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200 papers

Fundamental trade-off relations, such as quantum speed limit and quantum thermodynamic uncertainty relation, describe the performance limits of quantum systems by imposing that improvements in speed or precision necessitate a substantial…

Quantum Physics · Physics 2025-09-30 Hayato Yunoki , Yoshihiko Hasegawa

The method of tempered transitions was proposed by Neal (1996) for tackling the difficulties arising when using Markov chain Monte Carlo to sample from multimodal distributions. In common with methods such as simulated tempering and…

Computation · Statistics 2012-09-11 Gundula Behrens , Nial Friel , Merrilee Hurn

In the strong coupling limit, $n$-point functions in lattice QCD with staggered fermions can be rewritten exactly as sums over constrained configurations of monomers, dimers, and baryon loops covering the spacetime lattice. Worm algorithms…

High Energy Physics - Lattice · Physics 2017-02-01 Philippe de Forcrand , Paul Romatschke , Wolfgang Unger , Helvio Vairinhos

We study the relation between the dynamical critical behavior and the kinematics of stochastic multigrid algorithms. The scale dependence of acceptance rates for nonlocal Metropolis updates is analyzed with the help of an approximation…

High Energy Physics - Lattice · Physics 2007-05-23 Martin Grabenstein

Standard sampling algorithms for lattice QCD suffer from topology freezing (or critical slowing down) when approaching the continuum limit, thus leading to poor sampling of the distinct topological sectors. I will present a modified…

High Energy Physics - Lattice · Physics 2021-11-11 David Albandea , Pilar Hernández , Alberto Ramos , Fernando Romero-López

Nonperturbative inequalities constrain the thermodynamic pressure of Quantum Chromodynamics (QCD) with its phase-quenched version, a Sign-Problem-free theory amenable to lattice treatment. In the perturbative regime with a small QCD…

High Energy Physics - Phenomenology · Physics 2024-12-18 Pablo Navarrete , Risto Paatelainen , Kaapo Seppänen

The glass transition of supercooled fluids is a particular challenge for computer simulation, because the (longest) relaxation times increase by about 15 decades upon approaching the transition temperature T_g. Brute-force molecular…

Statistical Mechanics · Physics 2007-05-23 Kurt Binder , Jörg Baschnagel , Walter Kob , Wolfgang Paul

After developing an appropriate iteration procedure for the determination of the parameters, the method of simulated tempering has been successfully applied to the 2D Ising spin glass. The reduction of the slowing down is comparable to that…

Condensed Matter · Physics 2009-10-22 Werner Kerler , Peter Rehberg

Controlled Lagrangian and matching techniques are developed for the stabilization of relative equilibria and equilibria of discrete mechanical systems with symmetry as well as broken symmetry. Interesting new phenomena arise in the…

Optimization and Control · Mathematics 2007-05-23 Anthony M. Bloch , Melvin Leok , Jerrold E. Marsden , Dmitry V. Zenkov

We discuss the tempering Monte Carlo method, and its critical slowing down in the $3d$ Ising model. We show that at $T_c$ the tempering does not change the critical slowing down exponent $z$. We also discuss the exponential slowing down for…

Condensed Matter · Physics 2009-10-22 L. A. Fernandez , E. Marinari , J. J. Ruiz-Lorenzo

The scalability of massively parallel algorithms is a fundamental question in computer science. We study the scalability and the efficiency of a conservative massively parallel algorithm for discrete-event simulations where the discrete…

Statistical Mechanics · Physics 2007-05-23 G. Korniss , M. A. Novotny , Z. Toroczkai , P. A. Rikvold

Massively parallel hardware (GPUs) and long sequence data have made parallel algorithms essential for machine learning at scale. Yet dynamical systems, like recurrent neural networks and Markov chain Monte Carlo, were thought to suffer from…

Numerical Analysis · Mathematics 2026-03-18 Xavier Gonzalez

Quantum subspace diagonalization (QSD) algorithms have emerged as a competitive family of algorithms that avoid many of the optimization pitfalls associated with parameterized quantum circuit algorithms. While the vast majority of the QSD…

Quantum Physics · Physics 2022-10-19 Cristian L. Cortes , A. Eugene DePrince , Stephen K. Gray

We investigate the melting behavior of two-dimensional colloidal crystals stabilized by a core-softened potential featuring two competing interaction length scales. Using molecular dynamics simulations, we analyze three polymorphic solid…

Soft Condensed Matter · Physics 2025-07-21 Thiago Puccinelli , Alexandre V. Ilha , José Rafael Bordin

A new class of exclusion type processes acting in continuum with synchronous updating is introduced and studied. Ergodic averages of particle velocities are obtained and their connections to other statistical quantities, in particular to…

Dynamical Systems · Mathematics 2015-05-13 Michael Blank

We present simulation results for the dynamics of a schematic model based on the frustration-limited domain picture of glass-forming liquids. These results are compared with approximate theoretical predictions analogous to those commonly…

Statistical Mechanics · Physics 2009-11-10 Phillip L. Geissler , David R. Reichman

This paper presents an efficient parallel approximation scheme for a new class of min-max problems. The algorithm is derived from the matrix multiplicative weights update method and can be used to find near-optimal strategies for…

Quantum Physics · Physics 2015-03-17 Gus Gutoski , Xiaodi Wu

This study developed the theory of nonequilibrium thermodynamics for populations of low-temperature-differential (LTD) Stirling engines weakly-coupled in a general class of networks to clarify the effects of synchronous and asynchronous…

Statistical Mechanics · Physics 2025-02-26 Songhao Yin , Hiroshi Kori , Yuki Izumida

We present a new training methodology for transformers using a multilevel, layer-parallel approach. Through a neural ODE formulation of transformers, our application of a multilevel parallel-in-time algorithm for the forward and…

Machine Learning · Computer Science 2026-01-27 Shuai Jiang , Marc Salvadó-Benasco , Eric C. Cyr , Alena Kopaničáková , Rolf Krause , Jacob B. Schroder

Existing theory of momentum assumes that gradients arrive at every parameter at a roughly constant rate, an assumption violated in practice by heavy-tailed data distributions and modern architectures. We theoretically analyze the dynamics…

Machine Learning · Statistics 2026-05-29 Katie Everett , Elliot Paquette