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The partition function is an essential quantity in statistical mechanics, and its accurate computation is a key component of any statistical analysis of quantum system and phenomenon. However, for interacting many-body quantum systems, its…

Quantum Physics · Physics 2022-11-16 Yusen Wu , Jingbo Wang

We discuss the distribution of partition function zeros for the grand-canonical ensemble of the zeta-urn model, where tuning a single parameter can give a first or any higher order condensation transition. We compute the locus of zeros for…

Statistical Mechanics · Physics 2024-09-25 P. Bialas , Z. Burda , D. A. Johnston

We characterize the breaking of analyticity with respect to the replica number which occurs in random energy models via the complex zeros of the moment of the partition function. We perturbatively evaluate the zeros in the vicinity of the…

Disordered Systems and Neural Networks · Physics 2015-05-13 Kenzo Ogure , Yoshiyuki Kabashima

In this paper we study finite-size effects in the Blume-Capel model through the analysis of the zeros of the partition function. We consider a complete graph and make use of the behaviour of the partition function zeros to elucidate the…

Statistical Mechanics · Physics 2025-01-09 Yulian Honchar , Mariana Krasnytska , Bertrand Berche , Yurij Holovatch , Ralph Kenna

This paper is a continuation of our previous analysis [BBCKK] of partition functions zeros in models with first-order phase transitions and periodic boundary conditions. Here it is shown that the assumptions under which the results of…

Mathematical Physics · Physics 2007-05-23 Marek Biskup , Christian Borgs , Jennifer T. Chayes , Roman Kotecky

We present methods that provide all zeroes and extrema of a function that do not require differentiation. Using point process theory, we are able to describe the locations of zeroes or maxima, their number, as well as their distribution…

Methodology · Statistics 2025-12-01 Athanasios Christou Micheas

We present a unified formulation for quantum statistical physics based on the representation of the density matrix as a functional integral. We identify the stochastic variable of the effective statistical theory that we derive as a…

Quantum Physics · Physics 2014-11-18 A. Bessa , C. A. A. de Carvalho , E. S. Fraga

The key problem of statistical physics standing over one hundred years is how to exactly calculate the partition function (or free energy) of many-body interaction systems, which severely hinders application of the theory for realistic…

Statistical Mechanics · Physics 2019-04-26 Bo-Yuan Ning , Le-Cheng Gong , Tsu-Chien Weng , Xi-Jing Ning

Attempts to understand zero temperature phase transitions have forced physicists to consider a regime where the standard paradigms of condensed matter physics break down [1-4]. These quantum critical systems lack a simple description in…

Quantum Gases · Physics 2012-07-04 Kaden R. A. Hazzard , Erich J. Mueller

Thermodynamic properties can be in principle derived from the partition function, which, in many-atom systems, is hard to evaluate as it involves a sum on the accessible microscopic states. Recently, the partition function has been computed…

The Yang-Lee, Fisher and Potts zeros of the one-dimensional Q-state Potts model are studied using the theory of dynamical systems. An exact recurrence relation for the partition function is derived. It is shown that zeros of the partition…

Statistical Mechanics · Physics 2007-05-23 R. G. Ghulghazaryan , N. S. Ananikian

Partition functions of probability distributions are important quantities for model evaluation and comparisons. We present a new method to compute partition functions of complex and multimodal distributions. Such distributions are often…

Machine Learning · Statistics 2016-05-27 David Carlson , Patrick Stinson , Ari Pakman , Liam Paninski

Probabilistic graphical models are a key tool in machine learning applications. Computing the partition function, i.e., normalizing constant, is a fundamental task of statistical inference but it is generally computationally intractable,…

Machine Learning · Statistics 2020-01-29 Sungsoo Ahn , Michael Chertkov , Adrian Weller , Jinwoo Shin

The sign problem is a notorious problem, which occurs in Monte Carlo simulations of a system with a partition function whose integrand is not positive. One way to simulate such a system is to use the factorization method where one enforces…

High Energy Physics - Lattice · Physics 2012-11-08 Konstantinos N. Anagnostopoulos , Takehiro Azuma , Jun Nishimura

Quantum thermodynamics can be naturally phrased as a theory of quantum state transformation and energy exchange for small-scale quantum systems undergoing thermodynamical processes, thereby making the resource theoretical approach very well…

Quantum Physics · Physics 2023-07-19 Uttam Singh , Jarosław K. Korbicz , Nicolas J. Cerf

We extend the circle theorem on the zeros of the partition function to a continuum system. We also calculate the exact zeros of the partition function for a finite system where the probability distribution for the order parameter is given…

Condensed Matter · Physics 2007-05-23 Koo-Chul Lee

The statistical physics approach to the number partioning problem, a classical NP-hard problem, is both simple and rewarding. Very basic notions and methods from statistical mechanics are enough to obtain analytical results for the phase…

Condensed Matter · Physics 2007-05-23 Stephan Mertens

Lee-Yang (LY) zeros play a fundamental role in the formulation of statistical physics in terms of (grand) partition functions, and assume theoretical significance for the phenomenon of phase transitions. In this paper, motivated by recent…

Statistical Mechanics · Physics 2022-12-14 Chengshu Li , Fan Yang

Novel sampling algorithms can significantly impact open questions in computational biology, most notably the in silico protein folding problem. By using computational methods, protein folding aims to find the three-dimensional structure of…

Statistics Theory · Mathematics 2007-06-13 Peter Minary , Michael Levitt

The main contribution of this paper is the development of a new decision tree algorithm. The proposed approach allows users to guide the algorithm through the data partitioning process. We believe this feature has many applications but in…

Machine Learning · Statistics 2020-10-27 Cédric Beaulac , Jeffrey S. Rosenthal