Article
Materials Science, Multidisciplinary
Yi-Hsuan Liu, Sheng Zhang, Puhan Zhang, Ting-Kuo Lee, Gia-Wei Chern
Summary: The study introduces a machine learning model for predicting local electronic properties of disordered correlated electron systems. It shows that local electronic properties mainly depend on the immediate environment, and demonstrates good agreement between machine learning predictions and experimental data.
Article
Materials Science, Multidisciplinary
Vladislav Pokorny, Panch Ram
Summary: In this study, the behavior of in-gap bands in a heterostructure was investigated using the periodic Anderson model with superconducting correlations, and the lattice model was mapped onto the superconducting single impurity model using dynamical mean-field theory. Two distinct superconducting phases were observed in phase diagrams, each corresponding to different induced pairing signs, and the evolution of the spectral function near the transition was discussed. Additionally, the failure of iterative perturbation theory for superconducting models with spinful ground state and the behavior of the average expansion order in the continuous-time hybridization expansion simulation were explored.
Article
Physics, Fluids & Plasmas
Sangwon Lee, Vipul Periwal, Junghyo Jo
Summary: Inferring dynamics from incomplete time series data is challenging, but an expectation maximization algorithm proposed in this study demonstrates effectiveness in restoring missing data points and inferring underlying network models. Balancing consistency between observed and missing data points is crucial for accurate model inference during iterative processes.
Article
Physics, Multidisciplinary
A. Erpenbeck, E. Gull, G. Cohen
Summary: We propose a numerically exact method for nonequilibrium quantum impurity models, which directly formulates in the steady state, eliminating the need to traverse the transient dynamics and reducing computational costs. The method is benchmarked on quantum dots in the noninteracting and Kondo regime, as well as correlated materials driven away from equilibrium. Qualitative differences are observed in the response to bias voltage between correlated materials and bias-driven quantum dots.
PHYSICAL REVIEW LETTERS
(2023)
Article
Computer Science, Information Systems
Juan Carlos Seck-Tuoh-Mora, Norberto Hernandez-Romero, Joselito Medina-Marin, Genaro J. Martinez, Irving Barragan-Vite
Summary: Complex behaviors in cellular automata have been developed using randomly generated specimens to specify automata with complex behaviors, with an explanation provided for this method. Utilizing a genetic algorithm, the specification was optimized to obtain specimens of higher complexity.
INFORMATION SCIENCES
(2021)
Article
Materials Science, Multidisciplinary
Daniel Werner, Jan Lotze, Enrico Arrigoni
Summary: We propose a solver for correlated impurity problems out of equilibrium using the auxiliary master equation approach and the configuration interaction expansion. By mapping the impurity model onto an auxiliary open quantum system and adopting the configuration interaction approach augmented by active space extension, we can access a larger number of bath sites at lower computational costs. The approach combines the fast runtime of exact diagonalization with an accuracy close to the one achieved by matrix product states, making it an attractive solver for nonequilibrium dynamical mean field theory.
Article
Materials Science, Multidisciplinary
Jacob Park, Ehsan Khatami
Summary: This research utilized numerical methods to study the thermodynamic properties of the disordered Fermi-Hubbard model on different geometries and explored the effects of disorder on the system properties.
Article
Crystallography
Ka-Ming Tam, Hanna Terletska, Tom Berlijn, Liviu Chioncel, Juana Moreno
Summary: A real space cluster extension method was developed to study Anderson localization, successfully capturing the phenomena in all disorder regimes. The approach accurately obtained the critical disorder strength for 3D Anderson localization and systematically recovered the re-entrance behavior of the mobility edge. This methodology offers potential to study Anderson localization at surfaces within quantum embedding theory, allowing for the exploration of the interplay between topology and Anderson localization from first principles.
Article
Materials Science, Multidisciplinary
Steffen Backes, Jae-Hoon Sim, Silke Biermann
Summary: Motivated by the physics of quasi-two-dimensional fermionic systems, many-body computational methods that include both local and nonlocal electronic correlations are rapidly evolving. Methods may be hindered by the emergence of noncausal features, but the presented approach extends local many-body techniques to nonlocal correlations while preserving causality.
Article
Physics, Multidisciplinary
B. Pahlevanzadeh, P. Sahebsara, David Senechal
Summary: In the study of magic-angle twisted bilayer graphene, triplet superconductivity with p + ip symmetry and a subdominant singlet d + id state are stabilized by CDMFT. A minimum of the order parameter exists near quarter-filling and three-quarter filling, consistent with experimental observations.
Article
Physics, Multidisciplinary
Petar Mitric, Veljko Jankovic, Nenad Vukmirovic, Darko Tanaskovic
Summary: The dynamical mean field theory is an excellent, numerically cheap, approximate solution for the spectral function of the Holstein model even in one dimension, as revealed by detailed comparisons with other methods and literature results.
PHYSICAL REVIEW LETTERS
(2022)
Article
Physics, Multidisciplinary
Dongli Duan, Qi Yan, Yisheng Rong, Gege Hou
Summary: This article investigates the occurrence and prediction of disaster events in networks. By using a dynamical overload model, the study successfully distinguishes the effects of network structure and dynamic mechanisms on system robustness, and helps predict individual behavior in cascading processes.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2022)
Article
Computer Science, Artificial Intelligence
Zhuan Shen, Honghui Zhang, Zilu Cao, Luyao Yan, Yuzhi Zhao, Lin Du, Zichen Deng
Summary: This paper aims to analyze the possible mechanisms underlying the generation of generalized periodic epileptiform discharges (GPEDs) and design targeted optogenetic regulation strategies. A new computational framework is proposed by introducing a second inhibitory neuronal population and related synaptic connections into the classic Liley mean field model, which successfully simulates certain types of GPEDs that match clinical records. The results suggest that disinhibitory synaptic connections between inhibitory interneuronal populations are closely related to the occurrence, transition, and termination of GPEDs, supporting the hypothesis that selective changes of synaptic connections can trigger GPEDs. Additionally, six optogenetic strategies with dual targets are creatively offered, and the 1:1 coordinated reset stimulation with one period rest is concluded as the optimal strategy.
Article
Materials Science, Multidisciplinary
Philipp Werner, Denis Golez, Martin Eckstein
Summary: This study presents a formalism based on nonequilibrium dynamical mean-field theory (DMFT) to calculate the time-resolved x-ray absorption spectrum (XAS) of photoexcited solids. By applying this formalism to specific Hubbard models, the researchers reveal how the time-resolved XAS signal relates to the population of different local states. Additionally, they find that the atomic XAS spectrum computed with nonthermal state populations can provide a good approximation to the full nonequilibrium DMFT result, indicating a potential method to combine accurate DMFT description with cluster calculations of the XAS signal.
Article
Materials Science, Multidisciplinary
Jan Skolimowski
Summary: The impact of including edge states on the phase diagram of a spinless Falicov-Kimball model on the Haldane lattice is investigated. The presence of edge states leads to a charge density wave phase and metallic edge states. Two additional gapless phases caused by the edges are also discovered.