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In arXiv:1306.2914 a method for approximate solution of Sturm-Liouville equations and related spectral problems was presented based on the construction of the Delsarte transmutation operators. The problem of numerical approximation of…

Classical Analysis and ODEs · Mathematics 2016-09-06 Vladislav V. Kravchenko , Sergii M. Torba

Lie theory of continuous transformations provides a unified and powerful approach for handling differential equations. Unfortunately, any small perturbation of an equation usually destroys some important symmetries, and this reduces the…

Mathematical Physics · Physics 2021-08-05 Rosa Di Salvo , Matteo Gorgone , Francesco Oliveri

For a homogenization problem associated to a linear elliptic operator, we prove the existence of a distributional corrector and we find an approximation scheme for the homogenized coefficients. We also study the convergence rates in the…

Analysis of PDEs · Mathematics 2022-11-07 Willi Jäger , Antoine Tambue , Jean Louis Woukeng

This paper investigates the asymptotic convergence behavior of high-order proximal-point algorithms (HiPPA) toward global minimizers, extending the analysis beyond sublinear convergence rate results. Specifically, we consider the proximal…

Optimization and Control · Mathematics 2025-05-28 Masoud Ahookhosh , Alfredo Iusem , Alireza Kabgani , Felipe Lara

Neural oscillators, originating from second-order ordinary differential equations (ODEs), have demonstrated strong performance in stably learning causal mappings between long-term sequences or continuous temporal functions, as well as in…

Machine Learning · Computer Science 2026-04-21 Zifeng Huang , Konstantin M. Zuev , Yong Xia , Michael Beer

In this paper, by employing the asymptotic expansion method, we prove the existence and uniqueness of a smoothing solution for a time-dependent nonlinear singularly perturbed partial differential equation (PDE) with a small-scale parameter.…

Numerical Analysis · Mathematics 2022-10-11 Dmitrii Chaikovskii , Ye Zhang

In the asymptotic theory of quantum hypothesis testing, the minimal error probability of the first kind jumps sharply from zero to one when the error exponent of the second kind passes by the point of the relative entropy of the two states…

Quantum Physics · Physics 2014-02-28 Ke Li

An effective medium approach similar to the coherent potential approximation (CPA) in the theory of disordered alloys and to the DMFT has been extended to the renormalization group equations in the local potential approximation (LPA).…

Statistical Mechanics · Physics 2019-10-14 V. I. Tokar

Optimization on Riemannian manifolds widely arises in eigenvalue computation, density functional theory, Bose-Einstein condensates, low rank nearest correlation, image registration, and signal processing, etc. We propose an adaptive…

Optimization and Control · Mathematics 2017-08-08 Jiang Hu , Andre Milzarek , Zaiwen Wen , Yaxiang Yuan

Unitary best approximation to the exponential function on an interval on the imaginary axis has been introduced recently. In the present work two algorithms are considered to compute this best approximant: an algorithm based on rational…

Numerical Analysis · Mathematics 2025-04-15 Tobias Jawecki

The superiority of symplectic methods for stochastic Hamiltonian systems has been widely recognized, yet the probabilistic mechanism behind this superiority remains incompletely understood. This paper studies the superiority of symplectic…

Numerical Analysis · Mathematics 2025-05-29 Jialin Hong , Ge Liang , Derui Sheng

In this paper we establish a uniform $C^{2,\theta}$ estimate for level sets of stable solutions to the singularly perturbed Allen-Cahn equation in dimensions $ n\leq 10$ (which is optimal). The proof combines two ingredients: one is the…

Analysis of PDEs · Mathematics 2018-10-24 Kelei Wang , Juncheng Wei

This paper presents a saddlepoint approximation of the random-coding union bound of Polyanskiy et al. for i.i.d. random coding over discrete memoryless channels. The approximation is single-letter, and can thus be computed efficiently.…

Information Theory · Computer Science 2014-04-28 Jonathan Scarlett , Alfonso Martinez , Albert Guillén i Fàbregas

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 are concerned with the homogenization of second-order linear elliptic equations with random coefficient fields. For symmetric coefficient fields with only short-range correlations, quantified through a logarithmic Sobolev inequality for…

Analysis of PDEs · Mathematics 2016-11-08 Peter Bella , Benjamin Fehrman , Julian Fischer , Felix Otto

Nitsche's method is a standard device for weakly imposing Dirichlet boundary conditions, but for the stabilized nonsymmetric formulation the available $L^2$-error analysis for Poisson's equation still predicts a half-order loss, whereas…

Numerical Analysis · Mathematics 2026-04-21 Gang Chen , Chaoran Liu , Yangwen Zhang

We establish the asymptotic theory in quantile autoregression when the model parameter is specified with respect to moderate deviations from the unit boundary of the form (1 + c / k) with a convergence sequence that diverges at a rate…

Econometrics · Economics 2023-08-22 Christis Katsouris

In this paper, we investigate an optimal control problem with terminal stochastic linear complementarity constraints (SLCC), and its discrete approximation using the relaxation, the sample average approximation (SAA) and the implicit Euler…

Optimization and Control · Mathematics 2022-08-17 Jianfeng Luo , Xiaojun Chen

In the analysis of the $h$-version of the finite-element method (FEM), with fixed polynomial degree $p$, applied to the Helmholtz equation with wavenumber $k\gg 1$, the $\textit{asymptotic regime}$ is when $(hk)^p C_{\rm sol}$ is…

Numerical Analysis · Mathematics 2024-09-05 Jeffrey Galkowski , Euan A. Spence

This work proposes a universal and adaptive second-order method for minimizing second-order smooth, convex functions. Our algorithm achieves $O(\sigma / \sqrt{T})$ convergence when the oracle feedback is stochastic with variance $\sigma^2$,…

Optimization and Control · Mathematics 2022-12-13 Kimon Antonakopoulos , Ali Kavis , Volkan Cevher