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We propose a simple estimator that allows to calculate the absolute value of a system's partition function from a finite sampling of its canonical ensemble. The estimator utilizes a volume correction term to compensate the effect that the…

Statistical Mechanics · Physics 2024-09-05 Ying-Chih Chiang , Frank Otto , Jonathan W. Essex

It is well-known (cf. K.-Pudl\'ak 1989) that a polynomial time algorithm finding tautologies hard for a propositional proof system $P$ exists iff $P$ is not optimal. Such an algorithm takes $1^{(k)}$ and outputs a tautology $\tau_k$ of size…

Logic · Mathematics 2016-04-26 Jan Krajicek

We investigate the problem of computing tensor product multiplicities for complex semisimple Lie algebras. Even though computing these numbers is #P-hard in general, we show that if the rank of the Lie algebra is assumed fixed, then there…

Representation Theory · Mathematics 2016-09-07 Jesús A. De Loera , Tyrrell B. McAllister

We study the approximability of computing the partition functions of two-state spin systems. The problem is parameterized by a $2\times 2$ symmetric matrix. Previous results on this problem were restricted either to the case where the…

Computational Complexity · Computer Science 2025-08-19 Yumou Fei , Leslie Ann Goldberg , Pinyan Lu

We investigate the large deviation behavior of the overlap probability density in the Sherrington--Kirkpatrick model from several analytical perspectives. First we analyze the spin glass phase using the coupled replica scheme. Here…

Statistical Mechanics · Physics 2009-11-07 Alain Billoire , Silvio Franz , Enzo Marinari

Recently, a novel method based on coding partitions [1]-[4] has been used to derive power series expansions to previously intractable problems. In this method the coefficients at $k$ are determined by summing the contributions made by each…

Combinatorics · Mathematics 2012-03-23 Victor Kowalenko

An original approach to solving rather difficult probabilistic problems arising in studying the readout of random discrete fields and having no exact analytical solutions at the moment is proposed. Several algorithms for direct, iterative,…

Other Computer Science · Computer Science 2014-12-04 Aleksander Reznik , Vitaly Efimov , Aleksander Soloview , Andrey Torgov

This paper gives an exposition of well known results on vector partition functions. The exposition is based on works of M. Brion, A. Szenes and M. Vergne and is geared toward explicit computer realizations. In particular, the paper presents…

Representation Theory · Mathematics 2010-11-25 Todor Milev

This article presents a numerical illustration of a recently proposed strongly polynomial-time algorithm for the general linear programming (LP) problem. Each iteration of the proposed algorithm consists of two Gauss-Jordan pivoting…

Optimization and Control · Mathematics 2026-05-12 Samuel Awoniyi

We describe random generation algorithms for a large class of random combinatorial objects called Schur processes, which are sequences of random (integer) partitions subject to certain interlacing conditions. This class contains several…

Partition refinement is a method for minimizing automata and transition systems of various types. Recently, we have developed a partition refinement algorithm that is generic in the transition type of the given system and matches the run…

Data Structures and Algorithms · Computer Science 2020-11-26 Thorsten Wißmann , Hans-Peter Deifel , Stefan Milius , Lutz Schröder

Assigning jobs onto identical machines with the objective to minimize the maximal load is one of the most basic problems in combinatorial optimization. Motivated by product planing and data placement, we study a natural extension called…

Data Structures and Algorithms · Computer Science 2019-09-27 Klaus Jansen , Alexandra Lassota , Marten Maack

We establish three equivalent versions of a Parisi formula for the free energy of mean-field spin glasses in a transversal magnetic field. These results are derived from available results for classical vector spin glasses by an…

Disordered Systems and Neural Networks · Physics 2024-03-12 Chokri Manai , Simone Warzel

Gaussian boson sampling is a model of photonic quantum computing that has attracted attention as a platform for building quantum devices capable of performing tasks that are out of reach for classical devices. There is therefore significant…

We consider a natural generalization of classical scheduling problems in which using a time unit for processing a job causes some time-dependent cost which must be paid in addition to the standard scheduling cost. We study the scheduling…

Data Structures and Algorithms · Computer Science 2018-12-03 Lin Chen , Nicole Megow , Roman Rischke , Leen Stougie , José Verschae

We present a numerical study of ground states of the dilute versions of the Sherrington-Kirkpatrick (SK) mean-field spin glass. In contrast to so-called "sparse" mean-field spin glasses that have been studied widely on random networks of…

Disordered Systems and Neural Networks · Physics 2022-04-21 Stefan Boettcher

We study the problem of testing and recovering $k$-clique Ferromagnetic mean shift in the planted Sherrington-Kirkpatrick model (i.e., a type of spin glass model) with $n$ spins. The planted SK model -- a stylized mixture of an uncountable…

Statistics Theory · Mathematics 2024-03-25 Yihan He , Han Liu , Jianqing Fan

We study the partition function from random matrix theory using a well known connection to orthogonal polynomials, and a recently developed Riemann-Hilbert approach to the computation of detailed asymptotics for these orthogonal…

Mathematical Physics · Physics 2007-05-23 N. M. Ercolani , K. D. T-R McLaughlin

A mean field spherical model with random couplings between pairs, quartets, and possibly higher multiplets of spins is considered. It has the same critical behavior as the Sherrington-Kirkpatrick model. It thus exhibits replica symmetry…

Condensed Matter · Physics 2009-10-22 Th. M. Nieuwenhuizen

Seeking tighter relaxations of combinatorial optimization problems, semidefinite programming is a generalization of linear programming that offers better bounds and is still polynomially solvable. Yet, in practice, a semidefinite program is…

Optimization and Control · Mathematics 2023-11-17 Daniel Porumbel