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Gaussian Processes (GPs) are expressive models for capturing signal statistics and expressing prediction uncertainty. As a result, the robotics community has gathered interest in leveraging these methods for inference, planning, and…

Robotics · Computer Science 2023-08-29 Francesco Crocetti , Jeffrey Mao , Alessandro Saviolo , Gabriele Costante , Giuseppe Loianno

The wireless channel of 5G communications will have unique characteristics that can not be fully apprehended by the traditional fading models. For instance, the wireless channel may often be dominated by a finite number of specular…

Information Theory · Computer Science 2018-10-15 Young Jin Chun

The semiclassical approach introduced by Sachdev and collaborators proved to be extremely successful in the study of quantum quenches in massive field theories, both in homogeneous and inhomogeneous settings. While conceptually very simple,…

Statistical Mechanics · Physics 2019-07-11 Bruno Bertini , Lorenzo Piroli , Márton Kormos

We derive semiclassical expressions for spectra, weighted by matrix elements of a Gaussian observable, relevant to a range of molecular and mesoscopic systems. We apply the formalism to the particular example of the resonant tunneling diode…

chao-dyn · Physics 2009-10-31 D. S. Saraga , T. S. Monteiro

We develop generalized polynomial chaos (gPC) based stochastic Galerkin (SG) methods for a class of highly oscillatory transport equations that arise in semiclassical modeling of non-adiabatic quantum dynamics. These models contain…

Numerical Analysis · Mathematics 2017-04-05 Nicolas Crouseilles , Shi Jin , Mohammed Lemou , Liu Liu

In this paper we discuss some aspects of the theory of wave packets. We consider a popular non-covariant Gaussian model used in various applications and show that it predicts too slow a longitudinal dispersion rate for relativistic…

Quantum Physics · Physics 2015-06-17 D. V. Naumov

As a model for the semiclassical analysis of quantum-mechanical systems with both potentials and boundary conditions, we construct the WKB propagator for a linear potential sloping away from an impenetrable boundary. First, we find all…

Quantum Physics · Physics 2017-03-08 T. A. Zapata , S. A. Fulling

We propose a principled algorithm for robust Bayesian filtering and smoothing in nonlinear stochastic dynamic systems when both the transition function and the measurement function are described by non-parametric Gaussian process (GP)…

Systems and Control · Computer Science 2012-08-13 Marc Peter Deisenroth , Ryan Turner , Marco F. Huber , Uwe D. Hanebeck , Carl Edward Rasmussen

"Generalized Hydrodynamics" (GHD) stands for a model that describes one-dimensional \textit{integrable} systems in quantum physics, such as ultra-cold atoms or spin chains. Mathematically, GHD corresponds to nonlinear equations of kinetic…

Computational Physics · Physics 2023-11-21 Frederik Møller , Nicolas Besse , Igor E. Mazets , Hans-Peter Stimming , Norbert J. Mauser

This study develops a theoretical framework for modeling acoustic pulse propagation in a non-ideal shallow-water waveguide. We derive an {\epsilon}-pseudodifferential operator ({\epsilon}-PDO) formulation from the general three-dimensional…

Mathematical Physics · Physics 2025-12-16 Aleksandr Kaplun , Boris Katsnelson

Generalized hydrodynamics (GHD) is a large-scale theory for the dynamics of many-body integrable systems. It consists of an infinite set of conservation laws for quasi-particles traveling with effective ("dressed") velocities that depend on…

Statistical Mechanics · Physics 2018-01-19 Benjamin Doyon , Herbert Spohn , Takato Yoshimura

In the study of subdiffusive wave-packet spreading in disordered Klein-Gordon (KG) nonlinear lattices, a central open question is whether the motion continues to be chaotic despite decreasing densities, or tends to become quasi-periodic as…

Chaotic Dynamics · Physics 2017-10-11 Chris G. Antonopoulos , Charalampos Skokos , Tassos Bountis , Sergej Flach

We propose a semiclassical framework for solving open quantum dynamics in driven-dissipative spin systems. Our method consists of generalized spin-wave approximations tailored to describing quantum trajectories unravelled from the master…

Quantum Physics · Physics 2026-04-24 Zejian Li , Anna Delmonte , Rosario Fazio

In this paper, we develop a model to describe the generalized wave-particle instability in a quasi-neutral plasma. We analyze the quasi-linear diffusion equation for particles by expressing an arbitrary unstable and resonant wave mode as a…

Space Physics · Physics 2020-10-22 Seong-Yeop Jeong , Daniel Verscharen , Robert T. Wicks , Andrew N. Fazakerley

The Gaussian process is a powerful and flexible technique for interpolating spatiotemporal data, especially with its ability to capture complex trends and uncertainty from the input signal. This chapter describes Gaussian processes as an…

Machine Learning · Statistics 2021-10-11 Kien Nguyen , John Krumm , Cyrus Shahabi

In the realm of statistical learning, the increasing volume of accessible data and increasing model complexity necessitate robust methodologies. This paper explores two branches of robust Bayesian methods in response to this trend. The…

Methodology · Statistics 2024-12-02 Masahiro Tanaka

We study reaction-diffusion particle systems with several interaction mechanisms. As the number of particles tends to infinity, the system admits a mean-field limit describing the bulk behaviour. We focus on determining the propagation…

Probability · Mathematics 2026-04-21 Matthieu Jonckheere , Seva Shneer

We study the semiclassical propagation of coherent states in $d$ dimensions, which in general involves complex classical dynamics. Several simple approximations are derived that depend only on real classical trajectories, among them the…

Quantum Physics · Physics 2007-12-04 M. Novaes , M. A. M. de Aguiar

Uncertainty quantification plays a key role in the development of autonomous systems, decision-making, and tracking over wireless sensor networks (WSNs). However, there is a need of providing uncertainty confidence bounds, especially for…

Machine Learning · Statistics 2024-09-13 Xingchi Liu , Lyudmila Mihaylova , Jemin George , Tien Pham

In this paper, we report results for the wave packet dynamics in a class of quasiperiodic chains consisting of two types of weakly coupled clusters. The dynamics are studied by means of the return probability and the mean square…

Mesoscale and Nanoscale Physics · Physics 2010-01-29 Stefanie Thiem , Michael Schreiber , Uwe Grimm