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Using the strong coupling diagram technique, we calculate the zero-temperature density of states $\rho$ of electrons on a square lattice immersed in a perpendicular uniform magnetic field. The electrons are described by Hubbard Hamiltonian.…

Strongly Correlated Electrons · Physics 2025-04-10 Alexei Sherman

This paper presents a systematic study of the application of convolutional neural networks (CNNs) as an efficient and versatile tool for the analysis of critical and low-temperature phase states in spin system models. The problem of…

Computational Physics · Physics 2025-12-09 Dmitrii Kapitan , Pavel Ovchinnikov , Konstantin Soldatov , Petr Andriushchenko , Vitalii Kapitan

We introduce a one dimensional spin $\frac{1}{2}$ Hamiltonian with multi-site interactions, but still local. The algebra of its Hamiltonian densities resembles that of the transverse field Ising model. Using this fact we show that its…

Statistical Mechanics · Physics 2026-05-29 Akash Sinha , Somnath Maity , Pramod Padmanabhan , Vladimir Korepin

We present a novel Ensemble Monte Carlo Growth method to sample the equilibrium thermodynamic properties of random chains. The method is based on the multicanonical technique of computing the density of states in the energy space. Such a…

Statistical Mechanics · Physics 2020-03-04 Graziano Vernizzi , Trung Dac Nguyen , Henri Orland , Monica Olvera de la Cruz

A density estimation method in a Bayesian nonparametric framework is presented when recorded data are not coming directly from the distribution of interest, but from a length biased version. From a Bayesian perspective, efforts to…

Statistics Theory · Mathematics 2015-10-23 Spyridon J. Hatjispyros , Theodoros Nicoleris , Stephen G. Walker

We review a class of energy landscape analysis method that uses the Ising model and takes multivariate time series data as input. The method allows one to capture dynamics of the data as trajectories of a ball from one basin to a different…

Disordered Systems and Neural Networks · Physics 2025-05-13 Naoki Masuda , Saiful Islam , Si Thu Aung , Takamitsu Watanabe

In recent years it became clear that the metallic regime of systems that exhibit a many body localization (MBL) behavior show properties which are quite different than the vanilla metallic region of the single particle Anderson regime. Here…

Disordered Systems and Neural Networks · Physics 2022-04-06 Richard Berkovits

Boltzmann's microcanonical entropy is the link between statistical physics and thermodynamics, forasmuch as the behavior of any thermodynamic quantity is directly related to the number of microscopic configurations. Accordingly, in this…

Statistical Mechanics · Physics 2022-11-24 L. S. Ferreira , L. N. Jorge , C. J. DaSilva , A. A. Caparica

Combining traditional Wang-Landau sampling for multiple replica systems with an exchange of densities of states between replicas, we describe a general framework for simulations on massively parallel Petaflop supercomputers. The advantages…

Computational Physics · Physics 2014-03-13 Thomas Vogel , Ying Wai Li , Thomas Wüst , David P. Landau

Temperature Accelerated Sliced Sampling (TASS) is an efficient method to compute high dimensional free energy landscapes. The original TASS method employs the Weighted Histogram Analysis Method (WHAM) which is an iterative post-processing…

Computational Physics · Physics 2021-10-18 Asit Pal , Subhendu Pal , Shivani Verma , Motoyuki Shiga , Nisanth N. Nair

We use a two-fluid model combining the quantum Green's function technique for the electrons and a classical HNC description for the ions to calculate the high-density equation of state of hydrogen. This approach allows us to describe fully…

Plasma Physics · Physics 2011-08-25 J. Vorberger , D. O. Gericke , W. -D. Kraeft

We present an identity for an unbiased estimate of a general statistical distribution. The identity computes the distribution density from dividing a histogram sum over a local window by a correction factor from a mean-force integral, and…

Computational Physics · Physics 2012-06-04 Cheng Zhang , Jianpeng Ma

Length-biased data are a particular case of weighted data, which arise in many situations: biomedicine, quality control or epidemiology among others. In this paper we study the theoretical properties of kernel density estimation in the…

We consider the problem of estimating the partition function of the ferromagnetic Ising model in a consistent external magnetic field. The estimation is done via importance sampling in the dual of the Forney factor graph representing the…

Computation · Statistics 2017-01-27 Mehdi Molkaraie

We compare the ground state of the random-field Ising model with Gaussian distributed random fields, with its non-equilibrium hysteretic counterpart, the demagnetized state. This is a low energy state obtained by a sequence of slow magnetic…

Distance sampling is a widely used method for estimating wildlife population abundance. The fact that conventional distance sampling methods are partly design-based constrains the spatial resolution at which animal density can be estimated…

Methodology · Statistics 2017-06-23 Y. Yuan , F. E. Bachl , F. Lindgren , D. L. Brochers , J. B. Illian , S. T. Buckland , H. Rue , T. Gerrodette

We develop series expansions for the ground state properties of the Hubbard model, by introducing an Ising anisotropy into the Hamiltonian. For the two-dimensional (2D) square lattice half-filled Hubbard model, the ground state energy,…

Condensed Matter · Physics 2009-10-28 Zhu-Pei Shi , Rajiv R. P. Singh

We apply the method of asymptotic homogenization to metamaterials with microscopically bianisotropic inclusions to calculate a full set of constitutive parameters in the long wavelength limit. Two different implementations of…

Materials Science · Physics 2016-04-27 Chris Fietz

Accurate estimation of wildlife density is vital for effective ecological monitoring, conservation, and management. Line transect sampling, a central technique in distance sampling, relies on selecting an appropriate detection function to…

Methodology · Statistics 2025-07-16 Midhat M. Edous , Omar M. Eidous

Multiplex networks consist of a fixed set of nodes connected by several sets of edges which are generated separately and correspond to different networks ("layers"). Here, a simple variant of the Ising model on multiplex networks with two…

Statistical Mechanics · Physics 2018-01-17 Andrzej Krawiecki