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I review the development of numerical evolution codes for general relativity based upon the characteristic initial value problem. Progress is traced from the early stage of 1D feasibility studies to 2D axisymmetric codes that accurately…

General Relativity and Quantum Cosmology · Physics 2016-11-23 Jeffrey Winicour

We extend the formalism for the calculation of the relativistic corrections to the Sunyaev-Zel'dovich effect for clusters of galaxies and include the multiple scattering effects in the isotropic approximation. We present the results of the…

Astrophysics · Physics 2009-11-06 Naoki Itoh , Youhei Kawana , Satoshi Nozawa , Yasuharu Kohyama

Stochastic evolution equations with compensated Poisson noise are considered in the variational approach with monotone and coercive coefficients. Here the Poisson noise is assumed to be time-homogeneous with $\sigma$-finite intensity…

Probability · Mathematics 2022-04-20 Sima Mehri , Erfan Salavati , Bijan Z. Zangeneh

We are interested in the study of models describing the evolution of a polymorphic population with mutation and selection in the specific scales of the biological framework of adaptive dynamics. The population size is assumed to be large…

Probability · Mathematics 2011-12-05 Nicolas Champagnat , Sylvie Méléard

In this survey, we provide an in-depth exposition of our recent results on the well-posedness theory for stochastic evolution equations, employing maximal regularity techniques. The core of our approach is an abstract notion of critical…

Probability · Mathematics 2025-08-28 Antonio Agresti , Mark Veraar

We introduce two abstract theorems that reduce a variety of complex exponential distributional approximation problems to the construction of couplings. These are applied to obtain new rates of convergence with respect to the Wasserstein and…

Probability · Mathematics 2011-03-15 Erol A. Peköz , Adrian Röllin

Estimating time-varying correlation matrices is challenging because existing methods may adapt slowly to structural changes, impose insufficient regularization, or produce diffuse posterior uncertainty. In moderate dimensions, an additional…

Methodology · Statistics 2026-05-11 Daniel Andrew Coulson , David S. Matteson , Martin T. Wells

In this paper we present a theoretical background of a coupled analytical-numerical approach to model a crack propagation process in two-dimensional bounded domains. The goal of the coupled analytical-numerical approach is to obtain the…

Complex Variables · Mathematics 2021-08-11 Dmitrii Legatiuk , Daniel Weisz-Patrault

The development, assessment, and comparison of randomized search algorithms heavily rely on benchmarking. Regarding the domain of constrained optimization, the number of currently available benchmark environments bears no relation to the…

Neural and Evolutionary Computing · Computer Science 2018-07-27 Michael Hellwig , Hans-Georg Beyer

We study in general the time-evolution of correlation functions in a extended quantum system after the quench of a parameter in the hamiltonian. We show that correlation functions in d dimensions can be extracted using methods of boundary…

Statistical Mechanics · Physics 2011-02-16 Pasquale Calabrese , John Cardy

Phenomenological models of the dipole cross section that enters in the description of for instance deep inelastic scattering at very high energies have had considerable success in describing the available small-x data in both the saturation…

High Energy Physics - Phenomenology · Physics 2008-11-26 Daniel Boer , Andre Utermann , Erik Wessels

We investigate the Balitsky-Kovchegov (BK) equation for D=3 space-time dimensions, corresponding to one transverse coordinate, and we show that it can be solved analytically. The explicit solutions are found in the linear approximation and…

High Energy Physics - Phenomenology · Physics 2009-11-10 J. Bartels , V. S. Fadin , L. N. Lipatov

The new model for the QCD analytic running coupling, proposed recently, is extended to the timelike region. This running coupling naturally arises under unification of the analytic approach to QCD and the renormalization group (RG)…

High Energy Physics - Phenomenology · Physics 2007-05-23 A. V. Nesterenko

We explore the applicability of a stochastic time-evolution algorithm based on probabilistic angle interpolation. To simplify the pre-processing of the algorithm, we take the continuous-time limit, thereby explicitly eliminating Trotter…

Quantum Physics · Physics 2026-04-06 Tomoya Hayata , Yuta Kikuchi

We discuss the optimal Markovian coupling before an exponential time of the Kolmogorov diffusion, and a class of related stochastic control problems in which the aim is to hit the origin before an exponential time. We provide a scaling…

Probability · Mathematics 2007-05-23 Kalvis M. Jansons , Paul D. Metcalfe

Quantum mechanics is an inherently linear theory. However, collective effects in many body quantum systems can give rise to effectively nonlinear dynamics. In the present work, we analyze whether and to what extent such nonlinear effects…

Quantum Physics · Physics 2022-11-23 Sebastian Deffner

The nonlinear Balitsky-Kovchegov equation at small x is solved numerically, incorporating impact parameter dependence. Confinement is modeled by including effective gluon mass in the dipole evolution kernel, which regulates the splitting of…

High Energy Physics - Phenomenology · Physics 2015-05-28 Jeffrey Berger , Anna M. Stasto

A pathwise large deviation result is proved for the pure jump models of $k$-nary interacting particle system introduced by Kolokoltsov that generalize classical Boltzmann's collision model, Smoluchovski's coagulation model and many others.…

Probability · Mathematics 2021-06-09 Wen Sun

There is now overwhelming observational evidence that our Universe is accelerating in its expansion. I discuss how modified gravitational models can provide an explanation for this observed late-time cosmic acceleration. We consider…

Astrophysics · Physics 2008-11-26 Damien A. Easson

Generative models frequently suffer miscalibration, wherein statistics of the sampling distribution, such as the fraction of generations in a given class, deviate from desired values. We frame calibration as a constrained optimization…

Machine Learning · Statistics 2026-05-29 Henry D. Smith , Nathaniel L. Diamant , Brian L. Trippe