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We consider the propagation of Gaussian beams in a waveguide with gain and loss in the paraxial approximation governed by the Schr\"odinger equation. We derive equations of motion for the beam in the semiclassical limit that are valid when…

Quantum Physics · Physics 2016-01-29 Eva-Maria Graefe , Alexander Rush , Roman Schubert

Gaussian beams describe the amplitude and phase of rays and are widely used to model acoustic propagation. This paper describes four new results in the theory of Gaussian beams. (1) A new version of the \v{C}erven\'y equations for the…

Mathematical Physics · Physics 2018-04-12 Steven Thomas Smith

The posterior variance of Gaussian processes is a valuable measure of the learning error which is exploited in various applications such as safe reinforcement learning and control design. However, suitable analysis of the posterior variance…

Machine Learning · Computer Science 2019-06-05 Armin Lederer , Jonas Umlauft , Sandra Hirche

The reflection time, during which a particle is in the classically forbidden region, is described by the trajectory representation for reflection by a semi-infinite rectangular barrier. The Schr\"odinger wave function has microstates for…

Quantum Physics · Physics 2008-02-03 Edward R. Floyd

A local convergence rate is established for a Gauss orthogonal collocation method applied to optimal control problems with control constraints. If the Hamiltonian possesses a strong convexity property, then the theory yields convergence for…

Numerical Analysis · Mathematics 2018-09-17 William W. Hager , Jun Liu , Subhashree Mohapatra , Anil V. Rao , Xiang-Sheng Wang

We consider a class of linear ill-posed inverse problems arising from inversion of a compact operator with singular values which decay exponentially to zero. We adopt a Bayesian approach, assuming a Gaussian prior on the unknown function.…

Statistics Theory · Mathematics 2013-12-09 Sergios Agapiou , Andrew M. Stuart , Yuan-Xiang Zhang

We consider the generalized Forchheimer flows for slightly compressible fluids. Using Muskat's and Ward's general form of Forchheimer equations, we describe the fluid dynamics by a nonlinear degenerate parabolic equation for the density. We…

Numerical Analysis · Mathematics 2015-08-04 Thinh Kieu

We consider the Vlasov-Maxwell equations with one spatial direction and two momenta, one in the longitudinal direction and one in the transverse direction. By solving the Jacobi identity, we derive reduced Hamiltonian fluid models for the…

Chaotic Dynamics · Physics 2021-10-04 Cristel Chandre , Bradley A. Shadwick

In this paper, we derive tail approximations of integrals of exponential functions of Gaussian random fields with varying mean functions and approximations of the associated point processes. This study is motivated naturally by multiple…

Statistics Theory · Mathematics 2011-12-05 Jingchen Liu , Gongjun Xu

Inverse problems, i.e., estimating parameters of physical models from experimental data, are ubiquitous in science and engineering. The Bayesian formulation is the gold standard because it alleviates ill-posedness issues and quantifies…

Machine Learning · Statistics 2024-05-28 Sharmila Karumuri , Ilias Bilionis

Gaussian beams are often used in optical systems. The fundamental Gaussian TEM00 mode is the most common of the Gaussian modes present in various optical devices, systems and equipment. Within an optical system, it is common that this…

General Physics · Physics 2016-05-16 Tariq Shamim Khwaja , Syed Azer Reza

Inference for GP models with non-Gaussian noises is computationally expensive when dealing with large datasets. Many recent inference methods approximate the posterior distribution with a simpler distribution defined on a small number of…

Machine Learning · Computer Science 2018-09-11 Linfeng Liu , Liping Liu

This study leverages the basic insight that the gradient-flow equation associated with the relative Boltzmann entropy, in relation to a Gaussian reference measure within the Hellinger-Kantorovich (HK) geometry, preserves the class of…

Analysis of PDEs · Mathematics 2025-04-30 Matthias Liero , Alexander Mielke , Oliver Tse , Jia-Jie Zhu

Gaussian Quadrature is a well known technique for numerical integration. Recently Gaussian quadrature with respect to discrete measures corresponding to finite sums have found some new interest. In this paper we apply these ideas to…

Numerical Analysis · Mathematics 2007-05-23 Hartmut Monien

We investigate the scintillation index of multi-wavelength Gaussian optical beams propagating through a turbulent optical channel. We consider a turbulent environment ranging from weak to strong, with a specific focus on the weak turbulent…

Optics · Physics 2025-12-02 Shideh Tayebnaimi , Kamran Kiasaleh

We study the inverse problem of recovering a semilinear diffusion term $a(t,\lambda)$ as well as a quasilinear convection term $\mathcal B(t,x,\lambda,\xi)$ in a nonlinear parabolic equation $$\partial_tu-\textrm{div}(a(t,u) \nabla…

Analysis of PDEs · Mathematics 2023-05-10 Ali Feizmohammadi , Yavar Kian , Gunther Uhlmann

Under the introduction of any interface in its trajectory, an optical beam experiences polarization-dependent deflections in the longitudinal and transverse directions with respect to the plane of incidence. The physics of such optical beam…

We prove a central limit theorem for the winding number of a directed polymer on a cylinder, which is equivalent with proving the Gaussian fluctuations of the endpoint of the directed polymer in a spatial periodic environment.

Probability · Mathematics 2023-01-18 Yu Gu , Tomasz Komorowski

This paper addresses the question of when projections of a high-dimensional random vector are approximately Gaussian. This problem has been studied previously in the context of high-dimensional data analysis, where the focus is on…

Information Theory · Computer Science 2017-01-02 Galen Reeves

Topic models are Bayesian models that are frequently used to capture the latent structure of certain corpora of documents or images. Each data element in such a corpus (for instance each item in a collection of scientific articles) is…

Machine Learning · Statistics 2018-02-05 Behrooz Ghorbani , Hamid Javadi , Andrea Montanari
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