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The dynamics of strongly interacting many-body quantum systems are notoriously complex and difficult to simulate. A new theory, generalized hydrodynamics (GHD), promises to efficiently accomplish such simulations for nearly-integrable…

Quantum Gases · Physics 2021-09-09 Neel Malvania , Yicheng Zhang , Yuan Le , Jerome Dubail , Marcos Rigol , David S. Weiss

We study a class of Markov chains that describe reversible stochastic dynamics of a large class of disordered mean field models at low temperatures. Our main purpose is to give a precise relation between the metastable time scales in the…

Disordered Systems and Neural Networks · Physics 2016-08-31 A. Bovier , M. Eckhoff , V. Gayrard , M. Klein

Recent studies unveiled the Fickian yet non-Gaussian (FNG) dynamics of many soft matter systems and suggested this phenomenon as a general characteristic of the diffusion in complex fluids. In particular, it was shown that the distribution…

Soft Condensed Matter · Physics 2018-10-24 Alejandro Cuetos , Neftalí Morillo , Alessandro Patti

We apply the theory of Quantum Generalized Hydrodynamics (QGHD) introduced in [Phys. Rev. Lett. 124, 140603 (2020)] to derive asymptotically exact results for the density fluctuations and the entanglement entropy of a one-dimensional…

Quantum Gases · Physics 2021-12-21 Paola Ruggiero , Pasquale Calabrese , Benjamin Doyon , Jérôme Dubail

We study the normal approximation of functionals of Poisson measures having the form of a finite sum of multiple integrals. When the integrands are nonnegative, our results yield necessary and sufficient conditions for central limit…

Probability · Mathematics 2012-06-26 Raphael Lachieze-Rey , Giovanni Peccati

We investigate barycenters of Gaussian process laws in adapted Wasserstein space. The adapted Wasserstein distance refines classical optimal transport by enforcing compatibility of transport plans with the temporal flow of information, and…

Probability · Mathematics 2026-04-27 Francesco Mattesini , Johannes Wiesel

Using the adiabatic connection, we formulate the free energy in terms of the correlation function of a fictitious system, $h_{\lambda}({\bf r},{\bf r}')$, where $\lambda$ determines the interaction strength. To obtain $h_{\lambda}({\bf…

Statistical Mechanics · Physics 2016-06-15 Derek Frydel , Manman Ma

The recently proposed non-Gaussian Mat\'{e}rn random field models, generated through Stochastic Partial differential equations (SPDEs), are extended by considering the class of Generalized Hyperbolic processes as noise forcings. The models…

Applications · Statistics 2013-07-25 David Bolin , Jonas Wallin

In estimation theory, the Kushner equation provides the evolution of the probability density of the state of a dynamical system given continuous-time observations. Building upon our recent work, we propose a new way to approximate the…

Machine Learning · Statistics 2023-10-04 Marc Lambert , Silvère Bonnabel , Francis Bach

With the highly anticipated results from the Beam Energy Scan II program at RHIC being recently revealed, an understanding of particle-number fluctuations and their significance as a potential signature of a possible QCD critical point is…

This paper discusses the fractional diffusion equation forced by a tempered fractional Gaussian noise. The fractional diffusion equation governs the probability density function of the subordinated killed Brownian motion. The tempered…

Numerical Analysis · Mathematics 2020-07-14 Xing Liu , Weihua Deng

Gaussian mixture distributions are commonly employed to represent general probability distributions. Despite the importance of using Gaussian mixtures for uncertainty estimation, the entropy of a Gaussian mixture cannot be calculated…

Machine Learning · Statistics 2025-01-23 Takashi Furuya , Hiroyuki Kusumoto , Koichi Taniguchi , Naoya Kanno , Kazuma Suetake

We study the conformation and dynamics of a single polymer chain that is pulled by a constant force applied at its one end with the other end free. Such a situation is relevant to the growing technology of manipulating individual…

Soft Condensed Matter · Physics 2015-06-04 Takahiro Sakaue , Takuya Saito , Hirofumi Wada

The recently proposed fluctuation relation in unfolding forces [Phys. Rev. E ${\bf 84}$, $060101$(R) $(2011)$] is re-examined taking into account the explicit time dependence of the force distribution. The stretching of a tethered Rouse…

Statistical Mechanics · Physics 2014-05-06 Anoop Varghese , Satyavani Vemparala , R. Rajesh

We study fluctuations of mean-field interacting particle systems around their McKean--Vlasov limit. Our main result provides a uniform-in-time quantitative central limit theorem for the fluctuation process, with convergence rate of order…

Probability · Mathematics 2026-05-06 Solesne Bourguin , Konstantinos Spiliopoulos

The recent proof of quasi-Gaussianity for the 2D stochastic Navier--Stokes (SNS) equations by Coe, Hairer, and Tolomeo establishes that the system's unique invariant measure is equivalent (mutually absolutely continuous) to the Gaussian…

Dynamical Systems · Mathematics 2025-11-27 Boumediene Hamzi , Houman Owhadi

Stokesian Dynamics (SD) is a numerical framework used for simulating hydrodynamic interactions in particle suspensions at low Reynolds number. It combines far-field approximations with near-field lubrication corrections, offering a balance…

Fluid Dynamics · Physics 2025-03-21 Kim William Torre , Joost de Graaf

A central aim of statistical mechanics is to establish connections between a system's microscopic fluctuations and its macroscopic response to a perturbation. For non-equilibrium transport properties, this amounts to establishing Green-Kubo…

Statistical Mechanics · Physics 2024-11-28 Anna T. Bui , Stephen J. Cox

We present a reduced basis technique for long-time integration of parametrized incompressible turbulent flows. The new contributions are threefold. First, we propose a constrained Galerkin formulation that corrects the standard Galerkin…

Numerical Analysis · Mathematics 2017-10-11 Lambert Fick , Yvon Maday , Anthony T Patera , Tommaso Taddei

We present a Gaussian Process (GP) approach (Gaussian Process Hydrodynamics, GPH) for approximating the solution of the Euler and Navier-Stokes equations. As in Smoothed Particle Hydrodynamics (SPH), GPH is a Lagrangian particle-based…

Fluid Dynamics · Physics 2023-01-31 Houman Owhadi