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Given a set of numbers, the balanced partioning problem is to divide them into two subsets, so that the sum of the numbers in each subset are as nearly equal as possible, subject to the constraint that the cardinalities of the subsets be…

Data Structures and Algorithms · Computer Science 2007-05-23 Stephan Mertens

We study the problem of approximating the Ising model partition function with complex parameters on bounded degree graphs. We establish a deterministic polynomial-time approximation scheme for the partition function when the interactions…

Quantum Physics · Physics 2019-07-12 Ryan L. Mann , Michael J. Bremner

We introduce a problem class we call Polynomial Constraint Satisfaction Problems, or PCSP. Where the usual CSPs from computer science and optimization have real-valued score functions, and partition functions from physics have monomials,…

Discrete Mathematics · Computer Science 2010-01-14 Alexander D. Scott , Gregory B. Sorkin

Graph partitioning is a key fundamental problem in the area of big graph computation. Previous works do not consider the practical requirements when optimizing the big data analysis in real applications. In this paper, motivated by…

Databases · Computer Science 2024-04-10 Baoling Ning , Jianzhong Li

We consider a refinement of the partition function of graph homomorphisms and present a quasi-polynomial algorithm to compute it in a certain domain. As a corollary, we obtain quasi-polynomial algorithms for computing partition functions…

Combinatorics · Mathematics 2015-08-04 Alexander Barvinok , Pablo Soberón

In the number partitioning problem (NPP) one aims to partition a given set of $N$ real numbers into two subsets with approximately equal sum. The NPP is a well-studied optimization problem and is famous for possessing a…

Statistics Theory · Mathematics 2025-05-28 Rushil Mallarapu , Mark Sellke

We establish the average-case hardness of the algorithmic problem of exact computation of the partition function associated with the Sherrington-Kirkpatrick model of spin glasses with Gaussian couplings and random external field. In…

Probability · Mathematics 2023-09-19 David Gamarnik , Eren Kizildag

Column-sparse packing problems arise in several contexts in both deterministic and stochastic discrete optimization. We present two unifying ideas, (non-uniform) attenuation and multiple-chance algorithms, to obtain improved approximation…

Data Structures and Algorithms · Computer Science 2019-08-07 Brian Brubach , Karthik Abinav Sankararaman , Aravind Srinivasan , Pan Xu

The number partition problem is a well-known problem, which is one of 21 Karp's NP-complete problems \cite{karp}. The partition function is a boolean function that is equivalent to the number partition problem with number range restricted.…

Computational Complexity · Computer Science 2022-12-25 Chuyu Xiong

In this paper we relate the partition function to the max-statistics of random variables. In particular, we provide a novel framework for approximating and bounding the partition function using MAP inference on randomly perturbed models. As…

Machine Learning · Computer Science 2012-07-03 Tamir Hazan , Tommi Jaakkola

In the present paper, we study the limit sets of the almost periodic functions $f(x)$. It is interesting that the values $r=\inf|f(x)|$ and $R=\sup|f(x)|$ may be expressed in the exact form. We show that the ring $r\leq |z|\leq R$ is the…

Classical Analysis and ODEs · Mathematics 2021-10-28 Lev Sakhnovich

Karger (SIAM Journal on Computing, 1999) developed the first fully-polynomial approximation scheme to estimate the probability that a graph $G$ becomes disconnected, given that its edges are removed independently with probability $p$. This…

Data Structures and Algorithms · Computer Science 2023-10-13 David G. Harris , Aravind Srinivasan

Packing problems are an important class of optimization problems. The probably most well-known problem if this type is knapsack and many generalizations of it have been studied in the literature like Two-dimensional Geometric Knapsack…

Data Structures and Algorithms · Computer Science 2019-11-26 Tobias Mömke , Andreas Wiese

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

A well studied special case of bin packing is the 3-partition problem, where n items of size > 1/4 have to be packed in a minimum number of bins of capacity one. The famous Karmarkar-Karp algorithm transforms a fractional solution of a…

Discrete Mathematics · Computer Science 2012-02-03 Friedrich Eisenbrand , Dömötör Pálvölgyi , Thomas Rothvoß

Kernelization algorithms in the context of Parameterized Complexity are often based on a combination of reduction rules and combinatorial insights. We will expose in this paper a similar strategy for obtaining polynomial-time approximation…

Data Structures and Algorithms · Computer Science 2014-09-15 Faisal N. Abu-Khzam , Cristina Bazgan , Morgan Chopin , Henning Fernau

Partitioning and grouping of similar objects plays a fundamental role in image segmentation and in clustering problems. In such problems a typical goal is to group together similar objects, or pixels in the case of image processing. At the…

Computer Vision and Pattern Recognition · Computer Science 2010-10-12 Dorit S. Hochbaum

The number partitioning problem consists of partitioning a sequence of positive numbers ${a_1,a_2,..., a_N}$ into two disjoint sets, ${\cal A}$ and ${\cal B}$, such that the absolute value of the difference of the sums of $a_j$ over the two…

Statistical Mechanics · Physics 2009-10-31 F. F. Ferreira , J. F. Fontanari

In many high-dimensional problems,polynomial-time algorithms fall short of achieving the statistical limits attainable without computational constraints. A powerful approach to probe the limits of polynomial-time algorithms is to study the…

Statistics Theory · Mathematics 2025-07-11 Bertrand Even , Christophe Giraud , Nicolas Verzelen

We design two variational algorithms to optimize specific 2-local Hamiltonians defined on graphs. Our algorithms are inspired by the Quantum Approximate Optimization Algorithm. We develop formulae to analyze the energy achieved by these…

Quantum Physics · Physics 2024-12-20 Kunal Marwaha , Adrian She , James Sud
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