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The inverse conductivity problem aims at determining the unknown conductivity inside a bounded domain from boundary measurements. In practical applications, algorithms based on minimizing a regularized residual functional subject to PDE…

Numerical Analysis · Mathematics 2025-10-02 Lefu Cai , Zhixin Liu , Minghui Song , Xianchao Wang

Modern data analysis depends increasingly on estimating models via flexible high-dimensional or nonparametric machine learning methods, where the identification of structural parameters is often challenging and untestable. In linear…

Statistics Theory · Mathematics 2026-01-21 Andrii Babii , Jean-Pierre Florens

In this paper, we propose an easy-to-implement residual-based specification testing procedure for detecting structural changes in factor models, which is powerful against both smooth and abrupt structural changes with unknown break dates.…

Econometrics · Economics 2025-01-22 Bin Peng , Liangjun Su , Yayi Yan

We study the influence of structural obstacles in a disordered environment on the size and shape characteristics of long flexible polymer macromolecules. We use the model of self-avoiding random walks on diluted regular lattices at the…

Soft Condensed Matter · Physics 2010-11-22 Viktoria Blavatska , Wolfhard Janke

Within the differential equation method for multiloop calculations, we examine the systems irreducible to $\epsilon$-form. We argue that for many cases of such systems it is possible to obtain nontrivial quadratic constraints on the…

High Energy Physics - Phenomenology · Physics 2018-11-14 Roman N. Lee

An operator basis of an effective theory with a heavy particle, subject to external gauge fields, is spanned by a particular kind of neutral scalar primary of the nonrelativistic conformal group. We calculate the characters that can be used…

High Energy Physics - Phenomenology · Physics 2018-08-15 Andrew Kobach , Sridip Pal

In this article, we give a geometric description for any invertible operator on a finite dimensional inner--product space. With the aid of such a description, we are able to decompose any given conformal transformation as a product of…

General Mathematics · Mathematics 2013-09-24 Srikanth K. V. , Raj Bhawan Yadav

Copulas are essential tools in statistics and probability theory, enabling the study of the dependence structure between random variables independently of their marginal distributions. Among the various types of copulas, Ratio-Type Copulas…

Statistics Theory · Mathematics 2025-05-21 Ziad Adwan , Nicola Sottocornola

The pressure function $P(A, s)$ plays a fundamental role in the calculation of the dimension of "typical" self-affine sets, where $A=(A_1,\ldots, A_k)$ is the family of linear mappings in the corresponding generating iterated function…

Dynamical Systems · Mathematics 2015-11-06 De-Jun Feng , Pablo Shmerkin

Program behavior may depend on parameters, which are either configured before compilation time, or provided at run-time, e.g., by sensors or other input devices. Parametric program analysis explores how different parameter settings may…

Programming Languages · Computer Science 2014-06-23 Thomas M. Gawlitza , Martin D. Schwarz , Helmut Seidl

In this paper we give a general family of conformal invariants associated to bordered Riemann surfaces endowed with boundary parametrizations, or equivalently compact surfaces endowed with conformal maps. Each invariant is specified by a…

Differential Geometry · Mathematics 2026-05-13 Eric Schippers , Wolfgang Staubach

A nonconforming $P_2$ finite element is constructed by enriching the conforming $P_2$ finite element space with seven $P_2$ nonconforming bubble functions (out of fifteen such bubble functions on each tetrahedron). This spacial…

Numerical Analysis · Mathematics 2024-08-21 Shangyou Zhang

Over the past decade, characterizing the exact asymptotic risk of regularized estimators in high-dimensional regression has emerged as a popular line of work. This literature considers the proportional asymptotics framework, where the…

Statistics Theory · Mathematics 2024-01-02 Samriddha Lahiry , Pragya Sur

In this work we launch a systematic theory of superconformal blocks for four-point functions of arbitrary supermultiplets. Our results apply to a large class of superconformal field theories including 4-dimensional models with any number…

High Energy Physics - Theory · Physics 2020-02-19 Ilija Buric , Volker Schomerus , Evgeny Sobko

We study optimal design problems where the design corresponds to a coefficient in the principal part of the state equation. The state equation, in addition, is parameter dependent, and we allow it to change type in the limit of this…

Optimization and Control · Mathematics 2024-12-09 Tadele Mengesha , Abner J. Salgado , Joshua M. Siktar

The paper is devoted to the study of the unconditional extremal problem for a fractional linear integral functional defined on a set of probability distributions. In contrast to results proved earlier, the integrands of the integral…

Optimization and Control · Mathematics 2019-06-14 Peter Shnurkov , Kseniia Adamova

Robust global stabilization of nonlinear systems by observer-based feedback controllers is a challenging task. This article investigates the problem of designing observer-based stabilizing controllers for incrementally quadratic nonlinear…

Optimization and Control · Mathematics 2020-07-17 Xiangru Xu , Behcet Acikmese , Martin J. Corless

Independence testing plays a central role in statistical and causal inference from observational data. Standard independence tests assume that the data samples are independent and identically distributed (i.i.d.) but that assumption is…

Machine Learning · Statistics 2022-07-04 Ragib Ahsan , Zahra Fatemi , David Arbour , Elena Zheleva

We present a general formalism for the calculation of finite-width contributions to the differential production cross sections of unstable particles at hadron colliders. In this formalism, which employs an effective-theory description of…

High Energy Physics - Phenomenology · Physics 2015-06-15 P. Falgari , A. S. Papanastasiou , A. Signer

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