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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

The design of provably correct controllers for continuous-state stochastic systems crucially depends on approximate finite-state abstractions and their accuracy quantification. For this quantification, one generally uses approximate…

Systems and Control · Electrical Eng. & Systems 2022-01-17 B. C. van Huijgevoort , S. Haesaert

The development of physical simulators, called Ising machines, that sample from low energy states of the Ising Hamiltonian has the potential to drastically transform our ability to understand and control complex systems. However, most of…

Computational Physics · Physics 2021-03-10 Timothee Leleu , Farad Khoyratee , Timothee Levi , Ryan Hamerly , Takashi Kohno , Kazuyuki Aihara

Random packings of stiff rods are self-supporting mechanical structures stabilized by long range interactions induced by contacts. To understand the geometrical and topological complexity of the packings, we first deploy X-ray computerized…

Soft Condensed Matter · Physics 2024-09-24 Yeonsu Jung , Thomas Plumb-Reyes , Hao-Yu Greg Lin , L. Mahadevan

Bayesian model selection provides a powerful framework for objectively comparing models directly from observed data, without reference to ground truth data. However, Bayesian model selection requires the computation of the marginal…

Methodology · Statistics 2024-01-17 Xiaohao Cai , Jason D. McEwen , Marcelo Pereyra

Consider N equally-spaced points on a circle of circumference N. Choose at random n points out of $N$ on this circle and append clockwise an arc of integral length k to each such point. The resulting random set is made of a random number of…

Statistical Mechanics · Physics 2015-05-28 Thierry Huillet

We present our recent work on stochastic particle systems on complex networks. As a noninteracting system we first consider the diffusive motion of a random walker on heterogeneous complex networks. We find that the random walker is…

Statistical Mechanics · Physics 2007-05-23 Jae Dong Noh

In this paper we develop proximal methods for statistical learning. Proximal point algorithms are useful in statistics and machine learning for obtaining optimization solutions for composite functions. Our approach exploits closed-form…

Machine Learning · Statistics 2015-06-02 Nicholas G. Polson , James G. Scott , Brandon T. Willard

Many complex systems occurring in the natural or social sciences or economics are frequently described on a microscopic level, e.g., by lattice- or agent-based models. To analyze the states of such systems and their bifurcation structure on…

Adaptation and Self-Organizing Systems · Physics 2020-10-07 Clemens Willers , Uwe Thiele , Andrew J. Archer , David J. B. Lloyd , Oliver Kamps

We explore the potential of spatial-photonic Ising machines (SPIMs) to address computationally intensive Ising problems that employ low-rank and circulant coupling matrices. Our results indicate that the performance of SPIMs is critically…

We study Ising spin models on finitely connected random interaction graphs which are drawn from an ensemble in which not only the degree distribution $p(k)$ can be chosen arbitrarily, but which allows for further fine-tuning of the topology…

Disordered Systems and Neural Networks · Physics 2009-11-13 C. J. Perez-Vicente , A. C. C. Coolen

Tailoring many-body interactions among a proper quantum system endows it with computing ability by means of static quantum computation in the sense that some of the physical degrees of freedom can be used to store binary information and the…

Quantum Physics · Physics 2008-02-03 Haiqing Wei , Xin Xue

The order parameter cumulants of infinite matrix product ground states are evaluated across a quantum phase transition. A scheme using the Binder cumulant, finite-entanglement scaling and scaling functions to obtain the critical point and…

Strongly Correlated Electrons · Physics 2020-01-01 Jason C. Pillay , Ian P. McCulloch

We show that multipartite entanglement can be used as an efficient way of identifying the critical points of 1+1D systems. We demonstrate this with the quantum Ising model, lattice $\lambda \phi^4$ approximated with qutrits, and arrays of…

Quantum Physics · Physics 2026-03-13 Zane Ozzello , Yannick Meurice

The rapid development of quantum computers has enabled demonstrations of quantum advantages on various tasks. However, real quantum systems are always dissipative due to their inevitable interaction with the environment, and the resulting…

We study long-range interacting systems driven by external stochastic forces that act collectively on all the particles constituting the system. Such a scenario is frequently encountered in the context of plasmas, self-gravitating systems,…

Statistical Mechanics · Physics 2013-12-03 Cesare Nardini , Shamik Gupta , Stefano Ruffo , Thierry Dauxois , Freddy Bouchet

Several coupled maps models are sketched and reviewed in this short communication. First, a discrete logistic type model that was proposed for the symbiotic interaction of two species. Second, a model of many of these symbiotic species…

Adaptation and Self-Organizing Systems · Physics 2019-08-22 Ricardo Lopez-Ruiz

Trapped-ion quantum simulators have demonstrated a long history of studying the physics of interacting spin-lattice systems using globally addressed entangling operations. Here, we seek to broaden and delimit the classes of effective…

Quantum Physics · Physics 2024-04-16 Antonis Kyprianidis , A. J. Rasmusson , Philip Richerme

Since gene regulatory systems contain sometimes only a small number of molecules, these systems are not described well by macroscopic rate equations; a master equation approach is needed for such cases. We develop an approximation scheme…

Biological Physics · Physics 2015-05-20 Jun Ohkubo

This paper presents a scalable Bayesian technique for decentralized state estimation from multiple platforms in dynamic environments. As has long been recognized, centralized architectures impose severe scaling limitations for distributed…

Artificial Intelligence · Computer Science 2012-12-12 Matthew Rosencrantz , Geoffrey Gordon , Sebastian Thrun