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Chiral Edge Modes in Helmholtz-Onsager Vortex Systems

Vishal P. Patil    Jörn Dunkel Department of Mathematics, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA
Abstract

Vortices play a fundamental role in the physics of two-dimensional (2D) fluids across a range of length scales, from quantum superfluids to geophysical flows. Despite a history dating back to Helmholtz, point vortices in a 2D fluid continue to pose interesting theoretical problems, owing to their unusual statistical mechanics. Here, we show that the strongly interacting Helmholtz-Onsager vortex systems can form statistical edge modes at low energies, extending a previously identified analogy between vortex matter and quantum Hall systems. Through dynamical simulations, Monte-Carlo sampling and mean-field theory, we demonstrate that these edge modes are associated with the formation of dipoles of real and image vortices at boundaries. The edge modes are robust, persisting in nonconvex domains, and are in quantitative agreement with the mean-field predictions.

I Introduction

The Helmholtz-Onsager system of point vortices [1, 2] is a widely studied model for inviscid flows in classical [3, 4, 5, 6] and quantum [7, 8, 9, 10, 11, 12, 13] fluid dynamics. As demonstrated by Onsager [14], the classical point vortex system can condense into superclusters, thus reproducing a key element of two-dimensional (2D) turbulence phenomenology. This system has since emerged as a reduced model for turbulence, describing phenomena from spin-up turbulence [4] in the classical case, to energy cascades [10] and turbulence decay [15] in the quantum case. In addition, the quantized point vortex equations reproduce certain phenomenological aspects of the quantum Hall effect [9]. Experimentally, the point vortex model has recently been validated in quantum fluids [16, 17, 18], where point vortices emerge as topological defects [17, 18]. More generally, point vortices have become a minimal model for a variety of 2D turbulence phenomena, from atmospheric dynamics [14] to biochemical signaling in cell membranes [19].

A compelling property of the point vortex system is its anomalous statistical mechanics, in which the phase space is bounded [14] and equivalent to the configuration space. Previous important theoretical work has focused on the statistical properties of the high-energy regime [20, 21, 22, 23, 24, 25, 26, 4, 27] in flat space and curved space [28]. In contrast, the low-energy dynamics in the presence of boundaries has not yet been widely explored. In this regime, Onsager’s physical picture of strong attractive forces between vortices of opposite signs indicates the possibility of edge modes [14]. A particularly interesting question is whether boundary induced image vortices can give rise to stable vortex localization through the formation of such edge modes in convex and nonconvex domains. Additionally, the presence of such modes would supplement previously established mappings between the point vortex model and quantum Hall type systems [9].

Here we investigate the formation and dynamics of statistical edge modes in confined point vortex systems at low energy. Complementing previous studies of point vortex statistics at intermediate-to-high energies [23, 20, 29, 30], we examine the robustness of these edge modes in convex and nonconvex domains. Comparing Monte Carlo sampling, dynamical simulations and mean-field theory, we find vortex edge modes in disk and bean-shaped geometries, which survive at large vortex numbers. Strikingly, these edge modes are a robust, real-space phenomenon, despite the strongly interacting nature of the point vortex system. Furthermore, these modes persist in nonconvex domains, reminiscent of the edge mode signatures observed in topological systems.

II Helmholtz -Onsager model

II.1 Kirchhoff equations

The point vortex model consists of a system of NN point vortices in a 2D incompressible, inviscid fluid with constant density. Each vortex has strength λa\lambda_{a} and position 𝐱a(t)=(xa(t),ya(t))\mathbf{x}_{a}(t)=(x_{a}(t),y_{a}(t)) in a domain Ω\Omega, which corresponds to the following vorticity field

ω=aλaδ(𝐱𝐱a(t))\displaystyle\omega=\sum_{a}\lambda_{a}\delta\left(\mathbf{x}-\mathbf{x}_{a}(t)\right)

The flow field 𝐮(t,𝐱)\mathbf{u}(t,\mathbf{x}) for this vortex configuration is obtained from the streamfunction ψ(t,𝐱)\psi(t,\mathbf{x}) as [14]

𝐮=ψ×𝐞z,2ψ=ω\displaystyle\mathbf{u}=\nabla\psi\times\mathbf{e}_{z},\qquad\qquad\nabla^{2}\psi=-\omega

The streamfunction can be written in terms of Green’s functions

ψ=a=1NλaG(𝐱,𝐱a(t))\displaystyle\psi=-\sum_{a=1}^{N}\lambda_{a}G(\mathbf{x},\mathbf{x}_{a}(t))

where the Green’s function GG satisfies

2G(𝐱,𝐲)\displaystyle\nabla^{2}G(\mathbf{x},\mathbf{y}) =δ(𝐱𝐲),G|Ω=0\displaystyle=\delta(\mathbf{x}-\mathbf{y}),\qquad\qquad G|_{\partial\Omega}=0

The boundary condition for the Green’s function arises from the fact that the boundary of the domain must be a streamline, ψ|Ω=const.\psi|_{\partial\Omega}=\text{const.} For simply connected domains, we can set this constant to 0. Using this streamfunction as an ansatz for the inviscid vorticity equation [1, 31, 9]

ωt+𝐮ω=0\frac{\partial\omega}{\partial t}+\mathbf{u}\cdot\nabla\omega=0

yields a Hamiltonian system where xax_{a} and yay_{a} are canonically conjugate

λax˙a=ya,λay˙a=xa\displaystyle\lambda_{a}\dot{x}_{a}=\frac{\partial\mathcal{H}}{\partial y_{a}},\qquad\qquad\lambda_{a}\dot{y}_{a}=-\frac{\partial\mathcal{H}}{\partial x_{a}} (1)

The Hamiltonian is given by

\displaystyle\mathcal{H} =a<bλaλbG(𝐱a,𝐱b)12aλa2g(𝐱a)\displaystyle=-\sum_{a<b}\lambda_{a}\lambda_{b}G(\mathbf{x}_{a},\mathbf{x}_{b})-\frac{1}{2}\sum_{a}\lambda_{a}^{2}g(\mathbf{x}_{a}) (2)

where

g(𝐱a)=lim𝐱𝐱a(G(𝐱,𝐱a)12πlog|𝐱𝐱a|)g(\mathbf{x}_{a})=\lim_{\mathbf{x}\rightarrow\mathbf{x}_{a}}\left(G(\mathbf{x},\mathbf{x}_{a})-\frac{1}{2\pi}\log|\mathbf{x}-\mathbf{x}_{a}|\right)

is the regularized Green’s function. The Hamiltonian coincides with the regularized kinetic energy of the fluid [32]

𝒦=12Ωd2𝐱|𝐮|2=12Ωd2𝐱ψψ=12Ωd2𝐱ψω=\displaystyle\mathcal{K}=\frac{1}{2}\int_{\Omega}d^{2}\mathbf{x}\,|\mathbf{u}|^{2}=\frac{1}{2}\int_{\Omega}d^{2}\mathbf{x}\,\nabla\psi\cdot\nabla\psi=\frac{1}{2}\int_{\Omega}d^{2}\mathbf{x}\,\psi\omega=\mathcal{H}

The quantities defined only depend on length LL and time TT: [λ]=L2/T,[]=L4/T2[\lambda]=L^{2}/T,\;[\mathcal{H}]=L^{4}/T^{2}. Choosing a reference length scale L0L_{0}, we can define a timescale T0=L02/(N|λ|)T_{0}=L_{0}^{2}/(N|\lambda|). Since the fluid density plays no role in the system, this also gives energy scale E0=L04/T02E_{0}=L_{0}^{4}/T_{0}^{2} and angular momentum scale J0=L04/T0J_{0}=L_{0}^{4}/T_{0}. In particular

E0N2=|λ|2,J0NL02=|λ|\frac{E_{0}}{N^{2}}=|\lambda|^{2},\qquad\qquad\frac{J_{0}}{NL_{0}^{2}}=|\lambda|

In the remainder, we consider systems of identical vortices with positive circulation,

λaλ>0\lambda_{a}\equiv\lambda>0

We choose units so that L0=1L_{0}=1 and λ=1\lambda=1. This fixes the timescale, T0=1/NT_{0}=1/N, reflecting the fact that the fluid rotates faster as the number of point vortices increases. Below, we will focus on two different domains, the unit disk DD with radius L0=1L_{0}=1 and a bean-shaped domain BB obtained from DD by a conformal mapping specified below.

II.2 Disk-shaped domain

In complex coordinates, z=x+iyz=x+iy, the Green’s functions GG and gg for the disk DD are [33, 34, 35]

GD(z,w)\displaystyle G^{D}(z,w) =12πlog|zwzw1|gD(z)=12πlog|1zz|\displaystyle=\frac{1}{2\pi}\log\left|\frac{z-w}{z^{*}w-1}\right|\qquad\qquad g^{D}(z)=-\frac{1}{2\pi}\log|1-z^{*}z|

This gives a compact expression for the Hamiltonian

\displaystyle\mathcal{H} =12πa<bλ2log|zazbzazb1|+14πaλ2log|1zaza|\displaystyle=-\frac{1}{2\pi}\sum_{a<b}\lambda^{2}\log\left|\frac{z_{a}-z_{b}}{z_{a}^{*}z_{b}-1}\right|+\frac{1}{4\pi}\sum_{a}\lambda^{2}\log|1-z_{a}^{*}z_{a}|

and the velocity

λz˙a=2iz¯a\displaystyle\lambda\dot{z}_{a}=-2i\frac{\partial\mathcal{H}}{\partial\bar{z}_{a}} =iλ22πba1zazbiλ22πb1za(1/zb)\displaystyle=\frac{i\lambda^{2}}{2\pi}\sum_{b\neq a}\frac{1}{z_{a}^{*}-z_{b}^{*}}-\frac{i\lambda^{2}}{2\pi}\sum_{b}\frac{1}{z_{a}^{*}-(1/z_{b})}

The first sum captures the flow generated by point vortices at the locations zbz_{b}, in the the absence of boundaries. Analogously, the second sum, which includes b=ab=a, is due to image vortices located at the points 1/zb1/z_{b}^{*} [Fig. 1(a)]. The velocity of the whole fluid, 𝐮(t,z)=(u(t,z),v(t,z))\mathbf{u}(t,z)=(u(t,z),v(t,z)), is

u(t,z)+iv(t,z)=iλ2πa[1zza1z(1/za)]\displaystyle u(t,z)+iv(t,z)=\frac{i\lambda}{2\pi}\sum_{a}\left[\frac{1}{z^{*}-z_{a}^{*}}-\frac{1}{z^{*}-(1/z_{a})}\right]

The Hamiltonian for the unit disk can be split up into a bulk energy and a boundary energy, arising from the interaction between real vortices and image vortices [Figs. 1(a) and 1(b)]

\displaystyle\mathcal{H} =14πabλ2log|zazb|+14πa,bλ2log|1zazb|\displaystyle=-\frac{1}{4\pi}\sum_{a\neq b}\lambda^{2}\log\left|z_{a}-z_{b}\right|+\frac{1}{4\pi}\sum_{a,b}\lambda^{2}\log|1-z_{a}z_{b}^{*}|

The singularities of \mathcal{H} correspond to the locations of these real and image vortices. The energy is singular when the aa’th vortex approaches the real vortex at zbz_{b} or the image vortex at 1/zb1/z_{b}^{*} [Figs. 1(a) and 1(b)].

Refer to caption
Figure 1: Image vortices drive boundary accumulation in symmetric and nonconvex domains. (a) A real vortex with positive circulation inside the disk (red), gives rise to an image vortex with negative circulation outside (blue). The position of the image can be visualized through stereographic projection. (b) At sufficiently low energies, image dipoles form at the boundary of the disk. Streamlines demonstrate the corresponding flow patterns. (c) Image vortex dipoles persist upon conformal mapping to a bean-shaped domain.

II.3 Nonconvex bean-shaped domain

A bean-shaped domain BB can be obtained from the unit disk by a conformal mapping. Consider the image of DD under a map of the form f1(z)=(bz1)2/af^{-1}(z)=(b^{\prime}z-1)^{2}/a^{\prime}. When b=1b^{\prime}=1, this mapping produces a nonconvex cardioid domain, which posseses a cusp singularity at the boundary. By taking b=0.9b^{\prime}=0.9, we instead obtain a smooth nonconvex bean-shaped domain, BB [Fig. 1(c)]. We set a2=2b2(b2+2)a^{\prime 2}=2b^{\prime 2}(b^{\prime 2}+2) so that BB has area π\pi, equal to the unit disk. The Green’s function in BB transforms with the conformal map ff

GB(z,w)\displaystyle G^{B}(z,w) =GD(f(z),f(w))=12πlog|f(z)f(w)f(z)f(w)1|\displaystyle=G^{D}(f(z),f(w))=\frac{1}{2\pi}\log\left|\frac{f(z)-f(w)}{f(z)^{*}f(w)-1}\right|

and the regularized Green’s function is

gB(z)\displaystyle g^{B}(z) =limwz(12πlog|f(z)f(w)f(z)f(w)1|12πlog|zw|)\displaystyle=\lim_{w\rightarrow z}\left(\frac{1}{2\pi}\log\left|\frac{f(z)-f(w)}{f(z)^{*}f(w)-1}\right|-\frac{1}{2\pi}\log|z-w|\right)
=12π(log|1f(z)f(z)|log|f(z)|)\displaystyle=-\frac{1}{2\pi}\left(\log|1-f(z)^{*}f(z)|-\log|f^{\prime}(z)|\right)

As before, the form of the Hamiltonian indicates the presence of image vortices

\displaystyle\mathcal{H} =14πabλ2log|f(za)f(zb)|+14πa,bλ2log|1f(za)f(zb)|14πaλ2log|f(za)|\displaystyle=-\frac{1}{4\pi}\sum_{a\neq b}\lambda^{2}\log\left|f(z_{a})-f(z_{b})\right|+\frac{1}{4\pi}\sum_{a,b}\lambda^{2}\log|1-f(z_{a})f(z_{b})^{*}|-\frac{1}{4\pi}\sum_{a}\lambda^{2}\log|f^{\prime}(z_{a})| (3)

The positions of real and image vortices again follow from the singularities of the Hamiltonian. The first term is singular when zaz_{a} approaches the real vortex at zbz_{b}, and the second term is singular when zaz_{a} approaches the image vortex at f1(1/f(zb))f^{-1}\left(1/f(z_{b})^{*}\right) [Fig. 1(c)]. Furthermore, the first and third terms of the Hamiltonian in (3) are bounded below, unlike the second term. To see this, observe that the boundedness of the domain means that the expressions log|f(za)f(zb)|-\log|f(z_{a})-f(z_{b})| in the first term are bounded below. Similarly, log|f(za)|-\log|f^{\prime}(z_{a})| is bounded below whenever f(za)f^{\prime}(z_{a}) is bounded, as is the case for the mappings we consider. On the other hand, the second term of (3) approaches negative infinity when real vortices approach image vortices, although this divergence is not independent of divergences in the first term. Nevertheless, this heuristic argument indicates that an effective image vortex attraction at low energies will give rise to vortex clustering at the boundary of the domain. This image vortex dipole mechanism (Fig. 1) is responsible for the formation of edge modes.

II.4 Conserved quantities

In addition to the energy \mathcal{H}, an incompressible, inviscid fluid in 2D also has conservation laws for linear momentum 𝒫\mathcal{P}, angular momentum 𝒜\mathcal{A}, vorticity 𝒱\mathcal{V}, and enstrophy \mathcal{E}

𝒫=Ωd2𝐱𝐮,𝒜=Ωd2𝐱(𝐱𝐮),𝒱=Ωd2𝐱ω,=Ωd2𝐱ω2\displaystyle\mathcal{P}=\int_{\Omega}d^{2}\mathbf{x}\,\mathbf{u},\qquad\mathcal{A}=\int_{\Omega}d^{2}\mathbf{x}\,\left(\mathbf{x}\wedge\mathbf{u}\right),\qquad\mathcal{V}=\int_{\Omega}d^{2}\mathbf{x}\,\omega,\qquad\mathcal{E}=\int_{\Omega}d^{2}\mathbf{x}\,\omega^{2}

where the pseudoscalar 𝐱𝐮=xvyu\mathbf{x}\wedge\mathbf{u}=xv-yu corresponds to the zz-component of the 3D cross-product. The linear momentum vanishes in a bounded domain, which can be shown componentwise using the streamfunction 𝐮=(ψy,ψx)\mathbf{u}=(\psi_{y},-\psi_{x})

𝒫𝐞x=Ωd2𝐱(ψ𝐞y)=Ω𝑑𝐧𝐞yψ=0\displaystyle\mathcal{P}\cdot\mathbf{e}_{x}=\int_{\Omega}d^{2}\mathbf{x}\,\nabla\cdot\left(\psi\mathbf{e}_{y}\right)=\int_{\partial\Omega}d\mathbf{n}\cdot\mathbf{e}_{y}\psi=0

where d𝐧d\mathbf{n} is the normal curve element. The second equality follows from the divergence theorem and the final equality uses the fact that ψ|Ω\psi|_{\partial\Omega} is constant and Ω\partial\Omega is a closed curve. The vorticity and enstrophy have straightforward expressions in terms of the vortex strengths, however the enstrophy is singular

𝒱=aλa=Nλ,=a,bλaλbδ(𝐱a𝐱b)=λ2a,bδ(𝐱a𝐱b)\displaystyle\mathcal{V}=\sum_{a}\lambda_{a}=N\lambda,\qquad\qquad\mathcal{E}=\sum_{a,b}\lambda_{a}\lambda_{b}\delta(\mathbf{x}_{a}-\mathbf{x}_{b})=\lambda^{2}\sum_{a,b}\delta(\mathbf{x}_{a}-\mathbf{x}_{b})

In the systems of identical point vortices we consider here, the conservation of 𝒱\mathcal{V} is equivalent to the conservation of particle number, 𝒱=N\mathcal{V}=N. The conversation law for angular momentum depends on the pressure field p(t,𝐱)p(t,\mathbf{x}), which can be found in terms of the velocity field, 𝐮\mathbf{u}, through the Euler equation for an inviscid fluid

p=𝐮t+𝐮𝐮\displaystyle-\nabla p=\frac{\partial\mathbf{u}}{\partial t}+\mathbf{u}\cdot\nabla\mathbf{u}

Taking the cross product of the Euler equation with 𝐱\mathbf{x} gives an equation for angular momentum transport; integrating this transport equation and using the divergence theorem yields the conservation law for angular momentum in terms of the boundary advection of angular momentum and the boundary torque due to pressure

ddt𝒜\displaystyle\frac{d}{dt}\mathcal{A} =Ω𝑑𝐧𝐮(𝐱𝐮)+Ω𝑑𝐧𝐱p=Ω𝑑𝐧𝐱p\displaystyle=-\int_{\partial\Omega}d\mathbf{n}\cdot\mathbf{u}\,\left(\mathbf{x}\wedge\mathbf{u}\right)+\int_{\partial\Omega}d\mathbf{n}\wedge\mathbf{x}\,p=\int_{\partial\Omega}d\mathbf{n}\wedge\mathbf{x}\,p

The advection term vanishes since 𝐮\mathbf{u} has no normal component on the boundary. Angular momentum is globally conserved if the boundary torque vanishes, which occurs when the domain Ω\Omega has the appropriate symmetry [14, 24]. Using Stokes’ theorem, the angular momentum of the fluid can be expressed as

𝒜=12Ωd2𝐱[(𝐮|𝐱|2)ω|𝐱|2]=12Ω𝑑𝐫𝐮|𝐱|212𝒥\displaystyle\mathcal{A}=\frac{1}{2}\int_{\Omega}d^{2}\mathbf{x}\,\left[\nabla\wedge\left(\mathbf{u}|\mathbf{x}|^{2}\right)-\omega|\mathbf{x}|^{2}\right]=\frac{1}{2}\int_{\partial\Omega}d\mathbf{r}\cdot\mathbf{u}\,|\mathbf{x}|^{2}-\frac{1}{2}\mathcal{J}

where d𝐫d\mathbf{r} is the tangential curve element and

𝒥=aλ|𝐱a|2\mathcal{J}=\sum_{a}\lambda|\mathbf{x}_{a}|^{2}

If the domain has circular symmetry, 𝒜\mathcal{A} is conserved. In particular, when Ω\Omega is the unit disk DD, the circulation term can be simplified

𝒜=12aλa12aλa|𝐱a|2=12𝒱12𝒥\displaystyle\mathcal{A}=\frac{1}{2}\sum_{a}\lambda_{a}-\frac{1}{2}\sum_{a}\lambda_{a}|\mathbf{x}_{a}|^{2}=\frac{1}{2}\mathcal{V}-\frac{1}{2}\mathcal{J}

where 𝒥\mathcal{J} is the conserved vortex angular momentum. The statistical mechanics of the system can be described in terms of the nonzero and nonsingular conserved quantities ,𝒜\mathcal{H},\mathcal{A} and 𝒱\mathcal{V}.

II.5 Density of states

The different statistical regimes of the point vortex system can be identified through the density of states. For the disk DD, conservation of both \mathcal{H} and 𝒥\mathcal{J} implies there is a joint density of states W(E,J)W(E,J) [Fig. 2(a)]. Defining ξ=(x1,y1,x2,y2,,xN,yN)\xi=(x_{1},y_{1},x_{2},y_{2},...,x_{N},y_{N}), we have

W(E,J)\displaystyle W(E,J) =1πNDN𝑑ξδ((ξ)E)δ(𝒥(ξ)J)\displaystyle=\frac{1}{\pi^{N}}\int_{D^{N}}d\xi\,\delta\left(\mathcal{H}(\xi)-E\right)\delta\left(\mathcal{J}(\xi)-J\right)

The marginal densities W(E)W_{\mathcal{H}}(E) and W𝒥(J)W_{\mathcal{J}}(J) over energy and angular momentum follow from the joint density by [Fig. 2(b) and 2(c)]

W(E)\displaystyle W_{\mathcal{H}}(E) =1πNDN𝑑ξδ((ξ)E)\displaystyle=\frac{1}{\pi^{N}}\int_{D^{N}}d\xi\,\delta\left(\mathcal{H}(\xi)-E\right)
W𝒥(J)\displaystyle W_{\mathcal{J}}(J) =1πNDN𝑑ξδ(𝒥(ξ)J)\displaystyle=\frac{1}{\pi^{N}}\int_{D^{N}}d\xi\,\delta\left(\mathcal{J}(\xi)-J\right)

Flows where 𝒥\mathcal{J} is large in magnitude must involve a concentration of vortices at the boundary, and thus 𝒥\mathcal{J}-conservation may be thought of as an angular momentum barrier. However, due to the correlation between \mathcal{H} and 𝒥\mathcal{J} [Fig. 1(a)], it is hard to disentangle this effect from the low-energy boundary attraction described above.

As is typical of a generic bounded domain, the bean-shaped domain has no additional conserved quantities, so there is only a density of states over energy [Fig. 2(d)]. This density, W(E)W_{\mathcal{H}}(E), has a maximum at some energy, E=EE=E^{*}, which arises from the fact that the phase space is bounded [Figs. 2(b) and 2(d)]. Here, we focus on the low-energy regime, E<EE<E^{*}.

Refer to caption
Figure 2: Density of states for the unit disk and the bean of area π\pi for N=10N=10 vortices. (a) The joint density of states over energy, \mathcal{H}, and angular momentum, 𝒥\mathcal{J}, in the disk reveals a strong correlation between \mathcal{H} and 𝒥\mathcal{J}. (b) The marginal density of states over energy exhibits distinct low-energy (green) and high-energy (purple) regimes on either side of the mode, EE^{*}, of the distribution (yellow). (c) The marginal density of states over angular momentum is symmetric. (d) The density of states in the bean-shaped domain exhibits the same pattern of low- and high-energy regimes as the disk.

III Monte Carlo simulations and Hamiltonian dynamics predict edge modes

Boundary attraction through image vortices leads to the formation of a low-energy statistical edge mode in both the disk (Fig. 3) and the bean (Fig. 4) at small vortex number. As discussed above, the Hamiltonian for a general domain, obtained from the image of the unit disk under a conformal mapping f1f^{-1}, is

\displaystyle\mathcal{H} =14πabλ2log|f(za)f(zb)|+14πa,bλ2log|1f(za)f(zb)|14πaλ2log|f(za)|\displaystyle=-\frac{1}{4\pi}\sum_{a\neq b}\lambda^{2}\log\left|f(z_{a})-f(z_{b})\right|+\frac{1}{4\pi}\sum_{a,b}\lambda^{2}\log|1-f(z_{a})f(z_{b})^{*}|-\frac{1}{4\pi}\sum_{a}\lambda^{2}\log|f^{\prime}(z_{a})|

Only the second term is unbounded below, so states with sufficiently low energy are typically only produced when f(za)f(zb)f(z_{a})f(z_{b})^{*} is close to 1 for enough pairs of vortices, or equivalently, when enough vortices are close to the boundary. For the disk, such a configuration will have large angular momentum, 𝒥=aλ|𝐱a|2\mathcal{J}=\sum_{a}\lambda|\mathbf{x}_{a}|^{2}, which explains the 𝒥\mathcal{H}-\mathcal{J} correlation [Fig. 2(a)]. The agreement between the distributions produced by time-averaged Hamiltonian dynamics and Monte Carlo sampling (Figs. 3 and 4) also suggests that a mean-field approach can be used to formalize the above heuristic argument for edge modes.

Refer to caption
Figure 3: Monte Carlo sampling for the disk agrees with time-averaged Hamiltonian dynamics at low, intermediate and high energies (N=10N=10). (a) Streamlines demonstrate the flow patterns of sample points in phase space with given energy. (b) Monte Carlo sampling at fixed energy, and varying angular momentum reveals low-energy edge modes and high-energy vortex clustering in the disk; sample size >104>10^{4} configurations. (c) The time-averaged dynamics of the vortex system agrees with the Monte Carlo predicted statistical states. Energy from left to right in (a),(b),(c): E=0.0,0.8,2.0E=0.0,0.8,2.0. Angular momentum from left to right in (c): J=5.8,4.9,4.0J=5.8,4.9,4.0. Simulation time: T=105T0T=10^{5}T_{0}.
Refer to caption
Figure 4: Monte Carlo sampling for the bean also agrees with time-averaged Hamiltonian dynamics at low, intermediate and high energies (N=10N=10). (a) Streamlines demonstrate the flow patterns of sample points in phase space with given energy. (b) Monte Carlo sampling reveals low-energy edge modes and high-energy clustering in the bean; sample size >104>10^{4} configurations. (c) The time-averaged dynamics of the vortex system agrees with the Monte Carlo predicted statistical states. Energy from left to right [(a),(b),(c)]: E=0.0,0.8,2.0E=0.0,0.8,2.0. Simulation time: T=105T0T=10^{5}T_{0}.

IV Mean-field limit

IV.1 Edge modes persist in the mean-field limit

To identify the low-energy regime for large NN and understand the corresponding statistical states, we return to the density of states for a general bounded domain

W(E)\displaystyle W_{\mathcal{H}}(E) =1πNΩN𝑑ξδ((ξ)E)\displaystyle=\frac{1}{\pi^{N}}\int_{\Omega^{N}}d\xi\,\delta\left(\mathcal{H}(\xi)-E\right)

The function W(E)W_{\mathcal{H}}(E) can also be understood as the probability density function (pdf) of the energy when NN points are chosen uniformly at random in the domain. Let Za=Xa+iYaZ_{a}=X_{a}+iY_{a} be a collection of such uniform random variables for a=1a=1 to NN. The energy is now a random variable H^\hat{H}

H^=14πabG(Za,Zb)+14πag(Za)\displaystyle\hat{H}=-\frac{1}{4\pi}\sum_{a\neq b}G(Z_{a},Z_{b})+\frac{1}{4\pi}\sum_{a}g(Z_{a})

where the first sum contains N(N1)N(N-1) terms, the second sum contains NN terms and the strength of each vortex λ\lambda has been set to 1 as before. Previous work [36] has identified the limiting distribution of H^\hat{H} in bounded domains. For the identical vortex systems considered here, this limiting distribution is Gaussian. An informal derivation of this fact follows from the theory of UU-statistics [37, 38]. Set H¯=H^/N2\bar{H}=\hat{H}/N^{2}, and consider

N(H¯μ)=N(14πN2abG(Za,Zb)μ)+14πNNag(Za)\sqrt{N}(\bar{H}-\mu)=\sqrt{N}\left(-\frac{1}{4\pi N^{2}}\sum_{a\neq b}G(Z_{a},Z_{b})-\mu\right)+\frac{1}{4\pi N\sqrt{N}}\sum_{a}g(Z_{a}) (4)

where

μ=14π𝔼[G(Za,Zb)]\mu=-\frac{1}{4\pi}\mathbb{E}\left[G(Z_{a},Z_{b})\right]

The second term in (4) is a sum of only NN independent random variables, and thus converges to 0. A central limit type theorem [37] for the sequence of N(N1)N(N-1) random variables G(Za,Zb)G(Z_{a},Z_{b}) shows that N(H¯μ)\sqrt{N}(\bar{H}-\mu) is asymptotically normal, where μ\mu and the variance σ2\sigma^{2} are given by [37, 39, 36]

μ=14π𝔼G(Za,Zb),σ2=limNNVar(H¯)=limNVar(H^)N3\displaystyle\mu=-\frac{1}{4\pi}\mathbb{E}G(Z_{a},Z_{b}),\qquad\qquad\sigma^{2}=\lim_{N\rightarrow\infty}N\,\text{Var}(\bar{H})=\lim_{N\rightarrow\infty}\frac{\text{Var}(\hat{H})}{N^{3}}

Furthermore, UU-statistics theory [37] indicates that σ2>0\sigma^{2}>0 holds whenever 𝔼(G(z,Za))\mathbb{E}(G(z,Z_{a})) is not constant as a function of zz. Formalizing the above argument would require showing that GG and gg meet suitable regularity conditions [37]. The scaling of the variance is Var(H¯)O(1/N)\text{Var}(\bar{H})\sim O(1/N), analogous to the central limit theorem. This scaling may be understood intuitively as a consequence of the fact that there are only NN, and not N2N^{2}, independent points. Although 𝔼(H^/N2)O(1)\mathbb{E}(\hat{H}/N^{2})\sim O(1), as NN\rightarrow\infty, there is an O(1/N)O(1/N) contribution to the mean coming from the boundary terms, 𝔼(g(Za))\mathbb{E}(g(Z_{a})). For finite NN, the pdf of H^/N2\hat{H}/N^{2} can therefore be better approximated by a Gaussian with mean

𝔼(H^N2)=μ+μbN\mathbb{E}\left(\frac{\hat{H}}{N^{2}}\right)=\mu+\frac{\mu_{b}}{N}

where μb=𝔼(g(Za))/4π\mu_{b}=\mathbb{E}(g(Z_{a}))/4\pi. The limit allows us to define the low-energy regime in terms of a rescaled energy ϵ\epsilon, which measures the distance from the mean energy in units of standard deviation

ϵ=Nσ[N2(μ+μbN)]\displaystyle\epsilon=\frac{\sqrt{N}}{\sigma}\left[\frac{\mathcal{H}}{N^{2}}-\left(\mu+\frac{\mu_{b}}{N}\right)\right] (5)

Similarly, for the disk, the angular momentum becomes a random variable J^\hat{J}

J^=a|Za|2\displaystyle\hat{J}=\sum_{a}|Z_{a}|^{2}

where 𝔼(|Z|2)=1/2\mathbb{E}(|Z|^{2})=1/2 and Var(|Z|2)=1/12\text{Var}(|Z|^{2})=1/12. Using the central limit theorem, the appropriately rescaled angular momentum is therefore

=12N(J^N12)\displaystyle\ell=\sqrt{12N}\left(\frac{\hat{J}}{N}-\frac{1}{2}\right)

IV.2 Mean-field theory in the disk

Refer to caption
Figure 5: Low-energy edge modes persist at large vortex numbers and are in quantitative agreement with mean-field predictions. (N=80N=80). (a) Rescaled energy (ϵ\epsilon) and angular momentum (\ell) are strongly correlated at large NN. (b) The density of states over ϵ\epsilon for N=80N=80 (blue histogram) and N=1000N=1000 (red circles) demonstrates the convergence to the limiting density (solid curve). The green line selects the rescaled energy ϵ=2.5\epsilon=-2.5 at N=80N=80. (c) Streamlines demonstrate the flow pattern of a sample point in phase space with low energy, ϵ=2.5\epsilon=-2.5 (see movie S1). (d) The time-averaged Hamiltonian dynamics of N=80N=80 vortices at ϵ=2.5\epsilon=-2.5 exhibits edge modes (see movie S2). Simulation time: T=8×103T0T=8\times 10^{3}T_{0}. (e) Mean-field theory in the disk predicts edge modes (β=15,γ=0\beta=15,\gamma=0). (f) Predicted and measured probability density as a function of the radial coordinate rr. The zero-angular momentum mean-field prediction (solid black curve) agrees quantitatively with time-averaged Hamiltonian dynamics (N=80N=80, green circles), and deviates significantly from the uniform vortex distribution (solid horizontal line).
Refer to caption
Figure 6: Visualization of edge modes in the unit disk from Fig. 5(d) through stereographic projection (N=80N=80). The southern hemisphere, containing positive vortices (red) has λ=+1\lambda=+1, and the northern hemisphere, containing negative image vortices (blue) has λ=1\lambda=-1. The vortex circulation λ\lambda changes sign across the equator, leading to the formation of an edge mode.

Statistical edge modes persist in the disk at low energy for large vortex numbers NN. When NN is sufficiently large, the densities of state approach their limiting values [Figs. 5(a) and 5(b)], and the rescaled energy ϵ\epsilon defines the low-energy regime. The robustness of edge modes at low ϵ\epsilon [Figs. 5(c) and 5(d)], can be understood analytically through the mean-field approach of maximizing the entropy of the vortex system at fixed energy, particle number, and angular momentum if the domain has circular symmetry [40, 41, 32]. It is convenient to explicitly state factors of the vortex circulation λ\lambda in the mean-field picture. We set ρ=ωL02/(Nλ)\rho=\omega L_{0}^{2}/(N\lambda) to be the dimensionless vortex density, so ρ\rho integrates to L02=1L_{0}^{2}=1. Similarly, we rescale the streamfunction, ψ~=ψL02/N\tilde{\psi}=\psi L_{0}^{2}/N so that 2ψ~=λρ\nabla^{2}\tilde{\psi}=-\lambda\rho. The constrained entropy functional is [21]

[ρ]\displaystyle\mathcal{I}[\rho] =Sβλ2T02αΩd2𝐱ρβγL02NT0𝒥\displaystyle=S-\beta\lambda^{2}T_{0}^{2}\mathcal{H}-\alpha\int_{\Omega}d^{2}\mathbf{x}\,\rho-\frac{\beta\gamma L_{0}^{2}}{N}T_{0}\mathcal{J} (6)
=Ωd2𝐱ρlogρβλΩd2𝐱ψ~ραΩd2𝐱ρβγλΩd2𝐱r2ρ\displaystyle=-\int_{\Omega}d^{2}\mathbf{x}\,\rho\log\rho-\beta\lambda\int_{\Omega}d^{2}\mathbf{x}\,\tilde{\psi}\rho-\alpha\int_{\Omega}d^{2}\mathbf{x}\,\rho-\beta\gamma\lambda\int_{\Omega}d^{2}\mathbf{x}\,r^{2}\rho

where β\beta, α\alpha, γ\gamma are Lagrange multipliers enforcing the constraints of constant energy, particle number, and angular momentum, respectively, with units [β]=T2/L6[\beta]=T^{2}/L^{6}, [γ]=L2/T,[α]=0[\gamma]=L^{2}/T,[\alpha]=0. If Ω\Omega does not have circular symmetry, then γ=0\gamma=0. By analogy with the first law of thermodynamics, β\beta and α\alpha are sometimes thought of as an inverse temperature and a chemical potential. Extremizing \mathcal{I} yields

δδρ\displaystyle\frac{\delta\mathcal{I}}{\delta\rho} =logρ1βλψ~βλγr2α=0\displaystyle=-\log\rho-1-\beta\lambda\tilde{\psi}-\beta\lambda\gamma r^{2}-\alpha=0

and thus

ρ=e1αeβλ(ψ~+γr2)=1Zeβλ(ψ~+γr2)\displaystyle\rho=e^{-1-\alpha}e^{-\beta\lambda\left(\tilde{\psi}+\gamma r^{2}\right)}=\frac{1}{Z}e^{-\beta\lambda\left(\tilde{\psi}+\gamma r^{2}\right)}

where Z=e1+αZ=e^{1+\alpha}. Using the streamfunction-vorticity relation, 2ψ~=λρ\nabla^{2}\tilde{\psi}=-\lambda\rho, gives the mean-field equation

2ψ~=λZeβλ(ψ~+γr2),ψ~|Ω=0\displaystyle\nabla^{2}\tilde{\psi}=-\frac{\lambda}{Z}e^{-\beta\lambda\left(\tilde{\psi}+\gamma r^{2}\right)},\qquad\qquad\tilde{\psi}|_{\partial\Omega}=0 (7)

where

Z=Ωd2𝐱eβλ(ψ~+γr2)\displaystyle Z=\int_{\Omega}d^{2}\mathbf{x}\,e^{-\beta\lambda(\tilde{\psi}+\gamma r^{2})} (8)

By setting ϕ=βλψ~\phi=-\beta\lambda\tilde{\psi} and β1=β/Z\beta_{1}=\beta/Z, the mean-field equation can be expressed as a nonlinear eigenvalue problem

2ϕ\displaystyle\nabla^{2}\phi =β1λ2eβγλr2eϕ,ϕ|Ω=0\displaystyle=\beta_{1}\lambda^{2}e^{-\beta\gamma\lambda r^{2}}e^{\phi},\qquad\qquad\phi|_{\partial\Omega}=0

where

β\displaystyle\beta =β1λ2Ωd2𝐱eβλγr2eϕ\displaystyle=\beta_{1}\lambda^{2}\int_{\Omega}d^{2}\mathbf{x}\,e^{-\beta\lambda\gamma r^{2}}e^{\phi}

In the disk, we can simplify this equation by assuming axisymmetry, ϕ=ϕ(r)\phi=\phi(r), and neglecting angular momentum, γ=0\gamma=0, based on the strong correlation between angular momentum and energy [Fig. 5(a)]

ϕ′′+1rϕβ1λ2eϕ=0,ϕ(0)=0,ϕ(1)=0\displaystyle\phi^{\prime\prime}+\frac{1}{r}\phi^{\prime}-\beta_{1}\lambda^{2}e^{\phi}=0,\qquad\phi^{\prime}(0)=0,\quad\phi(1)=0

The boundary condition at 0 comes from the requirement that ϕ\phi is smooth at the origin. This equation can be solved exactly to give a vortex density ρ\rho with one free parameter [32]

ρ(r)=88π+β1(1βr28π+β)2,β>8π\displaystyle\rho(r)=\frac{8}{8\pi+\beta}\frac{1}{\left(1-\frac{\beta r^{2}}{8\pi+\beta}\right)^{2}},\qquad\beta>-8\pi (9)

This solution agrees quantitatively with simulations of Hamiltonian dynamics [Figs. 5(e) and 5(f)], confirming the validity of the mean-field theory at low energies. Furthermore, the mean-field solution predicts a wide range of low-energy edge modes. Whenever β>0\beta>0, the solution (9) is maximized on the boundary. For large β\beta, the solution describes an increasingly concentrated edge mode. The role of image vortices in this edge mode solution can be visualized by mapping the system onto a sphere [Figs. 1 and 6].

Refer to caption
Figure 7: Low-energy edge modes persist at large vortex numbers and are in quantitative agreement with mean-field predictions. (a) The density of states over rescaled energy (ϵ\epsilon) for N=80N=80 (blue histogram) and N=1000N=1000 (red circles) demonstrates convergence to the limiting density (solid curve). The green line selects the rescaled energy ϵ=2.5\epsilon=-2.5 at N=80N=80. (b) Streamlines demonstrate the flow pattern of a sample point in phase space with low energy, ϵ=2.5\epsilon=-2.5 (see movie S3). (c) The time-averaged Hamiltonian dynamics of N=80N=80 vortices at ϵ=2.5\epsilon=-2.5 exhibits edge modes (see movie S4). Simulation time: T=8×103T0T=8\times 10^{3}T_{0}. (d) Mean-field theory in a bean-shaped domain predicts edge modes (β=15\beta=15). (e, f) The mean-field theory prediction (solid black curve) agrees quantitatively with time-averaged Hamiltonian dynamics (green circles), and deviates significantly from the uniform vortex distribution (solid horizontal line).

IV.3 Topological interpretation of edge modes

Operators of the form 2m2\nabla^{2}-m^{2} have a topological interpretation in certain contexts, including in the theory of chiral hydrodynamics [42]. In our system, this operator appears in the linearization of the mean-field equations (7) after neglecting angular momentum (γ=0\gamma=0)

(2βZλ2)ψ~=λZ\displaystyle\left(\nabla^{2}-\frac{\beta}{Z}\lambda^{2}\right)\tilde{\psi}=-\frac{\lambda}{Z} (10)

This linearization is valid when |βλψ~||\beta\lambda\tilde{\psi}| is small, which holds close to the boundary, see Eq. (7). Although this equation has exponentially decaying solutions, the assumption that |βλψ~||\beta\lambda\tilde{\psi}| is small means that these solutions are not valid everywhere. The true decay behavior is given by exact solutions to the full nonlinear equation, such as (9). Setting ψ0=ψ~1/βλ\psi_{0}=\tilde{\psi}-1/\beta\lambda removes the constant term in equation (10)

(2β1λ2)ψ0=0\displaystyle\left(\nabla^{2}-\beta_{1}\lambda^{2}\right)\psi_{0}=0 (11)

where β1=β/Z\beta_{1}=\beta/Z as before.

The topological interpretation of this simplified equation comes from taking square root of the differential operator

M=(iyx+λβ1x+λβ1iy),M2=(2β1λ2)I2\displaystyle M=\begin{pmatrix}-i\partial_{y}&&-\partial_{x}+\lambda\sqrt{\beta_{1}}\\ \partial_{x}+\lambda\sqrt{\beta_{1}}&&i\partial_{y}\end{pmatrix},\qquad M^{2}=-\left(\nabla^{2}-\beta_{1}\lambda^{2}\right)I_{2}

where I2I_{2} is the 2×22\times 2 identity matrix. The matrix MM is the 2D Dirac Hamiltonian, and has topological properties [42]. In the Fourier representation, ixqx-i\partial_{x}\mapsto q_{x} and iyqy-i\partial_{y}\mapsto q_{y}, we can write the matrix operator MM as

M(qx,qy,λ)=(qyiqx+λβ1iqx+λβ1qy)\displaystyle M(q_{x},q_{y},\lambda)=\begin{pmatrix}q_{y}&&-iq_{x}+\lambda\sqrt{\beta_{1}}\\ iq_{x}+\lambda\sqrt{\beta_{1}}&&-q_{y}\end{pmatrix} (12)

When viewed as a function on the parameter space (qx,qy,λ)(q_{x},q_{y},\lambda), a topological quantity known as a Chern number [42, 43] can be associated with MM (Appendix). This invariant measures the winding of the eigenvectors of MM across the (qx,qy)(q_{x},q_{y}) plane, and depends only on the sign of λ\lambda. As a consequence, regions in the physical (x,y)(x,y) space where λ\lambda changes sign are special, and host localized steady-state flows [42] (Appendix). This corresponds exactly to our physical picture of vortex dynamics. Our systems of positive vortices have λ=1\lambda=1, and are surrounded by negative image vortices with λ=1\lambda=-1 (Fig. 6). At the boundary, where λ\lambda changes sign, we observe statistical edge modes. This argument requires β<0\beta<0, and so is not incompatible with the high energy regime, where edge modes are not observed. Although this description [42, 44] is not the standard picture of topological edge modes [43], it presents a possible avenue for exploring connections with other topological phenomena.

IV.4 Mean-field theory in nonconvex domains

Low-energy edge modes also survive in nonconvex domains at large NN. As in the disk, the rescaled energy ϵ\epsilon defines low-energy states [Fig. 7(a)] which display statistical edge modes [Figs. 7(b) and 7(c)]. Expressed as a nonlinear eigenvalue problem, the mean-field equation without angular momentum is

2ϕ=β1λ2eϕ,ϕ|Ω=0\displaystyle\nabla^{2}\phi=\beta_{1}\lambda^{2}e^{\phi},\qquad\qquad\phi|_{\partial\Omega}=0 (13)

where ρ\rho is obtained as

ρ=1β2ϕ,β=β1λ2Ωd2𝐱eϕ\displaystyle\rho=\frac{1}{\beta}\nabla^{2}\phi,\qquad\qquad\beta=\beta_{1}\lambda^{2}\int_{\Omega}d^{2}\mathbf{x}\,e^{\phi}

The numerical solution of this equation agrees with time-averaged simulations of the Hamiltonian dynamics [Fig. 7(c)-7(f)]. Mean-field theory thus remains valid for irregular, nonconvex domains at low energy, and produces statistical states with edge modes. In particular, any smooth solution of (13) with β1>0\beta_{1}>0 gives a vortex density which is maximized on the boundary. To see this, observe that ϕ\phi is subharmonic, 2ϕ>0\nabla^{2}\phi>0. By the maximum principle for subharmonic functions [32], ϕ\phi must be maximized on the boundary of its domain. Since ϕ\phi is constant on the boundary, we have

ϕ(𝐱b)ϕ(𝐱)𝐱bΩ,𝐱Ω\phi(\mathbf{x}_{b})\geq\phi(\mathbf{x})\qquad\forall\mathbf{x}_{b}\in\partial\Omega,\;\mathbf{x}\in\Omega

The vortex density ρ\rho is an increasing function of ϕ\phi,

ρ=1β2ϕ=β1λ2βeϕ\displaystyle\rho=\frac{1}{\beta}\nabla^{2}\phi=\frac{\beta_{1}\lambda^{2}}{\beta}e^{\phi}

Thus ρ\rho is also maximized on the boundary.

V Conclusions

By explicit treatment of boundaries, we have shown that the strongly interacting point vortex system displays statistical edge modes at low energy. These edge modes are robust to changes in geometry, surviving in convex and nonconvex domains, and persist in the large vortex number limit. An interesting future extension could be the investigation of similar phenomena in systems with multiple vortex species, and in more complicated domains, including multiply connected domains, for which there exist a wide variety of conformal mapping techniques [45, 46, 47, 48]. Although our edge modes are not explicitly topological, there might exist links to topological edge modes in other systems, as the mean-field theory used here bears some resemblance to the description of Chern-Simons vortices [49]. More generally, the above results raise the interesting question of whether an explicit treatment of boundaries could yield insights into the real-space mechanisms underlying other topological edge-mode phenomena [50, 51, 52, 42, 53, 54].

VI Acknowledgements

We are grateful to Henrik Ronellenfitsch, Peter Baddoo, Pearson Miller and Martin Zwierlein for valuable discussions and comments. This work was supported by a MathWorks Fellowship (V.P.P.), and the Robert E. Collins Distinguished Scholar Fund of the MIT Mathematics Department (J.D.).

Appendix

VI.1 Topological aspects of the mean-field equation

VI.1.1 Chern numbers

The linearized mean-field equation (11) can be interpreted topologically by virtue of its associated Dirac matrix operator from Eq. (12),

M(qx,qy,λ)=(qyiqx+λβ1iqx+λβ1qy)\displaystyle M(q_{x},q_{y},\lambda)=\begin{pmatrix}q_{y}&&-iq_{x}+\lambda\sqrt{\beta_{1}}\\ iq_{x}+\lambda\sqrt{\beta_{1}}&&-q_{y}\end{pmatrix}

Each eigenvector of MM corresponds to a Chern number. We sketch the calculation of these quantities following Refs.  [43, 42]. To this end, we first rewrite MM by formally expressing the matrix parameters (qx,qy,λβ1)(q_{x},q_{y},\lambda\sqrt{\beta_{1}}) in terms of spherical polar coordinates

λβ1=hcosϕsinθ,qx=hsinϕsinθ,qy=hcosθ\displaystyle\lambda\sqrt{\beta_{1}}=h\cos\phi\sin\theta,\quad q_{x}=h\sin\phi\sin\theta,\quad q_{y}=h\cos\theta

Then

M=(hcosθheiϕsinθheiϕsinθhcosθ)\displaystyle M=\begin{pmatrix}h\cos\theta&&he^{-i\phi}\sin\theta\\ he^{i\phi}\sin\theta&&-h\cos\theta\end{pmatrix}

The eigenvectors of MM are

Ψ=(eiϕsinθ/2cosθ/2),Ψ+=(eiϕcosθ/2sinθ/2)\displaystyle\Psi_{-}=\begin{pmatrix}e^{-i\phi}\sin\theta/2\\ -\cos\theta/2\end{pmatrix},\qquad\Psi_{+}=\begin{pmatrix}e^{-i\phi}\cos\theta/2\\ \sin\theta/2\end{pmatrix}

The Berry phase for each eigenvector is

Aθ\displaystyle A^{-}_{\theta} =iΨ|θΨ=0,Aϕ=iΨ|ϕΨ=sin2θ2\displaystyle=-i\langle\Psi_{-}|\partial_{\theta}\Psi_{-}\rangle=0,\qquad A^{-}_{\phi}=-i\langle\Psi_{-}|\partial_{\phi}\Psi_{-}\rangle=-\sin^{2}\frac{\theta}{2}
Aθ+\displaystyle A^{+}_{\theta} =iΨ+|θΨ+=0,Aϕ+=iΨ+|ϕΨ+=cos2θ2\displaystyle=-i\langle\Psi_{+}|\partial_{\theta}\Psi_{+}\rangle=0,\qquad A^{+}_{\phi}=-i\langle\Psi_{+}|\partial_{\phi}\Psi_{+}\rangle=-\cos^{2}\frac{\theta}{2}

This gives the Berry curvature in polar coordinates

Fθϕ±=θAϕ±ϕAθ±=±12sinθ\displaystyle F_{\theta\phi}^{\pm}=\partial_{\theta}A_{\phi}^{\pm}-\partial_{\phi}A_{\theta}^{\pm}=\pm\frac{1}{2}\sin\theta

Transforming back to Cartesian coordinates (qx,qy,λβ1)(q_{x},q_{y},\lambda\sqrt{\beta_{1}}), we find

F±=±12λβ1qx2+qy2+λ2β1\displaystyle F^{\pm}=\pm\frac{1}{2}\frac{\lambda\sqrt{\beta_{1}}}{q_{x}^{2}+q_{y}^{2}+\lambda^{2}\beta_{1}}

Finally, the Chern number for each eigenvector is given by integrating FF over qxq_{x} and qyq_{y}

C±=dqxdqy2πF±=±12sgn(λ)\displaystyle C^{\pm}=\int\frac{dq_{x}\,dq_{y}}{2\pi}F^{\pm}=\pm\frac{1}{2}\,\text{sgn}(\lambda)

Regions of the (x,y)(x,y) plane with λ\lambda’s of different signs are therefore associated with different Chern numbers. The nonzero difference in Chern number across such a boundary is responsible for presence of a localized edge mode

|ΔC|=|C±(λ>0)C±(λ<0)|=1\displaystyle|\Delta C|=|C^{\pm}(\lambda>0)-C^{\pm}(\lambda<0)|=1

VI.1.2 Localized states

Another way to see that localized states occur when λ\lambda changes sign is to look for solutions to the following equation [43]

M(fg)=(iyx+λβ1x+λβ1iy)(fg)=0\displaystyle M\begin{pmatrix}f\\ g\end{pmatrix}=\begin{pmatrix}-i\partial_{y}&&-\partial_{x}+\lambda\sqrt{\beta_{1}}\\ \partial_{x}+\lambda\sqrt{\beta_{1}}&&i\partial_{y}\end{pmatrix}\begin{pmatrix}f\\ g\end{pmatrix}=0

for some functions ff and gg. Assume that there is a boundary at x=0x=0, with positive vortices in the region x>0x>0 and negative (image) vortices in the region x<0x<0. For ease of notation, set m=λβ1m=\lambda\sqrt{\beta_{1}}, so m>0m>0 when x>0x>0 and m<0m<0 and x<0x<0. To solve these equations, we assume that mm is continuous but changes rapidly from β1-\sqrt{\beta_{1}} to +β1\sqrt{\beta_{1}} across the boundary at x=0x=0. We will look for separable functions ff and gg, which decay for large x,yx,y

ifygx+m(x)g\displaystyle-if_{y}-g_{x}+m(x)g =0\displaystyle=0
fx+m(x)f+igy\displaystyle f_{x}+m(x)f+ig_{y} =0\displaystyle=0

where subscripts denote derivatives here. Consider the first equation

ify(xm(x))g=0\displaystyle-if_{y}-\left(\partial_{x}-m(x)\right)g=0

Since m(x)m(x) and xx have the same sign, gg will grow exponentially. Therefore a bounded solution must have g=0g=0. This gives fy=0f_{y}=0 immediately, so the only remaining equation is

fx=m(x)f\displaystyle f_{x}=-m(x)f

This has solution

f(x)exp(0x𝑑xm(x))\displaystyle f(x)\propto\exp{\left(-\int_{0}^{x}dx^{\prime}\,m(x^{\prime})\right)}

As expected, this solution is sharply peaked around the boundary x=0x=0, and decays rapidly away from x=0x=0.

While the linearized mean-field equation (11) enables an interpretation within the conventional linear-operator framework of topologically protected modes, the more accurate description of the strongly interacting vortex system is provided by its nonlinear mean-field equation (7).

VI.2 Equilibration at large NN

Refer to caption
Figure 8: Hamiltonian dynamics, Monte Carlo sampling, and mean-field predictions are in quantitative agreement at low energy (N=500N=500). (a) Monte Carlo sampling at fixed energy (ϵ=2.5\epsilon=-2.5) and varying angular momentum reveals a low energy edge mode (n=3540n=3540 samples of N=500N=500 vortices). (b) The time-averaged Hamiltonian dynamics of N=500N=500 vortices at ϵ=2.5\epsilon=-2.5 exhibits edge modes. Simulation time: T=2×103T0T=2\times 10^{3}T_{0}. (c) Mean-field theory in the disk, at zero angular momentum, predicts edge modes (β=5.2,γ=0\beta=5.2,\gamma=0). Away from r=0r=0, quantitative agreement is observed between the mean-field theory prediction (solid black curve), time-averaged Hamiltonian dynamics (filled green circles) and Monte Carlo sampling (empty blue circles). Solid horizontal line shows uniform vortex distribution.

In the systems of positive point vortices considered here, time-averaged dynamical simulations are found to agree with vortex distributions obtained by Monte Carlo sampling at fixed energy, even for large (N=500)(N=500) vortex numbers (Fig. 8). Although there are mathematical questions which remain unresolved, it is believed that this observed ergodicity is an appropriate assumption for the point vortex model under certain conditions [55, 21]. In other cases, the system is known to be non-ergodic [56, 57]. Numerical studies indicate evidence for ergodicity at intermediate energies for mixed vortex systems (with λa=±1\lambda_{a}=\pm 1) in bounded [26, 36] and periodic [36] domains. On the sphere, the ergodic hypothesis appears to hold for a range of energies [58]. At very low energies, however, dipole formation in mixed vortex systems can produce quasi-stationary states [59, 36]. Furthermore, it is possible that the relaxation time scales unfavorably with the vortex number NN in certain scenarios [21]. Since we only consider positive vortices, we do not expect dipole formation to obstruct equilibration at very low energies. However, relaxation timescale issues could be responsible for the discrepancy we observe in the vortex distributions obtained from dynamical simulations, Monte Carlo sampling and mean-field theory, near the center (r0r\to 0) of the disk [Fig. 8(c)].

The edge mode obtained for N=500N=500 vortices at rescaled energy ϵ=2.5\epsilon=-2.5 (Fig. 8) is shallower than that obtained for (N,ϵ)=(80,2.5)(N,\epsilon)=(80,-2.5) (Figs. 5 and 7). In particular, the mean-field solution for the (N,ϵ)=(80,2.5)(N,\epsilon)=(80,-2.5) edge mode has β=15\beta=15, wheras the (N,ϵ)=(500,2.5)(N,\epsilon)=(500,-2.5) edge mode has β=5.2\beta=5.2. However, in both cases, the mean-field solution (9) accurately describes the vortex density

ρ(r)=88π+β1(1βr28π+β)2,β>8π\displaystyle\rho(r)=\frac{8}{8\pi+\beta}\frac{1}{\left(1-\frac{\beta r^{2}}{8\pi+\beta}\right)^{2}},\qquad\beta>-8\pi

This suggests that, by choosing an ϵ\epsilon which corresponds to a larger β\beta, a sharper edge mode can be found for N=500N=500.

VI.3 Mean-field theory from the canonical ensemble

The mean-field equations (7) can be derived using the canonical ensemble. Following the presentation in Ref. [60], the canonical partition function for NN vortices in a domain Ω\Omega is

Z(β)=ΩN𝑑ξeβ(ξ)\displaystyle Z(\beta)=\int_{\Omega^{N}}d\xi\,e^{-\beta\mathcal{H}(\xi)}

where ξ=(x1,y1,,xN,yN)\xi=(x_{1},y_{1},...,x_{N},y_{N}) is a point in ΩN\Omega^{N}. This can be rewritten in terms of the dimensionless vortex density ρ=ωT0\rho=\omega T_{0}. Let Γ[ρ]\Gamma[\rho] be the functional corresponding to the total vortex density

Γ[ρ]=Ωd2𝐱ρ(𝐱)=1\displaystyle\Gamma[\rho]=\int_{\Omega}d^{2}\mathbf{x}\,\rho(\mathbf{x})=1

Setting W[ρ]W[\rho] to be the number of microstates {ξ}\{\xi\} corresponding to the macrostate {ρ(𝐱)}\{\rho(\mathbf{x})\}, allows us to write Z(β)Z(\beta) as an integral over fields ρ(𝐱)\rho(\mathbf{x})

Z(β)=ΩN𝑑ξeβ(ξ)=𝒟ρW[ρ]δ(Γ[ρ]1)eβ[ρ]\displaystyle Z(\beta)=\int_{\Omega^{N}}d\xi\,e^{-\beta\mathcal{H}(\xi)}=\int\mathcal{D}\rho\,W[\rho]\,\delta\left(\Gamma[\rho]-1\right)e^{-\beta\mathcal{H}[\rho]}

The energy is

[ρ]=T02Ωd2𝐱d2𝐱ρ(𝐱)G(𝐱𝐱)ρ(𝐱)=T02Ωd2𝐱ψ~ρ\displaystyle\mathcal{H}[\rho]=-T_{0}^{2}\int_{\Omega}d^{2}\mathbf{x}\,d^{2}\mathbf{x}^{\prime}\,\rho(\mathbf{x})G(\mathbf{x}-\mathbf{x}^{\prime})\rho(\mathbf{x}^{\prime})=T_{0}^{2}\int_{\Omega}d^{2}\mathbf{x}\,\tilde{\psi}\rho

where the second equality uses ψ~=ψT0\tilde{\psi}=\psi T_{0} from (6). By a counting argument [32, 60], the entropy S[ρ]S[\rho] is related to W[ρ]W[\rho] by

S[ρ]=Ωd2𝐱ρlogρ=logW[ρ]\displaystyle S[\rho]=-\int_{\Omega}d^{2}\mathbf{x}\,\rho\log\rho=\log W[\rho]

The partition function Z(β)Z(\beta), and the probability P[ρ]P[\rho] of the density ρ\rho are therefore

Z(β)\displaystyle Z(\beta) =𝒟ρδ(Γ[ρ]1)eS[ρ]β[ρ]\displaystyle=\int\mathcal{D}\rho\,\delta\left(\Gamma[\rho]-1\right)e^{S[\rho]-\beta\mathcal{H}[\rho]}
P[ρ]\displaystyle P[\rho] δ(Γ[ρ]1)eS[ρ]β[ρ]\displaystyle\propto\delta\left(\Gamma[\rho]-1\right)e^{S[\rho]-\beta\mathcal{H}[\rho]}

The most probable distribution follows from maximizing SβS-\beta\mathcal{H} subject to Γ[ρ]=1\Gamma[\rho]=1. In other words, we must maximize the functional

[ρ]=SβαΩd2𝐱ρ\displaystyle\mathcal{I}[\rho]=S-\beta\mathcal{H}-\alpha\int_{\Omega}d^{2}\mathbf{x}\,\rho

Upon rescaling β\beta, this is exactly the maximization in (6) without angular momentum (γ=0\gamma=0). As before, this maximization yields the mean-field equations (7) with γ=0\gamma=0.

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