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Associative memory, a form of content-addressable memory, facilitates information storage and retrieval in many biological and physical systems. In statistical mechanics models, associative memory at equilibrium is represented through…

Disordered Systems and Neural Networks · Physics 2022-03-08 Agnish Kumar Behera , Madan Rao , Srikanth Sastry , Suriyanarayanan Vaikuntanathan

Thermalization of chaotic quantum many-body systems under unitary time evolution is related to the growth in complexity of initially simple Heisenberg operators. Operator growth is a manifestation of information scrambling and can be…

Strongly Correlated Electrons · Physics 2019-09-19 Shenglong Xu , Brian Swingle

Dissipation is inevitable in realistic quantum circuits. We examine the effects of dissipation on a class of monitored random circuits that exhibit a measurement-induced entanglement phase transition. This transition has previously been…

Statistical Mechanics · Physics 2023-10-13 Yue Li , Martin Claassen

We investigate the link between the irreversibility generated by a stationary dissipative process and the correlations established within a composite quantum system. We provide two equivalent expressions for the entropy generated in the…

Quantum Physics · Physics 2016-10-06 Matteo Brunelli , Mauro Paternostro

It is shown that a Hopfield recurrent neural network exhibits a scaling regime, whose specific exponents depend on the number of parcels used and the decay length of the coupling strength. This scaling regime recovers the picture introduced…

Disordered Systems and Neural Networks · Physics 2025-02-17 Giorgio Gosti , Sauro Succi , Giancarlo Ruocco

The dynamics of an extremely diluted neural network with high order synapses acting as corrections to the Hopfield model is investigated. As in the fully connected case, the high order terms may strongly improve the storage capacity of the…

Condensed Matter · Physics 2009-10-22 N. Lemke , J. J. Arenzon , F. A. Tamarit

Inspired by natural cooling processes, dissipation has become a promising approach for preparing low-energy states of quantum systems. However, the potential of dissipative protocols remains unclear beyond certain commuting Hamiltonians.…

Quantum Physics · Physics 2026-02-27 Yongtao Zhan , Zhiyan Ding , Jakob Huhn , Johnnie Gray , John Preskill , Garnet Kin-Lic Chan , Lin Lin

We study nano-pattern formation in a stochastic model for adsorption-desorption processes with interacting adsorbate and hyperbolic transport caused by memory effects. It is shown that at early stages the system manifests pattern selection…

Statistical Mechanics · Physics 2015-03-17 Dmitrii O. Kharchenko , Vasyl O. Kharchenko , Sergei V. Kokhan

Storing memory for molecular recognition is an efficient strategy for responding to external stimuli. Biological processes use different strategies to store memory. In the olfactory cortex, synaptic connections form when stimulated by an…

Biological Physics · Physics 2021-06-07 Oskar H Schnaack , Luca Peliti , Armita Nourmohammad

A one-dimensional quantum system with off diagonal disorder, consisting of a sample of conducting regions randomly interspersed within potential barriers is considered. Results mainly concerning the large $N$ limit are presented. In…

Disordered Systems and Neural Networks · Physics 2017-12-06 Tommaso Vanzan , Lamberto Rondoni

We explore the question as to whether quantum effects can yield a speedup of the non-equilibrium evolution of spin systems towards a classical thermal state. In our approach we exploit the fact that the thermal state of a spin system can be…

Statistical Mechanics · Physics 2019-04-03 Eliana Fiorelli , Pietro Rotondo , Matteo Marcuzzi , Juan P. Garrahan , Igor Lesanovsky

Quantum systems which interact with their environment are often modeled by maximal dissipative operators or so-called Pseudo-Hamiltonians. In this paper the scattering theory for such open systems is considered. First it is assumed that a…

Mathematical Physics · Physics 2007-05-23 J. Behrndt , M. M. Malamud , H. Neidhardt

Quantum coherence and quantum correlations are studied in the strongly interacting system composed of two qubits and an oscillator with the presence of a parametric medium. To analytically solve the system, we employ the adiabatic…

Quantum Physics · Physics 2021-12-14 V. Yogesh , Prosenjit Maity

Quantum small-worlds are quantum many-body systems that interpolate between completely ordered (nearest-neighbour, next-to-nearest-neighbour etc.) and completely random interactions. As such, they furnish a novel new laboratory to study…

High Energy Physics - Theory · Physics 2019-01-16 Jean-Gabriel Hartmann , Jeff Murugan , Jonathan P. Shock

Dissipative collective effects are ubiquitous in quantum physics, and their relevance ranges from the study of entanglement in biological systems to noise mitigation in quantum computers. Here, we put forward the first fully quantum…

Quantum Neural Networks (QNNs), or the so-called variational quantum circuits, are important quantum applications both because of their similar promises as classical neural networks and because of the feasibility of their implementation on…

Quantum Physics · Physics 2021-10-07 Xuchen You , Xiaodi Wu

To explore the relation between network structure and function, we studied the computational performance of Hopfield-type attractor neural nets with regular lattice, random, small-world and scale-free topologies. The random net is the most…

Disordered Systems and Neural Networks · Physics 2009-11-10 Patrick N. Mcgraw , Michael Menzinger

We consider a quantum system linearly coupled to a reservoir of harmonic oscillators. For finite coupling strengths, the stationary distribution of the damped system is not of the Gibbs form, in contrast to standard thermodynamics. With the…

Statistical Mechanics · Physics 2013-05-29 Stefanie Hilt , Benedikt Thomas , Eric Lutz

We investigate the computational limits of the memory retrieval dynamics of modern Hopfield models from the fine-grained complexity analysis. Our key contribution is the characterization of a phase transition behavior in the efficiency of…

Machine Learning · Computer Science 2024-06-04 Jerry Yao-Chieh Hu , Thomas Lin , Zhao Song , Han Liu

Isolation of a system from its environment is often desirable, from precision measurements to control of individual quantum systems; however, dissipation can also be a useful resource. Remarkably, engineered dissipation enables the…

Quantum Physics · Physics 2017-08-07 L. D. Tóth , N. R. Bernier , A. Nunnenkamp , A. K. Feofanov , T. J. Kippenberg