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The Poisson-Nernst-Planck (PNP) equations are one of the most effective model for describing electrostatic interactions and diffusion processes in ion solution systems, and have been widely used in the numerical simulations of biological…

Numerical Analysis · Mathematics 2023-12-19 Yang Liu , Shi Shu , Ying Yang

Counting independent sets on bipartite graphs (#BIS) is considered a canonical counting problem of intermediate approximation complexity. It is conjectured that #BIS neither has an FPRAS nor is as hard as #SAT to approximate. We study #BIS…

Computational Complexity · Computer Science 2016-05-30 Jin-Yi Cai , Andreas Galanis , Leslie Ann Goldberg , Heng Guo , Mark Jerrum , Daniel Stefankovic , Eric Vigoda

We investigate analytically and numerically an Ising spin model with ferromagnetic coupling defined on random graphs corresponding to Feynman diagrams of a $\phi^q$ field theory, which exhibits a mean field phase transition. We explicitly…

Statistical Mechanics · Physics 2011-04-21 Piotr Bialas , Andrzej K. Oleś

We consider the Partition problem and propose a deterministic FPTAS (Fully Polynomial-Time Approximation Scheme) that runs in $\widetilde{O}(n + 1/\varepsilon)$-time. This is the best possible (up to a polylogarithmic factor) assuming the…

Data Structures and Algorithms · Computer Science 2025-01-23 Lin Chen , Jiayi Lian , Yuchen Mao , Guochuan Zhang

We discuss analytical approximation schemes for the dynamics of diluted spin models. The original dynamics of the complete set of degrees of freedom is replaced by a hierarchy of equations including an increasing number of global…

Statistical Mechanics · Physics 2009-11-10 Guilhem Semerjian , Martin Weigt

The theoretical models providing mathematical abstractions for several significant optimization problems in machine learning, combinatorial optimization, computer vision and statistical physics have intrinsic similarities. We propose a…

Data Structures and Algorithms · Computer Science 2018-04-18 Yi-Kai Wang

Partitioning is a well studied research problem in the area of VLSI physical design automation. In this problem, input is an integrated circuit and output is a set of almost equal disjoint blocks. The main objective of partitioning is to…

Data Structures and Algorithms · Computer Science 2014-03-04 Mitali Sinha , Suchismita Pattanaik , Rakesh Mohanty , Prachi Tripathy

This paper develops results for the next nearest neighbour Ising model on random graphs. Besides being an essential ingredient in classic models for frustrated systems, second neighbour interactions interactions arise naturally in several…

Statistical Mechanics · Physics 2013-09-17 Jack Raymond , K. Y. Michael Wong

This is the second in a series of three articles about recovering the full algebraic structure of a boundary conformal field theory (CFT) from the scaling limit of the critical Ising model in slit-strip geometry. Here we study the fusion…

Mathematical Physics · Physics 2021-08-12 Taha Ameen , Kalle Kytölä , S. C. Park

Lee-Yang zeros are points in the complex plane of an external control parameter at which the partition function vanishes for a many-body system of finite size. In the thermodynamic limit, the Lee-Yang zeros approach the critical value on…

Mesoscale and Nanoscale Physics · Physics 2019-09-06 Aydin Deger , Christian Flindt

We consider the problem of learning the structure of ferromagnetic Ising models Markov on sparse Erdos-Renyi random graph. We propose simple local algorithms and analyze their performance in the regime of correlation decay. We prove that an…

Statistics Theory · Mathematics 2015-03-17 Animashree Anandkumar , Vincent Tan , Alan Willsky

Two kinds of approximation algorithms exist for the k-BALANCED PARTITIONING problem: those that are fast but compute unsatisfying approximation ratios, and those that guarantee high quality ratios but are slow. In this paper we prove that…

Computational Complexity · Computer Science 2019-04-29 Andreas Emil Feldmann

We apply a new updating algorithm scheme to investigate the critical behavior of the two-dimensional ferromagnetic Ising model on a triangular lattice with nearest neighbour interactions. The transition is examined by generating accurate…

Statistical Mechanics · Physics 2015-05-13 Zhi-Huan Luo , Mushtaq Loan , Yan Liu , Jian-Rong Lin

We give a deterministic polynomial-time approximation scheme (FPTAS) for the volume of the truncated fractional matching polytope for graphs of maximum degree $\Delta$, where the truncation is by restricting each variable to the interval…

Data Structures and Algorithms · Computer Science 2024-09-12 Heng Guo , Vishvajeet N

The Ising model is important in statistical modeling and inference in many applications, however its normalizing constant, mean number of active vertices and mean spin interaction -- quantities needed in inference -- are computationally…

Methodology · Statistics 2024-01-23 Alejandro Murua-Sazo , Ranjan Maitra

A general numerical method is presented to locate the partition function zeros in the complex beta plane for large lattice sizes. We apply this method to the 2D Ising model and results are reported for square lattice sizes up tp L=64. We…

Statistical Mechanics · Physics 2009-10-30 Nelson A. Alves , J. R. Drugowich de Felicio , Ulrich H. E. Hansmann

We study the stochastic parallel dynamics of Ising spin systems defined on finitely connected directed random graphs with arbitrary degree distributions, using generating functional analysis. For fully asymmetric graphs the dynamics of the…

Disordered Systems and Neural Networks · Physics 2009-09-24 Kazushi Mimura , A. C. C. Coolen

The Ising model on ``thin'' graphs (standard Feynman diagrams) displays several interesting properties. For ferromagnetic couplings there is a mean field phase transition at the corresponding Bethe lattice transition point. For…

High Energy Physics - Lattice · Physics 2016-08-31 C. F. Baillie , D. A. Johnston , J-P. Kownacki

We prove rapid mixing of the Prokofiev-Svistunov (or worm) algorithm for the zero-field ferromagnetic Ising model, on all finite graphs and at all temperatures. As a corollary, we show how to rigorously construct simple and efficient…

Mathematical Physics · Physics 2014-09-17 Andrea Collevecchio , Timothy M. Garoni , Timothy Hyndman , Daniel Tokarev

Understanding generalization in deep learning has been one of the major challenges in statistical learning theory over the last decade. While recent work has illustrated that the dataset and the training algorithm must be taken into account…