},\bm{x}^{ij}):=f(t_{ij};r_{ij},\bm{x}^{ij}) on Δp1n1(r)\Delta^{n-1}_{p-1}(r) for each tij[0,1]t_{ij}\in[0,1]. We also have

f(tij;rij,𝒙ij)tijf1(rij,𝒙ij)+(1tij)f0(rij,𝒙ij).f(t_{ij};r_{ij},\bm{x}^{ij})\leq t_{ij}f_{1}(r_{ij},\bm{x}^{ij})+(1-t_{ij})f_{0}(r_{ij},\bm{x}^{ij}).

Since upp1u^{\frac{p}{p-1}} is convex, we compute

Δp,ijn(r2)upp1𝑑𝒙\displaystyle\int_{\Delta^{n}_{p,ij}(\frac{r}{2})}u^{\frac{p}{p-1}}d\bm{x} =Pij(r2)𝑑tij𝑑𝒙ij𝑑rijriju(tij;rij,𝒙ij)pp1\displaystyle=\int_{P_{ij}(\frac{r}{2})}dt_{ij}d\bm{x}^{ij}dr_{ij}r_{ij}u(t_{ij};r_{ij},\bm{x}^{ij})^{\frac{p}{p-1}}
Pij(r2)𝑑tij𝑑𝒙ij𝑑rijrij(tiju1(rij,𝒙ij)pp1+(1tij)u0(rij,𝒙ij)pp1)\displaystyle\leq\int_{P_{ij}(\frac{r}{2})}dt_{ij}d\bm{x}^{ij}dr_{ij}r_{ij}(t_{ij}u_{1}(r_{ij},\bm{x}^{ij})^{\frac{p}{p-1}}+(1-t_{ij})u_{0}(r_{ij},\bm{x}^{ij})^{\frac{p}{p-1}})
Pij(r2)𝑑tij𝑑𝒙ij𝑑riju1(rij,𝒙ij)((2r)npΔp1n1(r)u1(rij,𝒙ij)𝑑𝒙(rijtij)p1rijki,jxk)1p1\displaystyle\leq\int_{P_{ij}(\frac{r}{2})}dt_{ij}d\bm{x}^{ij}dr_{ij}u_{1}(r_{ij},\bm{x}^{ij})\Big{(}\Big{(}\frac{2}{r}\Big{)}^{n-p}\int_{\Delta^{n-1}_{p-1}(r)}u_{1}(r_{ij},\bm{x}^{ij})d\bm{x}^{\prime}\cdot\frac{(r_{ij}t_{ij})^{p-1}}{r_{ij}\prod_{k\neq i,j}x_{k}}\Big{)}^{\frac{1}{p-1}}
+Pij(r2)dtijd𝒙ijdriju0(rij,𝒙ij))((2r)npΔp1n1(r)u0(rij,𝒙ij)d𝒙(rij(1tij))p1rijki,jxk)1p1.\displaystyle+\int_{P_{ij}(\frac{r}{2})}dt_{ij}d\bm{x}^{ij}dr_{ij}u_{0}(r_{ij},\bm{x}^{ij}))\Big{(}\Big{(}\frac{2}{r}\Big{)}^{n-p}\int_{\Delta^{n-1}_{p-1}(r)}u_{0}(r_{ij},\bm{x}^{ij})d\bm{x}^{\prime}\cdot\frac{(r_{ij}(1-t_{ij}))^{p-1}}{r_{ij}\prod_{k\neq i,j}x_{k}}\Big{)}^{\frac{1}{p-1}}.

Here again kk in \prod runs over 1,,p1,\ldots,p except for i,ji,j. Since

(rijtij)p1rijki,jxk,(rij(1tij))p1rijki,jxk1\frac{(r_{ij}t_{ij})^{p-1}}{r_{ij}\prod_{k\neq i,j}x_{k}},\frac{(r_{ij}(1-t_{ij}))^{p-1}}{r_{ij}\prod_{k\neq i,j}x_{k}}\leq 1

on Pij(r)P_{ij}(r), we get

Δi,jn(r2)unn1𝑑𝒙\displaystyle\int_{\Delta^{n}_{i,j}(\frac{r}{2})}u^{\frac{n}{n-1}}d\bm{x} Pij(r2)𝑑tij𝑑𝒙ij𝑑riju1(rij,𝒙ij)((2r)npΔp1n1(r)u1(rij,𝒙ij)𝑑𝒙)1p1\displaystyle\leq\int_{P_{ij}(\frac{r}{2})}dt_{ij}d\bm{x}^{ij}dr_{ij}u_{1}(r_{ij},\bm{x}^{ij})\Big{(}\Big{(}\frac{2}{r}\Big{)}^{n-p}\int_{\Delta^{n-1}_{p-1}(r)}u_{1}(r_{ij},\bm{x}^{ij})d\bm{x}^{\prime}\Big{)}^{\frac{1}{p-1}}
+Pij(r2)dtijd𝒙ijdriju0(rij,𝒙ij))((2r)npΔp1n1(r)u0(rij,𝒙ij)d𝒙)1p1\displaystyle+\int_{P_{ij}(\frac{r}{2})}dt_{ij}d\bm{x}^{ij}dr_{ij}u_{0}(r_{ij},\bm{x}^{ij}))\Big{(}\Big{(}\frac{2}{r}\Big{)}^{n-p}\int_{\Delta^{n-1}_{p-1}(r)}u_{0}(r_{ij},\bm{x}^{ij})d\bm{x}^{\prime}\Big{)}^{\frac{1}{p-1}}
=(2r)npp1Δp1n1(r2)u1(rij,𝒙ij)𝑑𝒙(Δp1n1(r)u1(rij,𝒙ij)𝑑𝒙)1p1\displaystyle=\Big{(}\frac{2}{r}\Big{)}^{\frac{n-p}{p-1}}\int_{\Delta^{n-1}_{p-1}(\frac{r}{2})}u_{1}(r_{ij},\bm{x}^{ij})d\bm{x}^{\prime}\Big{(}\int_{\Delta^{n-1}_{p-1}(r)}u_{1}(r_{ij},\bm{x}^{ij})d\bm{x}^{\prime}\Big{)}^{\frac{1}{p-1}}
+(2r)npp1Δp1n1(r2)u0(rij,𝒙ij)𝑑𝒙(Δp1n1(r)u0(rij,𝒙ij)𝑑𝒙)1p1\displaystyle+\Big{(}\frac{2}{r}\Big{)}^{\frac{n-p}{p-1}}\int_{\Delta^{n-1}_{p-1}(\frac{r}{2})}u_{0}(r_{ij},\bm{x}^{ij})d\bm{x}^{\prime}\Big{(}\int_{\Delta^{n-1}_{p-1}(r)}u_{0}(r_{ij},\bm{x}^{ij})d\bm{x}^{\prime}\Big{)}^{\frac{1}{p-1}}
(2r)npp1[(jΔpn(r)u𝑑𝒙)pp1+(iΔpn(r)u𝑑𝒙)pp1].\displaystyle\leq\Big{(}\frac{2}{r}\Big{)}^{\frac{n-p}{p-1}}\Big{[}\Big{(}\int_{\partial_{j}\Delta^{n}_{p}(r)}ud\bm{x}^{\prime}\Big{)}^{\frac{p}{p-1}}+\Big{(}\int_{\partial_{i}\Delta^{n}_{p}(r)}ud\bm{x}^{\prime}\Big{)}^{\frac{p}{p-1}}\Big{]}.

Taking the sum i<j\sum_{i<j} of this, we obtain the desired estimate. ∎

2.2. Rellich and Poincare type estimates

Here we establish a crucial compactness result.

2.2.1. Rellich type estimate

Proposition 2.6.

Let P=PP=P be a polytope. Using a flat measure dμd\mu, we put

δP(x):=inf{vol(P1([0,)))|:V is an affine function with (x)=0}.\delta_{P}(x):=\inf\{\mathrm{vol}(P\cap\ell^{-1}([0,\infty)))~{}|~{}\ell:V\to\mathbb{R}\text{ is an affine function with }\ell(x)=0\}.

Then δP(x)>0\delta_{P}(x)>0 for every xPx\in P^{\circ}. Moreover, for any non-negative convex function uu and xPx\in P, we have

u(x)Pu𝑑μ1δP(x).u(x)\leq\int_{P}ud\mu\cdot\frac{1}{\delta_{P}(x)}.
Proof.

Let S(V)S(V) be the set of half spaces H+=1([0,))H^{+}_{\ell}=\ell^{-1}([0,\infty)) with (x)=0\ell(x)=0. We identify S(V)S(V) with a sphere as topological space. Then the map S(V)[0,):H+vol(PH+)S(V)\to[0,\infty):H^{+}\mapsto\mathrm{vol}(P\cap H^{+}) is continuous, so that the infimum of δP(x)\delta_{P}(x) is attained by some H+H^{+}, so that we have δP(x)>0\delta_{P}(x)>0 on PP^{\circ} and δP(x)=0\delta_{P}(x)=0 on P\partial P. The inequality follows by the same argument as in the proof of Proposition 2.1. ∎

Theorem 2.7.

Let 𝒫=(P,dμ,dσ)\mathcal{P}=(P,d\mu,d\sigma) be an nn-dimensional system. There exists a lsc convex function U:P[0,]U:P\to[0,\infty] such that ULq(P,dμ)U\in L^{q}(P,d\mu) for every q[1,nn1)q\in[1,\frac{n}{n-1}) and

u(x)Pu𝑑σU(x)u(x)\leq\int_{\partial P}ud\sigma\cdot U(x)

for every non-negative lsc convex function u:P[0,]u:P\to[0,\infty] and xPx\in P.

Moreover, we can take such UU so that it is finite valued and continuous on P2PP\setminus\partial^{2}P and for each x2Px\in\partial^{2}P lying in the relative interior of a codimension p2p\geq 2 face, there exists a neighbourhood VV such that U|VLr(V,dμ|V)U|_{V}\in L^{r}(V,d\mu|_{V}) for every r[1,pp1)r\in[1,\frac{p}{p-1}).

Proof.

We put

U(x):=sup{u(x)Pu𝑑σ|u:P[0,] is lsc convex with 0<Pu𝑑σ<}.U(x):=\sup\Big{\{}\frac{u(x)}{\int_{\partial P}ud\sigma}~{}\Big{|}~{}u:P\to[0,\infty]\text{ is lsc convex with }0<\int_{\partial P}ud\sigma<\infty\Big{\}}.

This is clearly a lsc convex function on PP.

We firstly show that UU is finite valued and continuous on P2PP\setminus\partial^{2}P. For xP2Px\in\partial P\setminus\partial^{2}P lying in the relative interior of a facet QPQ\subset P, we have

u(x)Qu𝑑σ1δQ(x)Pu𝑑σ1δQ(x),u(x)\leq\int_{Q}ud\sigma\cdot\frac{1}{\delta_{Q}(x)}\leq\int_{\partial P}ud\sigma\cdot\frac{1}{\delta_{Q}(x)},

so that

U(x)1δQ(x).U(x)\leq\frac{1}{\delta_{Q}(x)}.

Thus U(x)U(x) is finite for xP2Px\in\partial P\setminus\partial^{2}P. For xP2Px\in P\setminus\partial^{2}P, we can take x,x′′P2Px^{\prime},x^{\prime\prime}\in\partial P\setminus\partial^{2}P and t[0,1]t\in[0,1] so that x=(1t)x+tx′′x=(1-t)x^{\prime}+tx^{\prime\prime}. Then by the convexity, we have U(x)(1t)U(x)+tU(x′′)<U(x)\leq(1-t)U(x^{\prime})+tU(x^{\prime\prime})<\infty.

Since PP is a polytope, the upper semi-continuity of UU follows by the convexity. Indeed, as for the interior PP^{\circ}, it is well-known that any convex function is continuous on open set. The upper semi-continuity around P2P\partial P\setminus\partial^{2}P can be seen as follows. Take a local neigbourhood of a point xP2Px\in\partial P\setminus\partial^{2}P so that it is affine isomorphic to Δ1n(2r)\Delta^{n}_{1}(2r). Then for any convex function uu on Δ1n(r)\Delta^{n}_{1}(r) we compute

u(x1i,,xni)(1x1ir)u(0,x2i,,xni)+x1iru(r,x2i,,xni).u(x^{i}_{1},\ldots,x^{i}_{n})\leq(1-\frac{x^{i}_{1}}{r})u(0,x^{i}_{2},\ldots,x^{i}_{n})+\frac{x^{i}_{1}}{r}u(r,x^{i}_{2},\ldots,x^{i}_{n}).

When xi=(x1i,,xni)0x^{i}=(x^{i}_{1},\ldots,x^{i}_{n})\to 0, we have

(1x1ir)u(0,x2i,,xni)+x1iru(r,x2i,,xni)u(0)(1-\frac{x^{i}_{1}}{r})u(0,x^{i}_{2},\ldots,x^{i}_{n})+\frac{x^{i}_{1}}{r}u(r,x^{i}_{2},\ldots,x^{i}_{n})\to u(0)

by the continuity of uu on Δ1n(2r)\Delta^{n}_{1}(2r)^{\circ} and on 1Δ1n(2r)\partial_{1}\Delta^{n}_{1}(2r). Thus we get

(2.4) lim supiu(xi)u(0),\displaystyle\limsup_{i\to\infty}u(x^{i})\leq u(0),

which shows the upper semi-continuity.

Now it follows that for any compact set KP2PK\subset P\setminus\partial^{2}P, there exists a constant C>0C>0 such that U|KCU|_{K}\leq C. In particular, U|KU|_{K} is LqL^{q} for any qq.

It suffices to show the integrability around 2P\partial^{2}P. We can reduce this task to show for every point x02Px_{0}\in\partial^{2}P there exists a neighbourhood VV of x0x_{0} in PP and a function f:V[0,]f:V\to[0,\infty] such that fLq(V,dμ)f\in L^{q}(V,d\mu) for every q[1,nn1)q\in[1,\frac{n}{n-1}) and U|VfU|_{V}\leq f.

For any boundary point x0Px_{0}\in\partial P lying in the relative interior of dimension pp face, we can take an affine map ϕ:nM\phi:\mathbb{R}^{n}\to M_{\mathbb{R}} so that

  • ϕ(0)=x0\phi(0)=x_{0},

  • The measure dμd\mu on VV is transformed into the Lebesgue measure d𝒙d\bm{x} on n\mathbb{R}^{n}.

  • There exists r>0r>0 such that ϕ\phi gives a homeomorphism from Δpn(r)\Delta^{n}_{p}(r) onto an open neighbourhood of x0x_{0} in PP.

  • For each i=1,,pi=1,\ldots,p, there exists a facet QiPQ_{i}\subset P containing x0x_{0} such that ϕ\phi gives a homeomorphism from iΔpn(r)\partial_{i}\Delta^{n}_{p}(r) onto an open neighbourhood of x0x_{0} in QiQ_{i}.

Since ϕ\phi is affine, the measure dσd\sigma on QiQ_{i} is transformed into aid𝒙a_{i}d\bm{x}^{\prime} on iΔpn(r)\partial_{i}\Delta^{n}_{p}(r) for some constant ai>0a_{i}>0.

For a convex function uu on PP, we have

i=1piΔpn(r)uϕ𝑑𝒙=i=1pai1Qiϕ(iΔpn(r))u𝑑σ1min{ai}Pu𝑑σ.\sum_{i=1}^{p}\int_{\partial_{i}\Delta^{n}_{p}(r)}u\circ\phi d\bm{x}^{\prime}=\sum_{i=1}^{p}a_{i}^{-1}\int_{Q_{i}\cap\phi(\partial_{i}\Delta^{n}_{p}(r))}ud\sigma\leq\frac{1}{\min\{a_{i}\}}\int_{\partial P}ud\sigma.

Then by Corollary 2.4, we have a function f~:Δpn(r)[0,]\tilde{f}:\Delta^{n}_{p}(r)\to[0,\infty] such that f~Lq(Δpn(r))\tilde{f}\in L^{q}(\Delta^{n}_{p}(r)) for every q[1,nn1)q\in[1,\frac{n}{n-1}) and

uϕ(x)Pu𝑑σf~(x)u\circ\phi(x)\leq\int_{\partial P}ud\sigma\cdot\tilde{f}(x)

on Δpn(r/2)\Delta^{n}_{p}(r/2) for every convex u:P[0,]u:P\to[0,\infty]. Now we put V:=ϕ(Δpn(r/2))V:=\phi(\Delta^{n}_{p}(r/2)) and f:=f~(ϕ1)|Vf:=\tilde{f}\circ(\phi^{-1})|_{V}, then we get the desired property. ∎

Corollary 2.8.

Let {ui:P[0,]}i\{u_{i}:P\to[0,\infty]\}_{i\in\mathbb{N}} be a sequence of non-negative convex functions with a uniform bound

Pui𝑑σC.\int_{\partial P}u_{i}d\sigma\leq C.

After taking a subsequence, there exists a unique lower semi-continuous convex function u:P[0,]u:P\to[0,\infty] such that uiu_{i} converges to uu in LqL^{q}-topology for every q[0,nn1)q\in[0,\frac{n}{n-1}). Moreover the convergence is uniform on each compact set KPK\subset P^{\circ}.

Proof.

If we put

u^i:=sup{(x)|:P is an affine function s.t. u},\hat{u}_{i}:=\sup\{\ell(x)~{}|~{}\ell:P\to\mathbb{R}\text{ is an affine function s.t. }\ell\leq u\},

we have u^i|P=ui|P\hat{u}_{i}|_{P^{\circ}}=u_{i}|_{P^{\circ}} by the supporting hyperplane theorem and Pu^i𝑑σPui𝑑σC\int_{\partial P}\hat{u}_{i}d\sigma\leq\int_{\partial P}u_{i}d\sigma\leq C. Thus we may assume uiu_{i} are lower semi-continuous. By the above theorem, we have

ui(x)CU(x).u_{i}(x)\leq C\cdot U(x).

It follows by the continuity of UU on P2PP\setminus\partial^{2}P that for any compact set KP2PK\subset P\setminus\partial^{2}P, ui|Ku_{i}|_{K} is uniformly bounded. Then by a general argument, for any compact set KPK^{\prime}\subset P^{\circ}, we get a uniform Lipschitz bound |ui|K|CK|\nabla u_{i}|_{K^{\prime}}|\leq C_{K^{\prime}}. Then by Arzelà–Ascoli theorem, we can find a subsequence uiu_{i} and a function uu^{\circ} on PP^{\circ} so that uiu_{i} converges uniformly to uu^{\circ} on every compact set KPK\subset P^{\circ}. Since uCU(x)u^{\circ}\leq C\cdot U(x), we have uiuu_{i}\to u^{\circ} in Lq(P)L^{q}(P^{\circ}) for every q[1,nn1)q\in[1,\frac{n}{n-1}) by the dominated convergence theorem.

Now we consider the lsc envelope

u(x):=sup{(x)|:V is an affine function s.t.|Pu}u(x):=\sup\{\ell(x)~{}|~{}\ell:V\to\mathbb{R}\text{ is an affine function s.t.}\ell|_{P^{\circ}}\leq u^{\circ}\}

on PP. By the supporting hyperplane theorem, uu coincides with uu^{\circ} on PP^{\circ}. Then since P\partial P is a zero set, we have uiuu_{i}\to u in Lq(P)L^{q}(P) for every q[1,nn1)q\in[1,\frac{n}{n-1}).

Since any convex function is continuous on open set, the LqL^{q}-convergence characterizes uu on PP^{\circ}. Since uu restricted to a segment is automatically upper semi-continuous, the lowe semi-continuity of uu implies that u|Pu|_{\partial P} is uniquely determined by u|Pu|_{P^{\circ}}, which shows the uniqueness. ∎

2.2.2. Poincare type estimate

Theorem 2.9.

Let 𝒫=(P,dμ,dσ)\mathcal{P}=(P,d\mu,d\sigma) be an nn-dimensional system. For every q[1,nn1]q\in[1,\frac{n}{n-1}], there exists a constant CP,q>0C_{P,q}>0 such that

(Puq𝑑μ)1qCP,qPu𝑑σ\Big{(}\int_{P}u^{q}d\mu\Big{)}^{\frac{1}{q}}\leq C_{P,q}\int_{\partial P}ud\sigma

for every non-negative convex function u:P[0,]u:P\to[0,\infty].

Proof.

We may assume uu is lower semi-continuous. Since the measure dμd\mu is finite, it suffices to show the claim for q=nn1q=\frac{n}{n-1}. For each x2Px\in\partial^{2}P, we take an affine chart ϕx:nM\phi_{x}:\mathbb{R}^{n}\to M_{\mathbb{R}} as in the above proof and cover PP by open sets Vx:=ϕx(Δpxn(rx/2))V_{x}:=\phi_{x}(\Delta^{n}_{p_{x}}(r_{x}/2)) and W={xP2P|U(x)<C}W=\{x\in P\setminus\partial^{2}P~{}|~{}U(x)<C\} for some C>0C>0. Take a finite subcover {Vx1,,VxN,W}\{V_{x_{1}},\ldots,V_{x_{N}},W\} so that it still covers PP. On WW, we have

(Wunn1𝑑μ)n1nCvol(P)n1n.\Big{(}\int_{W}u^{\frac{n}{n-1}}d\mu\Big{)}^{\frac{n-1}{n}}\leq C\mathrm{vol}(P)^{\frac{n-1}{n}}.

By Proposition 2.5, we have

(Vxmunn1𝑑μ)n1n\displaystyle\Big{(}\int_{V_{x_{m}}}u^{\frac{n}{n-1}}d\mu\Big{)}^{\frac{n-1}{n}} =(Δpxmn(rxm/2)(uϕxm)nn1𝑑𝒙)n1n\displaystyle=\Big{(}\int_{\Delta^{n}_{p_{x_{m}}}(r_{x_{m}}/2)}(u\circ\phi_{x_{m}})^{\frac{n}{n-1}}d\bm{x}\Big{)}^{\frac{n-1}{n}}
vol(Δpxmn(rxm/2))n1npxm1pxm(Δpxmn(rxm/2)(uϕxm)pxmpxm1𝑑𝒙)pxm1pxm\displaystyle\leq\mathrm{vol}(\Delta^{n}_{p_{x_{m}}}(r_{x_{m}}/2))^{\frac{n-1}{n}-\frac{p_{x_{m}}-1}{p_{x_{m}}}}\Big{(}\int_{\Delta^{n}_{p_{x_{m}}}(r_{x_{m}}/2)}(u\circ\phi_{x_{m}})^{\frac{p_{x_{m}}}{p_{x_{m}}-1}}d\bm{x}\Big{)}^{\frac{p_{x_{m}}-1}{p_{x_{m}}}}
Cxmi=1pxmiΔpxmn(rxm)uϕxm𝑑𝒙\displaystyle\leq C_{x_{m}}\sum_{i=1}^{p_{x_{m}}}\int_{\partial_{i}\Delta^{n}_{p_{x_{m}}}(r_{x_{m}})}u\circ\phi_{x_{m}}d\bm{x}^{\prime}
Cxmmin{ai(xm)}Pu𝑑σ.\displaystyle\leq\frac{C_{x_{m}}}{\min\{a_{i}(x_{m})\}}\int_{\partial P}ud\sigma.

Here we put

Cxm:=(pxm(pxm1))npxmpxm(2rxm)npxmpxmvol(Δpxmn(rxm/2))n1npxm1pxm.C_{x_{m}}:=(p_{x_{m}}(p_{x_{m}}-1))^{\frac{n-p_{x_{m}}}{p_{x_{m}}}}\Big{(}\frac{2}{r_{x_{m}}}\Big{)}^{\frac{n-p_{x_{m}}}{p_{x_{m}}}}\mathrm{vol}(\Delta^{n}_{p_{x_{m}}}(r_{x_{m}}/2))^{\frac{n-1}{n}-\frac{p_{x_{m}}-1}{p_{x_{m}}}}.

Take the sum for m=1,,Nm=1,\ldots,N, we get the result. ∎

Remark 2.10.

By inductive argument, we obtain the following: Let P=(P,dμ)P=(P,d\mu) be an nn-dimensional simple polytope. If we endow a flat measure dσkd\sigma_{k} on kP={ codimension k faces }\partial^{k}P=\bigcup\{\text{ codimension $k$ faces }\}, then for q[1,nnk]q\in[1,\frac{n}{n-k}], there exists a constant CP,dσk,q>0C_{P,d\sigma_{k},q}>0 such that

(Puq𝑑μ)1qCP,dσk,qkPu𝑑σk\Big{(}\int_{P}u^{q}d\mu\Big{)}^{\frac{1}{q}}\leq C_{P,d\sigma_{k},q}\int_{\partial^{k}P}ud\sigma_{k}

for every non-negative convex function u:P[0,]u:P\to[0,\infty]. It would be interesting to find application of this fact to the higher regularity of minimizer of F𝒫(T,)F_{\mathcal{P}}(T,\bullet).

We use the following log Sobolev type estimate in the next section.

Corollary 2.11.

For q(1,nn1]q\in(1,\frac{n}{n-1}], we have

Pulogudμqq1log(CP,qPu𝑑σ)\int_{P}u\log ud\mu\leq\frac{q}{q-1}\log(C_{P,q}\int_{\partial P}ud\sigma)

for every non-negative convex function u:P[0,]u:P\to[0,\infty] with Pu𝑑μ=1\int_{P}ud\mu=1.

Proof.

Since udμud\mu is a probability measure, we compute

Pulogudμ=1q1Ploguq1udμqq1log(Puqdμ)1q\int_{P}u\log ud\mu=\frac{1}{q-1}\int_{P}\log u^{q-1}~{}ud\mu\leq\frac{q}{q-1}\log\Big{(}\int_{P}u^{q}d\mu\Big{)}^{\frac{1}{q}}

by Jensen’s inequality on logx\log x. The claim follows by applying the above theorem. ∎

3. Optimizers for non-archimedean μ\mu-entropy

3.1. Existence and Uniqueness of optimizers

3.1.1. Existence of minimizer of F𝒫F_{\mathcal{P}}

Here we show the existence part of main theorem. Let us firstly observe the lower semi-continuity of F𝒫(T,u)F_{\mathcal{P}}(T,u).

Proposition 3.1.

Suppose uiNAexp,1(P)u_{i}\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(P) converges to uNAexp,1(P)u_{\infty}\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(P) in L1L^{1}-topology, then

(3.1) U𝒫(u)lim infiU𝒫(ui).\displaystyle U_{\mathcal{P}}(u_{\infty})\leq\liminf_{i\to\infty}U_{\mathcal{P}}(u_{i}).

If moreover the LpL^{p}-norm of ui,uu_{i},u_{\infty} is bounded for some p>1p>1, then we have

(3.2) S𝒫(ui)=limiS𝒫(u).\displaystyle S_{\mathcal{P}}(u_{i})=\lim_{i\to\infty}S_{\mathcal{P}}(u_{\infty}).
Proof.

We firstly note the following fact: for a sequence uiu_{i} of convex functions on PP, if the restriction ui|Pu_{i}|_{P^{\circ}} pointwisely converges to a convex function uu^{\circ} on PP^{\circ}, then for the lower semi-continuous extension uu on PP (see the proof of Corollary 2.8), we have

(3.3) u(x)lim infiui(x)\displaystyle u(x)\leq\liminf_{i\to\infty}u_{i}(x)

for every point xPx\in P. This can be seen as follows. Take a point pPp\in P^{\circ}. For xPx\in P, we have

ui((1t)p+tx)(1t)ui(p)+tui(x).u_{i}((1-t)p+tx)\leq(1-t)u_{i}(p)+tu_{i}(x).

For t[0,1)t\in[0,1), we have (1t)p+txP(1-t)p+tx\in P^{\circ}, so that we get

u((1t)p+tx)(1t)u(p)+tlim infiui(x)u((1-t)p+tx)\leq(1-t)u(p)+t\liminf_{i\to\infty}u_{i}(x)

by the pointwise convergence on PP^{\circ}. As uu is lower semi-continuous, it is continuous on the segment {(1t)p+tx}t[0,1]\{(1-t)p+tx\}_{t\in[0,1]}. Thus by taking the limit t1t\to 1, we get the claim.

Now since P𝑑μU𝒫(u)=Pu𝑑σ\int_{P}d\mu\cdot U_{\mathcal{P}}(u)=\int_{\partial P}ud\sigma, the inequality (3.1) is a consequence of Fatou’s lemma. Only the pointwise convergence on PP^{\circ} is important for this.

On the other hand, by mean value theorem on t2logt2t^{2}\log t^{2}, we compute

|xlogxylogy|\displaystyle|x\log x-y\log y| =2|xy||2zlogz+z|\displaystyle=2|\sqrt{x}-\sqrt{y}||2\sqrt{z}\log\sqrt{z}+\sqrt{z}|
2|xy|(2max{e1,ϵ1z1+ϵ|}+z)\displaystyle\leq 2|\sqrt{x}-\sqrt{y}|(2\max\{e^{-1},\epsilon^{-1}\sqrt{z}^{1+\epsilon}|\}+\sqrt{z})
2|xy|(2max{e1,ϵ1y1+ϵ}+y)\displaystyle\leq 2|\sqrt{x}-\sqrt{y}|(2\max\{e^{-1},\epsilon^{-1}\sqrt{y}^{1+\epsilon}\}+\sqrt{y})

for 0xy0\leq x\leq y and ϵ>0\epsilon>0, by taking suitable z[x,y]z\in[x,y]. It follows by Cauchy–Schwarz theorem that

|Puiloguidμ\displaystyle\Big{|}\int_{P}u_{i}\log u_{i}d\mu Pulogudμ|\displaystyle-\int_{P}u_{\infty}\log u_{\infty}d\mu\Big{|}
2P|uiu|\displaystyle\leq 2\int_{P}|\sqrt{u_{i}}-\sqrt{u_{\infty}}|
(2max{e1,ϵ1ui1+ϵ,ϵ1u1+ϵ}+max{ui,u})dμ\displaystyle\qquad\cdot(2\max\{e^{-1},\epsilon^{-1}\sqrt{u_{i}}^{1+\epsilon},\epsilon^{-1}\sqrt{u_{\infty}}^{1+\epsilon}\}+\max\{\sqrt{u_{i}},\sqrt{u_{\infty}}\})d\mu
uiuL2C\displaystyle\leq\|\sqrt{u_{i}}-\sqrt{u_{\infty}}\|_{L^{2}}\cdot C

with a constant CC which depends only on ϵ\epsilon and a uniform bound on L1+ϵL^{1+\epsilon}-norm of ui,uu_{i},u_{\infty}. This proves the claim for P𝑑μS𝒫(u)=Pulogudμ\int_{P}d\mu\cdot S_{\mathcal{P}}(u)=-\int_{P}u\log ud\mu. ∎

We prepare the following uniform estimate.

Lemma 3.2.

For any T,CT,C\in\mathbb{R}, there exists a constant C~>0\tilde{C}>0 depending only on T,C,n,CP,nn1T,C,n,C_{P,\frac{n}{n-1}} such that the following holds: if a non-negative convex function u:P[0,]u:P\to[0,\infty] with Pu𝑑μ=1\int_{P}ud\mu=1 satisfies

Pu𝑑σ+TPulogudμC,\int_{\partial P}ud\sigma+T\int_{P}u\log ud\mu\leq C,

then we have

Pu𝑑σC~.\int_{\partial P}ud\sigma\leq\tilde{C}.
Proof.

When T0T\geq 0, we can choose C~=C\tilde{C}=C since we have Pulogudμ0\int_{P}u\log ud\mu\geq 0 by Jensen’s inequality on xlogxx\log x.

Suppose T<0T<0. By Corollary 2.11, we get

Pu𝑑σnTlog(CP,nn1Pu𝑑σ)+C.\int_{\partial P}ud\sigma\leq-nT\log(C_{P,\frac{n}{n-1}}\int_{\partial P}ud\sigma)+C.

We get the result for the constant

C~:=sup{x[0,)|xnTlog(CP,nn1x)+C}<.\tilde{C}:=\sup\{x\in[0,\infty)~{}|~{}x\leq-nT\log(C_{P,\frac{n}{n-1}}x)+C\}<\infty.

Now we prove our main existence theorem.

Theorem 3.3.

Let 𝒫=(P,dμ,dσ)\mathcal{P}=(P,d\mu,d\sigma) be an nn-dimensional system. For every TT\in\mathbb{R}, there exists a convex function uNAexp,nn1(P)u\in\mathcal{M}_{\mathrm{NA}}^{\exp,\frac{n}{n-1}}(P) which minimizes F𝒫(T,)F_{\mathcal{P}}(T,\bullet) on NAexp,1(P)\mathcal{M}_{\mathrm{NA}}^{\exp,1}(P).

Proof.

We recall

P𝑑μF𝒫(T,u)=Pu𝑑σ+TPulogudμ.\int_{P}d\mu\cdot F_{\mathcal{P}}(T,u)=\int_{\partial P}ud\sigma+T\int_{P}u\log ud\mu.

By the above lemma, for any constant CC, Peq𝑑σ\int_{\partial P}e^{q}d\sigma is uniformly bounded on the subset

{uNAexp,1(P)|F𝒫(T,u)C}.\{u\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(P)~{}|~{}F_{\mathcal{P}}(T,u)\leq C\}.

Take a sequence uiNAexp,1(P)u_{i}\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(P) so that F𝒫(T,ui)infuF𝒫(T,u)F_{\mathcal{P}}(T,u_{i})\searrow\inf_{u}F_{\mathcal{P}}(T,u). Thanks to the above uniform bound and the compactness in Corollary 2.8, after taking a subsequence we may assume uiu_{i} converges in LpL^{p}-topology (p[1,nn1)p\in[1,\frac{n}{n-1})) to a lsc log convex function uu_{\infty}. (Note log concavity is preserved by pointwise convergence. ) By the L1L^{1}-convergence, we have Pu𝑑μ=limPui𝑑μ=P𝑑μ\int_{P}u_{\infty}d\mu=\lim\int_{P}u_{i}d\mu=\int_{P}d\mu, so that u>0u_{\infty}>0 and hence uNAexp,1(P)u_{\infty}\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(P). By the lower semi-continuity of F𝒫(T,)F_{\mathcal{P}}(T,\bullet) with respect to L1+ϵL^{1+\epsilon}-topology, we get F𝒫(T,u)=infuF𝒫(T,u)F_{\mathcal{P}}(T,u_{\infty})=\inf_{u}F_{\mathcal{P}}(T,u), which shows the existence of minimizer. Finally, since Pu𝑑σlim infiPui𝑑σ<\int_{\partial P}u_{\infty}d\sigma\leq\liminf_{i}\int_{\partial P}u_{i}d\sigma<\infty by the above uniform bound, we conclude uNAexp,nn1(P)u_{\infty}\in\mathcal{M}_{\mathrm{NA}}^{\exp,\frac{n}{n-1}}(P) by Theorem 2.9. ∎

3.1.2. Uniqueness for T0T\geq 0

While 𝝁ˇNAλ\bm{\check{\mu}}_{\mathrm{NA}}^{\lambda} has no convexity along the linear path (1t)q0+tq1(1-t)q_{0}+tq_{1} in NAexp,1(P)\mathcal{E}_{\mathrm{NA}}^{\exp,1}(P), F𝒫F_{\mathcal{P}} has convexity along the linear path (1t)u0+tu1(1-t)u_{0}+tu_{1} in NAexp,1(P)\mathcal{M}_{\mathrm{NA}}^{\exp,1}(P), which corresponds to the ‘log linear exp’ path log((1t)eq0+teq1)\log((1-t)e^{q_{0}}+te^{q_{1}}) in NAexp,1(P)\mathcal{E}_{\mathrm{NA}}^{\exp,1}(P).

Proposition 3.4.

For u0,u1NAexp,1(P)u_{0},u_{1}\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(P) and t[0,1]t\in[0,1], we put

ut:=(1t)u0+tu1.u_{t}:=(1-t)u_{0}+tu_{1}.

Then we have utNAexp,1(P)u_{t}\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(P) and

  • For T=0T=0, F𝒫(0,ut)=U𝒫(ut)F_{\mathcal{P}}(0,u_{t})=U_{\mathcal{P}}(u_{t}) is affine on tt.

  • For T>0T>0, F𝒫(T,ut)F_{\mathcal{P}}(T,u_{t}) is strictly convex when u0u1u_{0}\neq u_{1}.

  • For T<0T<0, F𝒫(T,ut)F_{\mathcal{P}}(T,u_{t}) is strictly concave when u0u1u_{0}\neq u_{1}.

Proof.

To see the log convexity of utu_{t}, we consider the space Ω={0,1}\Omega=\{0,1\} with the probability measure

pt(i)={1ti=0ti=1p_{t}(i)=\begin{cases}1-t&i=0\\ t&i=1\end{cases}

and we compute

ut((1θ)x0+θx1)\displaystyle u_{t}((1-\theta)x_{0}+\theta x_{1}) =Ωui((1θ)x0+θx1)𝑑pt(i)\displaystyle=\int_{\Omega}u_{i}((1-\theta)x_{0}+\theta x_{1})dp_{t}(i)
Ωui1θ(x0)uiθ(x1)𝑑pt(i)\displaystyle\leq\int_{\Omega}u_{i}^{1-\theta}(x_{0})u_{i}^{\theta}(x_{1})dp_{t}(i)
(Ωui(x0)𝑑pt(i))1θ(Ωui(x1)𝑑pt(i))θ=ut1θ(x0)utθ(x1)\displaystyle\leq\Big{(}\int_{\Omega}u_{i}(x_{0})dp_{t}(i)\Big{)}^{1-\theta}\Big{(}\int_{\Omega}u_{i}(x_{1})dp_{t}(i)\Big{)}^{\theta}=u_{t}^{1-\theta}(x_{0})u_{t}^{\theta}(x_{1})

by the Hölder inequality, for every x0,x1Px_{0},x_{1}\in P and θ[0,1]\theta\in[0,1].

Since U𝒫(u)=Pu𝑑σU_{\mathcal{P}}(u)=\int_{\partial P}ud\sigma, we obviously have

(3.4) U𝒫(ut)=(1t)U𝒫(u0)+tU𝒫(u1).\displaystyle U_{\mathcal{P}}(u_{t})=(1-t)U_{\mathcal{P}}(u_{0})+tU_{\mathcal{P}}(u_{1}).

On the other hand, since S𝒫(u)=PulogudμS_{\mathcal{P}}(u)=-\int_{P}u\log ud\mu, the strict convexity of xlogxx\log x implies

(3.5) S𝒫(ut)\displaystyle S_{\mathcal{P}}(u_{t}) (1t)S𝒫(u0)+tS𝒫(u1)\displaystyle\geq(1-t)S_{\mathcal{P}}(u_{0})+tS_{\mathcal{P}}(u_{1})

with the equality iff u0=u1u_{0}=u_{1}. This proves the claim. ∎

Now we obtain the following uniqueness.

Theorem 3.5.

For every T>0T>0, there exists a unique uTcanNAexp,nn1(P)u_{T}^{\mathrm{can}}\in\mathcal{M}_{\mathrm{NA}}^{\exp,\frac{n}{n-1}}(P) which minimizes F𝒫(T,)F_{\mathcal{P}}(T,\bullet), while for T=0T=0, there exists a unique u0canNAexp,nn1(P)u_{0}^{\mathrm{can}}\in\mathcal{M}_{\mathrm{NA}}^{\exp,\frac{n}{n-1}}(P) which satisfies the following

  • u0canu_{0}^{\mathrm{can}} minimizes F𝒫(0,)=U𝒫()F_{\mathcal{P}}(0,\bullet)=U_{\mathcal{P}}(\bullet) and

  • S𝒫(u0can)=max{S𝒫(u)|U𝒫(u)=minU𝒫()}S_{\mathcal{P}}(u_{0}^{\mathrm{can}})=\max\{S_{\mathcal{P}}(u)~{}|~{}U_{\mathcal{P}}(u)=\min U_{\mathcal{P}}(\bullet)\}.

Proof.

For T>0T>0, if we have two minimizers u0u1NAexp,1(P)u_{0}\neq u_{1}\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(P) of F𝒫(T,)F_{\mathcal{P}}(T,\bullet), we get F𝒫(T,12u0+12u1)<F𝒫(T,u0)=minF𝒫(T,)F_{\mathcal{P}}(T,\frac{1}{2}u_{0}+\frac{1}{2}u_{1})<F_{\mathcal{P}}(T,u_{0})=\min F_{\mathcal{P}}(T,\bullet) by the strict convexity, which contradicts to the assumption on uiu_{i}.

Similarly, for T=0T=0, if u0u1u_{0}\neq u_{1} satisfy the above two conditions, then 12u0+12u1\frac{1}{2}u_{0}+\frac{1}{2}u_{1} satisfy the first condition by affinity of U𝒫U_{\mathcal{P}}, while we have S𝒫(12u0+12u1)>S𝒫(u0)S_{\mathcal{P}}(\frac{1}{2}u_{0}+\frac{1}{2}u_{1})>S_{\mathcal{P}}(u_{0}), which is a contradiction. The existence of u0canu_{0}^{\mathrm{can}} satisfying the two conditions is another application of our compactness: by Corollary 2.8 and the lower semi-continuity of U𝒫U_{\mathcal{P}}, the set

{uNAexp,1(P)|U𝒫(u)=minU𝒫}\{u\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(P)~{}|~{}U_{\mathcal{P}}(u)=\min U_{\mathcal{P}}\}

is compact in L1+ϵL^{1+\epsilon}-topology, hence we can find a minimizer u0canu_{0}^{\mathrm{can}} of U𝒫U_{\mathcal{P}} which maximizes S𝒫S_{\mathcal{P}} among all minimizers of U𝒫U_{\mathcal{P}} thanks to the continuity of S𝒫S_{\mathcal{P}} with respect to L1+ϵL^{1+\epsilon}-topology. ∎

Let us adopt terminologies from physics for later discussion.

Definition 3.6 (μ\mu-canonical distribution, ground states, optimizer).

We call the above uTcanu_{T}^{\mathrm{can}} the μ\mu-canonical distribution of temperature T0T\geq 0. For T=0T=0, we call minimizers of F𝒫(0,)=U𝒫()F_{\mathcal{P}}(0,\bullet)=U_{\mathcal{P}}(\bullet) ground states. We also call loguTcan+const.NAexp,1(P)\log u_{T}^{\mathrm{can}}+\text{const.}\in\mathcal{E}_{\mathrm{NA}}^{\exp,1}(P) the optimizer for 𝝁ˇNA2πT\bm{\check{\mu}}_{\mathrm{NA}}^{-2\pi T}.

The following is a natural question.

Question 3.7.

Are all ground states are μ\mu-canonical?

3.1.3. Family over T[0,]T\in[0,\infty]

Let uTcanu_{T}^{\mathrm{can}} be the μ\mu-canonical distribution for T0T\geq 0 as in Theorem 3.5. We firstly observe the following generality.

Proposition 3.8.

Let 𝒫\mathcal{P} be a general system. The function F𝒫(T,uTcan)F_{\mathcal{P}}(T,u_{T}^{\mathrm{can}}) is increasing and concave, and the functions U𝒫(uTcan),S𝒫(uTcan)U_{\mathcal{P}}(u_{T}^{\mathrm{can}}),S_{\mathcal{P}}(u_{T}^{\mathrm{can}}) are increasing on T0T\geq 0. Moreover, we have

limTS𝒫(uTcan)=0.\lim_{T\to\infty}S_{\mathcal{P}}(u_{T}^{\mathrm{can}})=0.
Proof.

The infimum of concave functions is concave, so that

F𝒫(T,uTcan)=minu{U𝒫(u)TS𝒫(u)}F_{\mathcal{P}}(T,u_{T}^{\mathrm{can}})=\min_{u}\{U_{\mathcal{P}}(u)-TS_{\mathcal{P}}(u)\}

is concave. Since S𝒫(u)0-S_{\mathcal{P}}(u)\geq 0, each U𝒫(u)TS𝒫(u)U_{\mathcal{P}}(u)-TS_{\mathcal{P}}(u) is increasing, so that F𝒫(T,uTcan)F_{\mathcal{P}}(T,u_{T}^{\mathrm{can}}) is increasing.

To see that S𝒫(uTcan)S_{\mathcal{P}}(u_{T}^{\mathrm{can}}) is increasing, we compute

F𝒫(T,uTcan)F𝒫(T,uTcan)\displaystyle F_{\mathcal{P}}(T,u_{T}^{\mathrm{can}})\leq F_{\mathcal{P}}(T,u_{T^{\prime}}^{\mathrm{can}}) =F𝒫(T,uTcan)+(TT)S𝒫(uTcan)\displaystyle=F_{\mathcal{P}}(T^{\prime},u_{T^{\prime}}^{\mathrm{can}})+(T^{\prime}-T)S_{\mathcal{P}}(u_{T^{\prime}}^{\mathrm{can}})
F𝒫(T,uTcan)+(TT)S𝒫(uTcan)\displaystyle\leq F_{\mathcal{P}}(T^{\prime},u_{T}^{\mathrm{can}})+(T^{\prime}-T)S_{\mathcal{P}}(u_{T^{\prime}}^{\mathrm{can}})
=F𝒫(T,uTcan)+(TT)(S𝒫(uTcan)S𝒫(uTcan)),\displaystyle=F_{\mathcal{P}}(T,u_{T}^{\mathrm{can}})+(T^{\prime}-T)(S_{\mathcal{P}}(u_{T^{\prime}}^{\mathrm{can}})-S_{\mathcal{P}}(u_{T}^{\mathrm{can}})),

which shows

(TT)(S𝒫(uTcan)S𝒫(uTcan))0.(T^{\prime}-T)(S_{\mathcal{P}}(u_{T^{\prime}}^{\mathrm{can}})-S_{\mathcal{P}}(u_{T}^{\mathrm{can}}))\geq 0.

For TT0T^{\prime}\geq T\geq 0, we compute

U𝒫(uTcan)\displaystyle U_{\mathcal{P}}(u_{T}^{\mathrm{can}}) =F𝒫(T,uTcan)+TS𝒫(uTcan)\displaystyle=F_{\mathcal{P}}(T,u_{T}^{\mathrm{can}})+TS_{\mathcal{P}}(u_{T}^{\mathrm{can}})
F𝒫(T,uTcan)+TS𝒫(uTcan)=U𝒫(uTcan)+T(S𝒫(uTcan)S𝒫(uTcan))\displaystyle\leq F_{\mathcal{P}}(T,u_{T^{\prime}}^{\mathrm{can}})+TS_{\mathcal{P}}(u_{T}^{\mathrm{can}})=U_{\mathcal{P}}(u_{T^{\prime}}^{\mathrm{can}})+T(S_{\mathcal{P}}(u_{T}^{\mathrm{can}})-S_{\mathcal{P}}(u_{T^{\prime}}^{\mathrm{can}}))
U𝒫(uTcan),\displaystyle\leq U_{\mathcal{P}}(u_{T^{\prime}}^{\mathrm{can}}),

which shows the monotonicity for U𝒫U_{\mathcal{P}}.

Now we note we have the following uniform bounds:

F𝒫(T,uTcan)\displaystyle F_{\mathcal{P}}(T,u_{T}^{\mathrm{can}}) F𝒫(T,1P)=U𝒫(1𝒫),\displaystyle\leq F_{\mathcal{P}}(T,1_{P})=U_{\mathcal{P}}(1_{\mathcal{P}}),
S𝒫(uTcan)\displaystyle S_{\mathcal{P}}(u_{T}^{\mathrm{can}}) 0,\displaystyle\leq 0,
U𝒫(uTcan)\displaystyle U_{\mathcal{P}}(u_{T}^{\mathrm{can}}) =F𝒫(T,uTcan)+TS𝒫(uTcan)\displaystyle=F_{\mathcal{P}}(T,u_{T}^{\mathrm{can}})+TS_{\mathcal{P}}(u_{T}^{\mathrm{can}})
F𝒫(T,1P)=U𝒫(1P).\displaystyle\leq F_{\mathcal{P}}(T,1_{P})=U_{\mathcal{P}}(1_{P}).

It then follows by monotonicity that the limits of these exist as TT tends to \infty.

Since we have

(3.6) U𝒫(1P)=F𝒫(T,1P)\displaystyle U_{\mathcal{P}}(1_{P})=F_{\mathcal{P}}(T,1_{P}) F𝒫(T,uTcan)=U𝒫(uTcan)TS𝒫(uTcan)\displaystyle\geq F_{\mathcal{P}}(T,u_{T}^{\mathrm{can}})=U_{\mathcal{P}}(u_{T}^{\mathrm{can}})-TS_{\mathcal{P}}(u_{T}^{\mathrm{can}})
U𝒫(u0can)TS𝒫(uTcan),\displaystyle\geq U_{\mathcal{P}}(u_{0}^{\mathrm{can}})-TS_{\mathcal{P}}(u_{T}^{\mathrm{can}}),

we get

0TS𝒫(uTcan)U𝒫(u0)U𝒫(1P)0\geq TS_{\mathcal{P}}(u_{T}^{\mathrm{can}})\geq U_{\mathcal{P}}(u_{0})-U_{\mathcal{P}}(1_{P})

for every T0T\geq 0. It follows that

limTS𝒫(uTcan)=0.\lim_{T\to\infty}S_{\mathcal{P}}(u_{T}^{\mathrm{can}})=0.

Using the compactness we established, we further obtain the following.

Theorem 3.9.

Let 𝒫\mathcal{P} be a system. The map

[0,]NAexp,nn1(P):T{uTcanT[0,)1PT=[0,\infty]\to\mathcal{M}_{\mathrm{NA}}^{\exp,\frac{n}{n-1}}(P):T\mapsto\begin{cases}u_{T}^{\mathrm{can}}&T\in[0,\infty)\\ 1_{P}&T=\infty\end{cases}

is continuous with respect to LpL^{p}-topology for every p[1,nn1)p\in[1,\frac{n}{n-1}) with continuous F𝒫(T,uTcan),U𝒫(uTcan),S𝒫(uTcan)F_{\mathcal{P}}(T,u_{T}^{\mathrm{can}}),U_{\mathcal{P}}(u_{T}^{\mathrm{can}}),S_{\mathcal{P}}(u_{T}^{\mathrm{can}}). Furthermore, we have

limTF𝒫(T,uTcan)=limTU𝒫(uTcan)=U𝒫(1P),\lim_{T\to\infty}F_{\mathcal{P}}(T,u_{T}^{\mathrm{can}})=\lim_{T\to\infty}U_{\mathcal{P}}(u_{T}^{\mathrm{can}})=U_{\mathcal{P}}(1_{P}),
limTTS𝒫(uTcan)=0.\lim_{T\to\infty}TS_{\mathcal{P}}(u_{T}^{\mathrm{can}})=0.
Proof.

As we see in the above proof, we have U𝒫(uTcan)U𝒫(1P)U_{\mathcal{P}}(u_{T}^{\mathrm{can}})\leq U_{\mathcal{P}}(1_{P}), so by Corollary 2.8 the family {uTcan}T[0,)\{u_{T}^{\mathrm{can}}\}_{T\in[0,\infty)} is relatively compact in LpL^{p}-topology for p[1,nn1)p\in[1,\frac{n}{n-1}).

Take a convergent sequence TiT[0,]\infty\neq T_{i}\to T_{\infty}\in[0,\infty] and a subsequence Ti(j)T_{i(j)} so that uTi(j)canuu_{T_{i(j)}}^{\mathrm{can}}\to u in LpL^{p}-topology to some uNAexp,1(P)u\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(P). We show the limit is uTcanu_{T}^{\mathrm{can}} for T[0,)T\in[0,\infty) and 1P1_{P} for T=T=\infty, independent of the choice of subsequence.

Assume T[0,)T_{\infty}\in[0,\infty). By the lower semi-continuity, we get

lim infjF𝒫(Ti(j),uTi(j)can)=lim infjF𝒫(T,uTi(j)can)F𝒫(T,u).\liminf_{j\to\infty}F_{\mathcal{P}}(T_{i(j)},u_{T_{i(j)}}^{\mathrm{can}})=\liminf_{j\to\infty}F_{\mathcal{P}}(T_{\infty},u_{T_{i(j)}}^{\mathrm{can}})\geq F_{\mathcal{P}}(T_{\infty},u).

For any uNAexp,1(P)u^{\prime}\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(P), we compute

F𝒫(T,u)=limjF𝒫(Ti(j),u)lim infjF𝒫(Ti(j),uTi(j)can)F𝒫(T,u),F_{\mathcal{P}}(T_{\infty},u^{\prime})=\lim_{j\to\infty}F_{\mathcal{P}}(T_{i(j)},u^{\prime})\geq\liminf_{j\to\infty}F_{\mathcal{P}}(T_{i(j)},u_{T_{i(j)}}^{\mathrm{can}})\geq F_{\mathcal{P}}(T_{\infty},u),

which shows the limit uu is a minimizer of F𝒫(T,)F_{\mathcal{P}}(T_{\infty},\bullet). This shows u=uTu=u_{T_{\infty}} for T>0T_{\infty}>0 by the uniqueness of minimizer.

Suppose T=0T_{\infty}=0 and uu0u\neq u_{0}. Then we have S𝒫(uTi(j)can)S𝒫(u)<S𝒫(u0can)S_{\mathcal{P}}(u_{T_{i(j)}}^{\mathrm{can}})\to S_{\mathcal{P}}(u)<S_{\mathcal{P}}(u_{0}^{\mathrm{can}}) by the uniqueness of μ\mu-canonical distribution. Take large j0j_{0} so that S𝒫(uTi(j)can)<S𝒫(u0can)S_{\mathcal{P}}(u_{T_{i(j)}}^{\mathrm{can}})<S_{\mathcal{P}}(u_{0}^{\mathrm{can}}) for jj0j\geq j_{0}, which contradicts to the fact that S𝒫(uTcan)S_{\mathcal{P}}(u_{T}^{\mathrm{can}}) is increasing. Thus we have u=u0canu=u_{0}^{\mathrm{can}} when T=0T_{\infty}=0.

Suppose T=T_{\infty}=\infty. By the above proposition, we have

S𝒫(u)=limS𝒫(uTi(j)can)=0.S_{\mathcal{P}}(u)=\lim S_{\mathcal{P}}(u_{T_{i(j)}}^{\mathrm{can}})=0.

This implies u=1Pu=1_{P} as 0 is the maximum value of S𝒫S_{\mathcal{P}} attained only at 1P1_{P}. Thus we proved the continuity of the family uTcanu_{T}^{\mathrm{can}} on [0,][0,\infty].

Now it follows that

U𝒫(1P)lim supTU𝒫(uTcan)lim infTU𝒫(uTcan)U𝒫(1P).U_{\mathcal{P}}(1_{P})\geq\limsup_{T\to\infty}U_{\mathcal{P}}(u_{T}^{\mathrm{can}})\geq\liminf_{T\to\infty}U_{\mathcal{P}}(u_{T}^{\mathrm{can}})\geq U_{\mathcal{P}}(1_{P}).

On the other hand, by (3.6), we have

0TS𝒫(uTcan)U𝒫(uTcan)U𝒫(1P)0,0\geq TS_{\mathcal{P}}(u_{T}^{\mathrm{can}})\geq U_{\mathcal{P}}(u_{T}^{\mathrm{can}})-U_{\mathcal{P}}(1_{P})\searrow 0,

which shows

limTTS𝒫(uTcan)=0.\lim_{T\to\infty}TS_{\mathcal{P}}(u_{T}^{\mathrm{can}})=0.

Putting these together, we obtain

limTF𝒫(T,uTcan)=0.\lim_{T\to\infty}F_{\mathcal{P}}(T,u_{T}^{\mathrm{can}})=0.

Since F𝒫(T,uTcan)F_{\mathcal{P}}(T,u_{T}^{\mathrm{can}}) is concave, it is continuous. Since S𝒫S_{\mathcal{P}} is continuous with respect to L1+ϵL^{1+\epsilon}-topology, S𝒫(uTcan)S_{\mathcal{P}}(u_{T}^{\mathrm{can}}) is continuous. Finally since U𝒫(uTcan)=F𝒫(T,uTcan)+TS𝒫(uTcan)U_{\mathcal{P}}(u_{T}^{\mathrm{can}})=F_{\mathcal{P}}(T,u_{T}^{\mathrm{can}})+TS_{\mathcal{P}}(u_{T}^{\mathrm{can}}), U𝒫(uTcan)U_{\mathcal{P}}(u_{T}^{\mathrm{can}}) is continuous on [0,)[0,\infty), while the continuity at T=T=\infty is already proved. ∎

As a sophisticated version of the extremal limit observation in [22, 24], we speculate the optimal destabilizer for normalized Donaldson–Futaki invariant appears in the rescaled limit.

Conjecture 3.10.

As TT\to\infty, the convex function qT:=TloguTcanq_{T}:=T\log u_{T}^{\mathrm{can}} converges at least in L2L^{2}-topology to an lsc convex function qextL2(P)q_{\mathrm{ext}}\in L^{2}(P) characterized as follows: qextq_{\mathrm{ext}} minimizes the following normalized Donaldson–Futaki invariant among all L2L^{2}-integrable convex functions on PP:

DF(q)q^L2=2πPq𝑑σ+s¯Pq𝑑μ(P(qq¯)2𝑑μ)1/2,\frac{\mathrm{DF}(q)}{\|\hat{q}\|_{L^{2}}}=\frac{2\pi\int_{\partial P}qd\sigma+\bar{s}\int_{P}qd\mu}{(\int_{P}(q-\bar{q})^{2}d\mu)^{1/2}},

where q¯=Pq𝑑μ/P𝑑μ\bar{q}=\int_{P}qd\mu/\int_{P}d\mu.

The existence of qextq_{\mathrm{ext}} is proved in [33]. For a non-negative optimizer q0q\geq 0 of 𝝁ˇNAλ\bm{\check{\mu}}_{\mathrm{NA}}^{\lambda}, we have 1p!qpeq\frac{1}{p!}q^{p}\leq e^{q} for every pp\in\mathbb{N}, so that qq is LpL^{p} for every p[1,)p\in[1,\infty). This regularity is much better than L2L^{2}-regularity of qextq_{\mathrm{ext}} proved in [33].

3.2. Consequences on μ\mu-cscK metric and μ\muK-stability

3.2.1. Uniqueness of μ\mu-cscK metrics on toric manifolds for λ0\lambda\leq 0

Now we see μλ\mu^{\lambda}-cscK metric determines optimizer. Note if we have a μλ\mu^{\lambda}-cscK metric ω\omega on toric manifold (X,L)T(X,L)\circlearrowleft T, we can take gAut(X,L)g\in\mathrm{Aut}(X,L) so that gωg^{*}\omega is a μξλ\mu^{\lambda}_{\xi}-cscK metric with ξLie(Tcpt)\xi\in\mathrm{Lie}(T_{\mathrm{cpt}}).

Theorem 3.11.

Assume λ0\lambda\leq 0. If a toric manifold (X,L)(X,L) admits a μξλ\mu^{\lambda}_{\xi}-cscK metric with ξLie(Tcpt)\xi\in\mathrm{Lie}(T_{\mathrm{cpt}}), then the linear map |ξ:P:μμ,ξ\ket{\xi}:P\to\mathbb{R}:\mu\mapsto\langle\mu,\xi\rangle is the optimizer of 𝝁ˇNAλ\bm{\check{\mu}}_{\mathrm{NA}}^{\lambda}. Here the metric is not necessarily a priori TcptT_{\mathrm{cpt}}-invariant.

Proof.

Suppose we have a μξλ\mu^{\lambda}_{\xi}-cscK metric ω\omega with ξLie(Tcpt)\xi\in\mathrm{Lie}(T_{\mathrm{cpt}}). It is proved in [24] (see also [25]) that |ξ\ket{\xi} is a maximizer of 𝝁ˇNAλ\bm{\check{\mu}}_{\mathrm{NA}}^{\lambda} for λ0\lambda\leq 0. Indeed, we have

𝝁ˇNAλ(|ξ)maxq𝝁ˇNAλ(q)infωϕ𝝁Perλ(ωϕ)𝝁Perλ(ω),\bm{\check{\mu}}_{\mathrm{NA}}^{\lambda}(\ket{\xi})\leq\max_{q}\bm{\check{\mu}}_{\mathrm{NA}}^{\lambda}(q)\leq\inf_{\omega_{\phi}}\bm{\mu}_{\mathrm{Per}}^{\lambda}(\omega_{\phi})\leq\bm{\mu}_{\mathrm{Per}}^{\lambda}(\omega),

and for λ0\lambda\leq 0 we have

𝝁Perλ(ω)=𝝁ˇNAλ(|ξ).\bm{\mu}_{\mathrm{Per}}^{\lambda}(\omega)=\bm{\check{\mu}}_{\mathrm{NA}}^{\lambda}(\ket{\xi}).

This proves the claim for λ<0\lambda<0.

To see that |ξ\ket{\xi} is the optimizer for λ=0\lambda=0, we perturb the μξ0\mu^{0}_{\xi}-cscK metric ω\omega to μξλλ\mu^{\lambda}_{\xi_{\lambda}}-cscK metrics ωλ\omega_{\lambda} for λ(ϵ,0)\lambda\in(-\epsilon,0) as in the construction in [22], which is just an application of implicit function theorem. We obviously have ξλξ\xi_{\lambda}\to\xi as λ0\lambda\to 0 by the construction. We already know |ξλ\ket{\xi_{\lambda}} are the optimizers. By Theorem 3.9, we conclude |ξ=limλ0|ξλ\ket{\xi}=\lim_{\lambda\to 0}\ket{\xi_{\lambda}} is also the optimizer. ∎

By the uniqueness of optimizers of 𝝁ˇNAλ\bm{\check{\mu}}_{\mathrm{NA}}^{\lambda} for λ0\lambda\leq 0, we conclude the vectors ξ,ξ\xi,\xi^{\prime} associated to μλ\mu^{\lambda}-cscK metrics ω,ω\omega,\omega^{\prime} are conjugate. Then thanks to the result [28] on the uniqueness of μξλ\mu^{\lambda}_{\xi}-cscK metric for fixed ξ\xi, we obtain Theorem 1.6. Here we mention it again.

Corollary 3.12.

Assume λ0\lambda\leq 0. On a toric manifold, μλ\mu^{\lambda}-cscK metrics are unique modulo the action of automorphism group.

3.2.2. Toric μ\muK-semistability is μ\mu-entropy maximization

Theorem 3.13.

A toric variety (X,L)(X,L) is toric μξλ\mu^{\lambda}_{\xi}K-semistable for λ0\lambda\leq 0 if and only if the linear map |ξ:P\ket{\xi}:P\to\mathbb{R} maximizes 𝝁ˇNAλ\bm{\check{\mu}}_{\mathrm{NA}}^{\lambda}.

Proof.

Thanks to (1.16), (X,L)(X,L) is μξλ\mu^{\lambda}_{\xi}K-semistable if |ξ\ket{\xi} maximizes 𝝁ˇNAλ\bm{\check{\mu}}_{\mathrm{NA}}^{\lambda}.

Suppose (X,L)(X,L) is μξλ\mu^{\lambda}_{\xi}K-semistable for λ0\lambda\leq 0. Take a continuous convex function q:Pq:P\to\mathbb{R}. For the log linear exp path

qt:=log((1t)e|ξ+tPe|ξ𝑑μPeq𝑑μeq)NAexp,1(P),q_{t}:=\log((1-t)e^{\ket{\xi}}+t\frac{\int_{P}e^{\ket{\xi}}d\mu}{\int_{P}e^{q}d\mu}e^{q})\in\mathcal{E}_{\mathrm{NA}}^{\exp,1}(P),

we compute

ddtqt=Pe|ξ𝑑μPeq𝑑μeqe|ξ(1t)e|ξ+tPe|ξ𝑑μPeq𝑑μeq.\frac{d}{dt}q_{t}=\frac{\frac{\int_{P}e^{\ket{\xi}}d\mu}{\int_{P}e^{q}d\mu}e^{q}-e^{\ket{\xi}}}{(1-t)e^{\ket{\xi}}+t\frac{\int_{P}e^{\ket{\xi}}d\mu}{\int_{P}e^{q}d\mu}e^{q}}.

Since ddtq:P×[0,1]\frac{d}{dt}q_{\bullet}:P\times[0,1]\to\mathbb{R} is a continuous function, its absolute value is bounded from above by a uniform constant, so that we can compute

ddt|t=0𝝁ˇNAλ(qt)\displaystyle\frac{d}{dt}\Big{|}_{t=0}\bm{\check{\mu}}_{\mathrm{NA}}^{\lambda}(q_{t}) =Futξλ(ddt|t=0qt)=Pe|ξ𝑑μPeq𝑑μFutξλ(eq|ξ).\displaystyle=-\mathrm{Fut}^{\lambda}_{\xi}(\frac{d}{dt}\Big{|}_{t=0}q_{t})=-\frac{\int_{P}e^{\ket{\xi}}d\mu}{\int_{P}e^{q}d\mu}\mathrm{Fut}^{\lambda}_{\xi}(e^{q-\ket{\xi}}).

By Fenchel–Moreau theorem, we can take an increasing sequence 0uiNA(P)0\leq u_{i}\in\mathcal{H}_{\mathrm{NA}}(P) so that it converges to eq|ξe^{q-\ket{\xi}} pointwiesly. By monotone convergence theorem, we get

0Pe|ξ𝑑μPuie|ξ𝑑μFutξλ(ui)Pe|ξ𝑑μPeq𝑑μFutξλ(eq|ξ).0\leq\frac{\int_{P}e^{\ket{\xi}}d\mu}{\int_{P}u_{i}e^{\ket{\xi}}d\mu}\mathrm{Fut}^{\lambda}_{\xi}(u_{i})\to\frac{\int_{P}e^{\ket{\xi}}d\mu}{\int_{P}e^{q}d\mu}\mathrm{Fut}^{\lambda}_{\xi}(e^{q-\ket{\xi}}).

Therefore, the μξλ\mu^{\lambda}_{\xi}K-semistability implies

ddt|t=0𝝁ˇNAλ(qt)0.\frac{d}{dt}\Big{|}_{t=0}\bm{\check{\mu}}_{\mathrm{NA}}^{\lambda}(q_{t})\leq 0.

Since 𝝁ˇNAλ\bm{\check{\mu}}_{\mathrm{NA}}^{\lambda} is concave, we get 𝝁ˇNAλ(q)𝝁ˇNAλ(|ξ)\bm{\check{\mu}}_{\mathrm{NA}}^{\lambda}(q)\leq\bm{\check{\mu}}_{\mathrm{NA}}^{\lambda}(\ket{\xi}) for continuous qq.

For general qNAexp,1(P)q\in\mathcal{E}_{\mathrm{NA}}^{\exp,1}(P), if Peq𝑑σ=\int_{\partial P}e^{q}d\sigma=\infty, we obviously have =𝝁ˇNAλ(q)𝝁ˇNAλ(|ξ)-\infty=\bm{\check{\mu}}_{\mathrm{NA}}^{\lambda}(q)\leq\bm{\check{\mu}}_{\mathrm{NA}}^{\lambda}(\ket{\xi}). If Peq𝑑σ<\int_{\partial P}e^{q}d\sigma<\infty, take an increasing sequence qiNA(P)q_{i}\in\mathcal{H}_{\mathrm{NA}}(P) converging to qq pointwisely. Then by the monotone convergence theorem we get 𝝁ˇNAλ(qi)𝝁ˇNAλ(q)\bm{\check{\mu}}_{\mathrm{NA}}^{\lambda}(q_{i})\to\bm{\check{\mu}}_{\mathrm{NA}}^{\lambda}(q). This shows 𝝁ˇNAλ(q)𝝁ˇNAλ(|ξ)\bm{\check{\mu}}_{\mathrm{NA}}^{\lambda}(q)\leq\bm{\check{\mu}}_{\mathrm{NA}}^{\lambda}(\ket{\xi}) for general qNAexp,1(P)q\in\mathcal{E}_{\mathrm{NA}}^{\exp,1}(P). ∎

In particular for λ<0\lambda<0, a toric variety (X,L)(X,L) can be μξλ\mu^{\lambda}_{\xi}K-semistable at most one ξ𝔱\xi\in\mathfrak{t}. The following remark further implies a similar conclusion for λ=0\lambda=0 under μξλ\mu^{\lambda}_{\xi}K-polystability assumption.

Remark 3.14.

For λ=0\lambda=0, we can also compute directly

Futξ(eq|ξ)=Peq𝑑μPe|ξ𝑑μ(𝝁ˇNA(|ξ)𝝁ˇNA(q))\mathrm{Fut}_{\xi}(e^{q-\ket{\xi}})=\frac{\int_{P}e^{q}d\mu}{\int_{P}e^{\ket{\xi}}d\mu}(\bm{\check{\mu}}_{\mathrm{NA}}(\ket{\xi})-\bm{\check{\mu}}_{\mathrm{NA}}(q))

for qNAexp,1(P)q\in\mathcal{E}_{\mathrm{NA}}^{\exp,1}(P) with Peq𝑑σ<\int_{\partial P}e^{q}d\sigma<\infty.

Corollary 3.15.

For λ=0\lambda=0, if a toric variety (X,L)(X,L) is toric μξ\mu_{\xi}K-polystable with respect to NAnn1(P):=Conv(P)Lnn1(P)\mathcal{E}_{\mathrm{NA}}^{\frac{n}{n-1}}(P):=\mathrm{Conv}(P)\cap L^{\frac{n}{n-1}}(P), then ground states are unique and hence |ξ\ket{\xi} is the optimizer for 𝝁ˇNA\bm{\check{\mu}}_{\mathrm{NA}}.

Proof.

Suppose 𝝁ˇNA(q)=max𝝁ˇNA=𝝁ˇNA(|ξ)\bm{\check{\mu}}_{\mathrm{NA}}(q)=\max\bm{\check{\mu}}_{\mathrm{NA}}=\bm{\check{\mu}}_{\mathrm{NA}}(\ket{\xi}) for qNAexp,1(P)q\in\mathcal{E}_{\mathrm{NA}}^{\exp,1}(P). Since Peq𝑑σ<\int_{\partial P}e^{q}d\sigma<\infty, we have eq|ξConv(P)Lnn1(P)e^{q-\ket{\xi}}\in\mathrm{Conv}(P)\cap L^{\frac{n}{n-1}}(P). By the above remark, we have Futξ(eq|ξ)=0\mathrm{Fut}_{\xi}(e^{q-\ket{\xi}})=0, which implies q=|ξq=\ket{\xi} by our μξ\mu_{\xi}K-polystability assumption. ∎

3.3. Ground state in dimension 2 is bounded

As we have noted in Remark 1.9, a rational piecewise affine convex function on toric polytope realizes an algebro-geometric degeneration of toric variety: X𝒳0X\leadsto\mathcal{X}_{0}. In comparison with [4, 36], the best regularity we can expect for maximizer of 𝝁ˇNAλ\bm{\check{\mu}}_{\mathrm{NA}}^{\lambda} would be piecewise affinity. As noted in [21, 4] in the context of Kähler–Ricci soliton, this conjecture is deeply related to moduli theory for polarized varieties. To appreciate its extreme importance, we refer to this conjecture as crystal conjecture.

Conjecture 3.16 (μ\mu-entropy maximizer is crystalline).

Let 𝒫\mathcal{P} be a system. Then for each λ\lambda\in\mathbb{R}, every maximizer qq of 𝝁ˇNAλ\bm{\check{\mu}}_{\mathrm{NA}}^{\lambda} is piecewise affine.

Remark 3.17.

For a rational piecewise affine function qq, the base polytope of an affine component of qq (the image of a facet of Q𝔱×Q\subset\mathfrak{t}^{\vee}\times\mathbb{R} contained in the roof {(x,q(x))|xP}Q\{(x,-q(x))~{}|~{}x\in P\}\subset Q along the projection QPQ\to P) is rational and realizes an irreducible component of the central fibre 𝒳0\mathcal{X}_{0} of the associated test configuration.

On the other hand, for an non-rational piecewise affine function qq, the base polytope of an affine component of qq might be not rational. (In this case, the filtration on the graded ring R(X,L)=mH0(X,Lm)R(X,L)=\bigoplus_{m}H^{0}(X,L^{\otimes m}) associated to qq as in [25] would be not finitely generated. ) This implicates the category of algebraic scheme might be insufficient to realize qq in a geometric way. The author speculates there would be a nice category of spaces extending that of algebraic schemes in which we can realize optimizer of 𝝁ˇNAλ\bm{\check{\mu}}_{\mathrm{NA}}^{\lambda} in a geometric way. We do not pursue this further in this article, but we just refer to [26] as a hint for “extended toric geometry” on non-rational polytope/fan.

We have proved in the existence theorem that the exponential eqe^{q} of a maximizer qq is Lnn1L^{\frac{n}{n-1}}-intergable. To approach crystal conjecture, we confirm the continuity of maximizer for λ=0\lambda=0 in dimension 2.

Theorem 3.18.

Let 𝒫\mathcal{P} be a 22-dimensional system. Then every maximizer qNAexp,1(P)q\in\mathcal{E}_{\mathrm{NA}}^{\exp,1}(P) of 𝝁ˇNA\bm{\check{\mu}}_{\mathrm{NA}} is bounded and continuous.

We firstly observe every maximizer qq of 𝝁ˇNA\bm{\check{\mu}}_{\mathrm{NA}} is equal to

(3.7) q~:=sup{:affine||Pq|P}.\displaystyle\tilde{q}:=\sup\{\ell:\text{affine}~{}|~{}\ell|_{\partial P}\leq q|_{\partial P}\}.

Indeed, recall firstly

q=q^:=sup{:affine|q}q=\hat{q}:=\sup\{\ell:\text{affine}~{}|~{}\ell\leq q\}

for any lsc convex function qq by Fenchel–Moreau theorem. Since we obviously have q^q~\hat{q}\leq\tilde{q}, we get

q|P=q^|Pq~|Pq|Pq|_{\partial P}=\hat{q}|_{\partial P}\leq\tilde{q}|_{\partial P}\leq q|_{\partial P}

and hence q~|P=q|P\tilde{q}|_{\partial P}=q|_{\partial P} for any lsc convex function qq. If qq~q\neq\tilde{q}, we have qq~q\leq\tilde{q} and q|Bq~|Bεq|_{B}\leq\tilde{q}|_{B}-\varepsilon for small ε>0\varepsilon>0 on a small ball BPB\subset P^{\circ}. Then we compute

12π𝝁ˇNA(q)=Peq𝑑σPeq𝑑μPeq~𝑑σPBeq~𝑑μ+Beq~ε𝑑μ>Peq~𝑑σPeq~𝑑μ=12π𝝁ˇNA(q~),-\frac{1}{2\pi}\bm{\check{\mu}}_{\mathrm{NA}}(q)=\frac{\int_{\partial P}e^{q}d\sigma}{\int_{P}e^{q}d\mu}\geq\frac{\int_{\partial P}e^{\tilde{q}}d\sigma}{\int_{P\setminus B}e^{\tilde{q}}d\mu+\int_{B}e^{\tilde{q}-\varepsilon}d\mu}>\frac{\int_{\partial P}e^{\tilde{q}}d\sigma}{\int_{P}e^{\tilde{q}}d\mu}=-\frac{1}{2\pi}\bm{\check{\mu}}_{\mathrm{NA}}(\tilde{q}),

so that qq does not maximize 𝝁ˇNA\bm{\check{\mu}}_{\mathrm{NA}}.

In what follows, we consider convex function qq\not\equiv\infty of the form q=q~q=\tilde{q}. Take a vertex vPv\in P. For hh\in\mathbb{R}, we consider

(3.8) qv,h:=sup{:affine||Pq|P,(v)h}q.\displaystyle q_{v,h}:=\sup\{\ell:\text{affine}~{}|~{}\ell|_{\partial P}\leq q|_{\partial P},\ell(v)\leq h\}\leq q.

We will show if q(v)=q(v)=\infty then we can find large hh and small θ(0,1)\theta\in(0,1) so that 𝝁ˇNA(q)<𝝁ˇNA(qv,h,θ)\bm{\check{\mu}}_{\mathrm{NA}}(q)<\bm{\check{\mu}}_{\mathrm{NA}}(q_{v,h,\theta}) for qv,h,θ:=(1θ)q+θqv,hq_{v,h,\theta}:=(1-\theta)q+\theta q_{v,h}. For the computation, we observe a concrete description of qv,hq_{v,h}.

Lemma 3.19.

Suppose q=q~q=\tilde{q} as above. Let E0=vv0¯,E1=vv1¯PE^{0}=\overline{vv^{0}},E^{1}=\overline{vv^{1}}\subset\partial P be the edges (dimension one face) containing vv. Assume for each i=0,1i=0,1 the right differential t+q((1t)v+tvi)\partial_{t+}q((1-t)v+tv^{i}) diverges to -\infty as t0t\to 0, which is the case for instance when q(v)=q(v)=\infty.

Then for h<q(v)h<q(v) sufficiently colse to q(v)q(v), there exists a unique affine function h\ell_{h} on PP such that h(v)=h\ell_{h}(v)=h, hq\ell_{h}\leq q on PP and h(pi)=q(pi)\ell_{h}(p^{i})=q(p^{i}) for some piEivp^{i}\in E^{i}\setminus v for each i=0,1i=0,1. Moreover, we have h\ell\leq\ell_{h} for any affine function \ell on PP satisfying (v)=h\ell(v)=h and q\ell\leq q.

Proof.

Observe for each ii, there exists a unique affine function hi\ell^{i}_{h} on the edge EiE^{i} such that hi(v)=h\ell^{i}_{h}(v)=h, hiq|Ei\ell^{i}_{h}\leq q|_{E^{i}} and hi(pi)=q(pi)\ell^{i}_{h}(p^{i})=q(p^{i}) for some point piEivp^{i}\in E^{i}\setminus v. Thanks to hi((1t)v+tpi)=(1t)h+tq(pi)\ell^{i}_{h}((1-t)v+tp^{i})=(1-t)h+tq(p^{i}), we have ihi{\ell^{i}}^{\prime}\leq\ell^{i}_{h} for any other affine function i{\ell^{i}}^{\prime} on EiE^{i} satisfying i(v)=h{\ell^{i}}^{\prime}(v)=h and iq|Ei{\ell^{i}}^{\prime}\leq q|_{E^{i}}.

Let h\ell_{h} be the affine function whose graph represents the plane spanned by the graphs of h0\ell^{0}_{h} and h1\ell^{1}_{h}. We clearly have h(v)=h\ell_{h}(v)=h. Let QQ\in\mathbb{R} be the minimum of q|Pq|_{\partial P}. By our assumption on qq, we have q(v)>Qq(v)>Q. Moreover, for th[0,1]t_{h}\in[0,1] with phi=(1th)v+thvip^{i}_{h}=(1-t_{h})v+t_{h}v^{i}, we have

t+hi((1t)v+tvi)t+q((1th)v+thvi),\partial_{t+}\ell^{i}_{h}((1-t)v+tv^{i})\leq\partial_{t+}q((1-t_{h})v+t_{h}v^{i}),

so that taking hQh\geq Q sufficiently close to q(v)q(v), we may assume hi(vi)Q\ell^{i}_{h}(v^{i})\leq Q. (Compare the subsequent lemma. It implies th0t_{h}\to 0 under our assumption, so that t+q((1th)v+thvi)\partial_{t+}q((1-t_{h})v+t_{h}v^{i})\to-\infty as hq(v)h\to q(v). ) This implies h|P(E0E1)Q\ell_{h}|_{\partial P\setminus(E^{0}\cup E^{1})}\leq Q, so that we get h|Pq|P\ell_{h}|_{\partial P}\leq q|_{\partial P}. It follows that hq~=q\ell_{h}\leq\tilde{q}=q.

Let \ell be an affine function on PP satisfying (v)=h\ell(v)=h and q\ell\leq q, which in particular implies |Eiq|Ei\ell|_{E^{i}}\leq q|_{E^{i}}. By the above remark, we have |Eihi\ell|_{E^{i}}\leq\ell^{i}_{h}, hence h\ell\leq\ell_{h} on PP. ∎

Since Fi:={xEiv|(qh)(x)=0}F^{i}:=\{x\in E^{i}\setminus v~{}|~{}(q-\ell_{h})(x)=0\} is closed, we have a unique point phiEivp^{i}_{h}\in E^{i}\setminus v which is closest to vv in FiF^{i}. For this point, we have the following.

Lemma 3.20.

Under the assumption in the above lemma, we have phivp^{i}_{h}\to v monotonically as hq(v)h\to q(v).

Proof.

This is visually clear, but we show it logically in order to check how our assumption on qq works. For hhh\leq h^{\prime}, we have

h(v)=hh=h(v),h(phi)q(phi)=h(phi),h(phi)=q(phi)h(phi),\ell_{h}(v)=h\leq h^{\prime}=\ell_{h^{\prime}}(v),~{}~{}\ell_{h}(p^{i}_{h^{\prime}})\leq q(p^{i}_{h^{\prime}})=\ell_{h^{\prime}}(p^{i}_{h^{\prime}}),~{}~{}\ell_{h}(p^{i}_{h})=q(p^{i}_{h})\geq\ell_{h^{\prime}}(p^{i}_{h}),

which implies the length of the segment vphi¯\overline{vp^{i}_{h^{\prime}}} is shorter than vphi¯\overline{vp^{i}_{h}}.

By the monotonicity, we have a limit point pq(v)i:=limhq(v)phiEip^{i}_{q(v)}:=\lim_{h\to q(v)}p^{i}_{h}\in E^{i}. Suppose pq(v)ivp^{i}_{q(v)}\neq v. Then taking the limit hh\to\infty of

(1t)h+tq(phi)=hi((1t)v+tphi)q((1t)v+tphi),(1-t)h+tq(p^{i}_{h})=\ell^{i}_{h}((1-t)v+tp^{i}_{h})\leq q((1-t)v+tp^{i}_{h}),

we get

(1t)q(v)+tq(pq(v)i)q((1t)v+tpq(v)i),(1-t)q(v)+tq(p^{i}_{q(v)})\leq q((1-t)v+tp^{i}_{q(v)}),

while

q((1t)v+tpq(v)i)(1t)q(v)+tq(pq(v)i)q((1-t)v+tp^{i}_{q(v)})\leq(1-t)q(v)+tq(p^{i}_{q(v)})

by convexity. This implies qq is affine on the segment vpq(v)i¯\overline{vp^{i}_{q(v)}}, which contradicts to our assumption. ∎

Lemma 3.21.

Under the above assumption, we have

qv,h(x)={h on the triangle vph0ph1q on Pvph0ph1.q_{v,h}(x)=\begin{cases}\ell_{h}&\text{ on the triangle }\triangle vp^{0}_{h}p^{1}_{h}\\ q&\text{ on }P\setminus\triangle vp^{0}_{h}p^{1}_{h}\end{cases}.
Proof.

For xPvph0ph1x\in P^{\circ}\setminus\triangle vp^{0}_{h}p^{1}_{h}, take an affine function x\ell_{x} so that xq\ell_{x}\leq q on PP and x(x)=q(x)\ell_{x}(x)=q(x). The two segments ph0ph1¯\overline{p^{0}_{h}p^{1}_{h}} and vx¯\overline{vx} crosses at a point pht=(1t)ph0+tph1ph0ph1¯p^{t}_{h}=(1-t)p^{0}_{h}+tp^{1}_{h}\in\overline{p^{0}_{h}p^{1}_{h}}. Since x(pht)q(pht)=h(pht)\ell_{x}(p^{t}_{h})\leq q(p^{t}_{h})=\ell_{h}(p^{t}_{h}) and x(x)=q(x)h(x)\ell_{x}(x)=q(x)\geq\ell_{h}(x), we have x(v)h(v)=h\ell_{x}(v)\leq\ell_{h}(v)=h. Then by

q(x)=x(x)qv,h(x)q(x),q(x)=\ell_{x}(x)\leq q_{v,h}(x)\leq q(x),

we get qv,h(x)=q(x)q_{v,h}(x)=q(x). By the lower semi-continuity, we have

qv,h|Pvph0ph1=q|Pvph0ph1.q_{v,h}|_{P\setminus\triangle vp^{0}_{h}p^{1}_{h}}=q|_{P\setminus\triangle vp^{0}_{h}p^{1}_{h}}.

Take an affine function \ell on PP so that q\ell\leq q and (v)h\ell(v)\leq h. For xvph0ph1vx\in\triangle vp^{0}_{h}p^{1}_{h}\setminus v, let phtph0ph1¯p^{t}_{h}\in\overline{p^{0}_{h}p^{1}_{h}} be the intersection point with the line spanned by the segment vx¯\overline{vx}. Since (v)h=h(v)\ell(v)\leq h=\ell_{h}(v) and (pht)q(pht)=q~(pht)=h(pht)\ell(p^{t}_{h})\leq q(p^{t}_{h})=\tilde{q}(p^{t}_{h})=\ell_{h}(p^{t}_{h}), we have (x)h(x)\ell(x)\leq\ell_{h}(x). It follows that qh(x)h(x)q_{h}(x)\leq\ell_{h}(x). On the other hand, we have qhhq_{h}\geq\ell_{h} on PP as h(v)=h\ell_{h}(v)=h and h|Pq|P\ell_{h}|_{\partial P}\leq q|_{\partial P}. On the other hand, we obviously have qh(v)=hq_{h}(v)=h. Thus we get qh(x)=h(x)q_{h}(x)=\ell_{h}(x) for xvph0ph1x\in\vartriangle vp^{0}_{h}p^{1}_{h}. ∎

Now we show the continuity. By [17] (or by an extension of the argument of (2.4)), every bounded convex function on a convex polytope is known to be upper semi-continuous. Since we assume the lower semi-continuity for qNAexp,1(P)q\in\mathcal{E}_{\mathrm{NA}}^{\exp,1}(P), it suffices to show the boundedness.

Proof of Theorem 3.18.

Let qq be a maximizer of 𝝁ˇNA\bm{\check{\mu}}_{\mathrm{NA}}. We may normalize qq so that q0q\geq 0. Suppose qq is unbounded, then we can find a vertex vPv\in P with q(v)=q(v)=\infty by an easy argument. For sufficiently large h0h\geq 0, we take qv,h,hq_{v,h},\ell_{h} and ph0,ph1p^{0}_{h},p^{1}_{h} as above. We note

μ(vph0ph1),σ(vph0¯),σ(vph1¯)0\mu(\triangle vp^{0}_{h}p^{1}_{h}),\sigma(\overline{vp^{0}_{h}}),\sigma(\overline{vp^{1}_{h}})\to 0

as hh\to\infty, while

μ(vph0ph1)σ(vph0¯)σ(vph1¯)\frac{\mu(\triangle vp^{0}_{h}p^{1}_{h})}{\sigma(\overline{vp^{0}_{h}})\sigma(\overline{vp^{1}_{h}})}

is constant.

We put

uh:=qqv,h={qh on the triangle vph0ph10 on Pvph0ph1.u_{h}:=q-q_{v,h}=\begin{cases}q-\ell_{h}&\text{ on the triangle }\triangle vp^{0}_{h}p^{1}_{h}\\ 0&\text{ on }P\setminus\triangle vp^{0}_{h}p^{1}_{h}\end{cases}.

We consider a map from [0,1]2[0,1]^{2} to vph0ph1\triangle vp_{h}^{0}p_{h}^{1} given by

(s;r)v+(1s)rvph0+srvph1vph0ph1.(s;r)\mapsto v+(1-s)r\overrightarrow{vp^{0}_{h}}+sr\overrightarrow{vp^{1}_{h}}\in\triangle vp^{0}_{h}p^{1}_{h}.

The measure dμ|vph0ph1d\mu|_{\triangle vp^{0}_{h}p^{1}_{h}} is transformed to 2μ(vph0ph1)rdrds2\mu(\triangle vp^{0}_{h}p^{1}_{h})rdrds on [0,1]2[0,1]^{2} and the measure dσ|vphi¯d\sigma|_{\overline{vp^{i}_{h}}} is transformed to σ(vphi¯)dr\sigma(\overline{vp^{i}_{h}})dr on {i}×[0,1]\{i\}\times[0,1].

Now we compute

Puheq𝑑μ\displaystyle\int_{P}u_{h}e^{q}d\mu vph0ph1uheq𝑑μ\displaystyle\leq\int_{\triangle vp^{0}_{h}p^{1}_{h}}u_{h}e^{q}d\mu
=2μ(vph0ph1)01𝑑rr01uh(s;r)eq(s;r)𝑑s\displaystyle=2\mu(\triangle vp^{0}_{h}p^{1}_{h})\int_{0}^{1}dr\cdot r\int_{0}^{1}u_{h}(s;r)e^{q(s;r)}ds
2μ(vph0ph1)01𝑑rremaxs[0,1]h(s;r)01uh(s;r)euh(s;r)𝑑s\displaystyle\leq 2\mu(\triangle vp^{0}_{h}p^{1}_{h})\int_{0}^{1}dr\cdot re^{\max_{s\in[0,1]}\ell_{h}(s;r)}\int_{0}^{1}u_{h}(s;r)e^{u_{h}(s;r)}ds
2μ(vph0ph1)01𝑑rremax{h(0;r),h(1;r)}01{(1s)uh(0;r)euh(0;r)+suh(1;r)euh(1;r)}𝑑s\displaystyle\leq 2\mu(\triangle vp^{0}_{h}p^{1}_{h})\int_{0}^{1}dr\cdot re^{\max\{\ell_{h}(0;r),\ell_{h}(1;r)\}}\int_{0}^{1}\{(1-s)u_{h}(0;r)e^{u_{h}(0;r)}+su_{h}(1;r)e^{u_{h}(1;r)}\}ds
μ(vph0ph1)01𝑑rremax{h(0;r),h(1;r)}{uh(0;r)euh(0;r)+uh(1;r)euh(1;r)}.\displaystyle\leq\mu(\triangle vp^{0}_{h}p^{1}_{h})\int_{0}^{1}dr\cdot re^{\max\{\ell_{h}(0;r),\ell_{h}(1;r)\}}\{u_{h}(0;r)e^{u_{h}(0;r)}+u_{h}(1;r)e^{u_{h}(1;r)}\}.

Assume max{h(0;1),h(1;1)}=h(0;1)\max\{\ell_{h}(0;1),\ell_{h}(1;1)\}=\ell_{h}(0;1), we have max{h(0;r),h(1;r)}=h(0;r)\max\{\ell_{h}(0;r),\ell_{h}(1;r)\}=\ell_{h}(0;r) for every rr, then we further compute

Puheq𝑑μ\displaystyle\int_{P}u_{h}e^{q}d\mu μ(vph0ph1)01𝑑rreh(0;r){uh(0;r)euh(0;r)+uh(1;r)euh(1;r)}\displaystyle\leq\mu(\triangle vp^{0}_{h}p^{1}_{h})\int_{0}^{1}dr\cdot re^{\ell_{h}(0;r)}\{u_{h}(0;r)e^{u_{h}(0;r)}+u_{h}(1;r)e^{u_{h}(1;r)}\}
μ(vph0ph1)01𝑑r{uh(0;r)eq(0;r)+reh(0;r)uh(1;r)eq(1;r)}\displaystyle\leq\mu(\triangle vp^{0}_{h}p^{1}_{h})\int_{0}^{1}dr\cdot\{u_{h}(0;r)e^{q(0;r)}+re^{\ell_{h}(0;r)}u_{h}(1;r)e^{q(1;r)}\}
μ(vph0ph1){01uh(0;r)eq(0;r)𝑑r+01eq(0;r)𝑑r01uh(1;r)eq(1;r)𝑑r}\displaystyle\leq\mu(\triangle vp^{0}_{h}p^{1}_{h})\{\int_{0}^{1}u_{h}(0;r)e^{q(0;r)}dr+\int_{0}^{1}e^{q(0;r)}dr\cdot\int_{0}^{1}u_{h}(1;r)e^{q(1;r)}dr\}
μ(vph0ph1)σ(vph0¯)01uh(0;r)eq(0;r)σ(vph0¯)𝑑r\displaystyle\leq\frac{\mu(\triangle vp^{0}_{h}p^{1}_{h})}{\sigma(\overline{vp^{0}_{h}})}\int_{0}^{1}u_{h}(0;r)e^{q(0;r)}\sigma(\overline{vp^{0}_{h}})dr
+μ(vph0ph1)σ(vph0¯)σ(vph1¯)01eq(0;r)σ(vph0¯)𝑑r01uh(1;r)eq(1;r)σ(vph1¯)𝑑r\displaystyle\qquad+\frac{\mu(\triangle vp^{0}_{h}p^{1}_{h})}{\sigma(\overline{vp^{0}_{h}})\sigma(\overline{vp^{1}_{h}})}\int_{0}^{1}e^{q(0;r)}\sigma(\overline{vp^{0}_{h}})dr\cdot\int_{0}^{1}u_{h}(1;r)e^{q(1;r)}\sigma(\overline{vp^{1}_{h}})dr
=μ(vph0ph1)σ(vph0¯)E0uheq𝑑σ|E0\displaystyle=\frac{\mu(\triangle vp^{0}_{h}p^{1}_{h})}{\sigma(\overline{vp^{0}_{h}})}\int_{E^{0}}u_{h}e^{q}d\sigma|_{E^{0}}
+μ(vph0ph1)σ(vph0¯)σ(vph1¯)vph0¯eq𝑑σ|vph0¯E1uheq𝑑σ|E1,\displaystyle\qquad+\frac{\mu(\triangle vp^{0}_{h}p^{1}_{h})}{\sigma(\overline{vp^{0}_{h}})\sigma(\overline{vp^{1}_{h}})}\int_{\overline{vp^{0}_{h}}}e^{q}d\sigma|_{\overline{vp^{0}_{h}}}\cdot\int_{E^{1}}u_{h}e^{q}d\sigma|_{E^{1}},

where the third inequality follows by

reh(0;r)01eh(0;r)𝑑r01eq(0;r)𝑑r.re^{\ell_{h}(0;r)}\leq\int_{0}^{1}e^{\ell_{h}(0;r)}dr\leq\int_{0}^{1}e^{q(0;r)}dr.

Fix hh large so that

μ(vph0ph1)σ(vph0¯),μ(vph0ph1)σ(vph0¯)σ(vph1¯)vph0¯eq𝑑σ|vph0¯<(Peq𝑑μPeq𝑑σ)1.\frac{\mu(\triangle vp^{0}_{h}p^{1}_{h})}{\sigma(\overline{vp^{0}_{h}})},\frac{\mu(\triangle vp^{0}_{h}p^{1}_{h})}{\sigma(\overline{vp^{0}_{h}})\sigma(\overline{vp^{1}_{h}})}\int_{\overline{vp^{0}_{h}}}e^{q}d\sigma|_{\overline{vp^{0}_{h}}}<\Big{(}\frac{\int_{\partial P}e^{q}d\mu}{\int_{P}e^{q}d\sigma}\Big{)}^{-1}.

Then for qθ:=(1θ)q+θqhq_{\theta}:=(1-\theta)q+\theta q_{h}, we compute

ddθ|θ=0Peqθ𝑑σPeqθ𝑑μ\displaystyle\frac{d}{d\theta}\Big{|}_{\theta=0}\frac{\int_{\partial P}e^{q_{\theta}}d\sigma}{\int_{P}e^{q_{\theta}}d\mu} =ddθ|θ=0Peqθuh𝑑σPeqθuh𝑑μ\displaystyle=\frac{d}{d\theta}\Big{|}_{\theta=0}\frac{\int_{\partial P}e^{q-\theta u_{h}}d\sigma}{\int_{P}e^{q-\theta u_{h}}d\mu}
=1Peq𝑑μ(Puheq𝑑σ+Peq𝑑σPeq𝑑μPuheq𝑑μ)\displaystyle=\frac{1}{\int_{P}e^{q}d\mu}\Big{(}-\int_{\partial P}u_{h}e^{q}d\sigma+\frac{\int_{\partial P}e^{q}d\sigma}{\int_{P}e^{q}d\mu}\int_{P}u_{h}e^{q}d\mu\Big{)}
<1Peq𝑑μ(Puheq𝑑σ+E0uheq𝑑σ|E0+E1uheq𝑑σ|E1)\displaystyle<\frac{1}{\int_{P}e^{q}d\mu}\Big{(}-\int_{\partial P}u_{h}e^{q}d\sigma+\int_{E^{0}}u_{h}e^{q}d\sigma|_{E^{0}}+\int_{E^{1}}u_{h}e^{q}d\sigma|_{E^{1}}\Big{)}
=0,\displaystyle=0,

which shows

Peqθ𝑑σPeqθ𝑑μ<Peq𝑑σPeq𝑑μ\frac{\int_{\partial P}e^{q_{\theta}}d\sigma}{\int_{P}e^{q_{\theta}}d\mu}<\frac{\int_{\partial P}e^{q}d\sigma}{\int_{P}e^{q}d\mu}

for sufficiently small θ\theta. This contradicts to the assumption that qq is a maximizer of 𝝁ˇNA\bm{\check{\mu}}_{\mathrm{NA}}. The case max{h(0;1),h(1;1)}=h(1;1)\max\{\ell_{h}(0;1),\ell_{h}(1;1)\}=\ell_{h}(1;1) is similar. Thus qq must be bounded.

4. Thermodynamical structure

To appreciate the results of this section, let us briefly recall how the parameter λ\lambda appeared in the beginning [22] of μ\mu-cscK metric. The notion of μ\mu-cscK metric was introduced in [22] based on the moment map picture on Kähler–Ricci soliton observed in [21]. Given a symplectic manifold (M,ω)(M,\omega) with a Hamiltonian vector field ξ\xi, the space of ξ\xi-invariant almost complex structures 𝒥ξ(M,ω)\mathcal{J}_{\xi}(M,\omega) possesses a symplectic structure Ωξ\Omega_{\xi} and a moment map 𝒮ξ:𝒥ξ(M,ω)𝔥𝔞𝔪ξ(M,ω)\mathcal{S}_{\xi}:\mathcal{J}_{\xi}(M,\omega)\to\mathfrak{ham}_{\xi}(M,\omega)^{\vee} with respect to the action of ξ\xi-compatible Hamiltonian diffeomorphism group Hamξ(M,ω)\mathrm{Ham}_{\xi}(M,\omega). These are dependent on ξ\xi. The Hamiltonian potential μξ:M\mu_{\xi}:M\to\mathbb{R} of ξ\xi defines an element μξ|\bra{\mu_{\xi}} of 𝔥𝔞𝔪ξ(M,ω)\mathfrak{ham}_{\xi}(M,\omega)^{\vee} fixed by the coadjoint action, so that 𝒮ξ+λμξ|\mathcal{S}_{\xi}+\lambda\bra{\mu_{\xi}} gives another moment map for the same symplectic structure Ωξ\Omega_{\xi}. If we choose [ω]=T1c1(M,ω)[\omega]=-T^{-1}c_{1}(M,\omega) and λ=2πT\lambda=-2\pi T (T<0T<0), the symplectic reduction (Sξ+λμξ|)1(0)/Hamξ(M,ω)(S_{\xi}+\lambda\bra{\mu_{\xi}})^{-1}(0)/\mathrm{Ham}_{\xi}(M,\omega) can be interpreted as the moduli space of Kähler–Ricci soliton (cf. [21]).

At this point, there are at least two points of view to extend the theory of Kähler–Ricci soliton to general polarized manifold:

  1. (1)

    Determine the “best” λ=λ(X,L)\lambda=\lambda(X,L) for a given polarized manifold (X,L)(X,L) so that all things go well like Kähler–Ricci soliton. At least for a Fano manifold (X,L)=(X,T1KX)(X,L)=(X,-T^{-1}K_{X}), it would be λ=2πT\lambda=-2\pi T.

  2. (2)

    Regard λ\lambda\in\mathbb{R} as a free parameter in the theory and construct our theory for any λ\lambda\in\mathbb{R} as much as possible.

Nakagawa [31] takes the first stance, but it turns out in [22] that the latter perspective is more fruitful than the first one: the product μ\mu-cscK metrics behaves well for the same λ\lambda, extremal metric appears in the limit λ\lambda\to-\infty and so on. Moreover, contrary to the theory on Kähler–Ricci soliton, the general theory works well for λ0\lambda\leq 0 rather than λ>0\lambda>0. In any case, the parameter λ\lambda was just introduced at first as a free parameter which enriches the theory. Its geometric role was unclear.

Here we show our theory carries a thermodynamical sturcture for T=λ2π0T=-\frac{\lambda}{2\pi}\geq 0. It gives us a better geometric intuition on our enigmatic parameter TT and also implicates the geometry of μ\mu-cscK metric and μ\muK-stability is of infinite dimensional nature: it is the geometry of a composition of the space of our interest and an infinite dimensional space working as heat bath. This is reminiscent of Perelman’s statistical mechanical heuristic argument [32] on his WW-entropy.

4.1. Optimizer for product

Mutual interaction of thermodynamical systems is a key concept in thermodynamics. Mathematically, it is described as a process (or its terminal state) on the product (or tensor product, in quantum setup) of two systems 𝒫1,𝒫2\mathcal{P}_{1},\mathcal{P}_{2}. Let us begin with the simplest case: mutual interaction of isothermal systems.

For two systems 𝒫1=(P1,dμ1,dσ1)\mathcal{P}_{1}=(P_{1},d\mu_{1},d\sigma_{1}), 𝒫2=(P2,dμ2,dσ2)\mathcal{P}_{2}=(P_{2},d\mu_{2},d\sigma_{2}), we consider the following composite system

𝒫1×𝒫2:=(P1×P2,dμ1×dμ2,dσ1dσ2),\mathcal{P}_{1}\times\mathcal{P}_{2}:=(P_{1}\times P_{2},d\mu_{1}\times d\mu_{2},d\sigma_{1}\boxplus d\sigma_{2}),

where dμ1×dμ2d\mu_{1}\times d\mu_{2} denotes the product measure and dσ1dσ2d\sigma_{1}\boxplus d\sigma_{2} denotes the measure on (P1×P2)=P1×P2P2×P2\partial(P_{1}\times P_{2})=\partial P_{1}\times P_{2}\cup P_{2}\times\partial P_{2} given by

dσ1×dμ2+dμ1×dσ2.d\sigma_{1}\times d\mu_{2}+d\mu_{1}\times d\sigma_{2}.

We call 𝒫1,𝒫2\mathcal{P}_{1},\mathcal{P}_{2} subsystems of this composite system.

Theorem 4.1.

For T0T\geq 0, the μ\mu-canonical distribution uTcanNAexp,1(P1×P2)u^{\mathrm{can}}_{T}\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(P_{1}\times P_{2}) of temperature TT on the composyte system 𝒫1×𝒫2\mathcal{P}_{1}\times\mathcal{P}_{2} is the product

uTcan=u1×u2u^{\mathrm{can}}_{T}=u_{1}\times u_{2}

of the μ\mu-canonical distributions u1NAexp,1(P1),u2NAexp,1(P2)u_{1}\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(P_{1}),u_{2}\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(P_{2}) of the same temperature TT on the subsystems 𝒫1,𝒫2\mathcal{P}_{1},\mathcal{P}_{2}, respectively.

Proof.

For uNAexp,1(P1×P2)u\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(P_{1}\times P_{2}), we define a function uiu_{i} on PiP_{i} by

(4.1) u1(x)\displaystyle u_{1}(x) :=1P2𝑑μ2P2u(x,y)𝑑μ2(y),\displaystyle:=\frac{1}{\int_{P_{2}}d\mu_{2}}\int_{P_{2}}u(x,y)d\mu_{2}(y),
(4.2) u2(y)\displaystyle u_{2}(y) :=1P1𝑑μ1P1u(x,y)𝑑μ1(x).\displaystyle:=\frac{1}{\int_{P_{1}}d\mu_{1}}\int_{P_{1}}u(x,y)d\mu_{1}(x).

These are non-zero log convex functions by Hölder’s inequality, lower semi-continuous by Fatou’s lemma and P1u1𝑑μ1=P1𝑑μ1,P2u2𝑑μ2=P2𝑑μ2\int_{P_{1}}u_{1}d\mu_{1}=\int_{P_{1}}d\mu_{1},\int_{P_{2}}u_{2}d\mu_{2}=\int_{P_{2}}d\mu_{2} by Fubini’s theorem, so that u1NAexp,1(P1)u_{1}\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(P_{1}) and u2NAexp,1(P2)u_{2}\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(P_{2}). If uu is of the form u=u×u′′u=u^{\prime}\times u^{\prime\prime} for uNAexp,1(P1)u^{\prime}\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(P_{1}) and u′′NAexp,1(P2)u^{\prime\prime}\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(P_{2}), we have u1=uu_{1}=u^{\prime} and u2=u′′u_{2}=u^{\prime\prime}.

Now we compute

(P1×P2)u𝑑σ\displaystyle\int_{\partial(P_{1}\times P_{2})}ud\sigma =P1P2u𝑑μ2𝑑σ1+P2P1u𝑑μ1𝑑σ2\displaystyle=\int_{\partial P_{1}}\int_{P_{2}}ud\mu_{2}d\sigma_{1}+\int_{\partial P_{2}}\int_{P_{1}}ud\mu_{1}d\sigma_{2}
=P2𝑑μ2P1u1𝑑σ1+P1𝑑μ1P2u2𝑑σ2,\displaystyle=\int_{P_{2}}d\mu_{2}\cdot\int_{\partial P_{1}}u_{1}d\sigma_{1}+\int_{P_{1}}d\mu_{1}\cdot\int_{\partial P_{2}}u_{2}d\sigma_{2},

which shows

(4.3) U𝒫1×𝒫2(u)=U𝒫1(u1)+U𝒫2(u2).\displaystyle U_{\mathcal{P}_{1}\times\mathcal{P}_{2}}(u)=U_{\mathcal{P}_{1}}(u_{1})+U_{\mathcal{P}_{2}}(u_{2}).

This implies if uu minimizes U𝒫1×𝒫2U_{\mathcal{P}_{1}\times\mathcal{P}_{2}}, then uiu_{i} minimizes U𝒫iU_{\mathcal{P}_{i}} for each i=1,2i=1,2.

On the other hand, we have

(4.4) S𝒫1×𝒫2(u)S𝒫1(u1)+S𝒫2(u2)\displaystyle S_{\mathcal{P}_{1}\times\mathcal{P}_{2}}(u)\leq S_{\mathcal{P}_{1}}(u_{1})+S_{\mathcal{P}_{2}}(u_{2})

with the equality only when u=u1×u2u=u_{1}\times u_{2}. This is a paraphrase of the non-negativity of mutual information known in information theory. We can prove this as follows. Put dp~=udμ1×dμ2/P1×P2u𝑑μ1×𝑑μ2d\tilde{p}=ud\mu_{1}\times d\mu_{2}/\int_{P_{1}\times P_{2}}ud\mu_{1}\times d\mu_{2}, dp~1=u1dμ1/P1u1𝑑μ1d\tilde{p}_{1}=u_{1}d\mu_{1}/\int_{P_{1}}u_{1}d\mu_{1} and dp~2=u2dμ2/P2u2𝑑μ2d\tilde{p}_{2}=u_{2}d\mu_{2}/\int_{P_{2}}u_{2}d\mu_{2}. Then we have

P1×P2dp~dp~1dp~2logdp~dp~1dp~2dp~1dp~20\displaystyle\int_{P_{1}\times P_{2}}\frac{d\tilde{p}}{d\tilde{p}_{1}d\tilde{p}_{2}}\log\frac{d\tilde{p}}{d\tilde{p}_{1}d\tilde{p}_{2}}d\tilde{p}_{1}d\tilde{p}_{2}\geq 0

by Jensen’s inequality, where the equality holds if and only if dp~=dp~1×dp~2d\tilde{p}=d\tilde{p}_{1}\times d\tilde{p}_{2}. For dp=dμ/P1×P2𝑑μdp=d\mu/\int_{P_{1}\times P_{2}}d\mu, dp1=dμ1/P1𝑑μ1dp_{1}=d\mu_{1}/\int_{P_{1}}d\mu_{1} and dp2=dμ2/P2𝑑μ2dp_{2}=d\mu_{2}/\int_{P_{2}}d\mu_{2}, a simple calculation shows

P1×P2dp~dp~1dp~2logdp~dp~1dp~2dp~1dp~2\displaystyle\int_{P_{1}\times P_{2}}\frac{d\tilde{p}}{d\tilde{p}_{1}d\tilde{p}_{2}}\log\frac{d\tilde{p}}{d\tilde{p}_{1}d\tilde{p}_{2}}d\tilde{p}_{1}d\tilde{p}_{2} =P1×P2dp~dp1dp2logdp~dp1dp2dp1dp2\displaystyle=\int_{P_{1}\times P_{2}}\frac{d\tilde{p}}{dp_{1}dp_{2}}\log\frac{d\tilde{p}}{dp_{1}dp_{2}}dp_{1}dp_{2}
P1dp~1dp1logdp~1dp1dp1P2dp~2dp2logdp~2dp2dp2.\displaystyle-\int_{P_{1}}\frac{d\tilde{p}_{1}}{dp_{1}}\log\frac{d\tilde{p}_{1}}{dp_{1}}dp_{1}-\int_{P_{2}}\frac{d\tilde{p}_{2}}{dp_{2}}\log\frac{d\tilde{p}_{2}}{dp_{2}}dp_{2}.

The consequence is the inequality (4.4).

Now for T0T\geq 0, let uNAexp,1(P1),u′′NAexp,1(P2)u^{\prime}\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(P_{1}),u^{\prime\prime}\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(P_{2}) be the μ\mu-canonical distributions of temperature TT. Then for any uNAexp,1(P1×P2)u\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(P_{1}\times P_{2}), we have

F𝒫1×𝒫2(T,u)\displaystyle F_{\mathcal{P}_{1}\times\mathcal{P}_{2}}(T,u) F𝒫1(T,u1)+F𝒫2(T,u2)\displaystyle\geq F_{\mathcal{P}_{1}}(T,u_{1})+F_{\mathcal{P}_{2}}(T,u_{2})
F𝒫1(T,u)+F𝒫2(T,u′′)=F𝒫1×𝒫2(T,u×u′′),\displaystyle\geq F_{\mathcal{P}_{1}}(T,u^{\prime})+F_{\mathcal{P}_{2}}(T,u^{\prime\prime})=F_{\mathcal{P}_{1}\times\mathcal{P}_{2}}(T,u^{\prime}\times u^{\prime\prime}),

so that u×u′′u^{\prime}\times u^{\prime\prime} minimizes F𝒫1×𝒫2(T,)F_{\mathcal{P}_{1}\times\mathcal{P}_{2}}(T,\bullet), which shows the claim for T>0T>0 by the uniqueness of minimizer. On the other hand, if uu minimizes U𝒫1×𝒫2U_{\mathcal{P}_{1}\times\mathcal{P}_{2}}, then uiu_{i} minimizes U𝒫iU_{\mathcal{P}_{i}}, so that we compute

S𝒫1×𝒫2(u)S𝒫1(u1)+S𝒫2(u2)S𝒫1(u)+S𝒫2(u′′)=S𝒫1×𝒫2(u×u′′).S_{\mathcal{P}_{1}\times\mathcal{P}_{2}}(u)\leq S_{\mathcal{P}_{1}}(u_{1})+S_{\mathcal{P}_{2}}(u_{2})\leq S_{\mathcal{P}_{1}}(u^{\prime})+S_{\mathcal{P}_{2}}(u^{\prime\prime})=S_{\mathcal{P}_{1}\times\mathcal{P}_{2}}(u^{\prime}\times u^{\prime\prime}).

Now the uniqueness of μ\mu-canonical distribution completes the proof. ∎

4.2. Equilibrium and isothermality

Equilibrium and isothermality are fundamental notions in thermodynamics. To compare our argument, let us briefly recall how the notion of equilibrium is formalized in stochastic thermodynamics. In stochastic thermodynamics, a measure space (Ω,dμ)(\Omega,d\mu) (in a simple setup, a finite set with the counting measure) together with a function E:ΩE:\Omega\to\mathbb{R} called Hamiltonian is interpreted as a thermodynamical system, which serves as the space of possible (deterministic) states. A probability measure pp on Ω\Omega is interpreted as nonequilibrium state. Nonequilibrium entropy S(p)S(p) is defined by the relative entropy Ωdpdp0logdpdp0-\int_{\Omega}\frac{dp}{dp_{0}}\log\frac{dp}{dp_{0}} with respect to dp0=dμ/|Ω|dp_{0}=d\mu/|\Omega| and its nonequilibrium internal energy U(p)U(p) is defined by ΩE𝑑p\int_{\Omega}Edp. Equilibrium is described as entropy maximizer on a level set of internal energy.

By the method of Lagrange multiplier, we can describe equilibrium as critical point of βUS\beta U-S for a proper choice of β\beta\in\mathbb{R} depending on energy level. The critical state pcan(β)p_{\mathrm{can}}(\beta) can be written explicitly as

pcan(β)=eβEdμΩeβE𝑑μ,p_{\mathrm{can}}(\beta)=\frac{e^{-\beta E}d\mu}{\int_{\Omega}e^{-\beta E}d\mu},

which is well known as canonical distribution. We can apply a similar argument to non-archimedean μ\mu-entropy. We note maximizer of non-archimedean μ\mu-entropy has no simple explicit description, which is different from stochastic thermodynamics.

4.2.1. Equilibrium

Let 𝒫=(P,dμ,dσ)\mathcal{P}=(P,d\mu,d\sigma) be a system. For UU\in\mathbb{R}, we consider the energy level set:

(4.5) NAexp,1(𝒫,U):={uNAexp,1(P)|U𝒫(u)=U}.\displaystyle\mathcal{M}_{\mathrm{NA}}^{\exp,1}(\mathcal{P},U):=\{u\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(P)~{}|~{}U_{\mathcal{P}}(u)=U\}.

We call a state uNAexp,1(𝒫,U)u\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(\mathcal{P},U) equilibrium of internal μ\mu-energy UU if it maximizes the entropy S𝒫S_{\mathcal{P}} on the level set NAexp,1(𝒫,U)\mathcal{M}_{\mathrm{NA}}^{\exp,1}(\mathcal{P},U). For instance, the trivial state 1P1_{P} is equilibrium of internal μ\mu-energy U=U𝒫(1P)U=U_{\mathcal{P}}(1_{P}).

Our main interest is in the equilibrium of internal μ\mu-energy UU in the interval

(4.6) 𝔘𝒫:=[minU𝒫,U𝒫(1P)],\displaystyle\mathfrak{U}_{\mathcal{P}}:=[\min U_{\mathcal{P}},U_{\mathcal{P}}(1_{P})],

for which we can show the existence. We should note even though we have proved the compactness of the sublevel set UUNAexp,1(𝒫,U)\bigcup_{U\geq U^{\prime}}\mathcal{M}_{\mathrm{NA}}^{\exp,1}(\mathcal{P},U^{\prime}), we cannot conclude the compactness of the level set NAexp,1(𝒫,U)\mathcal{M}_{\mathrm{NA}}^{\exp,1}(\mathcal{P},U) as U𝒫U_{\mathcal{P}} is only lower semi-continuous, so the existence of equilibrium is not a direct consequence of our compactness result. We make use of the continuity of the family of μ\mu-canonical distributions uTcanu^{\mathrm{can}}_{T}, which is a consequence of the uniqueness.

Theorem 4.2.

Let 𝒫\mathcal{P} be a system. For U𝔘𝒫U\in\mathfrak{U}_{\mathcal{P}}, there exists a unique equilibrium ueq(U)u^{\mathrm{eq}}(U) of internal μ\mu-energy UU.

Proof.

The uniqueness of equilibrium follows by the affinity of U𝒫U_{\mathcal{P}} and the strict convexity of S𝒫S_{\mathcal{P}}. This is a general fact for UU\in\mathbb{R}.

As for U=minU𝒫U=\min U_{\mathcal{P}}, equilibrium of this internal μ\mu-energy is nothing but the μ\mu-canonical distribution of temperature T=0T=0, so we already proved the existence.

Now we assume U(minU𝒫,U𝒫(1P)]U\in(\min U_{\mathcal{P}},U_{\mathcal{P}}(1_{P})] and show the existence of equilibrium of internal μ\mu-energy UU. Recall we proved U𝒫(uTcan)U_{\mathcal{P}}(u_{T}^{\mathrm{can}}) for the μ\mu-canonical distribution uTcanu_{T}^{\mathrm{can}} is continuous on [0,][0,\infty] and its image is [minU𝒫,U𝒫(1P)][\min U_{\mathcal{P}},U_{\mathcal{P}}(1_{P})]. It follows that there is T(0,]T\in(0,\infty] satisfying U𝒫(uTcan)=UU_{\mathcal{P}}(u_{T}^{\mathrm{can}})=U, hence uTcanNAexp,1(𝒫,U)u_{T}^{\mathrm{can}}\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(\mathcal{P},U). For any other uNAexp,1(𝒫,U)u\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(\mathcal{P},U), we have

S𝒫(u)=1T(UF𝒫(T,u))1T(UF𝒫(T,uTcan))=S𝒫(uTcan),S_{\mathcal{P}}(u)=\frac{1}{T}(U-F_{\mathcal{P}}(T,u))\leq\frac{1}{T}(U-F_{\mathcal{P}}(T,u_{T}^{\mathrm{can}}))=S_{\mathcal{P}}(u_{T}^{\mathrm{can}}),

which shows uTcanu_{T}^{\mathrm{can}} is the equilibrium of internal μ\mu-energy UU. ∎

We recall a system 𝒫\mathcal{P} is called K-unstable if DF(q)<0\mathrm{DF}(q)<0 for some convex function qq. Thanks to Theorem 3.13, this is equivalent to say

(4.7) 𝔘𝒫:=[minU𝒫,U𝒫(1P))\displaystyle\mathfrak{U}_{\mathcal{P}}^{*}:=[\min U_{\mathcal{P}},U_{\mathcal{P}}(1_{P}))

is nonempty. For a system 𝒫1\mathcal{P}_{1} and a K-unstable system 𝒫2\mathcal{P}_{2}, we have 𝔘𝒫1+𝔘𝒫2=𝔘𝒫1×𝒫2\mathfrak{U}_{\mathcal{P}_{1}}+\mathfrak{U}_{\mathcal{P}_{2}}^{*}=\mathfrak{U}_{\mathcal{P}_{1}\times\mathcal{P}_{2}}^{*} for the Minkowski sum, and 𝔘𝒫1+𝔘𝒫2=𝔘𝒫1×𝒫2\mathfrak{U}_{\mathcal{P}_{1}}^{*}+\mathfrak{U}_{\mathcal{P}_{2}}^{*}=\mathfrak{U}_{\mathcal{P}_{1}\times\mathcal{P}_{2}}^{*} when further 𝒫1\mathcal{P}_{1} is K-unstable.

Now let 𝒫\mathcal{P} be a K-unstable system. By the monotonic continuity of U𝒫(uTcan)U_{\mathcal{P}}(u^{\mathrm{can}}_{T}), for each U𝔘𝒫U\in\mathfrak{U}_{\mathcal{P}}^{*}, the subset

(4.8) 𝕋𝒫can(U):={T[0,)|U𝒫(uTcan)=U}\displaystyle\mathbb{T}_{\mathcal{P}}^{\mathrm{can}}(U):=\{T\in[0,\infty)~{}|~{}U_{\mathcal{P}}(u_{T}^{\mathrm{can}})=U\}

is a nonempty compact interval of [0,)[0,\infty), which has only one element except for at most countably many U𝔘𝒫U\in\mathfrak{U}_{\mathcal{P}}^{*}. By the above proof, the μ\mu-canonical distribution of temperature T0T\geq 0 is the equilibrium of internal μ\mu-energy U𝔘𝒫U\in\mathfrak{U}_{\mathcal{P}}^{*} if and only if T𝕋𝒫can(U)T\in\mathbb{T}_{\mathcal{P}}^{\mathrm{can}}(U). Later we characterize this 𝕋𝒫can(U)\mathbb{T}_{\mathcal{P}}^{\mathrm{can}}(U) in terms of the equilibria ueq(U)u^{\mathrm{eq}}(U) rather than the μ\mu-canonical distributions uTcanu_{T}^{\mathrm{can}}.

By Remark 3.14, for any u=u(q)NAexp,1(P)u=u(q)\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(P) with U𝒫(u)𝔘𝒫U_{\mathcal{P}}(u)\in\mathfrak{U}_{\mathcal{P}}^{*}, we have

1Pu𝑑μDF(u)=2π(U𝒫(u)U𝒫(1P))<0.\frac{1}{\int_{P}ud\mu}\mathrm{DF}(u)=2\pi(U_{\mathcal{P}}(u)-U_{\mathcal{P}}(1_{P}))<0.

This allows us to interpret U𝒫U𝒫(1P)U_{\mathcal{P}}-U_{\mathcal{P}}(1_{P}) as “ability of destabilization” and equilibrium of internal μ\mu-energy U𝔘𝒫U\in\mathfrak{U}_{\mathcal{P}}^{*} as “the most balanced state among all states of the same ability of destabilization”.

4.2.2. Isothermality

We firstly began our theory with the enigmatic parameter TT called temperature, studied the minimization of F𝒫(T,)F_{\mathcal{P}}(T,\bullet) and finally reached the notion of equilibrium, which is a priori irrelevant to the parameter TT.

Now we can shift our perspective. According to the teaching of thermodynamics, we can rediscover the temperature TT at least in three essentially equivalent ways:

  1. (1)

    (Lagrange multiplier) 1/Teq(U)=(Seq/U)(U)1/T^{\mathrm{eq}}(U)=(\partial S^{\mathrm{eq}}/\partial U)(U).

  2. (2)

    (Mutual interaction) Mutual interaction with thermostat.

  3. (3)

    (Carnot theorem) The ratio of heats Q1/Q2Q_{1}/Q_{2} in Carnot cycle.

The aim of our observation is to understand the role of temperature TT and the free μ\mu-energy F𝒫(T,u)F_{\mathcal{P}}(T,u) in terms of mutual interaction.

Now consider equilibria u1,u2u_{1},u_{2} of internal μ\mu-energy U1,U2U_{1},U_{2} on systems 𝒫1,𝒫2\mathcal{P}_{1},\mathcal{P}_{2}, respectively. We are interested in comparing the product state u1×u2u_{1}\times u_{2} and the equilibrium uu of internal μ\mu-energy U1+U2U_{1}+U_{2} of the composite system 𝒫1×𝒫2\mathcal{P}_{1}\times\mathcal{P}_{2}. Since in general we have the strict inclusion

(4.9) NAexp,1(𝒫1,U1)×NAexp,1(𝒫2,U2)NAexp,1(𝒫1×𝒫2,U1+U2),\displaystyle\mathcal{M}_{\mathrm{NA}}^{\exp,1}(\mathcal{P}_{1},U_{1})\times\mathcal{M}_{\mathrm{NA}}^{\exp,1}(\mathcal{P}_{2},U_{2})\subsetneq\mathcal{M}_{\mathrm{NA}}^{\exp,1}(\mathcal{P}_{1}\times\mathcal{P}_{2},U_{1}+U_{2}),

the equilibrium uu of the composite system may differ from the initial interaction-free state u1×u2u_{1}\times u_{2}. In thermodynamics, this is known as thermalisation: the initial states are preserved under mutual interaction only when the systems are isothermal, otherwise, one subsystem is eventually warmed up and the other is cooled down.

Proposition 4.3.

Let uu be an equilibrium on the composite system 𝒫1×𝒫2\mathcal{P}_{1}\times\mathcal{P}_{2}. Then uiNAexp,1(Pi)u_{i}\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(P_{i}) defined by (4.1) and (4.2) are equilibria of subsystems 𝒫i\mathcal{P}_{i} and we have u=u1×u2u=u_{1}\times u_{2}.

Proof.

This is a consequence of (4.3) and (4.4). ∎

Definition 4.4.

Let u,u′′u^{\prime},u^{\prime\prime} be equilibria of two K-unstable systems 𝒫1,𝒫2\mathcal{P}_{1},\mathcal{P}_{2}, respectively. We say uu^{\prime} and u′′u^{\prime\prime} are isothermal if the product u×u′′u^{\prime}\times u^{\prime\prime} is the equilibrium of internal μ\mu-energy U𝒫1(u)+U𝒫2(u′′)U_{\mathcal{P}_{1}}(u^{\prime})+U_{\mathcal{P}_{2}}(u^{\prime\prime}) on the composite system 𝒫1×𝒫2\mathcal{P}_{1}\times\mathcal{P}_{2}.

Let us observe the isothermality is reflexive.

Lemma 4.5.

Let uu be an equilibrium of a system 𝒫\mathcal{P}. Then u×ku^{\times k} on 𝒫×k\mathcal{P}^{\times k} is the equilibrium of internal μ\mu-energy kU𝒫(u)kU_{\mathcal{P}}(u). In particular, u×ku^{\times k} and u×u^{\times\ell} are isothermal.

Proof.

Put U:=U𝒫(u)U:=U_{\mathcal{P}}(u). Let u~NAexp,1(P×k)\tilde{u}\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(P^{\times k}) be the equilibrium of internal μ\mu-energy kUkU. We put

u~i:=1P𝑑μPu~(x1,,xk)𝑑μ(xi).\displaystyle\tilde{u}_{i}:=\frac{1}{\int_{P}d\mu}\int_{P}\tilde{u}(x_{1},\ldots,x_{k})d\mu(x_{i}).

Suppose u~iu~j\tilde{u}_{i}\neq\tilde{u}_{j} for some i,ji,j. Then for u:=(u~1++u~k)/ku^{\prime}:=(\tilde{u}_{1}+\cdots+\tilde{u}_{k})/k, we have

U𝒫×k(u×k)\displaystyle U_{\mathcal{P}^{\times k}}({u^{\prime}}^{\times k}) =kU𝒫(u)=U𝒫(u~1)++U𝒫(u~k)=U𝒫×k(u~)=kU\displaystyle=kU_{\mathcal{P}}(u^{\prime})=U_{\mathcal{P}}(\tilde{u}_{1})+\cdots+U_{\mathcal{P}}(\tilde{u}_{k})=U_{\mathcal{P}^{\times k}}(\tilde{u})=kU
S𝒫×k(u×k)\displaystyle S_{\mathcal{P}^{\times k}}({u^{\prime}}^{\times k}) =kS𝒫(u)>S𝒫(u~1)++S𝒫(u~k)S𝒫×k(u~)\displaystyle=kS_{\mathcal{P}}(u^{\prime})>S_{\mathcal{P}}(\tilde{u}_{1})+\cdots+S_{\mathcal{P}}(\tilde{u}_{k})\geq S_{\mathcal{P}^{\times k}}(\tilde{u})

by the strict concavity of S𝒫S_{\mathcal{P}}. This contradicts to the assumption that u~\tilde{u} is the maximizer of S𝒫×kS_{\mathcal{P}^{\times k}} on NAexp,1(𝒫×k,kU)\mathcal{M}_{\mathrm{NA}}^{\exp,1}(\mathcal{P}^{\times k},kU). Thus we have u~i=u~j=u\tilde{u}_{i}=\tilde{u}_{j}=u for every i,ji,j and u~=u×k\tilde{u}=u^{\times k}, which shows the claim. ∎

We expect the isothermality is an equivalence relation for pairs (𝒫,U)(\mathcal{P},U), which in thermodynamics is assumed by the zeroth law. (Observe this is not true if we include K-stable systems. ) To see the transitivity, we need strict monotonicity of the canonical entropy S𝒫can(T)=S𝒫(uTcan)S_{\mathcal{P}}^{\mathrm{can}}(T)=S_{\mathcal{P}}(u^{\mathrm{can}}_{T}) on T0T\geq 0, but what we know at present is monotonicity in a weak sense.

We will prove the strict monotonicity under a slightly better regularity assumption on optimizer. Before discussing it, we observe the Lagrange multiplier interpretation of temperature.

4.2.3. Equilibrium temperature as Lagrange multiplier

Let 𝒫\mathcal{P} be a system. For UU\in\mathbb{R}, we put

(4.10) S𝒫eq(U):=sup{S𝒫(u)|uNAexp,1(𝒫,U)}.\displaystyle S_{\mathcal{P}}^{\mathrm{eq}}(U):=\sup\{S_{\mathcal{P}}(u)~{}|~{}u\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(\mathcal{P},U)\}.

We note S𝒫eq(U)=S_{\mathcal{P}}^{\mathrm{eq}}(U)=-\infty on U<minU𝒫U<\min U_{\mathcal{P}}. The following superadditivity is clear from (4.9):

(4.11) S𝒫1×𝒫2eq(U1+U2)S𝒫1eq(U1)+S𝒫2eq(U2).\displaystyle S_{\mathcal{P}_{1}\times\mathcal{P}_{2}}^{\mathrm{eq}}(U_{1}+U_{2})\geq S_{\mathcal{P}_{1}}^{\mathrm{eq}}(U_{1})+S_{\mathcal{P}_{2}}^{\mathrm{eq}}(U_{2}).

For general U1,U2U_{1},U_{2}\in\mathbb{R}, we say pairs (𝒫1,U1)(\mathcal{P}_{1},U_{1}) and (𝒫2,U2)(\mathcal{P}_{2},U_{2}) are isothermal if

S𝒫1×𝒫2eq(U1+U2)=S𝒫1eq(U1)+S𝒫2eq(U2).S_{\mathcal{P}_{1}\times\mathcal{P}_{2}}^{\mathrm{eq}}(U_{1}+U_{2})=S_{\mathcal{P}_{1}}^{\mathrm{eq}}(U_{1})+S_{\mathcal{P}_{2}}^{\mathrm{eq}}(U_{2}).

This definition makes sense even when there is no equilibria of internal μ\mu-energy UiU_{i}. When Ui𝔘𝒫U_{i}\in\mathfrak{U}_{\mathcal{P}}, this definition is equivalent to the former definition: the equality holds if and only if the equilibria u1,u2u_{1},u_{2} of internal μ\mu-energy U1,U2U_{1},U_{2} on 𝒫1,𝒫2\mathcal{P}_{1},\mathcal{P}_{2}, respectively, are isothermal. In particular, we have

S𝒫×keq(kU)=kS𝒫eq(U)S_{\mathcal{P}^{\times k}}^{\mathrm{eq}}(kU)=kS_{\mathcal{P}}^{\mathrm{eq}}(U)

by Lemma 4.5.

Proposition 4.6.

The functional S𝒫eq(U)S_{\mathcal{P}}^{\mathrm{eq}}(U) is concave on UU\in\mathbb{R} whose maximum is achieved at U=U𝒫(1P)U=U_{\mathcal{P}}(1_{P}). Moreover, it is strictly concave and strictly increasing on the interval 𝔘𝒫\mathfrak{U}_{\mathcal{P}}.

Proof.

For t=p/(p+q),1t=q/(p+q)t=p/(p+q),1-t=q/(p+q) with p,qp,q\in\mathbb{N}, we compute

S𝒫eq((1t)U0+tU1)\displaystyle S_{\mathcal{P}}^{\mathrm{eq}}((1-t)U_{0}+tU_{1}) =1p+qS𝒫×(p+q)eq(qU0+pU1)\displaystyle=\frac{1}{p+q}S_{\mathcal{P}^{\times(p+q)}}^{\mathrm{eq}}(qU_{0}+pU_{1})
qp+qS𝒫eq(U0)+pp+qS𝒫eq(U1),\displaystyle\geq\frac{q}{p+q}S_{\mathcal{P}}^{\mathrm{eq}}(U_{0})+\frac{p}{p+q}S_{\mathcal{P}}^{\mathrm{eq}}(U_{1}),

which shows the concavity. This product trick is expressive of a thermodynamical intuition behind the concavity, though we present another proof in the following.

We can also see the concavity in a more direct way: for u0NAexp,1(𝒫,U0)u_{0}\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(\mathcal{P},U_{0}) and u1NAexp,1(𝒫,u1)u_{1}\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(\mathcal{P},u_{1}), we have (1t)u0+tu1NAexp,1(𝒫,(1t)U0+tU1)(1-t)u_{0}+tu_{1}\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(\mathcal{P},(1-t)U_{0}+tU_{1}), so that

S𝒫eq((1t)U0+tU1)\displaystyle S_{\mathcal{P}}^{\mathrm{eq}}((1-t)U_{0}+tU_{1}) =sup{S𝒫(u)|uNAexp,1(𝒫,(1t)U0+tU1)}\displaystyle=\sup\{S_{\mathcal{P}}(u)~{}|~{}u\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(\mathcal{P},(1-t)U_{0}+tU_{1})\}
sup{S𝒫((1t)u0+tu1)|uiNAexp,1(𝒫,Ui) for i=0,1}\displaystyle\geq\sup\{S_{\mathcal{P}}((1-t)u_{0}+tu_{1})~{}|~{}u_{i}\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(\mathcal{P},U_{i})\text{ for }i=0,1\}
sup{(1t)S𝒫(u0)+tS𝒫(u1)|uiNAexp,1(𝒫,Ui) for i=0,1}\displaystyle\geq\sup\{(1-t)S_{\mathcal{P}}(u_{0})+tS_{\mathcal{P}}(u_{1})~{}|~{}u_{i}\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(\mathcal{P},U_{i})\text{ for }i=0,1\}
=(1t)S𝒫eq(U0)+tS𝒫eq(U1).\displaystyle=(1-t)S_{\mathcal{P}}^{\mathrm{eq}}(U_{0})+tS_{\mathcal{P}}^{\mathrm{eq}}(U_{1}).

Since the last supremum is achieved for U0,U1[minU𝒫,U𝒫(1P)]U_{0},U_{1}\in[\min U_{\mathcal{P}},U_{\mathcal{P}}(1_{P})], the third inequality is strict for U0U1U_{0}\neq U_{1} and t0,1t\neq 0,1 by the strict concavity of S𝒫S_{\mathcal{P}}. The strict monotonicity is a consequence of strict concavity. ∎

By the concavity, the right and left differentials exist. We put

(4.12) β𝒫eq,+(U)\displaystyle\beta_{\mathcal{P}}^{\mathrm{eq},+}(U) :=U+S𝒫eq(U),T𝒫eq,+(U):=β𝒫eq,+(U)1,\displaystyle:=\partial_{U_{+}}S_{\mathcal{P}}^{\mathrm{eq}}(U),\quad T_{\mathcal{P}}^{\mathrm{eq},+}(U):=\beta_{\mathcal{P}}^{\mathrm{eq},+}(U)^{-1},
(4.13) β𝒫eq,(U)\displaystyle\beta_{\mathcal{P}}^{\mathrm{eq},-}(U) :=US𝒫eq(U),T𝒫eq,(U):=β𝒫eq,(U)1,\displaystyle:=\partial_{U_{-}}S_{\mathcal{P}}^{\mathrm{eq}}(U),\quad T_{\mathcal{P}}^{\mathrm{eq},-}(U):=\beta_{\mathcal{P}}^{\mathrm{eq},-}(U)^{-1},

which are right and left continuous, respectively. We further put

(4.14) 𝕋𝒫eq(U):=[T𝒫eq,(U),T𝒫eq,+(U)].\displaystyle\mathbb{T}_{\mathcal{P}}^{\mathrm{eq}}(U):=[T_{\mathcal{P}}^{\mathrm{eq},-}(U),T_{\mathcal{P}}^{\mathrm{eq},+}(U)].

For U<U𝔘𝒫U^{\prime}<U\in\mathfrak{U}_{\mathcal{P}}^{*}, we have

0=T𝒫eq,(minU𝒫)𝕋𝒫eq(U)<𝕋𝒫eq(U)<0=T_{\mathcal{P}}^{\mathrm{eq},-}(\min U_{\mathcal{P}})\leq\mathbb{T}_{\mathcal{P}}^{\mathrm{eq}}(U^{\prime})<\mathbb{T}_{\mathcal{P}}^{\mathrm{eq}}(U)<\infty

by the strict concavity, where for two intervals [a,b],[c,d][a,b],[c,d] we write [a,b][c,d][a,b]\leq[c,d] (resp. [a,b]<[c,d][a,b]<[c,d]) if bcb\leq c (resp. b<cb<c). Now we show the following.

Proposition 4.7.

Let 𝒫\mathcal{P} be K-unstable system. Then for U𝔘𝒫U\in\mathfrak{U}_{\mathcal{P}}^{*}, we have

𝕋𝒫can(U)=𝕋𝒫eq(U).\mathbb{T}_{\mathcal{P}}^{\mathrm{can}}(U)=\mathbb{T}_{\mathcal{P}}^{\mathrm{eq}}(U).
Proof.

Since 𝒫\mathcal{P} is K-unstable, for the μ\mu-canonical distribution uTcanu_{T}^{\mathrm{can}} of temperature T0T\geq 0, we have U𝒫(uTcan)<U𝒫(1P)U_{\mathcal{P}}(u_{T}^{\mathrm{can}})<U_{\mathcal{P}}(1_{P}): if U𝒫(uTcan)=U𝒫(1P)U_{\mathcal{P}}(u_{T}^{\mathrm{can}})=U_{\mathcal{P}}(1_{P}), we have uTcan=1Pu_{T}^{\mathrm{can}}=1_{P}, so that 𝒫\mathcal{P} is K-semistable. This implies

U𝔘𝒫𝕋𝒫can(U)=[0,).\bigsqcup_{U\in\mathfrak{U}_{\mathcal{P}}^{*}}\mathbb{T}_{\mathcal{P}}^{\mathrm{can}}(U)=[0,\infty).

By the monotonicity of U𝒫(uTcan)U_{\mathcal{P}}(u_{T}^{\mathrm{can}}), we have

𝕋𝒫can(U)<𝕋𝒫can(U)\mathbb{T}_{\mathcal{P}}^{\mathrm{can}}(U^{\prime})<\mathbb{T}_{\mathcal{P}}^{\mathrm{can}}(U)

for U<U𝔘𝒫U^{\prime}<U\in\mathfrak{U}_{\mathcal{P}}^{*}. It follows that

(4.15) limUU𝒫(1P)min𝕋𝒫can(U)=.\displaystyle\lim_{U\nearrow U_{\mathcal{P}}(1_{P})}\min\mathbb{T}_{\mathcal{P}}^{\mathrm{can}}(U)=\infty.

Indeed, if not, we have U𝒫(uTcan)U𝒫(1P)U_{\mathcal{P}}(u_{T}^{\mathrm{can}})\geq U_{\mathcal{P}}(1_{P}) for T>limUU𝒫(1P)min𝕋𝒫can(U)T>\lim_{U\nearrow U_{\mathcal{P}}(1_{P})}\min\mathbb{T}_{\mathcal{P}}^{\mathrm{can}}(U), which is a contradiction.

We observe

𝕋𝒫eq(U)𝕋𝒫can(U).\displaystyle\mathbb{T}_{\mathcal{P}}^{\mathrm{eq}}(U)\subset\mathbb{T}_{\mathcal{P}}^{\mathrm{can}}(U).

For β[β𝒫eq,+(U),β𝒫eq,(U)]\beta\in[\beta_{\mathcal{P}}^{\mathrm{eq},+}(U),\beta_{\mathcal{P}}^{\mathrm{eq},-}(U)] and UU^{\prime}\in\mathbb{R}, we have

S𝒫eq(U)β(UU)+S𝒫eq(U)S_{\mathcal{P}}^{\mathrm{eq}}(U^{\prime})\leq\beta(U-U^{\prime})+S_{\mathcal{P}}^{\mathrm{eq}}(U)

by concavity. Thus for β[β𝒫eq,+(U),β𝒫eq,(U)]\beta\in[\beta_{\mathcal{P}}^{\mathrm{eq},+}(U),\beta_{\mathcal{P}}^{\mathrm{eq},-}(U)], we have

Uβ1S𝒫eq(U)Uβ1S𝒫eq(U).U-\beta^{-1}S_{\mathcal{P}}^{\mathrm{eq}}(U)\leq U^{\prime}-\beta^{-1}S_{\mathcal{P}}^{\mathrm{eq}}(U^{\prime}).

Now suppose uu is the equilibrium of internal μ\mu-energy UU, then for another state uNAexp,1(P)u^{\prime}\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(P), we compute

F𝒫(β1,u)\displaystyle F_{\mathcal{P}}(\beta^{-1},u) =Uβ1S𝒫eq(U)\displaystyle=U-\beta^{-1}S_{\mathcal{P}}^{\mathrm{eq}}(U)
U𝒫(u)β1S𝒫eq(U𝒫(u))U𝒫(u)β1S𝒫(u)F𝒫(β1,u).\displaystyle\leq U_{\mathcal{P}}(u^{\prime})-\beta^{-1}S_{\mathcal{P}}^{\mathrm{eq}}(U_{\mathcal{P}}(u^{\prime}))\leq U_{\mathcal{P}}(u^{\prime})-\beta^{-1}S_{\mathcal{P}}(u^{\prime})\leq F_{\mathcal{P}}(\beta^{-1},u^{\prime}).

Thus uu is the μ\mu-canonical distribution of temperature T=β1T=\beta^{-1} for T𝕋𝒫eq(U)T\in\mathbb{T}_{\mathcal{P}}^{\mathrm{eq}}(U), which shows 𝕋𝒫eq(U)𝕋𝒫can(U)\mathbb{T}_{\mathcal{P}}^{\mathrm{eq}}(U)\subset\mathbb{T}_{\mathcal{P}}^{\mathrm{can}}(U).

As a general property on left and right derivative of convex function, we have

U𝔘𝒫𝕋𝒫eq(U)=[0,limUU𝒫(1P)T𝒫eq,+(U)).\bigsqcup_{U\in\mathfrak{U}_{\mathcal{P}}^{*}}\mathbb{T}_{\mathcal{P}}^{\mathrm{eq}}(U)=[0,\lim_{U\nearrow U_{\mathcal{P}}(1_{P})}T_{\mathcal{P}}^{\mathrm{eq},+}(U)).

On the other hand, by 𝕋𝒫eq(U)𝕋𝒫can(U)\mathbb{T}_{\mathcal{P}}^{\mathrm{eq}}(U)\subset\mathbb{T}_{\mathcal{P}}^{\mathrm{can}}(U) and (4.15), we have

limUU𝒫(1P)T𝒫eq,+(U)limUU𝒫(1P)min𝕋𝒫can(U)=,\lim_{U\nearrow U_{\mathcal{P}}(1_{P})}T_{\mathcal{P}}^{\mathrm{eq},+}(U)\geq\lim_{U\nearrow U_{\mathcal{P}}(1_{P})}\min\mathbb{T}_{\mathcal{P}}^{\mathrm{can}}(U)=\infty,

so that we get

U𝔘𝒫𝕋𝒫eq(U)=[0,).\bigsqcup_{U\in\mathfrak{U}_{\mathcal{P}}^{*}}\mathbb{T}_{\mathcal{P}}^{\mathrm{eq}}(U)=[0,\infty).

It follows that

U𝔘𝒫(𝕋𝒫can(U)𝕋𝒫eq(U))=U𝔘𝒫𝕋𝒫can(U)U𝔘𝒫𝕋𝒫eq(U)=,\bigsqcup_{U\in\mathfrak{U}_{\mathcal{P}}^{*}}(\mathbb{T}_{\mathcal{P}}^{\mathrm{can}}(U)\setminus\mathbb{T}_{\mathcal{P}}^{\mathrm{eq}}(U))=\bigsqcup_{U\in\mathfrak{U}_{\mathcal{P}}^{*}}\mathbb{T}_{\mathcal{P}}^{\mathrm{can}}(U)\setminus\bigsqcup_{U\in\mathfrak{U}_{\mathcal{P}}^{*}}\mathbb{T}_{\mathcal{P}}^{\mathrm{eq}}(U)=\emptyset,

which shows 𝕋𝒫can(U)=𝕋𝒫eq(U)\mathbb{T}_{\mathcal{P}}^{\mathrm{can}}(U)=\mathbb{T}_{\mathcal{P}}^{\mathrm{eq}}(U). ∎

4.2.4. Thermalisation

Now we can characterize the isothermality by quantities for equilibrium.

Proposition 4.8.

Let 𝒫1,𝒫2\mathcal{P}_{1},\mathcal{P}_{2} be K-unstable systems and u1,u2u_{1},u_{2} be the equilibria of internal μ\mu-energy U1𝔘𝒫1,U2𝔘𝒫2U_{1}\in\mathfrak{U}_{\mathcal{P}_{1}}^{*},U_{2}\in\mathfrak{U}_{\mathcal{P}_{2}}^{*} on 𝒫1,𝒫2\mathcal{P}_{1},\mathcal{P}_{2}, respectively. Then the equilibria u1u_{1} and u2u_{2} are isothermal if and only if

(4.16) 𝕋𝒫1eq(U1)𝕋𝒫2eq(U2).\displaystyle\mathbb{T}_{\mathcal{P}_{1}}^{\mathrm{eq}}(U_{1})\cap\mathbb{T}_{\mathcal{P}_{2}}^{\mathrm{eq}}(U_{2})\neq\emptyset.

In this case, we have

𝕋𝒫1×𝒫2eq(U1+U2)=𝕋𝒫1eq(U1)𝕋𝒫2eq(U2).\mathbb{T}_{\mathcal{P}_{1}\times\mathcal{P}_{2}}^{\mathrm{eq}}(U_{1}+U_{2})=\mathbb{T}_{\mathcal{P}_{1}}^{\mathrm{eq}}(U_{1})\cap\mathbb{T}_{\mathcal{P}_{2}}^{\mathrm{eq}}(U_{2}).
Proof.

Assume (4.16) and take T𝕋𝒫1eq(U1)𝕋𝒫2eq(U2)T\in\mathbb{T}_{\mathcal{P}_{1}}^{\mathrm{eq}}(U_{1})\cap\mathbb{T}_{\mathcal{P}_{2}}^{\mathrm{eq}}(U_{2}). Since u1,u2u_{1},u_{2} are the μ\mu-canonical distribution of temperature TT, the product u1×u2u_{1}\times u_{2} is also the μ\mu-canonical distribution of temperature TT by Theorem 4.1. Thus we have T𝕋𝒫1×𝒫2eq(U1+U2)T\in\mathbb{T}_{\mathcal{P}_{1}\times\mathcal{P}_{2}}^{\mathrm{eq}}(U_{1}+U_{2}) and hence u1×u2u_{1}\times u_{2} is the equilibrium of internal μ\mu-energy U1+U2U_{1}+U_{2}. Therefore, u1u_{1} and u2u_{2} are isothermal.

Suppose conversely u1u_{1} and u2u_{2} are isothermal. Since u1×u2u_{1}\times u_{2} is the equilibrium of internal μ\mu-energy U1+U2U_{1}+U_{2}, it is the μ\mu-canonical distribution of temperature T𝕋𝒫1×𝒫2eq(U1+U2)T\in\mathbb{T}_{\mathcal{P}_{1}\times\mathcal{P}_{2}}^{\mathrm{eq}}(U_{1}+U_{2}). Again by Theorem 4.1, u1,u2u_{1},u_{2} are also the μ\mu-canonical distribution of temperature TT by the above proof. Thus we have T𝕋𝒫1can(U1)𝕋𝒫2can(U2)T\in\mathbb{T}_{\mathcal{P}_{1}}^{\mathrm{can}}(U_{1})\cap\mathbb{T}_{\mathcal{P}_{2}}^{\mathrm{can}}(U_{2}). Since 𝕋𝒫ican(Ui)=𝕋𝒫ieq(Ui)\mathbb{T}_{\mathcal{P}_{i}}^{\mathrm{can}}(U_{i})=\mathbb{T}_{\mathcal{P}_{i}}^{\mathrm{eq}}(U_{i}), we obtain the claim. ∎

Now we introduce the following notion.

Definition 4.9.

Let 𝒫\mathcal{P} be a K-unstable system. We call 𝒫\mathcal{P} mild if #𝕋𝒫eq(U)=1\#\mathbb{T}_{\mathcal{P}}^{\mathrm{eq}}(U)=1 for every U𝔘𝒫U\in\mathfrak{U}_{\mathcal{P}}^{*}.

We speculate every K-unstable system is mild, but this is still a conjecture. In the next section, we will see the mildness of some systems including μ\muK-semistable systems as a consequence of slightly better regularity of equilibrium. We note if 𝒫1\mathcal{P}_{1} is a system and 𝒫2\mathcal{P}_{2} is a mild K-unstable system, then the composite system 𝒫1×𝒫2\mathcal{P}_{1}\times\mathcal{P}_{2} is also a mild K-unstable system.

In view of Proposition 4.8, the mildness assumption is essential for the transitivity of isothermaility. Here we conclude the following.

Corollary 4.10.

Let 𝒫1,𝒫2,𝒫3\mathcal{P}_{1},\mathcal{P}_{2},\mathcal{P}_{3} be K-unstable systems. Suppose 𝒫2\mathcal{P}_{2} is mild. If for U1𝔘𝒫1,U2𝔘𝒫2,U3𝔘𝒫3U_{1}\in\mathfrak{U}_{\mathcal{P}_{1}}^{*},U_{2}\in\mathfrak{U}_{\mathcal{P}_{2}}^{*},U_{3}\in\mathfrak{U}_{\mathcal{P}_{3}}^{*}, (𝒫1,U1)(\mathcal{P}_{1},U_{1}) and (𝒫2,U2)(\mathcal{P}_{2},U_{2}), (𝒫2,U2)(\mathcal{P}_{2},U_{2}) and (𝒫3,U3)(\mathcal{P}_{3},U_{3}) are isothermal, respectively, then (𝒫1,U1)(\mathcal{P}_{1},U_{1}) and (𝒫3,U3)(\mathcal{P}_{3},U_{3}) are also isothermal.

𝒫1\mathcal{P}_{1}𝒫2\mathcal{P}_{2}
Figure 1. Thermalisation of composite system: entropy increases and energy transfer is recognized as heat.

When two systems are not isothermal, the composite system is thermalized to medium temperatue.

Proposition 4.11.

Let 𝒫1,𝒫2\mathcal{P}_{1},\mathcal{P}_{2} be K-unstable systems and 𝒫=𝒫1×𝒫2\mathcal{P}=\mathcal{P}_{1}\times\mathcal{P}_{2} be the composite system. For U1𝔘𝒫1,U2𝔘𝒫2U_{1}\in\mathfrak{U}_{\mathcal{P}_{1}}^{*},U_{2}\in\mathfrak{U}_{\mathcal{P}_{2}}^{*}, we have either

𝕋𝒫1eq(U1)<𝕋𝒫2eq(U2),𝕋𝒫1eq(U1)𝕋𝒫2eq(U2),𝕋𝒫1eq(U1)>𝕋𝒫2eq(U2).\mathbb{T}_{\mathcal{P}_{1}}^{\mathrm{eq}}(U_{1})<\mathbb{T}_{\mathcal{P}_{2}}^{\mathrm{eq}}(U_{2}),\quad\mathbb{T}_{\mathcal{P}_{1}}^{\mathrm{eq}}(U_{1})\cap\mathbb{T}_{\mathcal{P}_{2}}^{\mathrm{eq}}(U_{2})\neq\emptyset,\quad\mathbb{T}_{\mathcal{P}_{1}}^{\mathrm{eq}}(U_{1})>\mathbb{T}_{\mathcal{P}_{2}}^{\mathrm{eq}}(U_{2}).

Suppose 𝕋𝒫1eq(U1)<𝕋𝒫2eq(U2)\mathbb{T}_{\mathcal{P}_{1}}^{\mathrm{eq}}(U_{1})<\mathbb{T}_{\mathcal{P}_{2}}^{\mathrm{eq}}(U_{2}), then we have

𝕋𝒫1eq(U1)<𝕋𝒫1×𝒫2eq(U1+U2)<𝕋𝒫2eq(U2).\mathbb{T}_{\mathcal{P}_{1}}^{\mathrm{eq}}(U_{1})<\mathbb{T}_{\mathcal{P}_{1}\times\mathcal{P}_{2}}^{\mathrm{eq}}(U_{1}+U_{2})<\mathbb{T}_{\mathcal{P}_{2}}^{\mathrm{eq}}(U_{2}).
Proof.

Let u1,u2u_{1},u_{2} be the equilibria associated to uu as in (4.1) and (4.2). Since u1u_{1} and u2u_{2} are isothermal, by the above proposition, we have

𝕋𝒫1×𝒫2eq(U1+U2)=𝕋𝒫1eq(U𝒫1(u1))𝕋𝒫2eq(U𝒫2(u2)).\mathbb{T}_{\mathcal{P}_{1}\times\mathcal{P}_{2}}^{\mathrm{eq}}(U_{1}+U_{2})=\mathbb{T}_{\mathcal{P}_{1}}^{\mathrm{eq}}(U_{\mathcal{P}_{1}}(u_{1}))\cap\mathbb{T}_{\mathcal{P}_{2}}^{\mathrm{eq}}(U_{\mathcal{P}_{2}}(u_{2})).

Now we have exactly three possibilities: U𝒫1(u1)<U1U_{\mathcal{P}_{1}}(u_{1})<U_{1}, U𝒫1(u1)=U1U_{\mathcal{P}_{1}}(u_{1})=U_{1} and U𝒫1(u1)>U1U_{\mathcal{P}_{1}}(u_{1})>U_{1}. Suppose U𝒫1(u1)>U1U_{\mathcal{P}_{1}}(u_{1})>U_{1}, then

𝕋𝒫1×𝒫2eq(U1+U2)=𝕋𝒫1eq(U𝒫1(u1))𝕋𝒫2eq(U𝒫2(u2))𝕋𝒫1eq(U𝒫1(u1))>𝕋𝒫1eq(U1).\mathbb{T}_{\mathcal{P}_{1}\times\mathcal{P}_{2}}^{\mathrm{eq}}(U_{1}+U_{2})=\mathbb{T}_{\mathcal{P}_{1}}^{\mathrm{eq}}(U_{\mathcal{P}_{1}}(u_{1}))\cap\mathbb{T}_{\mathcal{P}_{2}}^{\mathrm{eq}}(U_{\mathcal{P}_{2}}(u_{2}))\geq\mathbb{T}_{\mathcal{P}_{1}}^{\mathrm{eq}}(U_{\mathcal{P}_{1}}(u_{1}))>\mathbb{T}_{\mathcal{P}_{1}}^{\mathrm{eq}}(U_{1}).

Since U𝒫2(u2)=(U1U𝒫1(u1))+U2<U2U_{\mathcal{P}_{2}}(u_{2})=(U_{1}-U_{\mathcal{P}_{1}}(u_{1}))+U_{2}<U_{2}, we get

𝕋𝒫2eq(U2)>𝕋𝒫1×𝒫2eq(U1+U2)\mathbb{T}_{\mathcal{P}_{2}}^{\mathrm{eq}}(U_{2})>\mathbb{T}_{\mathcal{P}_{1}\times\mathcal{P}_{2}}^{\mathrm{eq}}(U_{1}+U_{2})

by the same argument. It follows that 𝕋𝒫1eq(U1)<𝕋𝒫2eq(U2)\mathbb{T}_{\mathcal{P}_{1}}^{\mathrm{eq}}(U_{1})<\mathbb{T}_{\mathcal{P}_{2}}^{\mathrm{eq}}(U_{2}).

Similarly, we obtain 𝕋𝒫1eq(U1)>𝕋𝒫2eq(U2)\mathbb{T}_{\mathcal{P}_{1}}^{\mathrm{eq}}(U_{1})>\mathbb{T}_{\mathcal{P}_{2}}^{\mathrm{eq}}(U_{2}) when U𝒫1(u1)<U1U_{\mathcal{P}_{1}}(u_{1})<U_{1}, 𝕋𝒫1eq(U1)=𝕋𝒫2eq(U2)\mathbb{T}_{\mathcal{P}_{1}}^{\mathrm{eq}}(U_{1})=\mathbb{T}_{\mathcal{P}_{2}}^{\mathrm{eq}}(U_{2}) when U𝒫1(u1)=U1U_{\mathcal{P}_{1}}(u_{1})=U_{1}. Since these are exclusive conditions, the claim is proved. ∎

We will see the medium temperature 𝕋𝒫1×𝒫2eq(U1+U2)\mathbb{T}_{\mathcal{P}_{1}\times\mathcal{P}_{2}}^{\mathrm{eq}}(U_{1}+U_{2}) can be arbitrary close to 𝕋𝒫2eq\mathbb{T}_{\mathcal{P}_{2}}^{\mathrm{eq}} when the system 𝒫2\mathcal{P}_{2} is sufficiently large.

4.3. Thermodynamics of non-archimedean μ\mu-entropy

In the previous section, we discuss equilibrium and thermalisation. Here we rediscover the non-archimedean μ\mu-entropy from a further exploration on thermalisation. This observation is well-known in thermodynamics. We present it in a mathematically rigorous way.

4.3.1. Temperature as variable

Let us firstly consider change of variables as usual in thermodynamics.

Let 𝒫\mathcal{P} be a K-unstable system. Recall for T[0,)T\in[0,\infty), there exists unique U𝔘𝒫U\in\mathfrak{U}_{\mathcal{P}}^{*} such that T𝕋𝒫eqT\in\mathbb{T}_{\mathcal{P}}^{\mathrm{eq}}. For a system 𝒫\mathcal{P} and T[0,)T\in[0,\infty), we put

(4.17) U𝒫can(T):={U satisfying T𝕋𝒫eq(U)𝒫 is K-unstableU𝒫(1P)𝒫 is K-semistable\displaystyle U_{\mathcal{P}}^{\mathrm{can}}(T):=\begin{cases}U\text{ satisfying }T\in\mathbb{T}_{\mathcal{P}}^{\mathrm{eq}}(U)&\mathcal{P}\text{ is K-unstable}\\ U_{\mathcal{P}}(1_{P})&\mathcal{P}\text{ is K-semistable}\end{cases}

This can be regarded as the inverse function of 𝕋𝒫eq(U)\mathbb{T}_{\mathcal{P}}^{\mathrm{eq}}(U). It is continuous and increasing on TT. We further put

(4.18) S𝒫can(T):=S𝒫eq(U𝒫can(T)),\displaystyle S_{\mathcal{P}}^{\mathrm{can}}(T):=S_{\mathcal{P}}^{\mathrm{eq}}(U_{\mathcal{P}}^{\mathrm{can}}(T)),

which is also continuous and increasing.

Now for TT\in\mathbb{R}, we introduce

(4.19) F𝒫can(T):=minuNAexp,1(P)F𝒫(T,u)=minuNAexp,1(P)(U𝒫(u)TS𝒫(u)).\displaystyle F_{\mathcal{P}}^{\mathrm{can}}(T):=\min_{u\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(P)}F_{\mathcal{P}}(T,u)=\min_{u\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(P)}(U_{\mathcal{P}}(u)-TS_{\mathcal{P}}(u)).

This is a concave function on TT. Then we have the following.

Proposition 4.12.

For T[0,)T\in[0,\infty), we have

F𝒫can(T)=U𝒫can(T)TS𝒫can(T).F_{\mathcal{P}}^{\mathrm{can}}(T)=U_{\mathcal{P}}^{\mathrm{can}}(T)-TS_{\mathcal{P}}^{\mathrm{can}}(T).

Moreover, F𝒫can(T)F_{\mathcal{P}}^{\mathrm{can}}(T) is continuously differentiable on T[0,)T\in[0,\infty) with

(4.20) TF𝒫can(T)=S𝒫can(T).\displaystyle\partial_{T}F_{\mathcal{P}}^{\mathrm{can}}(T)=-S_{\mathcal{P}}^{\mathrm{can}}(T).
Proof.

For the μ\mu-canonical distribution of temperature TT, we have

F𝒫can(T)=F𝒫(uTcan)=U𝒫(uTcan)TS𝒫(uTcan)F_{\mathcal{P}}^{\mathrm{can}}(T)=F_{\mathcal{P}}(u_{T}^{\mathrm{can}})=U_{\mathcal{P}}(u_{T}^{\mathrm{can}})-TS_{\mathcal{P}}(u_{T}^{\mathrm{can}})

by definiton.

The μ\mu-canonical distribution uTcanu_{T}^{\mathrm{can}} of temperature T𝕋𝒫eq(U)T\in\mathbb{T}_{\mathcal{P}}^{\mathrm{eq}}(U) has internal μ\mu-energy U𝒫(uTcan)=UU_{\mathcal{P}}(u_{T}^{\mathrm{can}})=U, so that we have

U𝒫(uTcan)=U𝒫can(T).U_{\mathcal{P}}(u_{T}^{\mathrm{can}})=U_{\mathcal{P}}^{\mathrm{can}}(T).

Since uTcan=ueq(U)u_{T}^{\mathrm{can}}=u^{\mathrm{eq}}(U) for the equilibrium of internal μ\mu-energy U=U𝒫can(T)U=U_{\mathcal{P}}^{\mathrm{can}}(T), we have

S𝒫(uTcan)=S𝒫(ueq(U))=S𝒫eq(U)=S𝒫can(T).S_{\mathcal{P}}(u_{T}^{\mathrm{can}})=S_{\mathcal{P}}(u^{\mathrm{eq}}(U))=S_{\mathcal{P}}^{\mathrm{eq}}(U)=S_{\mathcal{P}}^{\mathrm{can}}(T).

Therefore we get the first claim.

To see the second claim, note

F𝒫can(T)U𝒫(u)TS𝒫(u)F_{\mathcal{P}}^{\mathrm{can}}(T)\leq U_{\mathcal{P}}(u)-TS_{\mathcal{P}}(u)

for every uNAexp,1(P)u\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(P). In particular for T,T0T,T^{\prime}\geq 0, we have

F𝒫can(T)U𝒫can(T)TS𝒫can(T)F_{\mathcal{P}}^{\mathrm{can}}(T)\leq U_{\mathcal{P}}^{\mathrm{can}}(T^{\prime})-TS_{\mathcal{P}}^{\mathrm{can}}(T^{\prime})

with the equality at T=TT=T^{\prime} thanks to the first claim. It follows that S𝒫can(T)S_{\mathcal{P}}^{\mathrm{can}}(T^{\prime}) is a subdifferential of the convex function F𝒫can(T)-F_{\mathcal{P}}^{\mathrm{can}}(T) at T=TT=T^{\prime}. Since S𝒫can(T)S_{\mathcal{P}}^{\mathrm{can}}(T) is continuous, F𝒫can(T)-F_{\mathcal{P}}^{\mathrm{can}}(T) is actually differentiable on T0T\geq 0 with the derivative S𝒫can(T)S_{\mathcal{P}}^{\mathrm{can}}(T). ∎

4.3.2. Mild regularity hypothesis

The mildness of a K-unstable system 𝒫\mathcal{P} is equivalent to the strict monotonicity of U𝒫can(T)U_{\mathcal{P}}^{\mathrm{can}}(T). Since S𝒫eq(U)S_{\mathcal{P}}^{\mathrm{eq}}(U) is strictly increasing, it is also equivalent to the strict monotonicity of S𝒫can(T)S_{\mathcal{P}}^{\mathrm{can}}(T).

Proposition 4.13.

Let 𝒫\mathcal{P} be a K-unstable system. Suppose for every T0T\geq 0 there exists p>1p>1 such that P(uTcan)p𝑑σ<\int_{\partial P}(u_{T}^{\mathrm{can}})^{p}d\sigma<\infty for the μ\mu-canonical distribution uTcanu_{T}^{\mathrm{can}} of temperature TT. Then S𝒫can(T)S_{\mathcal{P}}^{\mathrm{can}}(T) is strictly increasing, hence 𝒫\mathcal{P} is mild.

Proof.

Take T[0,)T\in[0,\infty). It suffices to show S𝒫can(T)>S𝒫can(T)S_{\mathcal{P}}^{\mathrm{can}}(T^{\prime})>S_{\mathcal{P}}^{\mathrm{can}}(T) for every T>TT^{\prime}>T. Suppose we could find a family {ut}t(ε,ε)\{u_{t}\}_{t\in(-\varepsilon,\varepsilon)} in NAexp,1(P)\mathcal{M}_{\mathrm{NA}}^{\exp,1}(P) so that

  • u0=uTcanu_{0}=u_{T}^{\mathrm{can}}

  • F𝒫(T,ut),S𝒫(ut)F_{\mathcal{P}}(T,u_{t}),S_{\mathcal{P}}(u_{t}) are differentiable at t=0t=0 and S˙:=t=0S𝒫(ut)>0\dot{S}:=\partial_{t=0}S_{\mathcal{P}}(u_{t})>0.

Since uTcanu_{T}^{\mathrm{can}} minimizes F𝒫(T,)F_{\mathcal{P}}(T,\bullet), we have t=0F𝒫(T,ut)=0\partial_{t=0}F_{\mathcal{P}}(T,u_{t})=0. This implies that for every T>TT^{\prime}>T, there exists tT>0t_{T^{\prime}}>0 such that

(TT)S𝒫(ut)S𝒫(uTcan)t>F𝒫(T,ut)F𝒫(T,uTcan)t(T^{\prime}-T)\frac{S_{\mathcal{P}}(u_{t})-S_{\mathcal{P}}(u_{T}^{\mathrm{can}})}{t}>\frac{F_{\mathcal{P}}(T,u_{t})-F_{\mathcal{P}}(T,u_{T}^{\mathrm{can}})}{t}

for every 0<t<tT0<t<t_{T^{\prime}}. Then using F𝒫(T,ut)=F𝒫(T,ut)(TT)S𝒫(ut)F_{\mathcal{P}}(T^{\prime},u_{t})=F_{\mathcal{P}}(T,u_{t})-(T^{\prime}-T)S_{\mathcal{P}}(u_{t}), we compute

F𝒫can(T)(TT)S𝒫can(T)\displaystyle F_{\mathcal{P}}^{\mathrm{can}}(T)-(T^{\prime}-T)S_{\mathcal{P}}^{\mathrm{can}}(T) =F𝒫(T,uTcan)(TT)S𝒫(uTcan)\displaystyle=F_{\mathcal{P}}(T,u_{T}^{\mathrm{can}})-(T^{\prime}-T)S_{\mathcal{P}}(u_{T}^{\mathrm{can}})
>F𝒫(T,ut)(TT)S𝒫(ut)\displaystyle>F_{\mathcal{P}}(T,u_{t})-(T^{\prime}-T)S_{\mathcal{P}}(u_{t})
=F𝒫(T,ut)F𝒫can(T).\displaystyle=F_{\mathcal{P}}(T^{\prime},u_{t})\geq F_{\mathcal{P}}^{\mathrm{can}}(T^{\prime}).

It follows by convexity that

S𝒫can(T)=TF𝒫can(T)F𝒫can(T)F𝒫can(T)TT>S𝒫can(T),S_{\mathcal{P}}^{\mathrm{can}}(T^{\prime})=-\partial_{T}F_{\mathcal{P}}^{\mathrm{can}}(T^{\prime})\geq-\frac{F_{\mathcal{P}}^{\mathrm{can}}(T^{\prime})-F_{\mathcal{P}}^{\mathrm{can}}(T)}{T^{\prime}-T}>S_{\mathcal{P}}^{\mathrm{can}}(T),

which shows the strict monotonicity of S𝒫can(T)S_{\mathcal{P}}^{\mathrm{can}}(T).

Now we construct the family {ut}t(ε,ε)\{u_{t}\}_{t\in(-\varepsilon,\varepsilon)} under the regularity assumption on uTcanu_{T}^{\mathrm{can}}. Take qNAexp,nn1(P)q\in\mathcal{E}_{\mathrm{NA}}^{\exp,\frac{n}{n-1}}(P) with q0q\geq 0 so that u(q)=uTcanu(q)=u_{T}^{\mathrm{can}}. We put ut:=u((1t)q)u_{t}:=u((1-t)q). For ddte(1t)q=qe(1t)q\frac{d}{dt}e^{(1-t)q}=-qe^{(1-t)q}, we have Pqe(1t)q𝑑σPe(1t+ϵ)q𝑑σ<\int_{\partial P}qe^{(1-t)q}d\sigma\leq\int_{\partial P}e^{(1-t+\epsilon)q}d\sigma<\infty for small tt by assumption. This implies the differentiability of F𝒫(T,ut)F_{\mathcal{P}}(T,u_{t}) around t=0t=0. Meanwhile, we have

ddt|t=0S𝒫(ut)=Pq2eq𝑑μPeq𝑑μ(Pqeq𝑑μPeq𝑑μ)2>0\frac{d}{dt}\Big{|}_{t=0}S_{\mathcal{P}}(u_{t})=\frac{\int_{P}q^{2}e^{q}d\mu}{\int_{P}e^{q}d\mu}-\Big{(}\frac{\int_{P}qe^{q}d\mu}{\int_{P}e^{q}d\mu}\Big{)}^{2}>0

by Cauchy–Schwarz inequality. This completes the proof. ∎

Corollary 4.14.

Let 𝒫\mathcal{P} be the system associated to a polarized toric variety (X,L)(X,L) which is μλ\mu^{\lambda}K-semistable for every λ0\lambda\leq 0. Then 𝒫\mathcal{P} is either K-semistable or mild K-unstable system.

In view of crystal conjecture (Conjecture 3.16), the assumption of the above theorem, which we call the mild regularity hypothesis, is believed to be always true.

Remark 4.15.

As a weak evidence for the mild regularity hypothesis, we note

Pulogudσ=Pqeq𝑑σ<\int_{\partial P}u\log ud\sigma=\int_{\partial P}qe^{q}d\sigma<\infty

for μ\mu-canonical distribution u=equ=e^{q} of any temperature. This could be viewed as a limit of N(u1+1Nu)N(u^{1+\frac{1}{N}}-u).

For t0t\searrow 0, we have pointwise monotone convergence 0(eqe(1t)q)/tqeq0\leq(e^{q}-e^{(1-t)q})/t\nearrow qe^{q} by the convexity of exponential. Then by monotone convergence theorem, we compute

ddt+|t=0Pe(1t)q𝑑σ=limt0Pe(1t)q𝑑σPeq𝑑σt=Pqeq𝑑σ.\frac{d}{dt_{+}}\Big{|}_{t=0}\int_{\partial P}e^{(1-t)q}d\sigma=\lim_{t\searrow 0}\frac{\int_{\partial P}e^{(1-t)q}d\sigma-\int_{\partial P}e^{q}d\sigma}{t}=-\int_{\partial P}qe^{q}d\sigma.

Since Pe(1t)q𝑑μ\int_{P}e^{(1-t)q}d\mu and 𝝈((1t)q)\bm{\sigma}((1-t)q) are smooth for 1t(0,nn1)1-t\in(0,\frac{n}{n-1}), we directly compute

0\displaystyle 0 ddt+|t=0𝝁ˇNA2πT((1t)q)\displaystyle\geq\frac{d}{dt_{+}}\Big{|}_{t=0}\bm{\check{\mu}}_{\mathrm{NA}}^{-2\pi T}((1-t)q)
=2πPeq𝑑μ(Pqeq𝑑σPeq𝑑σPeq𝑑μPqeq𝑑μ)2πTddt|t=0𝝈((1t)q),\displaystyle=\frac{2\pi}{\int_{P}e^{q}d\mu}(\int_{\partial P}qe^{q}d\sigma-\frac{\int_{\partial P}e^{q}d\sigma}{\int_{P}e^{q}d\mu}\int_{P}qe^{q}d\mu)-2\pi T\frac{d}{dt}\Big{|}_{t=0}\bm{\sigma}((1-t)q),

where the inequality holds as qq is a maximizer of 𝝁ˇNA2πT\bm{\check{\mu}}_{\mathrm{NA}}^{-2\pi T}. Since qNAexp,nn1(P)q\in\mathcal{E}_{\mathrm{NA}}^{\exp,\frac{n}{n-1}}(P), the integrals

Peq𝑑σPeq𝑑μPqeq𝑑μ,ddt|t=0𝝈((1t)q)=Pq2eq𝑑μPeq𝑑μ+(Pqeq𝑑μPeq𝑑μ)2\frac{\int_{\partial P}e^{q}d\sigma}{\int_{P}e^{q}d\mu}\int_{P}qe^{q}d\mu,\quad\frac{d}{dt}\Big{|}_{t=0}\bm{\sigma}((1-t)q)=-\frac{\int_{P}q^{2}e^{q}d\mu}{\int_{P}e^{q}d\mu}+\Big{(}\frac{\int_{P}qe^{q}d\mu}{\int_{P}e^{q}d\mu}\Big{)}^{2}

are finite, thus Pqeq𝑑σ0\int_{\partial P}qe^{q}d\sigma\geq 0 is also finite by the inequality.

Remark 4.16.

Later we further consider the assumption that S𝒫can(T)S_{\mathcal{P}}^{\mathrm{can}}(T) has strictly positive differential TS𝒫can(T)>0\partial_{T}S_{\mathcal{P}}^{\mathrm{can}}(T)>0 at some T>0T^{\prime}>0. In thermodynamical terminology, the quantity TU𝒫can(T)=TTS𝒫can(T)\partial_{T}U_{\mathcal{P}}^{\mathrm{can}}(T)=T\partial_{T}S_{\mathcal{P}}^{\mathrm{can}}(T) is called the heat capacity of (𝒫,T)(\mathcal{P},T).

If a polarized toric manifold (X,L)(X,L) admits μλ\mu^{\lambda}-cscK metric for every λ0\lambda\leq 0, then we can show the family of optimal vectors {ξλ𝔱}λ0\{\xi_{\lambda}\in\mathfrak{t}\}_{\lambda\leq 0} are smooth. (Apply implicit function theorem to μ\mu-cscK equation. Compare the proof of [22, Theorem 5.1]. ) It follows that for the associated system 𝒫\mathcal{P}, S𝒫can(T)=S𝒫(u(|ξ2πT))S_{\mathcal{P}}^{\mathrm{can}}(T)=S_{\mathcal{P}}(u(\ket{\xi_{-2\pi T}})) is smooth. We note the positivity of differential implies the strict monotonicity, but the strict monotonocity does not necessarily imply the positivity of differential.

4.3.3. Illustration

Here we illustrate an explicit example with positive heat capacity.

Let XX be the one point-blowing up of P2\mathbb{C}P^{2} and LL be the anti-canonical polarization KX-K_{X}. The associated polytope PP can be illustrated as follows.

(0,1)(0,-1)(2,1)(2,-1)(1,2)(-1,2)(1,0)(-1,0)

It is shown in [22] that (X,L)(X,L) admits μλ\mu^{\lambda}-cscK metric for every λ\lambda\in\mathbb{R} and the optimal vectors ξλ𝔱\xi_{\lambda}\in\mathfrak{t} is of the form xλ.η:=(xλ,xλ)2x_{\lambda}.\eta:=(x_{\lambda},x_{\lambda})\in\mathbb{R}^{2}.

Similarly as [25, section 5.2], we can compute

Pex|η𝑑μ\displaystyle\int_{\partial P}e^{x\ket{\eta}}d\mu =1x((2x)ex(3x+2)ex),\displaystyle=-\frac{1}{x}((2-x)e^{-x}-(3x+2)e^{x}),
Pex|η𝑑μ\displaystyle\int_{P}e^{x\ket{\eta}}d\mu =1x2((x+1)ex+(3x1)ex),\displaystyle=\frac{1}{x^{2}}((-x+1)e^{-x}+(3x-1)e^{x}),
Px|ηex|η𝑑μ\displaystyle\int_{P}x\ket{\eta}e^{x\ket{\eta}}d\mu =1x2((x22)ex+(3x24x+2)ex).\displaystyle=\frac{1}{x^{2}}((x^{2}-2)e^{-x}+(3x^{2}-4x+2)e^{x}).

Then we get the explicit expression

𝝁ˇNA(x|η)\displaystyle\bm{\check{\mu}}_{\mathrm{NA}}(x\ket{\eta}) =2πx(2x)ex(3x+2)ex(x+1)ex+(3x1)ex,\displaystyle=2\pi x\frac{(2-x)e^{-x}-(3x+2)e^{x}}{(-x+1)e^{-x}+(3x-1)e^{x}},
𝝈(x|η)\displaystyle\bm{\sigma}(x\ket{\eta}) =(x22)ex+(3x24x+2)ex(x+1)ex+(3x1)ex\displaystyle=\frac{(x^{2}-2)e^{-x}+(3x^{2}-4x+2)e^{x}}{(-x+1)e^{-x}+(3x-1)e^{x}}
log1x2((x+1)ex+(3x1)ex)logPen𝑑μ\displaystyle\qquad-\log\frac{1}{x^{2}}\Big{(}(-x+1)e^{-x}+(3x-1)e^{x}\Big{)}-\log\int_{P}e^{-n}d\mu

and

ddx𝝁ˇNA(x|η)\displaystyle\frac{d}{dx}\bm{\check{\mu}}_{\mathrm{NA}}(x\ket{\eta}) =(x22x+2)e2x(9x26x2)e2x+12x316x24x4(x22x+1)e2x+(9x26x+1)e2x3x2+4x1\displaystyle=\frac{(x^{2}-2x+2)e^{-2x}-(9x^{2}-6x-2)e^{2x}+12x^{3}-16x^{2}-4x-4}{(x^{2}-2x+1)e^{-2x}+(9x^{2}-6x+1)e^{2x}-3x^{2}+4x-1}
ddx𝝈(x|η)\displaystyle\frac{d}{dx}\bm{\sigma}(x\ket{\eta}) =(x22x+2)e2x(9x26x2)e2x+12x316x24x4(x22x+1)e2x+(9x26x+1)e2x3x2+4x1\displaystyle=-\frac{(x^{2}-2x+2)e^{-2x}-(9x^{2}-6x-2)e^{2x}+12x^{3}-16x^{2}-4x-4}{(x^{2}-2x+1)e^{-2x}+(9x^{2}-6x+1)e^{2x}-3x^{2}+4x-1}
(x22)ex+(3x24x+2)exx((x+1)ex+(3x1)ex)\displaystyle\qquad-\frac{(x^{2}-2)e^{-x}+(3x^{2}-4x+2)e^{x}}{x((-x+1)e^{-x}+(3x-1)e^{x})}
=(x24x+2)e2x+(9x212x+2)e2x12x4+16x32x2+16x4x((x22x+1)e2x+(9x26x+1)e2x3x2+4x1).\displaystyle=\frac{(x^{2}-4x+2)e^{-2x}+(9x^{2}-12x+2)e^{2x}-12x^{4}+16x^{3}-2x^{2}+16x-4}{x((x^{2}-2x+1)e^{-2x}+(9x^{2}-6x+1)e^{2x}-3x^{2}+4x-1)}.

We can see ddx𝝈(x|η)<0\frac{d}{dx}\bm{\sigma}(x\ket{\eta})<0 for x<0x<0 as illustrated in the following figure.

Refer to caption
Figure 2. The graph of ddx𝝈(x|η)\frac{d}{dx}\bm{\sigma}(x\ket{\eta}).

The optimal vector xλ.ηx_{\lambda}.\eta is the critical point of 𝝁ˇNAλ|𝔱\bm{\check{\mu}}_{\mathrm{NA}}^{\lambda}|_{\mathfrak{t}}, so we have

ddx𝝁ˇNA(xλ|η)+λddx𝝈(xλ|η)=0.\frac{d}{dx}\bm{\check{\mu}}_{\mathrm{NA}}(x_{\lambda}\ket{\eta})+\lambda\frac{d}{dx}\bm{\sigma}(x_{\lambda}\ket{\eta})=0.

If we put

λ(x):=2πx(9x26x2)e2x+(x2+2x2)e2x+(12x3+16x2+4x+4)(9x212x+2)e2x+(x24x+2)e2x+(12x4+16x32x2+16x4),\lambda(x):=2\pi x\frac{(9x^{2}-6x-2)e^{2x}+(-x^{2}+2x-2)e^{-2x}+(-12x^{3}+16x^{2}+4x+4)}{(9x^{2}-12x+2)e^{2x}+(x^{2}-4x+2)e^{-2x}+(-12x^{4}+16x^{3}-2x^{2}+16x-4)},

this is equivalent to the condition λ(xλ)=λ\lambda(x_{\lambda})=\lambda.

Refer to caption
Refer to caption
Figure 3. The graph of 12πλ(x)\frac{1}{2\pi}\lambda(x). The vertical axis represents λ\lambda. The left image focuses on the range λ0\lambda\leq 0, which illustrates xλ<0x_{\lambda}<0 and ddλxλ<0\frac{d}{d\lambda}x_{\lambda}<0. In the right image, we can observe more than one solutions appear around 12πλ3\frac{1}{2\pi}\lambda\approx 3.

For λ0\lambda\leq 0, we have xλ<0x_{\lambda}<0 and ddλxλ=(ddxλ(xλ))1<0\frac{d}{d\lambda}x_{\lambda}=(\frac{d}{dx}\lambda(x_{\lambda}))^{-1}<0. It follows that

TS𝒫can(T)=2πddλ𝝈(xλ|η)=ddλxλddx𝝈(xλ|η)>0\partial_{T}S_{\mathcal{P}}^{\mathrm{can}}(T)=2\pi\frac{d}{d\lambda}\bm{\sigma}(x_{\lambda}\ket{\eta})=\frac{d}{d\lambda}x_{\lambda}\cdot\frac{d}{dx}\bm{\sigma}(x_{\lambda}\ket{\eta})>0

for T=λ2π0T=-\frac{\lambda}{2\pi}\geq 0.

4.3.4. Heat bath

It is well known in thermodynamics that the free energy can be derived as the entropy of a composition of the system of our interest and a sufficiently large system working as heat bath. We can realize large system as limit of infinitely many composition. This observation gives us a new interpretation of μ\mu-canonical distribution: μ\mu-canonical distribution is equilibrium of an infinite dimensional system.

𝒫\mathcal{P}𝒫R\mathcal{P}_{R}𝒫R\mathcal{P}_{R}𝒫R×N\mathcal{P}_{R}^{\times N}\cdots
Figure 4. Realization of heat bath as the limit of infinitely many composition
Theorem 4.17 (Heat bath limit).

Let 𝒫\mathcal{P} be a K-unstable system and 𝒫R\mathcal{P}_{R} be a mild K-unstable system. Fix U𝔘𝒫U\in\mathfrak{U}_{\mathcal{P}}^{*} and TR[0,)T_{R}\in[0,\infty). For NN\in\mathbb{N}, consider the composite system

𝒫~N=𝒫×𝒫R×N.\tilde{\mathcal{P}}_{N}=\mathcal{P}\times\mathcal{P}_{R}^{\times N}.

Let u~NNAexp,1(P~N)\tilde{u}_{N}\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(\tilde{P}_{N}) be the equilibrium of internal μ\mu-energy U+NU𝒫Rcan(TR)U+NU_{\mathcal{P}_{R}}^{\mathrm{can}}(T_{R}). Then the following associated equilibrium on the subsystem PP

uN:=1PR×N𝑑μPR×NPR×Nu~N𝑑μPR×NNAexp,1(P),u_{N}:=\frac{1}{\int_{P_{R}^{\times N}}d\mu_{P_{R}}^{\times N}}\int_{P_{R}^{\times N}}\tilde{u}_{N}d\mu_{P_{R}}^{\times N}\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(P),

converges in LpL^{p}-topology (p[1,nn1)p\in[1,\frac{n}{n-1})) to the μ\mu-canonical distribution uNAexp,1(P)u_{\infty}\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(P) of temperature TRT_{R}, which is independent of the choice of U𝔘𝒫U\in\mathfrak{U}_{\mathcal{P}}.

Proof.

We note U+NU𝒫Rcan(TR)𝔘𝒫~NU+NU_{\mathcal{P}_{R}}^{\mathrm{can}}(T_{R})\in\mathfrak{U}_{\tilde{\mathcal{P}}_{N}}^{*}. Since 𝒫R\mathcal{P}_{R} is mild, the composite system 𝒫×𝒫R×N\mathcal{P}\times\mathcal{P}_{R}^{\times N} is also mild. Let TN[0,)T_{N}\in[0,\infty) be the element of the one point set

𝕋𝒫~Neq(U+NU𝒫Rcan(TR)).\mathbb{T}_{\tilde{\mathcal{P}}_{N}}^{\mathrm{eq}}(U+NU_{\mathcal{P}_{R}}^{\mathrm{can}}(T_{R})).

Since u~N\tilde{u}_{N} on 𝒫~N\tilde{\mathcal{P}}_{N} is the μ\mu-canonical distribution of temperature TNT_{N}, uNu_{N} on 𝒫\mathcal{P} is also the μ\mu-canonical distribution of temperature TNT_{N} by Theorem 4.1.

Since

(4.21) U𝒫can(TN)+NU𝒫Rcan(TN)=U𝒫~Ncan(TN)=U+NU𝒫Rcan(TR),\displaystyle U_{\mathcal{P}}^{\mathrm{can}}(T_{N})+NU_{\mathcal{P}_{R}}^{\mathrm{can}}(T_{N})=U_{\tilde{\mathcal{P}}_{N}}^{\mathrm{can}}(T_{N})=U+NU_{\mathcal{P}_{R}}^{\mathrm{can}}(T_{R}),

we compute

U𝒫Rcan(TN)=1N(U+NU𝒫Rcan(TR)U𝒫can(TN))=U𝒫Rcan(TR)+1N(UU𝒫can(TN)).U^{\mathrm{can}}_{\mathcal{P}_{R}}(T_{N})=\frac{1}{N}(U+NU_{\mathcal{P}_{R}}^{\mathrm{can}}(T_{R})-U_{\mathcal{P}}^{\mathrm{can}}(T_{N}))=U_{\mathcal{P}_{R}}^{\mathrm{can}}(T_{R})+\frac{1}{N}(U-U_{\mathcal{P}}^{\mathrm{can}}(T_{N})).

Since U𝒫can(TN)𝔘𝒫U_{\mathcal{P}}^{\mathrm{can}}(T_{N})\in\mathfrak{U}_{\mathcal{P}}^{*} is bounded, we get U𝒫Rcan(TN)U𝒫Rcan(TR)U^{\mathrm{can}}_{\mathcal{P}_{R}}(T_{N})\to U^{\mathrm{can}}_{\mathcal{P}_{R}}(T_{R}) as NN\to\infty. It follows that TNTRT_{N}\to T_{R}. By the continuity we already proved, we conclude uNu_{N} converges to the μ\mu-canonical distribution uu_{\infty} of temperature TRT_{R}. ∎

Now we obtain a characterization of free μ\mu-energy in terms of equilibrium of composite system.

Theorem 4.18 (Free μ\mu-energy as composite entropy).

Let 𝒫,𝒫R\mathcal{P},\mathcal{P}_{R}, U,TRU,T_{R} and u~N,u\tilde{u}_{N},u_{\infty} be the same as in the above theorem. Assume further the heat capacity TRTS𝒫can(TR)T_{R}\partial_{T}S_{\mathcal{P}}^{\mathrm{can}}(T_{R}) of (𝒫R,TR)(\mathcal{P}_{R},T_{R}) is positive. (See Remark 4.16. ) Namely we assume TR>0T_{R}>0, S𝒫RcanS^{\mathrm{can}}_{\mathcal{P}_{R}} is differentiable at TRT_{R} and TS𝒫Rcan(TR)>0\partial_{T}S^{\mathrm{can}}_{\mathcal{P}_{R}}(T_{R})>0.

Let uR×NNAexp,1(PR×N)u_{R}^{\times N}\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(P_{R}^{\times N}) be the equilibrium of internal μ\mu-energy NU𝒫Rcan(TR)NU_{\mathcal{P}_{R}}^{\mathrm{can}}(T_{R}) on 𝒫R×N\mathcal{P}_{R}^{\times N}. Then for any uNAexp,1(𝒫,U)u\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(\mathcal{P},U) of internal μ\mu-energy UU, the difference of composite entropy

ΔS𝒫~N\displaystyle\Delta S_{\tilde{\mathcal{P}}_{N}} :=S𝒫~N(u~N)S𝒫~N(u×uR×N)\displaystyle:=S_{\tilde{\mathcal{P}}_{N}}(\tilde{u}_{N})-S_{\tilde{\mathcal{P}}_{N}}(u\times u_{R}^{\times N})

converges to

1TR(F𝒫(TR,u)F𝒫(TR,u))-\frac{1}{T_{R}}(F_{\mathcal{P}}(T_{R},u_{\infty})-F_{\mathcal{P}}(T_{R},u))

as NN\to\infty, which is independent of the choice of the mild system 𝒫R\mathcal{P}_{R}.

Proof.

When TR𝕋𝒫eq(U)T_{R}\in\mathbb{T}_{\mathcal{P}}^{\mathrm{eq}}(U), we have

𝕋𝒫~Neq(U+NU𝒫Rcan(TR))=𝕋𝒫eq(U)𝕋𝒫Req(U𝒫Rcan(TR))={TR},\mathbb{T}_{\tilde{\mathcal{P}}_{N}}^{\mathrm{eq}}(U+NU_{\mathcal{P}_{R}}^{\mathrm{can}}(T_{R}))=\mathbb{T}_{\mathcal{P}}^{\mathrm{eq}}(U)\cap\mathbb{T}_{\mathcal{P}_{R}}^{\mathrm{eq}}(U_{\mathcal{P}_{R}}^{\mathrm{can}}(T_{R}))=\{T_{R}\},

so that TN=TRT_{N}=T_{R}. Then since uN=uu_{N}=u_{\infty} is the μ\mu-canonical distribution of temperature TRT_{R}, we have u~N=u×uR×N\tilde{u}_{N}=u_{\infty}\times u_{R}^{\times N}. Then by U𝒫(u)=U𝒫can(TR)=UU_{\mathcal{P}}(u_{\infty})=U_{\mathcal{P}}^{\mathrm{can}}(T_{R})=U, we can compute

ΔS𝒫~N=S𝒫(u)S𝒫(u)=1TR(F𝒫(TR,u)F𝒫(TR,u))\Delta S_{\tilde{\mathcal{P}}_{N}}=S_{\mathcal{P}}(u_{\infty})-S_{\mathcal{P}}(u)=-\frac{1}{T_{R}}(F_{\mathcal{P}}(T_{R},u_{\infty})-F_{\mathcal{P}}(T_{R},u))

for uNAexp,1(𝒫,U)u\in\mathcal{M}_{\mathrm{NA}}^{\exp,1}(\mathcal{P},U).

When TR𝕋𝒫eq(U)T_{R}\notin\mathbb{T}_{\mathcal{P}}^{\mathrm{eq}}(U), we have either

TR<TN<𝕋𝒫eq(U) or TR>TN>𝕋𝒫eq(U).T_{R}<T_{N}<\mathbb{T}_{\mathcal{P}}^{\mathrm{eq}}(U)\text{ or }T_{R}>T_{N}>\mathbb{T}_{\mathcal{P}}^{\mathrm{eq}}(U).

In either case, we have TR,TN,TRTN0T_{R},T_{N},T_{R}-T_{N}\neq 0. Since F𝒫Rcan(T)F_{\mathcal{P}_{R}}^{\mathrm{can}}(T) is differentiable on T[0,)T\in[0,\infty) by Proposition 4.12, U𝒫Rcan(T)=F𝒫Rcan(T)+TS𝒫Rcan(T)U_{\mathcal{P}_{R}}^{\mathrm{can}}(T)=F_{\mathcal{P}_{R}}^{\mathrm{can}}(T)+TS_{\mathcal{P}_{R}}^{\mathrm{can}}(T) is also differentiable at TRT_{R} by our assumption. Then by TNTRT_{N}\to T_{R}, we have

limNU𝒫Rcan(TR)U𝒫Rcan(TN)TRTN=TU𝒫Rcan(TR)=TRTS𝒫Rcan(TR)>0.\lim_{N\to\infty}\frac{U_{\mathcal{P}_{R}}^{\mathrm{can}}(T_{R})-U_{\mathcal{P}_{R}}^{\mathrm{can}}(T_{N})}{T_{R}-T_{N}}=\partial_{T}U_{\mathcal{P}_{R}}^{\mathrm{can}}(T_{R})=T_{R}\partial_{T}S_{\mathcal{P}_{R}}^{\mathrm{can}}(T_{R})>0.

On the other hand, by (4.21), we have

N(U𝒫Rcan(TR)U𝒫Rcan(TN))=UPcan(TN)U,N(U_{\mathcal{P}_{R}}^{\mathrm{can}}(T_{R})-U_{\mathcal{P}_{R}}^{\mathrm{can}}(T_{N}))=U_{P}^{\mathrm{can}}(T_{N})-U,

so that we compute

limNN(U𝒫Rcan(TR)U𝒫Rcan(TN))=U𝒫can(TR)U.\lim_{N\to\infty}N(U_{\mathcal{P}_{R}}^{\mathrm{can}}(T_{R})-U_{\mathcal{P}_{R}}^{\mathrm{can}}(T_{N}))=U_{\mathcal{P}}^{\mathrm{can}}(T_{R})-U.

It follows that

limNN(TRTN)=limNN(U𝒫can(TR)U𝒫can(TN))(U𝒫can(TR)U𝒫can(TN)TRTN)=U𝒫can(TR)UTU𝒫Rcan(TR).\lim_{N\to\infty}N(T_{R}-T_{N})=\lim_{N\to\infty}\frac{N(U_{\mathcal{P}}^{\mathrm{can}}(T_{R})-U_{\mathcal{P}}^{\mathrm{can}}(T_{N}))}{(\frac{U_{\mathcal{P}}^{\mathrm{can}}(T_{R})-U_{\mathcal{P}}^{\mathrm{can}}(T_{N})}{T_{R}-T_{N}})}=\frac{U_{\mathcal{P}}^{\mathrm{can}}(T_{R})-U}{\partial_{T}U_{\mathcal{P}_{R}}^{\mathrm{can}}(T_{R})}.

Since U𝒫~Ncan(TN)=U+NU𝒫Rcan(TR)U_{\tilde{\mathcal{P}}_{N}}^{\mathrm{can}}(T_{N})=U+NU_{\mathcal{P}_{R}}^{\mathrm{can}}(T_{R}), we have

S𝒫~N(u~N)=S𝒫~Neq(U+NU𝒫Rcan(TR))=S𝒫~Ncan(TN)=S𝒫can(TN)+NS𝒫Rcan(TN).S_{\tilde{\mathcal{P}}_{N}}(\tilde{u}_{N})=S_{\tilde{\mathcal{P}}_{N}}^{\mathrm{eq}}(U+NU_{\mathcal{P}_{R}}^{\mathrm{can}}(T_{R}))=S^{\mathrm{can}}_{\tilde{\mathcal{P}}_{N}}(T_{N})=S^{\mathrm{can}}_{\mathcal{P}}(T_{N})+NS^{\mathrm{can}}_{\mathcal{P}_{R}}(T_{N}).

We then compute

ΔS𝒫~N\displaystyle\Delta S_{\tilde{\mathcal{P}}_{N}} =S𝒫can(TN)S𝒫(u)+N(S𝒫Rcan(TN)S𝒫Rcan(TR))\displaystyle=S^{\mathrm{can}}_{\mathcal{P}}(T_{N})-S_{\mathcal{P}}(u)+N(S^{\mathrm{can}}_{\mathcal{P}_{R}}(T_{N})-S_{\mathcal{P}_{R}}^{\mathrm{can}}(T_{R}))
=S𝒫can(TN)S𝒫(u)1TRN(U𝒫Rcan(TR)U𝒫Rcan(TN))\displaystyle=S^{\mathrm{can}}_{\mathcal{P}}(T_{N})-S_{\mathcal{P}}(u)-\frac{1}{T_{R}}N(U_{\mathcal{P}_{R}}^{\mathrm{can}}(T_{R})-U^{\mathrm{can}}_{\mathcal{P}_{R}}(T_{N}))
+1TRN(F𝒫Rcan(TR)F𝒫Rcan(TN)))+N(1TN1TR)(U𝒫Rcan(TN)F𝒫Rcan(TN))\displaystyle\quad+\frac{1}{T_{R}}N(F_{\mathcal{P}_{R}}^{\mathrm{can}}(T_{R})-F^{\mathrm{can}}_{\mathcal{P}_{R}}(T_{N})))+N(\frac{1}{T_{N}}-\frac{1}{T_{R}})(U^{\mathrm{can}}_{\mathcal{P}_{R}}(T_{N})-F^{\mathrm{can}}_{\mathcal{P}_{R}}(T_{N}))
=S𝒫can(TN)S𝒫(u)1TR(U𝒫Rcan(TN)U)\displaystyle=S^{\mathrm{can}}_{\mathcal{P}}(T_{N})-S_{\mathcal{P}}(u)-\frac{1}{T_{R}}(U_{\mathcal{P}_{R}}^{\mathrm{can}}(T_{N})-U)
+N(TRTN)TRF𝒫Rcan(TR)F𝒫Rcan(TN)TRTN+N(TRTN)TRS𝒫Rcan(TN)\displaystyle\quad+\frac{N(T_{R}-T_{N})}{T_{R}}\frac{F_{\mathcal{P}_{R}}^{\mathrm{can}}(T_{R})-F^{\mathrm{can}}_{\mathcal{P}_{R}}(T_{N})}{T_{R}-T_{N}}+\frac{N(T_{R}-T_{N})}{T_{R}}S^{\mathrm{can}}_{\mathcal{P}_{R}}(T_{N})
S𝒫can(TR)S𝒫(u)1TR(U𝒫can(TR)U)\displaystyle\to S_{\mathcal{P}}^{\mathrm{can}}(T_{R})-S_{\mathcal{P}}(u)-\frac{1}{T_{R}}(U_{\mathcal{P}}^{\mathrm{can}}(T_{R})-U)
+U𝒫can(TR)UTRTU𝒫Rcan(TR)(TF𝒫Rcan(TR)+S𝒫Rcan(TR))\displaystyle\quad+\frac{U_{\mathcal{P}}^{\mathrm{can}}(T_{R})-U}{T_{R}\partial_{T}U_{\mathcal{P}_{R}}^{\mathrm{can}}(T_{R})}(\partial_{T}F^{\mathrm{can}}_{\mathcal{P}_{R}}(T_{R})+S^{\mathrm{can}}_{\mathcal{P}_{R}}(T_{R}))
=1TR(F𝒫can(TR)F𝒫(TR,u))=1TR(F𝒫(TR,u)F𝒫(TR,u)).\displaystyle=-\frac{1}{T_{R}}(F_{\mathcal{P}}^{\mathrm{can}}(T_{R})-F_{\mathcal{P}}(T_{R},u))=-\frac{1}{T_{R}}(F_{\mathcal{P}}(T_{R},u_{\infty})-F_{\mathcal{P}}(T_{R},u)).

Remark 4.19.

The above theorems are also valid for the case U=U𝒫(1P)U=U_{\mathcal{P}}(1_{P}). We do not even need to assume K-instability of 𝒫\mathcal{P}, but for the proofs we need separate arguments.

References

  • [1] V. Apostolov, S. Jubert, A. Lahdili, Weighted K-stability and coercivity with applications to extremal Kähler and Sasaki metrics, arXiv:2104.09709.
  • [2] J. C. Baez, O. Lynch, J. Moeller, Compositional thermostatics, J. Math. Phys. 64 (2023), 2, 023304, 16pp.
  • [3] R. J. Berman, Emergent Complex Geometry, arXiv:2109.00307.
  • [4] H. Blum, Y. Liu, C. Xu, Z. Zhuang, The existence of the Kähler–Ricci soliton degeneration, arXiv:2103.15278.
  • [5] S. Boucksom, M. Jonsson, Global pluripotential theory over a trivially valued field, Ann. Fac. Sci. Toulouse Math. (6) 31 (2022), 3, 647–836.
  • [6] S. Boucksom, M. Jonsson, A non-archimedean approach to K-stability, I: Metric geometry of spaces of test configurations and valuations, arXiv:2107.11221.
  • [7] S. Boucksom, M. Jonsson, A non-archimedean approach to K-stability, II: divisorial stability and openness, arXiv:2206.09492.
  • [8] X. Chen, J. Cheng, On the constant scalar curvature Kähler metrics (I) – apriori estimates, arXiv:1712.06697.
  • [9] X. Chen, J. Cheng, On the constant scalar curvature Kähler metrics (II) – Existence results, arXiv:1801.000656.
  • [10] X. Chen, J. Cheng, On the constant scalar curvature Kähler metrics (II) – Existence results, arXiv:1801.05907.
  • [11] X. Chen, S. Sun, B. Wang, Kähler–Ricci flow, Kähler–Einstein metric, and K-stability, Geom. Topol. 22, 6 (2108), 3145–3173.
  • [12] X. Chen, B. Wang, Space of Ricci flows (II) — Part B: weak compactness of the flows, J. Diff. Geom., 116 (2020), 1, 1–123.
  • [13] D. A. Cox, J. B. Little, H. K. Schenck, Toric varieties, Graduate Studies in Mathematics, 124, American Mathematical Society, Providence, RI, 2011.
  • [14] R. Dervan, G. Székelyhidi, The Kähler–Ricci flow and optimal degenerations, J. Diff. Geom. 116, 1 (2020), 187–203.
  • [15] S. Donaldson, Scalar curvature and stability of toric varieties, J. Diff. Geom. 62, 2 (2002), 289–349.
  • [16] S. Donaldson, Lower bounds on the Calabi functional, J. Diff. Geom. 70, 3 (2005), 453–472.
  • [17] D. Gale, V. Klee, R. T. Rockafellar, Convex functions on convex polytopes, Proc. Amer. Math. Soc. 19 (1968), 867–873.
  • [18] J. Han, C. Li, Algebraic uniqueness of Kähler–Ricci flow limits and optimal degenerations of Fano varieties, arXiv:2009.01010.
  • [19] T. Hisamoto, Stability and coercivity for toric polarizations, arXiv:1610.07998.
  • [20] T. Hisamoto, Geometric flow, multiplier ideal sheaves and optimal destabilizer for a Fano manifold, arXiv:1901.08480.
  • [21] E. Inoue, The moduli space of Fano manifolds with Kähler–Ricci solitons, Advances in Math. Volume 357 (2019), 106841.
  • [22] E. Inoue, Constant μ\mu-scalar curvature Kähler metric – formulation and foundational results, J. Geom. Anal. 32 (2022), Article number 145.
  • [23] E. Inoue, Equivariant calculus on μ\mu-character and μ\muK-stability of polarized schemes, arXiv:2004.06393.
  • [24] E. Inoue, Entropies in μ\mu-framework of canonical metrics and K-stability, I – Archimedean aspect: Perelman’s μ\mu-entropy and μ\mu-cscK metrics, arXiv:2101.11197.
  • [25] E. Inoue, Entropies in μ\mu-framework of canonical metrics and K-stability, II – Non-archimedean aspect: non-archimedean μ\mu-entropy and μ\muK-semistability, arXiv:2202.12168.
  • [26] D. Joyce, Manifolds with analytic corners, arXiv:1605.05913.
  • [27] A. Lahdili, Kähler metrics with constant weighted scalar curvature and weighted K-stability, Proc. London Math. Soc. (3) 119 (2019), 1065–1114.
  • [28] A. Lahdili, Convexity of the weighted Mabuchi functional and the uniqueness of weighted extremal metrics, arXiv:2007.01345.
  • [29] C. Li, Geodesic rays and stability in the cscK problem, Ann. Sci. Éc. Norm. Supér. (4) 55(2022), 6, 1529–1574.
  • [30] C. Li, K-stability and Fujita approximation, arXiv:2102.09457.
  • [31] Y. Nakagwa, On generalized Kähler–Ricci solitons, Osaka J. Math. 48, 2 (2011), 497–513.
  • [32] G. Perelman, The entropy formula for the Ricci flow and its geometric applications, arXiv:0211159.
  • [33] G. Szekelyhidi, Optimal test configurations for toric varieties, J. Diff. Geom. 80, 3 (2008), 501–523.
  • [34] F. Wang, B. Zhou, Fano manifolds with weak almost Kähler–Ricci solitons, Int. Math. Res. Not. IMRN 2015, 9, 2437–2464.
  • [35] M. Xia, On sharp lower bounds for Calabi type functionals and destabilizing properties of gradient flows, Anal. PDE 14, 6 (2021), 1951–1976.
  • [36] Y. Yao, Mabuchi solitons and relative Ding stability of toric Fano varieties, Int. Math. Res. Not. IMRN 2022, 24, 19790–19853.