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Transport in honeycomb lattice with random π\pi-fluxes: Implications for low-temperature thermal transport in the Kitaev spin liquids

Zekun Zhuang Center for Materials Theory, Rutgers University, Piscataway, New Jersey 08854, USA
Abstract

Motivated by the thermal transport problem in the Kitaev spin liquids, we consider a nearest-neighbor tight-binding model on the honeycomb lattice in the presence of random uncorrelated π\pi-fluxes. We employ different numerical methods to study its transport properties near half-filling. The zero-temperature DC conductivity away from the Dirac point is found to be quadratic in Fermi momentum and inversely proportional to the flux density. Localization due to the random π\pi-fluxes is observed and the localization length is extracted. Our results imply that, for realistic system size, the thermal conductivity of a pure Kitaev spin liquid diverges as κKT3eΔv/kBT\kappa_{\text{K}}\sim T^{3}e^{\Delta_{v}/k_{B}T} when kBTΔvk_{B}T\ll\Delta_{v}, and suggest the possible occurrence of strong Majorana localization κK/TkB2/2π\kappa_{\text{K}}/T\ll k_{B}^{2}/2\pi\hbar when kBTΔvk_{B}T\sim\Delta_{v}, where Δv\Delta_{v} is the vison gap.

I Introduction

Quantum spin liquids (QSLs) are an exotic state of matter with no local symmetry breaking, deconfined fractionalized quasiparticles, and emergent gauge excitations [1, 2, 3]. The Kitaev model, an exactly solvable honeycomb model, provides a typical framework for describing such a phase, where spins fractionalize to Majorana fermions and Z2Z_{2} gauge excitations (visons) [4]. Thanks to the proposal by Jackeli and Khaliullin [5], which suggests that the Kitaev model can be realized in certain strongly spin-orbit coupled systems, a growing number of Kitaev candidate materials have been discovered in the past decade [6, 7].

Despite the theoretical proposal of QSLs for several decades, their experimental identification remains challenging. Thermal transport experiments are a promising technique for characterizing QSLs, as they allow the detection of charge-neutral, mobile quasiparticles. For example, in the Kitaev candidate material αRuCl3\alpha-\text{RuCl}_{3}, a half-quantized thermal Hall conductance has been observed, indicating the existence of a chiral Majorana mode at the edge of the non-Abelian Kitaev spin liquid [8, 9, 10]. To fully understand the experimental results, it is crucial to predict the thermal transport signatures of QSLs, particularly those proximate to the exact Kitaev model, in various different regimes [11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21].

The longitudinal thermal conductivity κxx(ω,T)\kappa_{\text{xx}}(\omega,T) of the Kitaev model has been numerically investigated using Kubo’s formalism, and the DC thermal conductivity κK(T)\kappa_{\text{K}}(T) can be obtained by extrapolation of κxx(ω,T)\kappa_{\text{xx}}(\omega,T) to the ω0\omega\rightarrow 0 limit [11, 12, 13, 14, 15]. When the temperature TT is comparable to or smaller than the vison gap Δv\Delta_{v}, such extrapolation appears to give results with significant error bars and calculations with larger system sizes are needed [11, 15], leaving the low-temperature behavior of κK\kappa_{\text{K}} inconclusive. Neglecting the gauge excitations in the Kitaev model, it is possible to regard an undoped graphene as two stacks of the Kitaev model, and thus expect that the thermal transport of Kitaev spin liquid and the electric transport of graphene may have similar low-temperature behavior. It was proposed that in graphene there exists a universal minimum electrical conductivity σmin=e2/πh\sigma_{\text{min}}=e^{2}/\pi h per valley per spin, regardless of the concentration of disorders [22, 23, 24]. It is thus natural to ask whether a similar ‘minimum thermal conductivity’ (MTC) also exists in a pure Kitaev model. A previous quantum Monte Carlo study seems to support the existence of MTC in the low-temperature regime, i.e. limT0κK/T=kB2/12\lim_{T\rightarrow 0}\kappa_{\text{K}}/T=k_{B}^{2}/12\hbar, but further justification is required due to the significant uncertainties and finite-size effects in the numerical simulation [11]. Moreover, at low temperatures, the phase coherence length may exceed the dimensions of a realistic sample, within which the quantum interference effects are essential. Consequently, the thermally excited random Z2Z_{2} flux background may strongly localize Majorana particles [25, 14, 26], provided that the localization length is smaller than the system size. Such localization effects are uncaptured by previous calculations performed for relatively small systems, and overlooking these effects may crucially affect the interpretation of experimental results.

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Figure 1: (a) Kitaev on the honeycomb lattice, where different colors denote different types of bonds. (b) The nearest-neighbor tight-binding model on the honeycomb lattice threaded by random π\pi-fluxes (grey areas), where the solid (dashed) lines denote the bonds on which the Z2Z_{2} gauge field takes value 1(1)1(-1).

To understand the low-temperature thermal conductivity of the Kitaev model in the absence of disorder and magnetic fields, in this work we numerically study the transport of complex fermions in a random π\pi-flux honeycomb model (RPFHM) near half-filling. This approach is motivated by the observation that the Kitaev model (see Fig. 1) can be seen as half of the RPFHM (see Fig. 1), and the thermal conductivity of the former is linked to the electrical conductivity of the latter via the Wiedemann-Franz (WF) law. Furthermore, the RPFHM is of academic interest on its own, as this random Z2Z_{2}-flux problem is less studied compared to random U(1)U(1)-flux models [27, 28, 29, 30, 31].

We focus on the zero-temperature longitudinal DC conductivity of the RPFHM and its localization properties as a function of flux density and chemical potential. We extract the dependence of DC conductivity on flux density and Fermi wavevector in the semi-classical diffusive regime. Our analysis reveals Anderson localization due to random π\pi-fluxes, and we obtain 2-D localization lengths. Our results indicate that the low-temperature thermal conductivity of a clean Kitaev model neither exhibits MTC nor vanishes, but instead diverges as κKT3eΔv/kBT\kappa_{\text{K}}\sim T^{3}e^{\Delta_{v}/k_{B}T}, which is unexpected based on previous studies. Additionally, when kBTΔvk_{B}T\sim\Delta_{v}, the thermal conductivity could be significantly suppressed due to strong Majorana localization.

II Random π\pi-flux honeycomb model

II.1 Model

We consider a spinless tight-binding model on the honeycomb lattice (Fig. 1) with Hamiltonian

HG=ti,juijfifj,H_{\text{G}}=-t\sum_{\langle i,j\rangle}u_{ij}f_{i}^{\dagger}f_{j}, (1)

where i,j\langle i,j\rangle denotes the nearest-neighbor coupling between site ii and jj, tt is a real number and uij=uji=±1u_{ij}=u_{ji}=\pm 1 is the Z2Z_{2} gauge field coupled to charge ee fermions. The creation and annihilation operators obey the anticommutation relation {fi,fj}=δij\{f_{i},f_{j}^{\dagger}\}=\delta_{ij}. To avoid the gauge redundancy, one could define the gauge-invariant Z2Z_{2} flux operator Wp=jkpujk=±1W_{p}=\prod_{\langle jk\rangle\in p}u_{jk}=\pm 1 on each plaquette pp. On each plaquette, the value of Z2Z_{2} flux takes 11 with probability 1nv1-n_{v} and 1-1 (π\pi-flux) with probability nvn_{v}, and WpW_{p} on different hexagons are uncorrelated. We emphasize that this differs from having independent random Z2Z_{2} gauge fields on each bond. According to the Altland-Zirnbauer classification [32, 33, 34], the system is in the orthogonal symmetry class AI when ϵ=E/t0\epsilon=E/t\neq 0, while it belongs to the chiral orthogonal symmetry class BDI at the Dirac point ϵ=0\epsilon=0. We aim to calculate the quench average of gauge-invariant observables, which are demonstrated in the following.

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Figure 2: The averaged DOS near the Dirac point for different flux densities. The DOS for nv0n_{v}\neq 0 is obtained via exact diagonalization of 10000-site systems and averaging over 190 random flux configurations.

II.2 Density of states

In the fluxless sector, Eq. (1) corresponds to the nearest-neighbor tight-binding model of graphene, which can be easily diagonalized and the analytic form of its density of states (DOS) is well known [35]. When π\pi fluxes are present, as seen in Fig. 2, for nv0.1n_{v}\lesssim 0.1 the DOS close to the Dirac point is greatly enhanced, while the DOS away from the Dirac point but below the Van Hove point remains almost unaffected. Remarkably, there appears a sharp DOS peak at the Dirac point, which is a characteristic of the chiral orthogonal symmetry class BDI [36, 37, 38, 39, 40, 41]. The non-vanishing DOS around the Dirac point suggests that, as long as the low-energy states are not fully localized, the conductance will be finite around the Dirac point and might even be enhanced due to the increasing DOS [42]. This contrasts with a pristine graphene whose conductance is either zero or of a few conductance quantum e2/he^{2}/h [43, 44].

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Figure 3: Schematics of the two-terminal setup used to compute the DC conductivity of RPFHM. The middle region, which is penetrated by random π\pi-fluxes (grey areas), is sandwiched between two semi-infinite ‘clean’ leads.

II.3 DC conductivity

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Figure 4: (a) DC conductivity σG\sigma_{\text{G}} (in unit of e2/he^{2}/h) versus (kFrm)2(k_{F}r_{m})^{2} for different nvn_{v} when LM=1083aL\approx M=108\sqrt{3}a; the inset is the zoom-in plot. (b) DC conductivity σG\sigma_{\text{G}} versus ln(L/a)\ln(L/a) for different energies and flux densities nv=0.02(yellow),0.03(red),0.05(blue)n_{v}=0.02(\text{yellow}),0.03(\text{red}),0.05(\text{blue}) and ϵ\epsilon; from top to the bottom, ϵ\epsilon decreases by 0.05 for same nvn_{v}. The error bars are smaller than the marker size and hence not shown.

To compute the DC conductivity, we employ the recursive Green’s function method to calculate the transmission function 𝐓(E,M,L)\mathbf{T}(E,M,L) between the left and right leads depicted in Fig. 3, as a function of energy EE, width MM and length LL. The conductance is given by the Landauer formula G=𝐓e2/hG=\mathbf{T}e^{2}/h [45], and the conductivity can be extracted by subtracting the contact resistance from the total resistance

σG=GLM=LM1𝐓(E,M,L)1𝐓(E,M,0)1e2h.\sigma_{\text{G}}=\frac{GL}{M}=\frac{L}{M}\frac{1}{\mathbf{T}(E,M,L)^{-1}-\mathbf{T}(E,M,0)^{-1}}\frac{e^{2}}{h}. (2)

The transmission coefficient can be calculated by [46, 47]

𝐓=Tr(ΓLGRΓRGA),\mathbf{T}=\text{Tr}(\Gamma_{L}G^{R}\Gamma_{R}G^{A}), (3)

where GR(A)=(EHGΣLR(A)ΣRR(A))1G^{R(A)}=(E-H_{\text{G}}-\Sigma_{L}^{R(A)}-\Sigma_{R}^{R(A)})^{-1} is the retarded (advanced) Green’s function in the presence of semi-infinite leads, ΣαR(A)\Sigma_{\alpha}^{R(A)} is the self-energy due to the lead α\alpha, and Γα=i(ΣαRΣαA)\Gamma_{\alpha}=i(\Sigma_{\alpha}^{R}-\Sigma_{\alpha}^{A}). The self-energies of the leads can be obtained by computing the transfer matrix iteratively [48, 49] and the bulk Green’s function can be calculated efficiently with recursive method [50]. Although we only consider the case that the edge is armchair-type, we expect the result for the zigzag edge to be similar in the thermodynamic limit, as the pure system is isotropic at low energies. We compute the conductivity of 2000 different samples and then take the mean value. In general, the conductivity depends on the aspect ratio M/LM/L and we fix it to be close to unity.

Figure 4 shows the dependence of DC conductivity on the dimensionless parameter kFrmk_{F}r_{m} for fixed system size L=1083aL=108\sqrt{3}a, where rm=(33a2/2πnv)1/2r_{m}=(3\sqrt{3}a^{2}/2\pi n_{v})^{1/2} is the average distance between π\pi-fluxes. Due to the existence of particle-hole symmetry, we only show results for positive ϵ\epsilon hereafter. We also only demonstrate the results away from the Dirac point where the DOS is not significantly changed by π\pi-fluxes, such that Eq. (2) is applicable and the conductivity is not underestimated due to the vanishing DOS of leads [51]. The failure of the Landauer approach at the Dirac point can also be understood by noting that it is based on the calculation of transition probabilities between different unperturbed states in clean leads, while the unperturbed eigenstates may not be a good description in the vicinity of the Dirac point where the disorder effects are significant. When the Fermi wavelength λF=2π/kF\lambda_{F}=2\pi/k_{F} of Dirac fermion is much shorter than the mean flux distance rmr_{m}, one observes that the DC conductivity is approximately linear in (kFrm)2(k_{F}r_{m})^{2}, namely

σG/(e2/h)d(kFrm)2+b,\sigma_{\text{G}}/(e^{2}/h)\approx d(k_{F}r_{m})^{2}+b, (4)

where d1.6d\approx 1.6, and bb weakly depends on nvn_{v} and LL (see also Fig. 4). In this work, we assume the above relation holds as long as the momentum kFk_{F} is small so that the dispersion can be regarded as linear. Compared to the Drude conductivity σsc=kFlee2/h\sigma_{\text{sc}}=k_{F}l_{e}e^{2}/h, this suggests a semiclassical transport regime where, for sufficiently large σG\sigma_{\text{G}}, the mean free path lel_{e} is approximately inversely proportional to nvn_{v} and proportional to the Fermi wavevector kFk_{F}. Using the Drude formula, we estimate that in Fig. 4, the largest mean free path le,max80al_{e,\text{max}}\approx 80a is smaller than the system size LL, consistent with the diffusive transport regime for which the Drude formula is applicable. When σGe2/h\sigma_{\text{G}}\lesssim e^{2}/h, which also coincides with kFrm1k_{F}r_{m}\lesssim 1, the system enters the quantum regime where the conductivity starts to saturate, evidenced by the upturn at small kFrmk_{F}r_{m} shown in the inset of Fig. 4.

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Figure 5: (a) Log-log plot of λM/M\lambda_{M}/M versus M/aM/a for nv=0.05n_{v}=0.05; we choose M/(3a)=48,60,72,90M/(\sqrt{3}a)=48,60,72,90 for 0.05ϵ0.50.05\leq\epsilon\leq 0.5 (black, the arrow denotes the ascending order and ϵ\epsilon increases by 0.025 between adjacent lines), M/(3a)=48,49,50,60,61,62,72,73,74,90,91,92M/(\sqrt{3}a)=48,49,50,60,61,62,72,73,74,90,91,92 for ϵ=0.025\epsilon=0.025 (red) and ϵ=0\epsilon=0 (blue). (b) One-parameter scaling of the Mackinnon-Kramer parameter λM/M\lambda_{M}/M. The circles denote the data for ϵ[0.025,0.5](nv=0.02,0.03,0.05,0.1,0.2,0.5)\epsilon\in[0.025,0.5](n_{v}=0.02,0.03,0.05,0.1,0.2,0.5); to linearly fit the scaling function at small ξ/M\xi/M we also compute the parameter range ϵ[2.96,3](nv=0.05)\epsilon\in[2.96,3](n_{v}=0.05), represented by the triangles. (c) The 2-D localization length ξ\xi extracted by the scaling analysis as a function of ϵ\epsilon.

In graphene, the inter(intra)-valley scattering leads to (anti-)localization due to the constructive(destructive) quantum interference of backscattering amplitude [35, 52, 53]. In RPFHM, the π\pi-fluxes may be regarded as short-range scatters that mix different valleys and are hence expected to localize the Dirac fermions. According to the theory of weak-localization [54], the conductivity acquires a logarithmic quantum correction, namely

σG=σscαe2hlnLl0,\sigma_{\text{G}}=\sigma_{\text{sc}}-\frac{\alpha e^{2}}{h}\ln\frac{L}{l_{0}}, (5)

where l0l_{0} is the lower cutoff length of the diffusive transport regime and is comparable to the mean free path lel_{e}. Our results in Fig. 4 suggest that the conductivity decreases logarithmically with the system size, thus supporting the existence of weak localization. By numerical fitting, we obtain α0.39\alpha\approx 0.39, which is close to α=1/π\alpha=1/\pi predicted for the orthogonal universality class AI.

II.4 Anderson Localization

To further study the effects of localization in the RPFHM, we use the transfer matrix method [55, 56] to compute the Lyapunov exponent of the system around its Dirac point. We consider the same geometry as shown in Fig. 3, in which the system can be divided into successive slices labeled by nn. The Schrödinger equation at given energy EE can be written in the form of

(|Ψn+1|Ψn)=Tn(|Ψn|Ψn1),\left(\begin{array}[]{c}|\Psi_{n+1}\rangle\\ |\Psi_{n}\rangle\end{array}\right)=T_{n}\left(\begin{array}[]{c}|\Psi_{n}\rangle\\ |\Psi_{n-1}\rangle\end{array}\right), (6)

where |Ψn|\Psi_{n}\rangle is the wavefunction of slice nn, TnT_{n} is the transfer matrix

Tn=(Hn,n+11(EHn,n)Hn,n+11Hn,n1𝟙0),T_{n}=\left(\begin{array}[]{cc}H_{n,n+1}^{-1}(E-H_{n,n})&-H_{n,n+1}^{-1}H_{n,n-1}\\ \mathds{1}&0\end{array}\right), (7)

and Hm,nH_{m,n} is the Hamiltonian matrix between slice mm and nn. By iteration, one obtains

(|Ψn+1|Ψn)=Mn(|Ψ1|Ψ0),\left(\begin{array}[]{c}|\Psi_{n+1}\rangle\\ |\Psi_{n}\rangle\end{array}\right)=M_{n}\left(\begin{array}[]{c}|\Psi_{1}\rangle\\ |\Psi_{0}\rangle\end{array}\right), (8)

where Mn=TnTn1T2T1M_{n}=T_{n}T_{n-1}\cdots T_{2}T_{1}. There exists a limiting matrix M=limn(MnMn)1/(2n)M_{\infty}=\text{lim}_{n\rightarrow\infty}(M_{n}M_{n}^{\dagger})^{1/(2n)}, which has eigenvalues eγie^{\gamma_{i}}, where γi\gamma_{i} is the Lyapunov exponent. The Lyapunov exponents must come in opposite pairs and the quasi-one-dimensional localization length λM\lambda_{M} can be defined as the inverse of the smallest positive Lyapunov exponent. In all the simulations, we implement Gram-Schmidt orthonormalization every 8 steps for numerical stability (e.g. see [28] and references herein) and the relative error of all the data is controlled within ϵerror1%\epsilon_{\text{error}}\lesssim 1\%.

According to the one-parameter scaling theory of Anderson localization [55, 56], the MacKinnon-Kramer parameter λM/M\lambda_{M}/M is a single-parameter function of ξ/M\xi/M, namely λM/M=f(ξ/M)\lambda_{M}/M=f(\xi/M), where the 2-D localization length ξ\xi depends on all parameters except MM, which are nvn_{v} and ϵ\epsilon in our case. For the system in the orthogonal universality class AI, the scaling function f(x)f(x) is a monotonically increasing function and f(x)xf(x)\rightarrow x when x0x\rightarrow 0. We find that all states near the Dirac point except ϵ=0\epsilon=0 are consistent with this hypothesis (see Fig. 5), confirming the disorder-free localization also observed earlier. The extracted 2-D localization length ξ\xi shown in Fig. 5 indicated that the low-energy states could be strongly localized in mesoscopic systems with size larger than 102103a10^{2}-10^{3}a.

The case of the exact Dirac point ϵ=0\epsilon=0 requires special attention, as the RPFHM belongs to the chiral orthogonal class BDI at this special energy. As shown in Fig. 5, we observe significant oscillations of λM/M\lambda_{M}/M at ϵ=0\epsilon=0 (blue line) due to the finite-size effects, in contrast to the ϵ=0.025\epsilon=0.025 (red line) case where the fluctuations are negligible. The oscillation has a period of three, which is likely related to the quasi-periodicity of the finite-size gap in a clean armchair-type graphene nanoribbon [57, 44]. Similar behaviors have also been seen in random flux models on the square lattice, where λM/M\lambda_{M}/M is sensitive to the parity of the width (in units of lattice spacing) [58, 59, 60, 28]. It seems that the amplitude of oscillations tends to zero and λM/M\lambda_{M}/M remains finite when MM\rightarrow\infty, supporting the existence of critical and delocalized state at the band center of chiral metals [36, 37, 61, 59, 39]. A definite conclusion requires careful numerical analysis with a substantially larger system size and fine energy resolution, which is beyond the scope of this work. We note that this band-centered state may hardly affect the transport at realistic temperatures as it only exists within a very narrow energy window, making its identification challenging.

III Thermal conductivity of the Kitaev model

The low-temperature behavior of thermal conductivity κK\kappa_{\text{K}} of the Kitaev model can be inferred using earlier results. We first briefly introduce the Kitaev model [4]

HK=ijλJλσiλσjλ,H_{\text{K}}=\sum_{\langle ij\rangle_{\lambda}}J_{\lambda}\sigma_{i}^{\lambda}\sigma_{j}^{\lambda}, (9)

where Pauli matrices σi=(σix,σiy,σiz)\vec{\sigma_{i}}=(\sigma^{x}_{i},\sigma^{y}_{i},\sigma^{z}_{i}) describe the spin degrees of freedom on site ii, ijλ\langle ij\rangle_{\lambda} denotes the λ\lambda-type nearest-neighbor bond (λ=x,y,z\lambda=x,y,z) between site ii and jj and each bond is only summed once, as shown in Fig. 1. In this work, we are only interested in the isotropic case so we set J=Jx=Jy=JzJ=J_{x}=J_{y}=J_{z} hereafter. The Kitaev model can be exactly solved by mapping spins to Majorana fermions and the Hamiltonian becomes

HKSL=i,jiJu~ij2γiγj,H_{\text{KSL}}=\sum_{\langle i,j\rangle}\frac{iJ\tilde{u}_{ij}}{2}\gamma_{i}\gamma_{j}, (10)

where the Majorana fermions satisfy anticommutation relations {γi,γj}=2δij\{\gamma_{i},\gamma_{j}\}=2\delta_{ij}, and the bond operator u~ij=u~ji=±1\tilde{u}_{ij}=-\tilde{u}_{ji}=\pm 1 acts as a Z2Z_{2} gauge field.

After making a gauge transformation fjifj,jAf_{j}^{\dagger}\rightarrow-if_{j}^{\dagger},j\in A sublattice, followed by a Majorana transformation fi=(γi1+iγi2)/2f_{i}^{\dagger}=(\gamma_{i}^{1}+i\gamma_{i}^{2})/2 to Eq. (1), one can see the RPFHM (1) is exactly two copies of the Kitaev model (10), with t=2Jt=2J. Therefore the thermal conductivity of the Kitaev model (9) is half of that of the RPFHM (1), namely κG=2κK\kappa_{\text{G}}=2\kappa_{\text{K}}, provided both have the same flux configuration. At thermal equilibrium, κK\kappa_{\text{K}} can be expressed as the weighted average of thermal conductivity κK\kappa_{\text{K}}^{\vbox{\hbox{\scalebox{0.7}{$\varhexagon$}}}} over every flux configuration \varhexagon, namely κK=(ZκK)/(Z)\kappa_{\text{K}}=(\sum_{\vbox{\hbox{\scalebox{0.7}{$\varhexagon$}}}}Z_{\vbox{\hbox{\scalebox{0.7}{$\varhexagon$}}}}\kappa_{\text{K}}^{\vbox{\hbox{\scalebox{0.7}{$\varhexagon$}}}})/(\sum_{\vbox{\hbox{\scalebox{0.7}{$\varhexagon$}}}}Z_{\vbox{\hbox{\scalebox{0.7}{$\varhexagon$}}}}). Here Z=TreβHZ_{\vbox{\hbox{\scalebox{0.7}{$\varhexagon$}}}}=\text{Tr}e^{-\beta H_{\vbox{\hbox{\scalebox{0.7}{$\varhexagon$}}}}} is the partition function for specific flux configuration \varhexagon described by the Hamiltonian HH_{\vbox{\hbox{\scalebox{0.7}{$\varhexagon$}}}}, and \sum_{\vbox{\hbox{\scalebox{0.7}{$\varhexagon$}}}} denotes sum over all flux configurations. In the Kitaev model the ground state contains no flux [62], while at temperatures much lower than the vison gap Δv0.1536J\Delta_{v}\approx 0.1536J [4], thermally excited visons are dilute and may be regarded as uncorrelated on different plaquettes, with flux density approximately given by

nv=1eΔv/kBT+1.n_{v}=\frac{1}{e^{\Delta_{v}/k_{B}T}+1}. (11)

Here we emphasize that although the calculation of κK\kappa_{\text{K}} seems a quenched disorder problem, it is an artifact as the bond variables uiju_{ij} commute with the Hamiltonian. In fact, it is still an annealed average problem, as the free energy is given by =kBTlnZ\mathcal{F}=-k_{B}T\ln\sum_{\vbox{\hbox{\scalebox{0.7}{$\varhexagon$}}}}Z_{\vbox{\hbox{\scalebox{0.7}{$\varhexagon$}}}}, where the logarithm is taken after the sum over all flux configurations is computed.

The thermal conductivity κG\kappa_{\text{G}} of RPFHM is linked to the electrical conductivity σG\sigma_{G} by the Wiedemann–Franz (WF) law κG=σGT\kappa_{\text{G}}=\sigma_{\text{G}}\mathcal{L}T where \mathcal{L} is the Lorentz number. For a non-interacting Fermi liquid, the Lorentz number is a universal constant 0=π2kB2/3e2\mathcal{L}_{0}=\pi^{2}k_{B}^{2}/3e^{2}, while around the Dirac point, the Lorentz number may be a few times larger than 0\mathcal{L}_{0} even for the non-interacting case [63, 64]. Combining the above arguments, one obtains

κK(T)σG(nv,T,μ=0)=2T,\frac{\kappa_{\text{K}}\left(T\right)}{\sigma_{\text{G}}(n_{v},T,\mu=0)}=\frac{\mathcal{L}}{2}T, (12)

where σG(nv,T,μ)\sigma_{\text{G}}(n_{v},T,\mu) denotes the DC conductivity of RPFHM, which has flux density nvn_{v}, Fermi level μ\mu and temperature TT.

We shall now demonstrate the low-temperature behavior of κK\kappa_{\text{K}} using Eq. (12). As kBT|μ|k_{B}T\gg|\mu|, the conduction is mainly contributed by the thermally excited quasiparticles with energy EkBTE\sim k_{B}T. When kBTΔvk_{B}T\ll\Delta_{v}, we observe that the thermal de Broglie wavelength λthT1\lambda_{\text{th}}\sim T^{-1} is much shorter than the mean flux distance rmeΔv/2kBTr_{m}\sim e^{\Delta_{v}/2k_{B}T}. This indicates that the transport is away from the Dirac point and in the semiclassical regime. As the localization length is exponentially large ξl0eπkFle\xi\approx l_{0}e^{\pi k_{F}l_{e}} in this regime, the localization effects are negligible for realistic system size, or when the phase coherence length is much smaller than the localization length LϕξL_{\phi}\ll\xi due to the coupling to environments. Substituting the thermal de Broglie wavevector kth=2π/λthk_{\text{th}}=2\pi/\lambda_{\text{th}} to Eq. (4) (see appendix A for the justification), which is applicable when kthrm1k_{\text{th}}r_{m}\gg 1, and using Eqs. (11)(12), one obtains diverging thermal conductivity κKT3eΔv/kBT\kappa_{\text{K}}\sim T^{3}e^{\Delta_{v}/k_{B}T} at low temperatures. When kBTΔv0.15Jk_{B}T\sim\Delta_{v}\approx 0.15J, which corresponds to λthrm\lambda_{\text{th}}\gtrsim r_{m}, the thermal transport is in the quantum regime and localization effects are non-negligible. We assume both the system size LL and phase coherence length LϕL_{\phi} is much larger than the thermal localization length ξT=ξ(nv(T),kth(T))\xi_{T}=\xi(n_{v}(T),k_{\text{th}}(T)), which is estimated to be a few hundred of lattice spacing from Fig. 5. In this case, the Majorana fermions are strongly localized and significantly suppressed thermal conductivity κK/TkB2/2π\kappa_{\text{K}}/T\ll k_{B}^{2}/2\pi\hbar may be observable. This is in contrast with the low-temperature case kBTΔvk_{B}T\ll\Delta_{v} where κK/TkB2/2π\kappa_{\text{K}}/T\gg k_{B}^{2}/2\pi\hbar and analogous to the large resistivity ρh/e2\rho\gg h/e^{2} observed in graphene due to the strong localization [65, 66, 67]. We note that it is difficult to obtain κK\kappa_{\text{K}} at higher temperature kBTJΔvk_{B}T\sim J\gg\Delta_{v} using our calculations, as the thermal transport is also contributed by quasiparticles at high energies that are not considered in this work. Besides, in this regime visons can no longer be regarded as dilute, and the validity of Eq. (11) becomes questionable.

IV Conclusion

In this work, we have utilized a combination of numerical methods to investigate the transport of RPFHM near the Dirac point. Our results reveal that when the wavelength of Dirac fermion is much shorter than the average flux spacing, the semiclassical DC conductivity is quadratic in the Fermi momentum and inversely proportional to the flux density. We have also demonstrated that intervalley scattering by the π\pi-fluxes leads to weak (strong) localization of Dirac fermions at high (low) Fermi energy.

Refer to caption
Figure 6: Schematics of the low-temperature thermal conductivity versus temperature. Note that the Boltzmann constant kB=1k_{B}=1.

Our results imply that the thermal transport of the Kitaev model is semiclassical at low temperatures kBTΔvk_{B}T\ll\Delta_{v}, and that the thermal conductivity diverges as κKT3eΔv/kBT\kappa_{\text{K}}\sim T^{3}e^{\Delta_{v}/k_{B}T}. When kBTΔvk_{B}T\sim\Delta_{v}, the itinerant Majorana fermions may be strongly localized, leading to a significantly suppressed thermal conductivity κK/TkB2/2π\kappa_{\text{K}}/T\ll k_{B}^{2}/2\pi\hbar. Our predictions are expected to hold even in the presence of disorder as long as τv1τd1\tau_{v}^{-1}\gg\tau_{d}^{-1}, where τv1(τd1)\tau_{v}^{-1}(\tau_{d}^{-1}) is the scattering rate due to vison (disorder). When the temperature is much smaller than the crossover temperature TdT_{d} at which τd1=τv1\tau_{d}^{-1}=\tau_{v}^{-1}, the disorder becomes the dominant source of elastic scattering and the transport is similar to that of an undoped graphene. Consequently, κK/T\kappa_{\text{K}}/T should reduce with decreasing temperature and finally saturates to a value comparable or smaller to 1/2π1/2\pi\hbar [35, 52, 53]. Such temperature dependence, as shown in Fig. 6, was unseen in previous numerical simulations and may be observable in a clean sample at very low temperatures. In realistic Kitaev materials, non-Kitaev-type interactions also allow the hopping of visons and may have important consequences [16, 18], which are left for future studies.

Acknowledgements.
I would like to thank P. Coleman for giving valuable feedback on the manuscript and J. Nasu for fruitful discussions. The author acknowledges the support of two grant funding agencies, which funded two distinct components of the research carried out at different times. The early calculation of the conductivity of the random π\pi-flux honeycomb lattice was supported by grant DE-SC0020353 funded by the U.S. Department of Energy, Office of Science. A later component of the research, calculating the two-dimensional localization length from transfer matrices, was supported by the NSF Division of Materials Research grant NSF grant DMR-1830707.

Appendix A The DC conductivity of RPFHM at intermediate temperatures

Refer to caption
Figure 7: The DC conductivity σG\sigma_{\text{G}} (in units of e2/he^{2}/h) of the RPFHM versus (T/t)2(T/t)^{2} for nv=0.01n_{v}=0.01 when LM=1083aL\approx M=108\sqrt{3}a (the Boltzmann constant kBk_{B} is set to unity).

In this appendix, we calculate the finite-temperature DC conductivity of the RPFHM at half-filling and show that it is proportional to T2T^{2}, when a/rmkBT/t1a/r_{m}\lesssim k_{B}T/t\ll 1. This justifies that, in this temperature regime, the finite-temperature conductivity of RPFHM at half-filling can be inferred from the zero-temperature conductivity of RPFHM at finite Fermi energy, by replacing the Fermi momentum kFk_{F} in Eq. (4) with the thermal de Broglie wavevector kth=2π/λthk_{\text{th}}=2\pi/\lambda_{\text{th}}.
The current can be calculated using the Landauer formula

I=eh𝑑E[f(EμL)f(EμR)]𝐓(E),I=\frac{e}{h}\int dE\left[f(E-\mu_{L})-f(E-\mu_{R})\right]\mathbf{T}(E), (13)

where f(E)=1/(eE/kBT+1)f(E)=1/(e^{E/k_{B}T}+1) is the Fermi distribution function, and μL(μR)\mu_{L}(\mu_{R}) is the chemical potential of the left(right) lead. In the linear response regime, the above equation gives the conductance

G=e2h𝑑E𝐓(E)(df(E)dE),G=\frac{e^{2}}{h}\int dE\mathbf{T}(E)\left(-\frac{df(E)}{dE}\right), (14)

where we have used μL+μR=0\mu_{L}+\mu_{R}=0 and μLμR=eV\mu_{L}-\mu_{R}=eV. The finite-temperature conductivity can then be extracted using Eq. (2) for fixed flux density nvn_{v} and system size, and the result is shown in Fig. 7. We note that σG\sigma_{G} shows a T2T^{2} temperature dependence at intermediate temperatures a/rmkBT/t1a/r_{m}\lesssim k_{B}T/t\ll 1, which originates from the kF2k_{F}^{2} dependence of the zero-temperature conductivity (see Eq. (4)). The deviation from the T2T^{2} dependence at low temperatures kBT/ta/rmk_{B}T/t\lesssim a/r_{m} is due to the quantum transport near the Dirac point, for which Eq. (4) no longer applies. The discrepancy at high temperatures kBT/t1k_{B}T/t\sim 1 is attributed to the nonlinearity of Dirac dispersion and the thermally excited carriers above the Van Hove point. We remark that although the Landauer approach fails near the Dirac point E=0E=0, it does not affect our finite-temperature calculation significantly, as long as a/rmkBT/ta/r_{m}\lesssim k_{B}T/t.

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