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Computer models are used as a way to explore complex physical systems. Stationary Gaussian process emulators, with their accompanying uncertainty quantification, are popular surrogates for computer models. However, many computer models are…

Methodology · Statistics 2024-11-25 Faezeh Yazdi , Derek Bingham , Daniel Williamson

We develop an algebraic approach to studying the spectral properties of the stationary Schr\"odinger equation in one dimension based on its high order conditional symmetries. This approach makes it possible to obtain in explicit form…

High Energy Physics - Theory · Physics 2009-10-30 R. Z. Zhdanov

We propose a numerical method to solve the Wigner equation in quantum systems of spinless, non-relativistic particles. The method uses a spectral decomposition into $L^2(\mathbb{R}^d)$ basis functions in momentum-space to obtain a system of…

Quantum Physics · Physics 2015-12-09 Oliver Furtmaier , Sauro Succi , Miller Mendoza

We develop two novel stochastic variance-reduction methods to approximate solutions of a class of nonmonotone [generalized] equations. Our algorithms leverage a new combination of ideas from the forward-reflected-backward splitting method…

Optimization and Control · Mathematics 2025-05-30 Quoc Tran-Dinh

We consider a quantization of relativistic wave equations which allows to treat quantum fields together with interacting particles at a finite time. We discuss also a dissipative interaction with the environment. We introduce a stochastic…

High Energy Physics - Theory · Physics 2007-05-23 Z. Haba

This paper presents a general approach to linear stochastic processes driven by various random noises. Mathematically, such processes are described by linear stochastic differential equations of arbitrary order (the simplest non-trivial…

Condensed Matter · Physics 2009-10-28 Alon Drory

The optimistic gradient method is useful in addressing minimax optimization problems. Motivated by the observation that the conventional stochastic version suffers from the need for a large batch size on the order of…

Machine Learning · Computer Science 2024-01-29 Haoyuan Cai , Sulaiman A. Alghunaim , Ali H. Sayed

The solutions of Hamiltonian equations are known to describe the underlying phase space of a mechanical system. In this article, we propose a novel spatio-temporal model using a strategic modification of the Hamiltonian equations,…

Methodology · Statistics 2026-02-17 Satyaki Mazumder , Sayantan Banerjee , Sourabh Bhattacharya

We derive sufficient conditions for the convex and monotonic g-stochastic ordering of diffusion processes under nonlinear g-expectations and g-evaluations. Our approach relies on comparison results for forward-backward stochastic…

Probability · Mathematics 2022-04-13 Sel Ly , Nicolas Privault

Parameter estimation for non-stationary stochastic differential equations (SDE) with an arbitrary nonlinear drift, and nonlinear diffusion is accomplished in combination with a non-parametric clustering methodology. Such a model-based…

Optimization and Control · Mathematics 2021-09-07 Vyacheslav Boyko , Sebastian Krumscheid , Nikki Vercauteren

Inspired by the idea of mimicking the measurement on a quantum system through a decoherence process to target specific eigenstates based on Born's law, i.e. the hiearchy of probabilities instead of the hierarchy of eigenvalues, we transform…

Quantum Physics · Physics 2017-09-06 Oliver Furtmaier , Miller Mendoza

This work deals with the one-dimensional Stefan problem with a general time-dependent boundary condition at the fixed boundary. Stochastic solutions are obtained using discrete random walks, and the results are compared with analytic…

Analysis of PDEs · Mathematics 2023-02-06 M. Ogren

We construct an explicit one-to-one correspondence between non-relativistic stochastic processes and solutions of the Schrodinger equation and between relativistic stochastic processes and solutions of the Klein-Gordon equation. The…

Quantum Physics · Physics 2023-06-21 Folkert Kuipers

We show how to compute the generating function of the self-avoiding polygons on a lattice by using the statistical mechanics Schwinger-Dyson equations for the correlation functions of the $N$-vector spin model on that lattice.

Condensed Matter · Physics 2007-05-23 P. Butera , M. Comi

We prescribe a formulation of the particle production with real-time Stochastic Quantization. To construct the retarded and the time-ordered propagators we decompose the stochastic variables into positive- and negative-energy parts. In this…

High Energy Physics - Theory · Physics 2014-09-02 Kenji Fukushima , Tomoya Hayata

We present a quantum algorithm based on repeated measurement to solve initial-value problems for nonlinear ordinary differential equations (ODEs), which may be generated from partial differential equations in plasma physics. We map a…

Quantum Physics · Physics 2025-04-30 Joseph Andress , Alexander Engel , Yuan Shi , Scott Parker

A stochastic field theory approach is applied to a coarse-grained polymer model that will enable studies of polymer behavior under non-equilibrium conditions. This article is focused on the validation of the new model in comparison to…

Soft Condensed Matter · Physics 2024-03-04 Shangren Zhu , Patrick T. Underhill

The general idea of a stochastic gauge representation is introduced and compared with more traditional phase-space expansions, like the Wigner expansion. Stochastic gauges can be used to obtain an infinite class of positive-definite…

Soft Condensed Matter · Physics 2009-11-10 P. D. Drummond , P. Deuar

We show that non-relativistic Quantum Mechanics can be faithfully represented in terms of a classical diffusion process endowed with a gauge symmetry of group Z_4. The representation is based on a quantization condition for the realized…

Probability · Mathematics 2007-11-23 Claudio Albanese

This paper presents theoretical advances in the application of the Stochastic Partial Differential Equation (SPDE) approach in geostatistics. We show a general approach to construct stationary models related to a wide class of linear SPDEs,…

Statistics Theory · Mathematics 2018-07-30 Ricardo Carrizo Vergara , Denis Allard , Nicolas Desassis
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