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We consider the statistical properties of eigenstates of the time-evolution operator in chaotic many-body quantum systems. Our focus is on correlations between eigenstates that are specific to spatially extended systems and that…

Quantum Physics · Physics 2024-08-21 Dominik Hahn , David J. Luitz , J. T. Chalker

Polynomial Chaos Expansions represent a powerful tool to simulate stochastic models of dynamical systems. Yet, deriving the expansion's coefficients for complex systems might require a significant and non-trivial manipulation of the model,…

Computation · Statistics 2012-11-13 Lorenzo Fagiano , Mustafa Khammash

Out-of-time-order correlators (OTOCs) have become established as a tool to characterise quantum information dynamics and thermalisation in interacting quantum many-body systems. It was recently argued that the expected exponential growth of…

Statistical Mechanics · Physics 2021-09-21 Marlon Brenes , Silvia Pappalardi , Mark T. Mitchison , John Goold , Alessandro Silva

We derive the Eigenstate Thermalization Hypothesis (ETH) from a random matrix Hamiltonian by extending the model introduced by J. M. Deutsch [Phys. Rev. A 43, 2046 (1991)]. We approximate the coupling between a subsystem and a many-body…

Statistical Mechanics · Physics 2018-09-26 Charlie Nation , Diego Porras

A new algorithm named EXPected Similarity Estimation (EXPoSE) was recently proposed to solve the problem of large-scale anomaly detection. It is a non-parametric and distribution free kernel method based on the Hilbert space embedding of…

Machine Learning · Computer Science 2015-11-18 Markus Schneider , Wolfgang Ertel , Günther Palm

We introduce a classical algorithm to approximate the free energy of local, translation-invariant, one-dimensional quantum systems in the thermodynamic limit of infinite chain size. While the ground state problem (i.e., the free energy at…

Quantum Physics · Physics 2024-07-04 Hamza Fawzi , Omar Fawzi , Samuel O. Scalet

Reinforcement learning algorithms commonly seek to optimize policies for solving one particular task. How should we explore an unknown dynamical system such that the estimated model globally approximates the dynamics and allows us to solve…

Machine Learning · Computer Science 2023-10-31 Bhavya Sukhija , Lenart Treven , Cansu Sancaktar , Sebastian Blaes , Stelian Coros , Andreas Krause

Predicting observables in equilibrium states is a central yet notoriously hard question in quantum many-body systems. In the physically relevant thermodynamic limit, certain mathematical formulations of this task have even been shown to…

Quantum Physics · Physics 2025-08-15 Hamza Fawzi , Omar Fawzi , Samuel O. Scalet

Tobasco et al. [Physics Letters A, 382:382-386, 2018; see https://doi.org/10.1016/j.physleta.2017.12.023] recently suggested that trajectories of ODE systems that optimize the infinite-time average of a certain observable can be localized…

Partially Observable Markov Decision Processes (POMDPs) are a natural and general model in reinforcement learning that take into account the agent's uncertainty about its current state. In the literature on POMDPs, it is customary to assume…

Machine Learning · Computer Science 2022-03-24 Noah Golowich , Ankur Moitra , Dhruv Rohatgi

An efficient numerical method is developed using the matrix product formalism for computing the properties at finite energy densities in one-dimensional (1D) many-body localized (MBL) systems. Arguing that any efficient (possibly quantum)…

Disordered Systems and Neural Networks · Physics 2015-08-20 Yichen Huang

Quantum dynamics can be analyzed via the structure of energy eigenstates. However, in the many-body setting, preparing eigenstates associated with finite temperatures requires time scaling exponentially with system size. In this work we…

Quantum Physics · Physics 2024-07-11 Samuel J. Garratt , Soonwon Choi

The eigenstate thermalization hypothesis (ETH) provides a powerful framework for understanding thermalization in isolated quantum many-body systems, yet a complete and conceptually transparent derivation has remained elusive. In this work,…

Statistical Mechanics · Physics 2025-12-23 Yucheng Wang

Surrogate modeling of costly mathematical models representing physical systems is challenging since it is typically not possible to create a large experimental design. Thus, it is beneficial to constrain the approximation to adhere to the…

Machine Learning · Computer Science 2023-09-06 Lukáš Novák , Himanshu Sharma , Michael D. Shields

The Eigenstate Thermalization Hypothesis (ETH) is a framework for discussing thermal behavior originating from chaotic dynamics in isolated many-body quantum systems. The PXP model, where certain states do not thermalize, has been compared…

Quantum Physics · Physics 2025-03-17 Maanav Srihari , Anil Shaji

We present the new Orthogonal Polynomials Approximation Algorithm (OPAA), a parallelizable algorithm that estimates probability distributions using functional analytic approach: first, it finds a smooth functional estimate of the…

Machine Learning · Computer Science 2024-01-23 Lilian W. Bialokozowicz

We propose a method of estimating ergodization time of a chaotic many-particle system by monitoring equilibrium noise before and after time reversal of dynamics (Loschmidt echo). The ergodization time is defined as the characteristic time…

Quantum Physics · Physics 2019-10-10 Andrei E. Tarkhov , Boris V. Fine

The eigenstate thermalization hypothesis (ETH) insists that for nonintegrable systems each energy eigenstate accurately gives microcanonical expectation values for a class of observables. As a mechanism for ETH to hold, we show that the…

Statistical Mechanics · Physics 2018-05-15 Takaaki Monnai

We introduce an orbital-optimized double-hybrid (DH) scheme using the optimized-effective-potential (OEP) method. The orbitals are optimized using a local potential corresponding to the complete exchange-correlation energy expression…

Local Operator Entanglement (LOE) has emerged an indicator of quantum chaos in many-body systems. Numerical studies have shown that, in chaotic systems, LOE grows linearly in time and displays a volume-law behavior at late times, scaling…

Quantum Physics · Physics 2026-03-27 Guilherme Ilário Correr , John Goold , Marco Cattaneo
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