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Tensor network (TN) methods are well established for computing partition functions in statistical mechanics, though this use has traditionally been limited to lattice models. We extend the scope of TN methodology to interacting particle…

Statistical Mechanics · Physics 2026-04-29 Gunhee Park , Tomislav Begušić , Si-Jing Du , Johnnie Gray , Garnet Kin-Lic Chan

We investigate the computational hardness of spin-glass instances on a square lattice, generated via a recently introduced tunable and scalable approach for planting solutions. The method relies on partitioning the problem graph into…

Disordered Systems and Neural Networks · Physics 2020-03-02 Dilina Perera , Firas Hamze , Jack Raymond , Martin Weigel , Helmut G. Katzgraber

We introduce an algorithm to generate (not solve) spin-glass instances with planted solutions of arbitrary size and structure. First, a set of small problem patches with open boundaries is solved either exactly or with a heuristic, and then…

Disordered Systems and Neural Networks · Physics 2017-08-31 Wenlong Wang , Salvatore Mandrà , Helmut G. Katzgraber

Spin-glass systems are universal models for representing many-body phenomena in statistical physics and computer science. High quality solutions of NP-hard combinatorial optimization problems can be encoded into low energy states of…

Disordered Systems and Neural Networks · Physics 2020-01-14 Gavin S. Hartnett , Masoud Mohseni

The knapsack problem (KP) is a very famous NP-hard problem in combinatorial optimization. Also its generalization to multiple dimensions named d-dimensional knapsack problem (d-KP) and to multiple knapsacks named multiple knapsack problem…

Computational Complexity · Computer Science 2016-11-24 Carolin Albrecht , Frank Gurski , Jochen Rethmann , Eda Yilmaz

In certain classes of physical quantum systems, the exponentially large state space "fragments" into many low-dimensional, dynamically disconnected subspaces. We introduce a learning problem known as fragment classification, where given a…

Quantum Physics · Physics 2026-05-08 Mikhail Mints , Eric R. Anschuetz

Exploiting quantum properties to outperform classical ways of information-processing is an outstanding goal of modern physics. A promising route is quantum simulation, which aims at implementing relevant and computationally hard problems in…

We consider the random number partitioning problem (\texttt{NPP}): given a list $X\sim \mathcal{N}(0,I_n)$ of numbers, find a partition $\sigma\in\{-1,1\}^n$ with a small objective value $H(\sigma)=\frac{1}{\sqrt{n}}\left|\langle…

Statistics Theory · Mathematics 2023-09-27 Eren C. Kızıldağ

We compare two methods for evaluating the cardinality of the Cartesian product $N \times N$ of the set of natural numbers $N$. The first is used to explain the thermodynamics of black body radiation by using convergent functions on $N…

General Physics · Physics 2026-04-23 Kaushik Ghosh

The phase transition in the number partitioning problem (NPP), i.e., the transition from a region in the space of control parameters in which almost all instances have many solutions to a region in which almost all instances have no…

Condensed Matter · Physics 2016-08-16 Peter F. Stadler , Wim Hordijk , José F. Fontanari

We present two algorithms, one quantum and one classical, for estimating partition functions of quantum spin Hamiltonians. The former is a DQC1 (Deterministic quantum computation with one clean qubit) algorithm, and the first such for…

Quantum Physics · Physics 2023-02-01 Andrew Jackson , Theodoros Kapourniotis , Animesh Datta

We study the non-canonical symplectic structure, or K-symplectic structure inherited by the charged particle dynamics. Based on the splitting technique, we construct non-canonical symplectic methods which is explicit and stable for the…

Computational Physics · Physics 2015-09-28 Yang He , Yajuan Sun , Zhaoqi Zhou , Jian Liu , Hong Qin

Combinatorial optimization problems are pervasive across science and industry. Modern deep learning tools are poised to solve these problems at unprecedented scales, but a unifying framework that incorporates insights from statistical…

Machine Learning · Computer Science 2022-04-26 Martin J. A. Schuetz , J. Kyle Brubaker , Helmut G. Katzgraber

Qualitative numerical planning is classical planning extended with non-negative real variables that can be increased or decreased "qualitatively", i.e., by positive indeterminate amounts. While deterministic planning with numerical…

Artificial Intelligence · Computer Science 2020-11-30 Blai Bonet , Hector Geffner

The Critical Node Problem (CNP) is to identify a subset of nodes in a graph whose removal maximally degrades pairwise connectivity. The CNP is an important variant of the Critical Node Detection Problem (CNDP) with wide applications. Due to…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-09-04 Biqing Fang , Hai Wan , Shaowei Cai , Zejie Cai

Given a sequence of $N$ positive real numbers $\{a_1,a_2,..., a_N \}$, the number partitioning problem consists of partitioning them into two sets such that the absolute value of the difference of the sums of $a_j$ over the two sets is…

adap-org · Physics 2009-10-30 F F Ferreira , J F Fontanari

Various real-world problems consist of partitioning a set of locations into disjoint subsets, each subset spread in a way that it covers the whole set with a certain radius. Given a finite set S, a metric d, and a radius r, define a subset…

Data Structures and Algorithms · Computer Science 2023-02-08 Eran Rosenbluth

Two quantum algorithms are presented, which tackle well--known problems in the context of numerical semigroups: the numerical semigroup membership problem (NSMP) and the Sylvester denumerant problem (SDP).

Quantum Physics · Physics 2024-02-09 J. Ossorio-Castillo , José M. Tornero

This paper presents a unified framework for investigating the partial condition number (CN) of the solution of double saddle point problems (DSPPs) and provides closed-form expressions for it. This unified framework encompasses the…

Numerical Analysis · Mathematics 2025-06-17 Sk. Safique Ahmad , Pinki Khatun

We consider the problem of covering hypersphere by a set of spherical hypercaps. This sort of problem has numerous practical applications such as error correcting codes and reverse k-nearest neighbor problem. Using the reduction of non…

Computational Geometry · Computer Science 2015-03-19 Marko D. Petkovic , Dragoljub Pokrajac , Longin Jan Latecki