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Memory effects play a key role in the dynamics of strongly correlated systems driven out of equilibrium. In the present study, we explore the nature of memory in the nonequilibrium Anderson impurity model. The Nakajima--Zwanzig--Mori…

Strongly Correlated Electrons · Physics 2013-01-28 Guy Cohen , Eran Rabani

Industrial polymeric materials often rely on antioxidants to achieve long-term reliability. Previous studies have frequently discussed the stabilization effect in the presence of macroscopic additive migration. However, the micro- to…

Soft Condensed Matter · Physics 2026-02-17 Takato Ishida , Emmanuel Richaud

This manuscript aims to illustrate a quantum-classical dissipative theory (suited to be converted to effective algorithms for numerical simulations) within the long-term project of studying molecular processes in the brain. Other…

Neurons and Cognition · Quantitative Biology 2025-03-04 Alessandro Sergi , Antonino Messina , Rosalba Saija , Gabriella Martino , Maria Teresa Caccamo , Min-Fang Kuo , Michael A. Nitsche

Memory effects in the dynamics of open systems have been the subject of significant interest in the last decades. The methods involved in quantifying this effect, however, are often difficult to compute and may lack analytical insight. With…

Quantum Physics · Physics 2021-02-10 Rolando Ramirez Camasca , Gabriel T. Landi

We investigate memory effects in non-Markovian dynamics on superconducting quantum processors provided by IBM Quantum. We use a collision-model approach to implement suitable single- and two-qubit dynamics with a gate-based quantum circuit.…

Quantum Physics · Physics 2026-04-24 Charlotte Bäcker , Krishna Palaparthy , Walter T. Strunz

Extensive experimental and numerical studies of the non-equilibrium dynamics of spin glasses subjected to temperature or bond perturbations have been performed to investigate chaos and memory effects in selected spin glass systems.…

Materials Science · Physics 2015-06-24 P. E. Jönsson , R. Mathieu , P. Nordblad , H. Yoshino , H. Aruga Katori , A. Ito

Critical slowing down dynamics of supercooled glass-forming liquids is usually understood at the mean-field level in the framework of Mode Coupling Theory, providing a two-time relaxation scenario and power-law behaviors of the time…

Disordered Systems and Neural Networks · Physics 2013-01-30 Ulisse Ferrari , Luca Leuzzi , Giorgio Parisi , Tommaso Rizzo

We show that the effect of a Gaussian Bosonic environment linearly coupled to a quantum system can be simulated by a stochastic Lindblad master equation characterized by a set of ancillary Bosonic modes initially at zero temperature and…

Quantum Physics · Physics 2023-10-31 Si Luo , Neill Lambert , Pengfei Liang , Mauro Cirio

We construct a class of systems for which quantum dynamics can be expanded around a mean field approximation with essentially classical content. The modulus of the quantum overlap of mean field states naturally introduces a classical…

We investigate theoretically the slow non-exponential relaxation dynamics of the electron glass out of equilibrium, where a sudden change in carrier density reveals interesting memory effects. The self-consistent model of the dynamics of…

Disordered Systems and Neural Networks · Physics 2015-06-16 Yasmine Meroz , Yuval Oreg , Yoseph Imry

Motivated by understanding the emergence of thermodynamic restoring forces and oscillations, we develop a quantum-mechanical model of a bath of spins coupled to the elasticity of a material. We show our model reproduces the behavior of a…

Quantum Physics · Physics 2016-10-10 Chiao-Hsuan Wang , Jacob M. Taylor

The effect of the Coulomb interaction on the phase diagram of finite nuclei is studied within the Canonical Thermodynamic Model. If Coulomb effects are artificially switched off, this model shows a phenomenology consistent with the…

Nuclear Theory · Physics 2008-12-18 G. Chaudhuri , S. Das Gupta , F. Gulminelli

Classical learning of the expectation values of observables for quantum states is a natural variant of learning quantum states or channels. While learning-theoretic frameworks establish the sample complexity and the number of measurement…

Quantum Physics · Physics 2024-08-12 Beng Yee Gan , Po-Wei Huang , Elies Gil-Fuster , Patrick Rebentrost

We develop a generic method to compute the dynamics induced by quenches in completely connected quantum systems. These models are expected to provide a mean-field description at least of the short time dynamics of finite dimensional system.…

Quantum Gases · Physics 2014-05-13 Bruno Sciolla , Giulio Biroli

We study a dephasing channel with memory, described by a Hamiltonian model in which the system-environment interaction is described by a stochastic process. We propose a useful way to describe the channel uses correlations. Moreover, we…

Quantum Physics · Physics 2009-09-02 A. D'Arrigo , G. Benenti , G. Falci

Advancements in the implementation of quantum hardware have enabled the acquisition of data that are intractable for emulation with classical computers. The integration of classical machine learning (ML) algorithms with these data holds…

Quantum Physics · Physics 2025-01-22 Gyungmin Cho , Dohun Kim

Virtually all aspects of many-body atomic physics are challenging: experiments are technically demanding, datasets have become enormous, and the memory and CPU requirements for classical simulation of generic quantum systems often scale…

Quantum Gases · Physics 2026-05-19 I. B. Spielman amd J. P. Zwolak

We review the model of two qubits coupled locally to an environment which consists of nonlocally correlated field modes [Phys. Rev.Lett. 108, 210402 (2012)]. We derive the correct expressions for the reduced dynamics of the two-qubit system…

Quantum Physics · Physics 2013-10-30 Steffen Wißmann , Heinz-Peter Breuer

The experimental realisation of large scale many-body systems has seen immense progress in recent years, rendering full tomography tools for state identification inefficient, especially for continuous systems. In order to work with these…

Quantum neural networks form one pillar of the emergent field of quantum machine learning. Here, quantum generalisations of classical networks realizing associative memories - capable of retrieving patterns, or memories, from corrupted…

Quantum Physics · Physics 2025-03-28 Lukas Bödeker , Eliana Fiorelli , Markus Müller