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The ferromagnetic Ising model is a model of a magnetic material and a central topic in statistical physics. It also plays a starring role in the algorithmic study of approximate counting: approximating the partition function of the…

Data Structures and Algorithms · Computer Science 2021-11-05 Charlie Carlson , Ewan Davies , Alexandra Kolla , Will Perkins

In this work we propose a new numerical method to evaluate the critical point, the susceptibility critical exponent and the correlation length critical exponent of the three dimensional Ising model without external field using an algorithm…

Statistical Mechanics · Physics 2021-02-19 Francisco Sastre

We enlighten some critical aspects of the three-dimensional ($d=3$) random-field Ising model from simulations performed at zero temperature. We consider two different, in terms of the field distribution, versions of model, namely a Gaussian…

Disordered Systems and Neural Networks · Physics 2015-01-13 P. E. Theodorakis , N. G. Fytas

Lightning plays a crucial role in the Earth's climate system, yet existing parameterizations for use in forecasting and earth system models show room for improvement in capturing spatial and temporal variations in its frequency. This study…

Atmospheric and Oceanic Physics · Physics 2025-09-15 Randall Jones , Joel A. Thornton , Chris J. Wright , Robert Holzworth

We investigate the large order aspects of the delta-expansion under the estimation procession of the critical quantities. As illustrative examples, we revisit one-dimensional Ising model for the analytic study and two-dimensional square…

High Energy Physics - Lattice · Physics 2015-06-22 Hirofumi Yamada

A two-dimensional fluid of hard spheres each having a spin $\pm 1$ and interacting via short-range Ising-like interaction is studied near the second order phase transition from the paramagnetic gas to the ferromagnetic gas phase. Monte…

Statistical Mechanics · Physics 2009-10-30 A. L. Ferreira , W. Korneta

The deployment of deep convolutional neural networks (CNNs) in many real world applications is largely hindered by their high computational cost. In this paper, we propose a novel learning scheme for CNNs to simultaneously 1) reduce the…

Computer Vision and Pattern Recognition · Computer Science 2017-08-23 Zhuang Liu , Jianguo Li , Zhiqiang Shen , Gao Huang , Shoumeng Yan , Changshui Zhang

While deep neural networks (NN) significantly advance image compressed sensing (CS) by improving reconstruction quality, the necessity of training current CS NNs from scratch constrains their effectiveness and hampers rapid deployment.…

Computer Vision and Pattern Recognition · Computer Science 2025-02-04 Bin Chen , Zhenyu Zhang , Weiqi Li , Chen Zhao , Jiwen Yu , Shijie Zhao , Jie Chen , Jian Zhang

Recent advances in deep learning and neural networks have led to an increased interest in the application of generative models in statistical and condensed matter physics. In particular, restricted Boltzmann machines (RBMs) and variational…

Disordered Systems and Neural Networks · Physics 2020-06-09 Francesco D'Angelo , Lucas Böttcher

The critical properties of the single-crystalline semiconducting ferromagnet CrGeTe$_3$ were investigated by bulk dc magnetization around the paramagnetic to ferromagnetic phase transition. Critical exponents $\beta = 0.200\pm0.003$ with…

Materials Science · Physics 2017-08-16 Yu Liu , C. Petrovic

We study numerically the region above the critical temperature of the four dimensional Random Field Ising Model. Using a cluster dynamic we measure the connected and disconnected magnetic susceptibility and the connected and disconnected…

Disordered Systems and Neural Networks · Physics 2009-10-30 Roberto Sacconi

Thick, Charge Coupled Devices (CCDs) have recently been explored for applied physics, such as nuclear explosion monitoring, and dark matter detection purposes. When run in fully-depleted mode, these devices are sensitive detectors for…

Instrumentation and Detectors · Physics 2022-01-25 C. Britt , E. Church , T. Hossbach , B. Loer , R. Saldanha , N. Sinha , K. Woodruff

We extend the Prometheus framework for unsupervised phase transition discovery from two-dimensional classical systems to three-dimensional classical systems and quantum many-body systems. Building upon preliminary observations from a 2D…

Disordered Systems and Neural Networks · Physics 2026-04-21 Brandon Yee , Wilson Collins , Pairie Koh , Maximilian Rutkowski

The recent advancement in deep learning (DL) for automatic modulation classification (AMC) of wireless signals has encouraged numerous possible applications on resource-constrained edge devices. However, developing optimized DL models…

Signal Processing · Electrical Eng. & Systems 2024-04-25 Nayan Moni Baishya , B. R. Manoj , Prabin K. Bora

We employ the microcanonical inflection-point analysis method, developed for the systematic identification and classification of phase transitions in systems of any size, to study the two-dimensional Ising model at various lattice sizes and…

Statistical Mechanics · Physics 2023-06-30 Kedkanok Sitarachu , Michael Bachmann

The random-field Ising model shows extreme critical slowdown that has been described by activated dynamic scaling: the characteristic time for the relaxation to equilibrium diverges exponentially with the correlation length, $\ln \tau\sim…

Statistical Mechanics · Physics 2017-10-12 Ivan Balog , Gilles Tarjus

Dominant energy subspaces of statistical systems are defined with the help of restrictive conditions on various characteristics of the energy distribution, such as the probability density and the forth order Binder's cumulant. Our analysis…

Statistical Mechanics · Physics 2007-05-23 A. Malakis , S. S. Martinos , I. A. Hadjiagapiou , N. G. Fytas , P. Kalozoumis

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 critical phenomena of two-dimensional (2D) antiferromagnetic $q$-state Potts model on the square lattice with $q=2,3,4,5$ and 6 are investigated using the technique of supervised neural network (NN). Unlike the conventional NN…

High Energy Physics - Lattice · Physics 2026-03-26 Shang-Wei Li , Kai-Wei Huang , Chien-Ting Chen , Fu-Jiun Jiang

The critical behavior of the classical Ising model on a three-dimensional fractal lattice with Hausdorff dimension $d_H = \ln32 / \ln4 = 2.5$ is investigated using the higher-order tensor renormalization group (HOTRG) method. We determine…

Statistical Mechanics · Physics 2025-06-27 Jozef Genzor , Roman Krčmár , Hiroshi Ueda , Denis Kochan , Andrej Gendiar , Tomotoshi Nishino
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