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A Lie system is a non-autonomous system of ordinary differential equations describing the integral curves of a $t$-dependent vector field taking values in a finite-dimensional Lie algebra of vector fields. Lie systems have been generalised…

Mathematical Physics · Physics 2023-04-25 J. F. Cariñena , J. de Lucas , C. Sardón

The outcome statistics of an informationally complete quantum measurement for a system in a given state can be used to evaluate the ensemble expectation of any linear operator in the same state, by averaging a function of the outcomes that…

Quantum Physics · Physics 2009-12-21 G. M. D'Ariano , D. F. Magnani , P. Perinotti

Importance Sampling (IS), an effective variance reduction strategy in Monte Carlo (MC) simulation, is frequently utilized for Bayesian inference and other statistical challenges. Quasi-Monte Carlo (QMC) replaces the random samples in MC…

Numerical Analysis · Mathematics 2024-03-19 Zhijian He , Hejin Wang , Xiaoqun Wang

Motivated by discrete kinetic models for non-cooperative molecular motors on periodic tracks, we consider random walks (also not Markov) on quasi one dimensional (1d) lattices, obtained by gluing several copies of a fundamental graph in a…

Statistical Mechanics · Physics 2017-04-26 Alessandra Faggionato , Vittoria Silvestri

A unified approach has been developed to study nonlinear dynamics of a 1D lattice of particles with long-range power-law interaction. A classical case is treated in the framework of the generalization of the well-known Frenkel-Kontorova…

Exactly Solvable and Integrable Systems · Physics 2009-11-11 N. Laskin , G. Zaslavsky

We propose a stability analysis method for sampled-data switched linear systems with quantization. The available information to the controller is limited: the quantized state and switching signal at each sampling time. Switching between…

Systems and Control · Computer Science 2014-08-13 Masashi Wakaiki , Yutaka Yamamoto

A central problem in uncertainty quantification is how to characterize the impact that our incomplete knowledge about models has on the predictions we make from them. This question naturally lends itself to a probabilistic formulation, by…

Statistical Mechanics · Physics 2018-09-03 Giovanni Dematteis , Tobias Grafke , Eric Vanden-Eijnden

Path integrals describing quantum many-body systems can be calculated with Monte Carlo sampling techniques, but average quantities are often subject to signal-to-noise ratios that degrade exponentially with time. A phase-reweighting…

High Energy Physics - Lattice · Physics 2017-07-12 Michael L. Wagman , Martin J. Savage

This dissertation studies the statistics and modeling of a quantum system probed by a coherent laser field. We focus on an ensemble of qubits dispersively coupled to a traveling wave light field. The first research topic explores the…

Quantum Physics · Physics 2013-01-29 Robert L. Cook

In recent years there has been significant interest in the concepts of synthetic dimensions, where one couples the internal degrees of freedom of a particle to form higher-dimensional lattices in lower-dimensional physical structures. For…

Optics · Physics 2019-07-24 Avik Dutt , Momchil Minkov , Qian Lin , Luqi Yuan , David A. B. Miller , Shanhui Fan

Machine-learned normalizing flows can be used in the context of lattice quantum field theory to generate statistically correlated ensembles of lattice gauge fields at different action parameters. This work demonstrates how these…

We present a theory of quantum work statistics in generic chaotic, disordered Fermi liquid systems within a driven random matrix formalism. By extending P. W. Anderson's orthogonality determinant formula to compute quantum work…

Mesoscale and Nanoscale Physics · Physics 2023-03-16 András Grabarits , Márton Kormos , Izabella Lovas , Gergely Zaránd

A general technique for the periodic orbit quantization of systems with near-integrable to mixed regular-chaotic dynamics is introduced. A small set of periodic orbits is sufficient for the construction of the semiclassical recurrence…

chao-dyn · Physics 2009-10-31 J. Main , G. Wunner

Simulating nonlinear classical dynamics on a quantum computer is an inherently challenging task due to the linear operator formulation of quantum mechanics. In this work, we provide a systematic approach to alleviate this difficulty by…

Quantum walks, both discrete (coined) and continuous time, form the basis of several quantum algorithms and have been used to model processes such as transport in spin chains and quantum chemistry. The enhanced spreading and mixing…

Quantum Physics · Physics 2010-12-10 Godfrey Leung , Paul Knott , Joe Bailey , Viv Kendon

In this lecture we review recent lattice QCD studies of the statistical properties of the eigenvalues of the QCD Dirac operator. We find that the fluctuations of the smallest Dirac eigenvalues are described by chiral Random Matrix Theories…

High Energy Physics - Lattice · Physics 2009-10-31 J. J. M. Verbaarschot

We investigate universal features of measurement-and-feedback control of quantum chaotic dynamics by examining the quantum Arnold cat map, a paradigmatic model of quantum chaos. Inspired by probabilistic control of classical chaos, our…

Quantum Physics · Physics 2026-02-26 Andrew A. Allocca , Devesh K. Verma , Sriram Ganeshan , Justin H. Wilson

Quantum trajectories are Markov processes modeling the evolution of a quantum system subjected to repeated independent measurements. Inspired by the theory of random products of matrices, it has been shown that these Markov processes admit…

Probability · Mathematics 2025-03-25 Tristan Benoist , Arnaud Hautecoeur , Clément Pellegrini

A straightforward analytical scheme is proposed for computing the long-time, asymptotic mean velocity and dispersivity (effective diffusivity) of a particle undergoing a discrete biased random walk on a periodic lattice amongst an array of…

Soft Condensed Matter · Physics 2009-11-10 Kevin D. Dorfman

Linear mixed-effects models are widely used in analyzing clustered or repeated measures data. We propose a quasi-likelihood approach for estimation and inference of the unknown parameters in linear mixed-effects models with high-dimensional…

Methodology · Statistics 2021-03-10 Sai Li , Tony T. Cai , Hongzhe Li