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The emergent dynamics in spacetime diagrams of cellular automata (CAs) is often organised by means of a number of behavioural classes. Whilst classification of elementary CAs is feasible and well-studied, non-elementary CAs are generally…

Cellular Automata and Lattice Gases · Physics 2025-07-10 Michiel Rollier , Aisling J. Daly , Jan M. Baetens

Compared to periodic systems, quasicrystals without translational invariance exhibit unexpected localization properties. The extended-localized transition in quasicrystals has been observed in both quantum and classical wave systems.…

Applied Physics · Physics 2024-06-18 Zhoufei Liu , Pei-Chao Cao , Ying Li , Jiping Huang

In this paper, we look at four generalizations of the one dimensional Aubry-Andre-Harper (AAH) model which possess mobility edges. We map out a phase diagram in terms of population imbalance, and look at the system size dependence of the…

Statistical Mechanics · Physics 2021-05-19 Sayantan Roy , Subroto Mukerjee , Manas Kulkarni

A new class of distributions based on phase-type distributions is introduced in the current paper to model lifetime data in the field of reliability analysis. This one is the natural extension of the distribution proposed by Acal et al.…

Methodology · Statistics 2025-01-13 Juan Eloy Ruiz-Castro , Christian Acal , Juan B. Roldán

Determining phase diagrams and phase transitions semi-automatically using machine learning has received a lot of attention recently, with results in good agreement with more conventional approaches in most cases. When it comes to more…

Disordered Systems and Neural Networks · Physics 2019-12-04 Hugo Théveniaut , Fabien Alet

From known phase diagram regions of different model Hamiltonians describing strongly correlated systems we deduced new domains of the ground state phase diagram of the same model by an unitary transformation. Different types of extended…

Strongly Correlated Electrons · Physics 2017-08-23 E Kovacs , Zs. Gulacsi

We investigate a two leg ladder system subjected to an external magnetic field. In the absence of a magnetic field, the system is described by a clean tight binding model, with no disorder in either the onsite potential or the hopping…

Disordered Systems and Neural Networks · Physics 2026-04-14 Arpita Goswami , Pallabi Chatterjee , Ranjan Modak , Shaon Sahoo

We propose an iterative proposal to estimate critical points for statistical models based on configurations by combing machine-learning tools. Firstly, phase scenarios and preliminary boundaries of phases are obtained by…

Disordered Systems and Neural Networks · Physics 2019-10-23 X. L. Zhao , L. B. Fu

Random electron systems show rich phases such as Anderson insulator, diffusive metal, quantum and anomalous quantum Hall insulator, Weyl semimetal, as well as strong/weak topological insulators. Eigenfunctions of each matter phase have…

Disordered Systems and Neural Networks · Physics 2016-11-21 Tomoki Ohtsuki , Tomi Ohtsuki

We investigate the phase diagram of two-dimensional (2D) Hubbard model by employing the optimization variational Monte Carlo method. The 2D Hubbard model is the most simple electronic model for cuprate high-temperature superconductors. The…

Strongly Correlated Electrons · Physics 2020-05-13 Takashi Yanagisawa , Mitake Miyazaki , Kunihiko Yamaji

We propose an efficient end-to-end deep learning method for solving nonlocal Allen-Cahn (AC) and Cahn-Hilliard (CH) phase-field models. One motivation for this effort emanates from the fact that discretized partial differential…

Machine Learning · Computer Science 2024-10-14 Yuwei Geng , Olena Burkovska , Lili Ju , Guannan Zhang , Max Gunzburger

Advanced Persistent Threats (APTs) evolve through multiple stages, each exhibiting distinct temporal and structural behaviors. Accurate stage estimation is critical for enabling adaptive cyber defense. This paper presents StageFinder, a…

Cryptography and Security · Computer Science 2026-05-06 Trung V. Phan , Thomas Bauschert

Data imbalance between common and rare diseases during model training often causes intelligent diagnosis systems to have biased predictions towards common diseases. The state-of-the-art approaches apply a two-stage learning framework to…

Computer Vision and Pattern Recognition · Computer Science 2022-07-15 Chenghua Zeng , Huijuan Lu , Kanghao Chen , Ruixuan Wang , Wei-Shi Zheng

We study localization in a one-dimensional quasiperiodic lattice obtained by extending the Aubry-Andr\'e model with an additional $N$th-neighbor hopping term of strength $J_{N}$. This long-range tunneling couples successive windings of an…

Disordered Systems and Neural Networks · Physics 2026-05-19 Taylan Yildiz , B. Tanatar , Balázs Hetényi

We study the phase transitions of three-dimensional (3D) classical O(3) model and the two-dimensional (2D) classical XY model, as well as both the quantum phase transitions of 2D and 3D dimerized spin-1/2 antiferromagnets, using the…

Disordered Systems and Neural Networks · Physics 2021-01-04 D. -R. Tan , F. -J. Jiang

The analytical approach developed by us for the calculation of the phase diagram for the Anderson localization via disorder [J.Phys.: Condens. Matter 14, 13777 (2002)] is generalized here to the case of a strong magnetic field when $q$…

Disordered Systems and Neural Networks · Physics 2008-06-12 V N Kuzovkov

How neural network behaves during the training over different choices of hyperparameters is an important question in the study of neural networks. In this work, inspired by the phase diagram in statistical mechanics, we draw the phase…

Machine Learning · Computer Science 2020-10-14 Tao Luo , Zhi-Qin John Xu , Zheng Ma , Yaoyu Zhang

We present a thorough pedagogical analysis of the single particle localization phenomenon in a quasiperiodic lattice in one dimension. Description of disorder in the lattice is represented by the Aubry-Andr\'e model. Characterization of…

Quantum Gases · Physics 2019-05-03 G. A. Domínguez-Castro , R. Paredes

Chimera and Solitary states have captivated scientists and engineers due to their peculiar dynamical states corresponding to the co-existence of coherent and incoherent dynamical evolution in coupled units in various natural and artificial…

Adaptation and Self-Organizing Systems · Physics 2022-02-15 Niraj Kushwaha , Naveen Kumar Mendola , Saptarshi Ghosh , Ajay Deep Kachhvah , Sarika Jalan

We use machine learning to classify rational two-dimensional conformal field theories. We first use the energy spectra of these minimal models to train a supervised learning algorithm. We find that the machine is able to correctly predict…

Strongly Correlated Electrons · Physics 2021-07-13 En-Jui Kuo , Alireza Seif , Rex Lundgren , Seth Whitsitt , Mohammad Hafezi