arXiv subjects

Ka-Ming Tam

Publications and source records attributed to Ka-Ming Tam.

At least 37 records · Page 2Linked to original sources

arXiv2020

Non-Fermi Liquid Behaviour in the Three Dimensional Hubbard Model

We present a numerical study on non-Fermi liquid behaviour of a three dimensional system. The Hubbard model in a cubic lattice is simulated by the dynamical cluster approximation, in particular the quasi-particle weight is calculated at finite dopings for a range of temperatures. Near the putative quantum critical point, we find evidence of a separatrix at a finite doping which separates the Fermi liquid from non-Fermi liquid as the doping increases. Our results suggest that a marginal Fermi liquid and possibly a quantum critical point should exist in the three dimensions interacting Fermi system.

cond-mat.str-el↗

arXiv2020

Neural Network Solver for Small Quantum Clusters

Machine learning approaches have recently been applied to the study of various problems in physics. Most of the studies are focused on interpreting the data generated by conventional numerical methods or an existing database. An interesting question is whether it is possible to use a machine learning approach, in particular a neural network, for solving the many-body problem. In this paper, we present a solver for interacting quantum problem for small clusters based on the neural network. We study the small quantum cluster which mimics the single impurity Anderson model. We demonstrate that the neural network based solver provides quantitatively accurate results for the spectral function as compared to the exact diagonalization method. This opens the possibility of utilizing the neural network approach as an impurity solver for other many body numerical approaches, such as dynamical mean field theory.

cond-mat.str-el↗

arXiv2020

Deep Learning on the 2-Dimensional Ising Model to Extract the Crossover Region with a Variational Autoencoder

The 2-dimensional Ising model on a square lattice is investigated with a variational autoencoder in the non-vanishing field case for the purpose of extracting the crossover region between the ferromagnetic and paramagnetic phases. The encoded latent variable space is found to provide suitable metrics for tracking the order and disorder in the Ising configurations that extends to the extraction of a crossover region in a way that is consistent with expectations. The extracted results achieve an exceptional prediction for the critical point as well as agreement with previously published results on the configurational magnetizations of the model. The performance of this method provides encouragement for the use of machine learning to extract meaningful structural information from complex physical systems where little a priori data is available.

physics.comp-ph↗

arXiv2020

Effect of Mitigation Measures on the Spreading of COVID-19 in Hard-Hit States

State government-mandated social distancing measures have helped to slow down the growth of the COVID-19 pandemic in the United States. Current predictive models of the development of COVID-19, especially after mitigation efforts, are largely based on extrapolating the data from other countries. Since most states enforced stay-at-home orders towards the end of March, their effect should be reflected in the death and infection counts at the end of April. Using the data available until April 25th, we investigate the change in the infection rate due to the mitigation efforts, and project death and infection counts until September, 2020, for some of the most heavily impacted states: New York, New Jersey, Michigan, Massachusetts, Illinois and Louisiana. We find that with the current mitigation efforts five of those six states reduce their reproduction number to a value less than one, stopping the exponential growth of the pandemic. We also projected different scenarios after the mitigation is relaxed. Analysis for other states can be found at https://covid19projection.org/.

q-bio.PE↗

arXiv2020

Projected Development of COVID-19 in Louisiana

At the time of writing, Louisiana has the third highest COVID-19 infection per capita in the United States. The state government issued a stay-at-home order effective March 23rd. We analyze the projected spread of COVID-19 in Louisiana without including the effects of the stay-at-home order. We predict that a large fraction of the state population would be infected without the mitigation efforts, and would certainly overwhelm the capacity of Louisiana health care system. We further predict the outcomes with different degrees of reduction in the infection rate. More than 70% of reduction is required to cap the number of infected to under one million.

q-bio.PE↗

arXiv2019

Interatomic Potential in a Simple Dense Neural Network Representation

Simulations at the atomic scale provide a direct and effective way to understand the mechanical properties of materials. In the regime of classical mechanics, simulations for the thermodynamic properties of metals and alloys can be done by either solving the equations of motion or performing Monte Carlo sampling. The key component for an accurate simulation of such physical systems to produce faithful physical quantities is the use of an appropriate potential or a force field. In this paper, we explore the use of methods from the realm of machine learning to overcome and bypass difficulties encountered when fitting potentials for atomic systems. Particularly, we will show that classical potentials can be represented by a dense neural network with good accuracy.

physics.comp-ph↗

arXiv2019

Locally self-consistent embedding approach for disordered electronic systems

We present a new embedding scheme for the locally self-consistent method to study disordered electron systems. We test this method in a tight-binding basis and apply it to the single band Anderson model. The local interaction zone is used to efficiently compute the local Green's function of a supercell embeded into a local typical medium. We find a quick convergence as the size of the local interaction zone which reduces the computational costs as expected. This method captures the Anderson localization transition and accurately predicts the critical disorder strength. The present work opens the path towards the development of a typical medium embedding scheme for the $O(N)$ multiple scattering methods.

cond-mat.dis-nn↗

arXiv2019

Periodic Anderson model with Holstein phonons for the description of the Cerium volume collapse

Recent experiments have suggested that the electron-phonon coupling may play an important role in the $γ\rightarrow α$ volume collapse transition in Cerium. A minimal model for the description of such transition is the periodic Anderson model. In order to better understand the effect of the electron-phonon interaction on the volume collapse transition, we study the periodic Anderson model with coupling between Holstein phonons and electrons in the conduction band. We find that the electron-phonon coupling enhances the volume collapse, which is consistent with experiments in Cerium. While we start with the Kondo Volume Collapse scenario in mind, our results capture some interesting features of the Mott scenario, such as a gap in the conduction electron spectra which grows with the effective electron-phonon coupling.

cond-mat.str-el↗

arXiv2018

Identifying structural changes with unsupervised machine learning methods

Unsupervised machine learning methods are used to identify structural changes using the melting point transition in classical molecular dynamics simulations as an example application of the approach. Dimensionality reduction and clustering methods are applied to instantaneous radial distributions of atomic configurations from classical molecular dynamics simulations of metallic systems over a large temperature range. Principal component analysis is used to dramatically reduce the dimensionality of the feature space across the samples using an orthogonal linear transformation that preserves the statistical variance of the data under the condition that the new feature space is linearly independent. From there, k-means clustering is used to partition the samples into solid and liquid phases through a criterion motivated by the geometry of the reduced feature space of the samples, allowing for an estimation of the melting point transition. This pattern criterion is conceptually similar to how humans interpret the data but with far greater throughput, as the shapes of the radial distributions are different for each phase and easily distinguishable by humans. The transition temperature estimates derived from this machine learning approach produce comparable results to other methods on similarly small system sizes. These results show that machine learning approaches can be applied to structural changes in physical systems.

physics.comp-ph↗

arXiv2015

Study of multiband disordered systems using the typical medium dynamical cluster approximation

We generalize the typical medium dynamical cluster approximation to multiband disordered systems. Using our extended formalism, we perform a systematic study of the non-local correlation effects induced by disorder on the density of states and the mobility edge of the three-dimensional two-band Anderson model. We include inter-band and intra-band hopping and an intra-band disorder potential. Our results are consistent with the ones obtained by the transfer matrix and the kernel polynomial methods. We apply the method to K$_x$Fe$_{2-y}$Se$_2$ with Fe vacancies. Despite the strong vacancy disorder and anisotropy, we find the material is not an Anderson insulator. Our results demonstrate the application of the typical medium dynamical cluster approximation method to study Anderson localization in real materials.

cond-mat.dis-nn↗

arXiv2014

Ferromagnetic phase in the polarized two-species bosonic Hubbard Model

We recently studied a doped two-dimensional bosonic Hubbard model with two hard-core species, with different masses, using quantum Monte Carlo simulations [Phys. Rev. B 88, 161101(R) (2013)]. Upon doping away from half-filling, we find several distinct phases, including a phase-separated ferromagnet with Mott behavior for the heavy species and both Mott insulating and superfluid behaviors for the light species. Introducing polarization, an imbalance in the population between species, we find a fully phase-separated ferromagnet. This phase exists for a broad range of temperatures and polarizations. By using finite size scaling of the susceptibility, we find a critical exponent which is consistent with the two-dimensional Ising universality class. Significantly, since the global entropy of this phase is higher than that of the ferromagnetic phase with single species, its experimental observation in cold atoms may be feasible.

cond-mat.quant-gas↗

arXiv2014

Three Dimensional Edwards-Anderson Spin Glass Model in an External Field

We study the Edwards-Anderson model on a simple cubic lattice with a finite constant external field. We employ an indicator composed of a ratio of susceptibilities at finite wavenumbers, which was recently proposed to avoid the difficulties of a zero momentum quantity, for capturing the spin glass phase transition. Unfortunately, this new indicator is fairly noisy, so a large pool of samples at low temperature and small external field are needed to generate results with sufficiently small statistical error for analysis. We thus implement the Monte Carlo method using graphics processing units to drastically speedup the simulation. We confirm previous findings that conventional indicators for the spin glass transition, including the Binder ratio and the correlation length do not show any indication of a transition for rather low temperatures. However, the ratio of spin glass susceptibilities do show crossing behavior, albeit a systematic analysis is beyond the reach of the present data. This calls for a more thorough study of the three-dimension Edwards-Anderson model in an external field.

cond-mat.stat-mech↗

arXiv2013

Parallel Tempering Simulation of the three-dimensional Edwards-Anderson Model with Compact Asynchronous Multispin Coding on GPU

Monte Carlo simulations of the Ising model play an important role in the field of computational statistical physics, and they have revealed many properties of the model over the past few decades. However, the effect of frustration due to random disorder, in particular the possible spin glass phase, remains a crucial but poorly understood problem. One of the obstacles in the Monte Carlo simulation of random frustrated systems is their long relaxation time making an efficient parallel implementation on state-of-the-art computation platforms highly desirable. The Graphics Processing Unit (GPU) is such a platform that provides an opportunity to significantly enhance the computational performance and thus gain new insight into this problem. In this paper, we present optimization and tuning approaches for the CUDA implementation of the spin glass simulation on GPUs. We discuss the integration of various design alternatives, such as GPU kernel construction with minimal communication, memory tiling, and look-up tables. We present a binary data format, Compact Asynchronous Multispin Coding (CAMSC), which provides an additional $28.4\%$ speedup compared with the traditionally used Asynchronous Multispin Coding (AMSC). Our overall design sustains a performance of 33.5 picoseconds per spin flip attempt for simulating the three-dimensional Edwards-Anderson model with parallel tempering, which significantly improves the performance over existing GPU implementations.

cond-mat.dis-nn↗

arXiv2013

Complex phases in the doped two-species bosonic Hubbard Model

We study a two-dimensional bosonic Hubbard model with two hard-core species away from half filling using Quantum Monte Carlo simulations. The model includes a repulsive interspecies interaction and different nearest-neighbor hopping terms for the two species. By varying the filling we find a total of five distinct phases, including a normal liquid phase at higher temperature, and four different phases at lower temperature. We find an anti-ferromagnetically ordered Mott insulator and a region of coexistent anti-ferromagnetic and superfluid phases near half filling. Further away from half filling the phase diagram displays a superfluid phase and a novel phase inside the superfluid region at even lower temperatures. In this novel phase separated region, the heavy species has a Mott behavior with integer filling, while the lighter species shows phase separated Mott and superfluid behaviors.

cond-mat.quant-gas↗

arXiv2013

Phase diagram of the Bose-Hubbard model on a ring-shaped lattice with tunable weak links

Motivated by recent experiments on toroidal Bose-Einstein condensates in all-optical traps with tunable weak links, we study the one-dimensional Bose-Hubbard model on a ring-shaped lattice with a small region of weak hopping integrals using quantum Monte Carlo simulations. Besides the usual Mott insulating and superfluid phases, we find a phase which is compressible but non superfluid with a local Mott region. This `local Mott' phase extends in a large region of the phase diagram. These results suggest that the insulating and conducting phases can be tuned by a local parameter which may provide a new insight to the design of atomtronic devices.

cond-mat.quant-gas↗

arXiv2013

The Boson-Hubbard Model on a Kagome Lattice with Sextic Ring-Exchange Terms

High order ring-exchange interactions are crucial for the study of quantum fluctuations on highly frustrated systems. We present the first exact quantum Monte Carlo study of a model of hard-core bosons with sixth order ring-exchange interactions on a two-dimensional kagome lattice. By using the Stochastic Green Function algorithm, we show that the system becomes unstable in the limit of large ring-exchange interactions. It undergoes a phase separation at all fillings, except at 1/3 and 2/3 fillings for which the superfluid density vanishes and an unusual mixed valence bond and charge density ordered solid is formed.

cond-mat.quant-gas↗

arXiv2013

Dominant Superconducting Fluctuations in the One-Dimensional Extended Holstein-Extended Hubbard model

The search for realistic one-dimensional (1D) models that exhibit dominant superconducting (SC) fluctuations effects has a long history. In these 1D systems, the effects of commensurate band fillings--strongest at half-filling--and electronic repulsions typically lead to a finite charge gap and the favoring of insulating density wave ordering over superconductivity. Accordingly, recent proposals suggesting a gapless metallic state in the Holstein-Hubbard (HH) model, possibly superconducting, have generated considerable interest and controversy, with the most recent work demonstrating that the putative dominant superconducting state likely does not exist. In this paper we study a model with non-local electron-phonon interactions, in addition to electron-electron interactions, this model unambiguously possesses dominant superconducting fluctuations at half filling in a large region of parameter space. Using both the numerical multi-scale functional renormalization group for the full model and an analytic conventional renormalization group for a bosonized version of the model, we demonstrate the existence of dominant superconducting (SC) fluctuations. These dominant SC fluctuations arise because the spin-charge coupling at high energy is weakened by the non-local electron-phonon interaction and the charge gap is destroyed by the resultant suppression of the Umklapp process. The existence of the dominant SC pairing instability in this half-filled 1D system suggests that non-local boson-mediated interactions may be important in the superconductivity observed in the organic superconductors.

cond-mat.str-el↗

arXiv2012

Periodic Anderson model with electron-phonon correlated conduction band

This paper reports dynamical mean field calculations for the periodic Anderson model in which the conduction band is coupled to phonons. Motivated in part by recent attention to the role of phonons in the $γ$-$α$ transition in Ce, this model yields a rich and unexpected phase diagram which is of intrinsic interest. Specifically, above a critical value of the electron-phonon interaction, a first order transition with two coexisting phases develops in the temperature-hybridization plane, which terminates at a second order critical point. The coexisting phases display the familiar Kondo screened and local moment character, yet they also exhibit pronounced polaronic and bipolaronic properties, respectively.

cond-mat.str-el↗