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Diffusion approximation provides weak approximation for stochastic gradient descent algorithms in a finite time horizon. In this paper, we introduce new tools motivated by the backward error analysis of numerical stochastic differential…

Machine Learning · Computer Science 2019-09-05 Yuanyuan Feng , Tingran Gao , Lei Li , Jian-Guo Liu , Yulong Lu

A major challenge in extracting information from current and upcoming surveys of cosmological Large-Scale Structure (LSS) is the limited availability of computationally expensive high-fidelity simulations. We introduce calibrated Neural…

Cosmology and Nongalactic Astrophysics · Physics 2026-04-24 He Jia

This paper introduces a variational approximation framework using direct optimization of what is known as the {\it scale invariant Alpha-Beta divergence} (sAB divergence). This new objective encompasses most variational objectives that use…

Machine Learning · Statistics 2018-05-22 Jean-Baptiste Regli , Ricardo Silva

This article presents a new distance for measuring shape dissimilarity between objects. Recent publications introduced the use of eigenvalues of the Laplace operator as compact shape descriptors. Here, we revisit the eigenvalues to define a…

Computer Vision and Pattern Recognition · Computer Science 2015-03-20 Ender Konukoglu , Ben Glocker , Antonio Criminisi , Kilian M. Pohl

In this study, we analyze the bound-state energy spectrum of quark-antiquark systems using the semiclassical WKB approximation. We consider the Cornell potential, which combines a linear confinement term with a Coulombic interaction, and…

High Energy Physics - Phenomenology · Physics 2025-08-11 Bhaskar Jyoti Hazarika , Tanmay Dev

We discuss the role of the proximity force approximation in deriving limits to the existence of Yukawian forces - predicted in the submillimeter range by many unification models - from Casimir force experiments using the sphere-plane…

Quantum Physics · Physics 2010-03-30 Diego A. R. Dalvit , Roberto Onofrio

In this paper, we investigate the properties of the Sliced Wasserstein Distance (SW) when employed as an objective functional. The SW metric has gained significant interest in the optimal transport and machine learning literature, due to…

Machine Learning · Statistics 2025-08-21 Christophe Vauthier , Anna Korba , Quentin Mérigot

A discrete version of the WKB method is developed and applied to calculate the tunnel splittings between classically degenerate states of spin Hamiltonians. The results for particular model problems are in complete accord with those…

Condensed Matter · Physics 2009-10-31 Anupam Garg

As we all known that non-relativistic or semi-relativistic constituent quark models can describe a large number of the meson sand baryon properties with surprising accuracy. In this work, we studied Killingbeck potential by using WKB…

High Energy Physics - Phenomenology · Physics 2022-05-03 Lhamo chosto , Ya-rong Wang , Zhi-bin Gao , Cheng-qun Pang , Hao Chen , Yu-Long Kang

We develop a method to compute the Casimir effect for arbitrary geometries. The method is based on the string-inspired worldline approach to quantum field theory and its numerical realization with Monte-Carlo techniques. Concentrating on…

High Energy Physics - Theory · Physics 2009-11-10 Holger Gies , Kurt Langfeld , Laurent Moyaerts

Using the variational formula for operator product coefficients a method for perturbative calculation of the short-distance expansion of the Spin-Spin correlation function in the two dimensional Ising model is presented. Results of explicit…

High Energy Physics - Theory · Physics 2009-10-22 B. Mikhak , A. M. Zarkesh

Recently, Kr\"uger and Vlugt [Phys. Rev. E 97, 051301(R) (2018)] have proposed a method to approximate an improper integral $\int_0^\infty \text{d}r\, F(r)$, where $F(r)$ is a given oscillatory function, by a finite-range integral $\int_0^L…

Computational Physics · Physics 2018-12-04 Andrés Santos

The higher-order WKB Mathematica code for computing quasinormal modes, whose accuracy was significantly enhanced through extensions to higher orders and, in particular, through the use of Pad\'e resummation, has been widely employed in…

General Relativity and Quantum Cosmology · Physics 2026-03-25 Roman A. Konoplya , Jerzy Matyjasek , Alexander Zhidenko

The n-vicinities method for approximate calculations of the partition function of a spin system was proposed previously. The equation of state was obtained in the most general form. In the present publication these results are adapted to…

Disordered Systems and Neural Networks · Physics 2016-06-30 Boris Kryzhanovsky , Leonid Litinskii

The Laplace approximation has been one of the workhorses of Bayesian inference. It often delivers good approximations in practice despite the fact that it does not strictly take into account where the volume of posterior density lies.…

Machine Learning · Statistics 2022-03-02 Nikolaos Gianniotis

The aim of this paper is to discuss both higher-order asymptotic expansions and skewed approximations for the Bayesian Discrepancy Measure for testing precise statistical hypotheses. In particular, we derive results on third-order…

Methodology · Statistics 2025-05-02 Elena Bortolato , Francesco Bertolino , Monica Musio , Laura Ventura

The paper presents the derivation of the asymptotic behavior of $\nu$-zeros of the modified Bessel function of imaginary order $K_{{\rm i}\nu}(z)$. This derivation is based on the quasiclassical treatment of the exponential potential on the…

Mathematical Physics · Physics 2021-06-11 Yuri Krynytskyi , Andrij Rovenchak

We study the accuracy of several alternative semiclassical methods by computing analytically the energy levels for many large classes of exactly solvable shape invariant potentials. For these potentials, the ground state energies computed…

Quantum Physics · Physics 2009-09-01 Marina Hruska , Wai-Yee Keung , Uday Sukhatme

Estimation and inference in dynamic discrete choice models often relies on approximation to lower the computational burden of dynamic programming. Unfortunately, the use of approximation can impart substantial bias in estimation and results…

Econometrics · Economics 2020-10-23 Ben Deaner

Quenched chiral perturbation theory is extended to include heavy-light mesons. Non-analytic corrections to the decay constants, Isgur-Wise function and masses and mixing of heavy mesons are then computed. The results are used to estimate…

High Energy Physics - Phenomenology · Physics 2010-11-01 Michael J. Booth
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