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Perturbative expansions in physical applications are generically divergent, and their physical content can be studied using Borel analysis. Given just a finite number of terms of such an expansion, this input data can be analyzed in…

High Energy Physics - Theory · Physics 2021-10-22 Ovidiu Costin , Gerald V. Dunne

A new analytical approximation function is proposed to accurately fit the solution of a fractional differential equation of order one-half, whose nonhomogeneous term is defined by a modified Bessel function of the first kind. The exact…

General Mathematics · Mathematics 2025-12-03 Byron Droguett , Pablo Martin , Eduardo Rojas , Jorge Olivares

Regression problems with bounded continuous outcomes frequently arise in real-world statistical and machine learning applications, such as the analysis of rates and proportions. A central challenge in this setting is predicting a response…

Machine Learning · Statistics 2025-07-21 Zhanli Wu , Fabrizio Leisen , F. Javier Rubio

Precision matrix estimation is a fundamental topic in multivariate statistics and modern machine learning. This paper proposes an adversarially perturbed precision matrix estimation framework, motivated by recent developments in adversarial…

Methodology · Statistics 2026-03-25 Yiling Xie

We developed a conformal map technique to analyze the attenuation of edge modes propagating along imperfect boundaries. In systems where the potential energy exhibits conformal invariance, the conformal transformation can straighten the…

Strongly Correlated Electrons · Physics 2024-12-12 Grigor Adamyan

We discuss conformal manifolds for conformal field theories with boundaries or defects. Using conformal perturbation theory we derive constraints on coefficients appearing in the boundary operator product expansion and three-point functions…

High Energy Physics - Theory · Physics 2018-08-15 Andreas Karch , Yoshiki Sato

Functional error estimates are well-established tools for a posteriori error estimation and related adaptive mesh-refinement for the finite element method (FEM). The present work proposes a first functional error estimate for the boundary…

Numerical Analysis · Mathematics 2020-10-29 Stefan Kurz , Dirk Pauly , Dirk Praetorius , Sergey Repin , Daniel Sebastian

This paper is concerned with the derivation of conforming and non-conforming functional a posteriori error estimates for elliptic boundary value problems in exterior domains. These estimates provide computable and guaranteed upper and lower…

Numerical Analysis · Mathematics 2014-07-22 Olli Mali , Alexey Muzalevskiy , Dirk Pauly

The conformal mapping of the Borel plane can be utilized for the analytic continuation of the Borel transform to the entire positive real semi-axis and is thus helpful in the resummation of divergent perturbation series in quantum field…

High Energy Physics - Phenomenology · Physics 2008-11-26 U. D. Jentschura , G. Soff

The recent work [Kurz et al., Numer. Math., 147 (2021)] proposed functional a posteriori error estimates for boundary element methods (BEMs) together with a related adaptive mesh-refinement strategy. Unlike most a posteriori BEM error…

Numerical Analysis · Mathematics 2025-06-13 Alexander Freiszlinger , Dirk Pauly , Dirk Praetorius

Numerical simulations of crystal defects are necessarily restricted to finite computational domains, supplying artificial boundary conditions that emulate the effect of embedding the defect in an effectively infinite crystalline…

Numerical Analysis · Mathematics 2016-05-25 V. Ehrlacher , C. Ortner , A. V. Shapeev

Conformal field theories play a central role in theoretical physics with many applications ranging from condensed matter to string theory. The conformal bootstrap studies conformal field theories using mathematical consistency conditions…

High Energy Physics - Theory · Physics 2021-04-09 Johan Henriksson

The paper is devoted to a detailed analysis of nonlocal error bounds for nonconvex piecewise affine functions. We both improve some existing results on error bounds for such functions and present completely new necessary and/or sufficient…

Optimization and Control · Mathematics 2024-04-23 M. V. Dolgopolik

Conformance checking techniques allow us to quantify the correspondence of a process's execution, captured in event data, w.r.t., a reference process model. In this context, alignments have proven to be useful for calculating conformance…

Software Engineering · Computer Science 2021-03-25 Mohammadreza Fani Sani , Martin Kabierski , Sebastiaan J. van Zelst , Wil M. P. van der Aalst

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 study numerical computation of conformal invariants of domains in the complex plane. In particular, we provide an algorithm for computing the conformal capacity of a condenser. The algorithm applies for wide kind of geometries: domains…

Complex Variables · Mathematics 2020-08-19 Mohamed M S Nasser , Matti Vuorinen

Measurement error is an important problem that has not been very well studied in the context of Functional Data Analysis. To the best of our knowledge, there are no existing methods that address the presence of functional measurement errors…

Statistics Theory · Mathematics 2018-09-19 Sneha Jadhav , Shuangge Ma

Many major works in social science employ matching to make causal conclusions, but different matches on the same data may produce different treatment effect estimates, even when they achieve similar balance or minimize the same loss…

Applications · Statistics 2023-03-23 Marco Morucci , Cynthia Rudin

In Constraint Programming, constraints are usually represented as predicates allowing or forbidding combinations of values. However, some algorithms exploit a finer representation: error functions. Their usage comes with a price though: it…

Artificial Intelligence · Computer Science 2023-03-09 Florian Richoux , Jean-François Baffier

To derive the auto-covariance function from a sampled and time-limited signal or the cross-covariance function from two such signals, the mean values must be estimated and removed from the signals. If no a priori information about the…

Methodology · Statistics 2023-03-21 Holger Nobach
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