arXiv subjects

Ka-Ming Tam

Publications and source records attributed to Ka-Ming Tam.

At least 19 recordsLinked to original sources

arXiv2026

Mechanism of charge transfer and electrostatic field fluctuations in complex metallic alloys

Complex metallic alloys exhibit rich disorder-driven electronic, magnetic, and vibrational behavior arising from strong chemical disorder, leading to unconventional structure-property relationships with applications in extreme-environment materials, catalysis, spintronics, and thermoelectrics. Despite their technological relevance, the microscopic nature of charge redistribution and electrostatic fluctuations in chemically disordered alloys remains incompletely understood. Here, we develop a theoretical framework that uncovers universal statistical trends of disorder-driven charge transfer and Madelung-field fluctuations. Our analytical formalism demonstrates that local charge transfer and electrostatic potentials exhibit Gaussian-like statistics and universal linear charge-potential (qV) correlations emerging directly from the underlying disorder landscape. We identify the physical origin of these correlations in the interplay between electronic screening and impurity scattering and show how their statistical properties depend on carrier density, disorder strength, and compositional complexity. We further derive scaling relations governing qV trends across binary and multicomponent alloys, including high-entropy materials. Large-supercell density-functional theory (DFT) calculations show good quantitative agreement with the predicted statistical behavior for representative metallic alloys. Our results provide a computationally efficient framework for incorporating disorder-driven electrostatic fluctuations into effective-medium electronic-structure theories and establish a statistical-physics foundation for the predictive design of complex alloys.

cond-mat.mtrl-sci↗

arXiv2026

Green's Functions from Sample-based Krylov Quantum Diagonalization: An Impurity Solver for Dynamical Mean-Field Theory

We generalize the sample-based Krylov quantum diagonalization (SKQD) method from ground-state calculations to the evaluation of single-particle Green's functions. By constructing and sampling unitary Krylov subspaces in the N +/- 1 particle-number sectors and evaluating all sector-connecting overlaps classically, the approach reconstructs the Green's function via a Lanczos continued fraction while retaining the shallow-circuit, ancilla-free character of SKQD. The quantum device is required only to prepare and sample short-time evolutions. Applied to the particle-hole-symmetric single-impurity Anderson model in chain geometry, with the discrete bath representation used in dynamical mean-field theory (DMFT), the method recovers the spectral function using a relatively small fraction of the full Hilbert space. Across a range of interaction strengths that spans the metal-insulator transition, the main spectral features are reproduced. These results suggest that SKQD-based Green's-function calculations may allow DMFT impurity solvers with a larger number of bath sites on near-term quantum hardware than is currently practical.

cond-mat.str-el↗

arXiv2026

Classical Benchmarks of a Symmetry-Adapted Variational Quantum Eigensolver for Real-Time Green's Functions in Dynamical Mean-Field Theory

We present a variational quantum eigensolver (VQE) approach for solving the Anderson Impurity Model (AIM) arising in Dynamical Mean-Field Theory (DMFT). Recognizing that the minimal two-site approximation often fails to resolve essential spectral features, we investigate the efficacy of VQE for larger bath discretizations while adhering to near-term hardware constraints. We employ a symmetry-adapted ansatz enforcing conservation of particle number $(N)$, spin projection $(S_z=0)$, and total spin $(S^2=0)$ symmetry, benchmarking the performance against exact diagonalization across different interaction strengths using bath parameters extracted from the DMFT self-consistency loop. For a four-site model, the relative error in the ground state energy remains well below $0.01%$ with a compact parameter set $(N_p \le 30)$. Crucially, we demonstrate that the single-particle Green's function-the central quantity for DMFT-can be accurately extracted from VQE-prepared ground states via real-time evolution in the intermediate to strong interaction regimes. However, in the weak interaction regime, the Green's function exhibits noticeable deviations from the exact benchmark, particularly in resolving low-energy spectral features, despite the ground state energy showing excellent agreement. These findings demonstrate that VQE combined with real-time evolution can effectively extend quantum-classical hybrid DMFT beyond the two-site approximation, particularly for describing insulating phases. While this approach offers a viable pathway for simulating strongly correlated materials on near-term devices, the observation that accurate ground state energy does not guarantee accurate dynamical properties highlights a key challenge for applying such approaches to correlated metals.

cond-mat.str-el↗

arXiv2026

Real-Time Iteration Scheme for Dynamical Mean-Field Theory: A Framework for Near-Term Quantum Simulation

We present a time-domain iteration scheme for solving the Dynamical Mean-Field Theory (DMFT) self-consistent equations using retarded Green's functions in real time. Unlike conventional DMFT approaches that operate in imaginary time or frequency space, our scheme operates directly with real-time quantities. This makes it particularly suitable for near-term quantum computing hardware with limited Hilbert spaces, where real-time propagation can be efficiently implemented via Trotterization or variational quantum algorithms. We map the effective impurity problem to a finite one-dimensional chain with a small number of bath sites, solved via exact diagonalization as a proof-of-concept. The hybridization function is iteratively updated through time-domain fitting until self-consistency. We demonstrate stable convergence across a wide range of interaction strengths for the half-filled Hubbard model on a Bethe lattice, successfully capturing the metal-to-insulator transition. Despite using limited time resolution and a minimal bath discretization, the spectral functions clearly exhibit the emergence of Hubbard bands and the suppression of spectral weight at the Fermi level as interaction strength increases. This overcomes major limitations of two-site DMFT approximations by delivering detailed spectral features while preserving efficiency and compatibility with quantum computing platforms through real-time dynamics.

cond-mat.str-el↗

arXiv2025

Interplay of non-Hermitian skin effect and electronic correlations in the non-Hermitian Hubbard model via Real-space dynamical mean field theory

Non-Hermitian quantum systems, characterized by their ability to model open systems with gain and loss, have unveiled striking phenomena such as the non-Hermitian skin effect (NHSE), where eigenstates localize at boundaries under open boundary conditions. While extensively studied in non-interacting systems, the interplay between NHSE and strong electron correlations remains largely unexplored. Here, we investigate the non-Hermitian Hubbard model with asymmetric hopping, employing real-space dynamical mean-field theory (R-DMFT), a novel extension to such non-Hermitian correlated models-to capture both local correlations and spatial inhomogeneities. By analyzing the end-to-end Green's function as probes of directional amplification, we demonstrate that strong correlations can suppress the skin effect, leading to a crossover from boundary-dominated to correlation-driven dynamics. Our systematic study reveals that correlations dominate at small to intermediate strength of asymmetric hopping, inducing exponential decay in the end-to-end Green's function, but higher strength of asymmetric hopping can restore amplification even at strong interaction. These results illuminate the tunable interplay between correlations and non-Hermitian physics, suggesting avenues for engineering non-reciprocal transport in correlated open quantum systems.

cond-mat.str-el↗

arXiv2025

Disorder Enhanced Thermalization in Interacting Many-Particle System

We introduce an extension of the non-equilibrium dynamical mean field theory to incorporate the effects of static random disorder in the dynamics of a many-particle system by integrating out different disorder configurations resulting in an effective time-dependent density-density interaction. We use this method to study the non-equilibrium transient dynamics of a system described by the Fermi Anderson-Hubbard model following an interaction and disorder quench. The method recovers the solution of the disorder-free case for which the system exhibits qualitatively distinct dynamical behaviors in the weak-coupling (prethermalization) and strong-coupling regimes (collapse-and-revival oscillations). However, we find that weak random disorder promotes thermalization. In the weak coupling regime, the jump in the quasiparticle weight in the prethermal regime is suppressed by random disorder while in the strong-coupling regime, random disorder reduces the amplitude of the quasiparticle weight oscillations. These results highlight the importance of disorder in the dynamics of realistic many-particle systems.

cond-mat.str-el↗

arXiv2024

Quantum Classical Algorithm for the Study of Phase Transitions in the Hubbard Model via Dynamical Mean-Field Theory

Simulating quantum many-body systems is believed to be one of the most promising applications of near-term noisy quantum computers. However, in the near term, system size limitation will remain a severe barrier for applications in materials science or strongly correlated systems. A promising avenue of research is to combine many-body physics with machine learning for the classification of distinct phases. In this paper, we propose a workflow that synergizes quantum computing, many-body theory, and quantum machine learning(QML) for studying strongly correlated systems. In particular, it can capture a putative quantum phase transition of the stereotypical strongly correlated system, the Hubbard model. Following the recent proposal of the hybrid classical-quantum algorithm for the two-site dynamical mean-field theory(DMFT), we present a modification that allows the self-consistent solution of the single bath site DMFT. The modified algorithm can easily be generalized for multiple bath sites. This approach is used to generate a database of zero-temperature wavefunctions of the Hubbard model within the DMFT approximation. We then use a QML algorithm to distinguish between the metallic phase and the Mott insulator phase to capture the metal-to-Mott insulator phase transition. We train a quantum convolutional neural network(QCNN) and then utilize the QCNN as a quantum classifier to capture the phase transition region. This work provides a recipe for application to other phase transitions in strongly correlated systems and represents an exciting application of small-scale quantum devices realizable with near-term technology.

cond-mat.str-el↗

arXiv2024

Out of Time Order Correlation of the Hubbard Model with Random Local Disorder

The out of time order correlator (OTOC) serves as a powerful tool for investigating quantum information spreading and chaos in complex systems. We present a method employing non-equilibrium dynamical mean-field theory (DMFT) and coherent potential approximation (CPA) combined with diagrammatic perturbation on the Schwinger-Keldysh contour to calculate the OTOC for correlated fermionic systems subjected to both random disorder and electrons interaction. Our key finding is that random disorder enhances the OTOC decay in the Hubbard model for the metallic phase in the weak coupling limit. However, the current limitation of our perturbative solver restricts the applicability to weak interaction regimes.

cond-mat.str-el↗

arXiv2023

Mechanism of charge transfer and electrostatic field fluctuations in high entropy metallic alloys

High entropy alloys present a new class of disordered metals which hold promising prospects for the next generation of materials and technology. However, much of the basic physics underlying these robust, multifunctional materials -- and those of other, more generic forms of disordered matter -- still remain the subject of ongoing inquiry. We thus present a minimal-working model that describes the disorder-driven fluctuations in the electronic charge distributions and electrostatic "Madelung" fields in disordered metals. Our theory follows a standard perturbative scheme and captures the leading contributions from dominant electronic processes, including electrostatic screening and impurity scattering events. We show here that a modest first-order treatment incorporating these effects is sufficient to reproduce the linear charge transfer trends featured in both high-entropy and other conventional alloys, our model also shedding light on the microscopic origins of these statistical features. We further elaborate on the nature of these electronic charge and Madelung field fluctuations by determining how these emerge from the statistics of the underlying disorder, and how these can be described using the linear response formulation that we develop here. In doing so, our work answers various questions which have long-perplexed the disordered materials community. It also opens up possible avenues for providing systematic corrections to modern first-principles approaches to disorder-modeling (e.g. the conventional CPA method) which currently lack these statistical features.

cond-mat.dis-nn↗

arXiv2023

Engineering non-Hermitian Second Order Topological Insulator in Quasicrystals

Non-Hermitian topological phases have gained immense attention due to their potential to unlock novel features beyond Hermitian bounds. PT-symmetric (Parity Time-reversal symmetric) non-Hermitian models have been studied extensively over the past decade. In recent years, the topological properties of general non-Hermitian models, regardless of the balance between gains and losses, have also attracted vast attention. Here we propose a non-Hermitian second-order topological (SOT) insulator that hosts gapless corner states on a two-dimensional quasi-crystalline lattice (QL). We first construct a non-Hermitian extension of the Bernevig-Hughes-Zhang (BHZ) model on a QL generated by the Amman-Beenker (AB) tiling. This model has real spectra and supports helical edge states. Corner states emerge by adding a proper Wilson mass term that gaps out the edge states. We propose two variations of the mass term that result in fascinating characteristics. In the first variation, we obtain a purely real spectra for the second-order topological phase. In the latter, we get a complex spectra with corner states localized at only two corners. Our findings pave a path to engineering exotic SOT phases where corner states can be localized at designated corners.

cond-mat.mes-hall↗

arXiv2022

Nonequilibrium DMFT+CPA for Correlated Disordered Systems

We present a solution for the nonequilibrium dynamics of an interacting disordered system. The approach adapts the combination of the equilibrium dynamical mean field theory (DMFT) and the equilibrium coherent potential approximation (CPA) methods to the nonequilibrium many-body formalism, using the Kadanoff-Baym-Keldysh complex time contour, for the dynamics of interacting disordered systems away from equilibrium. We use our time domain solution to obtain the equilibrium density of states of the disordered interacting system described by the Anderson-Hubbard model, bypassing the necessity for the cumbersome analytical continuation process. We further apply the nonequilibrium solution to the interaction quench problem for an isolated disordered system. Here, the interaction is abruptly changed from zero (non-interacting system) to another constant (finite) value at which it is subsequently kept. We observe via the time-dependence of the potential, kinetic, and total energies, the effect of disorder on the relaxation of the system as a function of final interaction strength. The real-time approach has the potential to shed new light on the fundamental role of disorder in the nonequilibrium dynamics of interacting quantum systems.

cond-mat.str-el↗

arXiv2022

Phonon Induced Instabilities in Correlated Electron Hamiltonians

Studies of Hamiltonians modeling the coupling between electrons as well as to local phonon excitations have been fundamental in capturing the novel ordering seen in many quasi-one dimensional condensed matter systems. Extending studies of such Hamiltonians to quasi-two dimensional systems is of great current interest, as electron-phonon couplings are predicted to play a major role in the stabilization or enhancement of novel phases in 2D material systems. In this work, we study model systems that describe the interplay between the Hubbard coupling and the phonon modes in the Holstein (H) and Su-Schrieffer-Heeger (SSH) Hamiltonians using the functional renormalization group (fRG). For both types of electron phonon couplings, we find the predicted charge density wave phases in competition with anti-ferromagnetic ($AF$) ordering. As the system is doped, the transition shifts, with both orders showing incommensurate peaks. We compare the evolution of the quasiparticle weight for the Holstein model with that of the SSH model as the systems transition from antiferromagnetic to charge-ordered ground states. Finally, we calculate the self-energy of the phonon and capture the impact of charge ordering on the phonon modes.

cond-mat.str-el↗

arXiv2022

Ab initio Approaches to High Entropy Alloys: A Comparison of CPA, SQS, and Supercell Methods

We present a comparative study of different modeling approaches to the electronic properties of the $\textrm{Hf}_{0.05}\textrm{Nb}_{0.05}\textrm{Ta}_{0.8}\textrm{Ti}_{0.05}\textrm{Zr}_{0.05}$ high entropy alloy. Common to our modeling is the methodology to compute the one-particle Green's function in the framework of density functional theory. We demonstrate that the special quasi-random structures modeling and the supercell, i.e. the locally self-consistent multiple-scatering methods provide very similar results for the ground state properties such as the spectral function (density of states) and the equilibrium lattice parameter. To reconcile the multiple-scattering single-site coherent potential approximation with the real space supercell methods, we included the effect of screening of the net charges of the alloy components. Based on the analysis of the total energy and spectral functions computed within the density functional theory, we found no signature for the long-range or local magnetic moments formation in the $\textrm{Hf}_{0.05}\textrm{Nb}_{0.05}\textrm{Ta}_{0.8}\textrm{Ti}_{0.05}\textrm{Zr}_{0.05}$ high entropy alloy, instead we find possible superconductivity below $\sim 9$K.

cond-mat.mtrl-sci↗

arXiv2022

Beyond Quantum Cluster Theories: Multiscale Approaches for Strongly Correlated Systems

The degrees of freedom that confer to strongly correlated systems their many intriguing properties also render them fairly intractable through typical perturbative treatments. For this reason, the mechanisms responsible for these technologically promising properties remain mostly elusive. Computational approaches have played a major role in efforts to fill this void. In particular, dynamical mean field theory (DMFT) and its cluster extension, the dynamical cluster approximation (DCA) have allowed significant progress. However, despite all the insightful results of these embedding schemes, computational constraints, such as the minus sign problem in Quantum Monte Carlo (QMC), and the exponential growth of the Hilbert space in exact diagonalization (ED) methods, still limit the length scale within which correlations can be treated exactly in the formalism. A recent advance to overcome these difficulties is the development of multiscale many body approaches whereby this challenge is addressed by introducing an intermediate length scale between the short length scale where correlations are treated exactly using a cluster solver such QMC or ED, and the long length scale where correlations are treated in a mean field manner. At this intermediate length scale correlations can be treated perturbatively. This is the essence of multiscale many-body methods. We will review various implementations of these multiscale many-body approaches, the results they have produced, and the outstanding challenges that should be addressed for further advances.

cond-mat.str-el↗

arXiv2021

An Application of Quantum Machine Learning on Quantum Correlated Systems: Quantum Convolutional Neural Network as a Classifier for Many-Body Wavefunctions from the Quantum Variational Eigensolver

Machine learning has been applied on a wide variety of models, from classical statistical mechanics to quantum strongly correlated systems for the identification of phase transitions. The recently proposed quantum convolutional neural network (QCNN) provides a new framework for using quantum circuits instead of classical neural networks as the backbone of classification methods. We present here the results from training the QCNN by the wavefunctions of the variational quantum eigensolver for the one-dimensional transverse field Ising model (TFIM). We demonstrate that the QCNN identifies wavefunctions which correspond to the paramagnetic phase and the ferromagnetic phase of the TFIM with good accuracy. The QCNN can be trained to predict the corresponding phase of wavefunctions around the putative quantum critical point, even though it is trained by wavefunctions far away from it. This provides a basis for exploiting the QCNN to identify the quantum critical point.

cond-mat.str-el↗

arXiv2021

Application of the Variational Autoencoder to Detect the Critical Points of the Anisotropic Ising Model

We generalize the previous study on the application of variational autoencoders to the two-dimensional Ising model to a system with anisotropy. Due to the self-duality property of the system, the critical points can be located exactly for the entire range of anisotropic coupling. This presents an excellent testbed for the validity of using a variational autoencoder to characterize an anisotropic classical model. We reproduce the phase diagram for a wide range of anisotropic couplings and temperatures via a variational autoencoder without the explicit construction of an order parameter. Considering that the partition function of $(d+1)$-dimensional anisotropic models can be mapped to that of the $d$-dimensional quantum spin models, the present study provides numerical evidence that a variational autoencoder can be applied to analyze quantum systems via Quantum Monte Carlo.

cond-mat.dis-nn↗

arXiv2021

Real Space Quantum Cluster Formulation for the Typical Medium Theory of Anderson Localization

We develop a real space cluster extension of the typical medium theory (cluster-TMT) to study Anderson localization. By construction, the cluster-TMT approach is formally equivalent to the real space cluster extension of the dynamical mean field theory. Applying the developed method to the 3D Anderson model with a box disorder distribution, we demonstrate that cluster-TMT successfully captures the localization phenomena in all disorder regimes. As a function of the cluster size, our method obtains the correct critical disorder strength for the Anderson localization in 3D, and systematically recovers the re-entrance behavior of the mobility edge. From a general perspective, our developed methodology offers the potential to study Anderson localization at surfaces within quantum embedding theory.

cond-mat.dis-nn↗

arXiv2020

Influence of State Reopening Policies in COVID-19 Mortality

By the end of May 2020, all states in the US have eased their COVID-19 mitigation measures. Different states adopted markedly different policies and timing for reopening. An important question remains in how the relaxation of mitigation measures is related to the number of casualties. To address this question, we compare the actual data to a hypothetical case in which the mitigation measures are left intact using a projection of the data from before mitigation measures were eased. We find that different states have shown significant differences in the number of deaths, possibly due to their different policies and reopening schedules. Our study provides a gauge for the effectiveness of the approaches by different state governments and can serve as a guide for implementing best policies in the future. It also indicates that the face mask mandate seems to correlate with the change in the death count more dramatically than other measures.

physics.soc-ph↗