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For any near-threshold asymptotic regime and for any Feynman diagram (involving loop and/or phase space integrals), a systematic prescription for explicitly constructing all-logs, all-powers (all-twists) expansions in perfectly factorized…

High Energy Physics - Phenomenology · Physics 2009-10-30 Fyodor V. Tkachov

We compute exact second-order asymptotics for the cost of an optimal solution to the entropic optimal transport problem in the continuous-to-discrete, or semi-discrete, setting. In contrast to the discrete-discrete or continuous-continuous…

Optimization and Control · Mathematics 2022-03-17 Jason M. Altschuler , Jonathan Niles-Weed , Austin J. Stromme

We construct an asymptotic approximation to the solution of a transmission problem for a body containing a region occupied by many small inclusions. The cluster of inclusions is characterised by two small parameters that determine the…

Analysis of PDEs · Mathematics 2016-07-22 Michael Nieves

The self-consistent expansion (SCE) is a powerful technique for obtaining perturbative solutions to problems in statistical physics but it suffers from a subtle problem - too much freedom! The SCE can be used to generate an enormous number…

Statistical Mechanics · Physics 2024-07-12 Chanania Steinbock , Eytan Katzav

We consider a family of parallel methods for constrained optimization based on projected gradient descents along individual coordinate directions. In the case of polyhedral feasible sets, local convergence towards a regular solution occurs…

Optimization and Control · Mathematics 2015-09-18 Olivier Bilenne

In this contribution, we address the numerical solutions of high-order asymptotic equivalent partial differential equations with the results of a lattice Boltzmann scheme for an inhomogeneous advection problem in one spatial dimension. We…

Numerical Analysis · Mathematics 2024-12-11 Bruce M Boghosian , François Dubois , Pierre Lallemand

We study the problem of nonparametric estimation of density functions with a product form on the domain $\triangle=\{( x_1, \ldots, x_d)\in \mathbb{R}^d, 0\leq x_1\leq \dots \leq x_d \leq 1\}$. Such densities appear in the random truncation…

Statistics Theory · Mathematics 2016-04-22 Cristina Butucea , Jean-François Delmas , Anne Dutfoy , Richard Fischer

By application of the theory for second-order linear differential equations with two turning points developed in [Olver F.W.J., Philos. Trans. Roy. Soc. London Ser. A 278 (1975), 137-174], uniform asymptotic approximations are obtained in…

Classical Analysis and ODEs · Mathematics 2015-11-25 Karen Ogilvie , Adri B. Olde Daalhuis

We establish a connection between the $L^{q}$-spectrum of a Borel measure $\nu $ on the $m$-dimensional unit cube and the approximation order of Kolmogorov diameters of the unit sphere with respect to Sobolev norms in $L_{\nu }^{p}$. This…

Functional Analysis · Mathematics 2024-01-05 Marc Kesseböhmer , Aljoscha Niemann

We consider a singularly perturbed second order elliptic system in the whole space. The coefficients of the systems fast oscillate and depend both of slow and fast variables. We obtain the homogenized operator and in the uniform norm sense…

Mathematical Physics · Physics 2007-05-23 Denis Borisov

This paper develops an asymptotic expansion technique in momentum space for stochastic filtering. It is shown that Fourier transformation combined with a polynomial-function approximation of the nonlinear terms gives a closed recursive…

Computational Finance · Quantitative Finance 2013-03-26 Masaaki Fujii

Recently, Mboup, Join and Fliess [27], [28] introduced non-asymptotic integer order differentiators by using an algebraic parametric estimation method [7], [8]. In this paper, in order to obtain non-asymptotic fractional order…

Numerical Analysis · Mathematics 2012-07-03 Dayan Liu , Olivier Gibaru , Wilfrid Perruquetti

The adaptive perturbation chooses a non-standard decomposition. The Hamiltonian becomes a sum of solvable and perturbation parts. We calculate the spectrum using the adaptive perturbation method at the leading-order to compare to numerical…

Quantum Physics · Physics 2021-07-08 Chen-Te Ma

In stochastic optimization, a common tool to deal sequentially with large sample is to consider the well-known stochastic gradient algorithm. Nevertheless, since the stepsequence is the same for each direction, this can lead to bad results…

Optimization and Control · Mathematics 2023-03-03 Antoine Godichon-Baggioni , Pierre Tarrago

In this work we explore the fidelity of numerical approximations to the analytic spectra of hyperbolic partial differential equation systems with variable coefficients. We are particularly interested in the ability of discrete methods to…

Numerical Analysis · Mathematics 2025-08-12 Brittany A. Erickson

We develop symbolic methods of asymptotic approximations for solutions of linear ordinary differential equations and use to them stabilize numerical calculations. Our method follows classical analysis for first-order systems and…

Symbolic Computation · Computer Science 2011-10-12 Christopher J. Winfield

We consider the supersymmetric approach to gaussian disordered systems like the random bond Ising model and Dirac model with random mass and random potential. These models appeared in particular in the study of the integer quantum Hall…

High Energy Physics - Theory · Physics 2009-10-30 Z. Maassarani , D. Serban

A simple ansatz is suggested for the structure of threshold resummation of the momentum space physical evolution kernels (`physical anomalous dimensions') at all orders in (1-x), taking as examples Deep Inelastic Scattering (F_2(x, Q^2) and…

High Energy Physics - Phenomenology · Physics 2007-11-13 Georges Grunberg

We study nonparametric covariance function estimation for functional data observed with noise at discrete locations on a $d$-dimensional domain. Estimating the covariance function from discretely observed data is a challenging nonparametric…

Statistics Theory · Mathematics 2026-03-25 Yoshikazu Terada , Atsutomo Yara

In this paper, we propose and analyse a family of generalised stochastic composite mirror descent algorithms. With adaptive step sizes, the proposed algorithms converge without requiring prior knowledge of the problem. Combined with an…

Optimization and Control · Mathematics 2022-11-22 Weijia Shao , Fikret Sivrikaya , Sahin Albayrak
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