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Based on a recently introduced metric for measuring distances between configurations, we in- troduce distance-energy (DE) plots to characterize the potential energy surface (PES) of clusters. Producing such plots is computationally feasible…

Atomic and Molecular Clusters · Physics 2013-11-19 Sandip De , Bastian Schaefer , Ali Sadeghi , Michael Sicher , D. G. Kanhere , Stefan Goedecker

We study analytically M-spin-flip stable states in disordered short-ranged Ising models (spin glasses and ferromagnets) in all dimensions and for all M. Our approach is primarily dynamical and is based on the convergence of a…

Disordered Systems and Neural Networks · Physics 2009-10-31 C. M. Newman , D. L. Stein

A constructive scheme for determining pure states (clusters) at very low temperature in the 3-spins glass model on a random lattice is provided, in full agreement with Parisi's one step replica symmetry breaking (RSB) scheme. Proof is based…

Statistical Mechanics · Physics 2009-11-07 S. Cocco , O. Dubois , J. Mandler , R. Monasson

To understand how a complex system is organized and functions, researchers often identify communities in the system's network of interactions. Because it is practically impossible to explore all solutions to guarantee the best one, many…

Physics and Society · Physics 2019-11-27 Joaquín Calatayud , Rubén Bernardo-Madrid , Magnus Neuman , Alexis Rojas , Martin Rosvall

A quantum state's entanglement across a bipartite cut can be quantified with entanglement entropy or, more generally, Schmidt norms. Using only Schmidt decompositions, we present a simple iterative algorithm to maximize Schmidt norms.…

Quantum Physics · Physics 2018-06-14 Robin Reuvers

We consider the Edwards-Anderson Ising spin glass model on the half-plane $Z \times Z^+$ with zero external field and a wide range of choices, including mean zero Gaussian, for the common distribution of the collection J of i.i.d. nearest…

Probability · Mathematics 2015-05-14 Louis-Pierre Arguin , Michael Damron , Charles Newman , Daniel Stein

We investigate the entanglement content of the ground state of a system characterized by effective elementary degrees of freedom with fractional statistics. To this end, we explicitly construct the ground state for a chain of $N$ spins with…

Strongly Correlated Electrons · Physics 2015-05-14 D. Giuliano , A. Sindona , G. Falcone , F. Plastina , L. Amico

The nature of the spin glass state is investigated by studying changes to the ground state when a weak perturbation is applied to the bulk of the system. We consider short range models in three and four dimensions and the infinite range…

Disordered Systems and Neural Networks · Physics 2009-10-31 Matteo Palassini , A. P. Young

By variational Monte-Carlo method developed Ceperley et al. for the simulation of fermi systems in macroscopic confining potential well we simulate various spin ground states of the coulomb clusters with 2,3 and 4 particles in a broad…

Condensed Matter · Physics 2007-05-23 B. Abdullaev , A. D. Kidisyuk , M. M. Musakhanov

Spin glasses are notoriously difficult to study both analytically and numerically due to the presence of frustration and metastability. Their highly non-convex landscapes require collective updates to explore efficiently. Currently, most…

Disordered Systems and Neural Networks · Physics 2022-01-03 Yan Ru Pei , Massimiliano Di Ventra

We wish to thank Stefan Boettcher for prompting us to further check and highlight the accuracy and scaling of our results. Here we provide a comprehensive response to the Comment written by him. We argue that the Comment did not account for…

Disordered Systems and Neural Networks · Physics 2023-05-15 Changjun Fan , Mutian Shen , Zohar Nussinov , Zhong Liu , Yizhou Sun , Yang-Yu Liu

The minimum requirements for entanglement detection are discussed for a spin chain in which the spins cannot be individually accessed. The methods presented detect entangled states close to a cluster state and a many-body singlet state, and…

Quantum Physics · Physics 2007-05-23 Geza Toth

Identification of the clusters from an unlabeled data set is one of the most important problems in Unsupervised Machine Learning. The state of the art clustering algorithms are based on either the statistical properties or the geometric…

Machine Learning · Computer Science 2018-01-04 Sambarta Dasgupta , Keivan Ebrahimi , Umesh Vaidya

Ground states of the three dimensional Edwards-Anderson spin glass are computed in the presence of an external magnetic field. Our algorithm is sufficiently powerful for us to treat systems with up to 600 spins. We perform a statistical…

Disordered Systems and Neural Networks · Physics 2009-10-31 J. Houdayer , O. C. Martin

We show that the notion of critical droplets is central to an understanding of the nature of ground states in the Edwards-Anderson Ising model of a spin glass in arbitrary dimension. Given a specific ground state, suppose the coupling value…

Disordered Systems and Neural Networks · Physics 2024-11-25 C. M. Newman , D. L. Stein

The ground state entropy of the 2D Ising spin glass with +1 and -1 bonds is studied for $L \times M$ square lattices with $L \le M$ and $p$ = 0.5, where $p$ is the fraction of negative bonds, using periodic and/or antiperiodic boundary…

Disordered Systems and Neural Networks · Physics 2007-12-26 Ronald Fisch

Quantum computers promise a qualitative speedup in solving a broad spectrum of practical optimization problems. The latter can be mapped onto the task of finding low-energy states of spin glasses, which is known to be exceedingly difficult.…

Disordered Systems and Neural Networks · Physics 2024-12-31 Hao Zhang , Kelly Boothby , Alex Kamenev

A ground state path integral quantum Monte Carlo algorithm is introduced that allows for the study of entanglement in lattice bosons at zero temperature. The R\'enyi entanglement entropy between spatial subregions is explored across the…

Quantum Gases · Physics 2023-03-29 Emanuel Casiano-Diaz , C. M. Herdman , Adrian Del Maestro

Lattice models, also known as generalized Ising models or cluster expansions, are widely used in many areas of science and are routinely applied to alloy thermodynamics, solid-solid phase transitions, magnetic and thermal properties of…

Disordered Systems and Neural Networks · Physics 2016-11-17 Wenxuan Huang , Daniil A. Kitchaev , Stephen Dacek , Ziqin Rong , Alexander Urban , Shan Cao , Chuan Luo , Gerbrand Ceder

Clustering methods are a valuable tool for the identification of patterns in high dimensional data with applications in many scientific problems. However, quantifying uncertainty in clustering is a challenging problem, particularly when…

Methodology · Statistics 2018-06-01 Marcio Valk , Gabriela Bettella Cybis