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Related papers: Simulating the Generalized Gibbs Ensemble (GGE): a…

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We consider the Generalized Gibbs Ensemble (GGE) in the context of global quantum quenches in XXZ Heisenberg spin chains. Embedding the GGE into the Quantum Transfer Matrix formalism we develop an iterative procedure to fix the…

Statistical Mechanics · Physics 2015-06-15 Balázs Pozsgay

The generalized Gibbs ensemble (GGE) was introduced ten years ago to describe observables in isolated integrable quantum systems after equilibration. Since then, the GGE has been demonstrated to be a powerful tool to predict the outcome of…

Statistical Mechanics · Physics 2016-06-29 Lev Vidmar , Marcos Rigol

In this paper we present two new numerical methods for studying thermodynamic quantities of integrable models. As an example of the effectiveness of these two approaches, results from numerical solutions of all sets of Bethe ansatz…

Strongly Correlated Electrons · Physics 2015-06-24 Shi-Jian Gu , N. M. R. Peres , You-Quan Li

The non-equilibrium steady states of integrable models are believed to be described by the Generalized Gibbs Ensemble (GGE), which involves all local and quasi-local conserved charges of the model. In this work we investigate integrable…

Statistical Mechanics · Physics 2020-03-04 György Z. Fehér , Balázs Pozsgay

We revisit the question of whether and how the steady states arising after non-equilibrium time evolution in integrable models (and in particular in the XXZ spin chain) can be described by the so-called Generalized Gibbs Ensemble (GGE). It…

Statistical Mechanics · Physics 2017-10-11 B. Pozsgay , E. Vernier , M. A. Werner

We reconsider the non-equilibrium dynamics of closed quantum systems. In particular we focus on the thermalization of integrable systems. Here we show how the generalized Gibbs Ensemble (GGE) can be constructed as the best approximation to…

Quantum Physics · Physics 2017-05-11 Dries Sels , Michiel Wouters

We propose a Gaussian ensemble as a description of the long-time dynamics of isolated quantum integrable systems. Our approach extends the Generalized Gibbs Ensemble (GGE) by incorporating fluctuations of integrals of motion. It is…

Statistical Mechanics · Physics 2017-05-24 Hyungwon Kim , Anatoli Polkovnikov , Emil A. Yuzbashyan

Classical Markov Chain Monte Carlo methods have been essential for simulating statistical physical systems and have proven well applicable to other systems with many degrees of freedom. Motivated by the statistical physics origins, Chen,…

Quantum Physics · Physics 2026-01-26 András Gilyén , Chi-Fang Chen , Joao F. Doriguello , Michael J. Kastoryano

The Generalized Gibbs Ensemble (GGE) is relevant to understand the thermalization of quantum systems with an infinite set of conserved charges. In this work, we analyze the GGE partition function of 2D Conformal Field Theories (CFTs) with a…

High Energy Physics - Theory · Physics 2021-06-02 Fábio Novaes

We prove two statements about the long time dynamics of integrable Hamiltonian systems. In classical mechanics, we prove the microcanonical version of the Generalized Gibbs Ensemble (GGE) by mapping it to a known theorem and then extend it…

Statistical Mechanics · Physics 2016-04-12 Emil A. Yuzbashyan

In complex systems with many degrees of freedom such as spin glass and biomolecular systems, conventional simulations in canonical ensemble suffer from the quasi-ergodicity problem. A simulation in generalized ensemble performs a random…

Statistical Mechanics · Physics 2008-06-24 Y. Okamoto

In integrable many-particle systems, it is widely believed that the stationary state reached at late times after a quantum quench can be described by a generalized Gibbs ensemble (GGE) constructed from their extensive number of conserved…

In non-interacting isolated quantum systems out of equilibrium, local subsystems typically relax to non-thermal stationary states. In the standard framework, information on the rest of the system is discarded, and such states are described…

Quantum Physics · Physics 2023-03-23 Maxime Lucas , Lorenzo Piroli , Jacopo De Nardis , Andrea De Luca

We present a novel Monte Carlo algorithm which enhances equilibrization of low-temperature simulations and allows sampling of configurations over a large range of energies. The method is based on a non-Boltzmann probability weight factor…

Condensed Matter · Physics 2009-10-30 Ulrich H. E. Hansmann , Yuko Okamoto

We investigate the impact of the boundary shape on the thermalization behavior of a confined system of classical hard disks at low packing fraction and thus in the gas regime. We use both analytical calculations and numerical simulations,…

Statistical Mechanics · Physics 2026-02-25 Francesco Caravelli , Marc D. Vuffray

A representation of Lattice Gauge Theories (LGT) suitable for simulations with tensor network state methods or with quantum computers requires a truncation of the Hilbert space to a finite dimensional approximation. In particular for U(1)…

High Energy Physics - Lattice · Physics 2025-12-19 Timo Jakobs , Marco Garofalo , Tobias Hartung , Karl Jansen , Paul Ludwig , Johann Ostmeyer , Simone Romiti , Carsten Urbach

We propose an exact summation method to compute thermodynamic observables in integrable quantum field theories. The key idea is to use the matrix-tree theorem to write the Gaudin determinants that appear in the cluster expansion as a sum…

High Energy Physics - Theory · Physics 2020-08-18 Dinh-Long Vu

We investigate the modular properties of Generalised Gibbs Ensembles (GGEs) in two dimensional conformal field theories. These are obtained by inserting higher spin charges in the expressions for the partition function of the theory. We…

High Energy Physics - Theory · Physics 2025-03-12 Max Downing , Faisal Karimi

Generative neural samplers offer a complementary approach to Monte Carlo methods for problems in statistical physics and quantum field theory. This work tests the ability of generative neural samplers to estimate observables for real-world…

Statistical Mechanics · Physics 2021-06-16 Johanna Vielhaben , Nils Strodthoff

Machine learning algorithms often take inspiration from established results and knowledge from statistical physics. A prototypical example is the Boltzmann machine algorithm for supervised learning, which utilizes knowledge of classical…

Statistical Mechanics · Physics 2018-12-04 Tatjana Puskarov , Axel Cortes Cubero
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