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Self-similar sequence transformation is an original type of nonlinear sequence transformations allowing for defining effective limits of asymptotic sequences. The method of self-similar factor transformations is shown to be regular. This…

Statistical Mechanics · Physics 2022-01-28 V. I. Yukalov , E. P. Yukalova

The challenge to measure exposures regularly forces financial institutions into a choice between an overwhelming computational burden or oversimplification of risk. To resolve this unsettling dilemma, we systematically investigate replacing…

Computational Finance · Quantitative Finance 2025-07-15 Domagoj Demeterfi , Kathrin Glau , Linus Wunderlich

We use a semiclassical approximation to derive the partition function for an arbitrary potential in one-dimensional Quantum Statistical Mechanics, which we view as an example of finite temperature scalar Field Theory at a point. We rely on…

Quantum Physics · Physics 2009-10-31 C. A. A. de Carvalho , R. M. Cavalcanti

We first study subextensions of m-subharmonic functions in weighted energy classes with given boundary values. The results are used to approximate an m-subharmonic function in weighted energy classes with given boundary values by an…

Complex Variables · Mathematics 2025-06-11 Nguyen Van Phu

Finite metric spaces are the object of study in many data analysis problems. We examine the concept of weak isometry between finite metric spaces, in order to analyse properties of the spaces that are invariant under strictly increasing…

Metric Geometry · Mathematics 2020-05-08 Alessandro De Gregorio , Ulderico Fugacci , Facundo Memoli , Francesco Vaccarino

We study a class of self-adjoint operators defined on the direct sum of two Hilbert spaces: a finite dimensional one called sometimes a ``small subsystem'' and an infinite dimensional one -- a ``reservoir''. The operator, which we call a…

Mathematical Physics · Physics 2009-11-11 Jan Derezinski , Wojciech De Roeck

A weak measurement on a system is made by coupling a pointer weakly to the system and then measuring the position of the pointer. If the initial wavefunction for the pointer is real, the mean displacement of the pointer is proportional to…

Quantum Physics · Physics 2009-11-13 Graeme Mitchison

Starting from the five-loop renormalization-group expansions for the two-dimensional Euclidean scalar \phi^4 field theory (field-theoretical version of two-dimensional Ising model), pseudo-\epsilon expansions for the Wilson fixed point…

Statistical Mechanics · Physics 2014-11-17 A. I. Sokolov

This paper explores the well known approximation approach to decide weak bisimilarity of Basic Parallel Processes. We look into how different refinement functions can be used to prove weak bisimilarity decidable for certain subclasses. We…

Formal Languages and Automata Theory · Computer Science 2012-08-15 Piotr Hofman , Patrick Totzke

A continuous infinite system of point particles interacting via two-body strong superstable potential is considered in the framework of classical statistical mechanics. We define some kind of approximation of main quantities, which describe…

Mathematical Physics · Physics 2010-07-27 Alexei Rebenko , Maksym Tertychnyi

This paper provides convergence analysis for the approximation of a class of path-dependent functionals underlying a continuous stochastic process. In the first part, given a sequence of weak convergent processes, we provide a sufficient…

Probability · Mathematics 2013-07-22 Qingshuo Song , George Yin , Qing Zhang

We propose a new approach towards approximating the density-to-pair-density map based on copula theory from statistics. We extend the copula theory to multi-dimensional marginals, and deduce that one can describe any (exact or approximate)…

Computational Physics · Physics 2025-03-11 Geneviève Dusson , Claudia Klüppelberg , Gero Friesecke

We study the problem of maximizing a function that is approximately submodular under a cardinality constraint. Approximate submodularity implicitly appears in a wide range of applications as in many cases errors in evaluation of a…

Data Structures and Algorithms · Computer Science 2024-11-19 Thibaut Horel , Yaron Singer

Numerical simulations demonstrate a link between dynamically cold initial solutions and an evolution towards self-similarity. However the nature of this link is not fully understood. In this work the link between cold initial conditions and…

Pattern Formation and Solitons · Physics 2020-10-20 C. Alard

We introduce certain linear positive operators and study some approximation properties of these operators in the space of functions, continuous on a compact set, of two variables. We also find the order of this approximation by using…

Classical Analysis and ODEs · Mathematics 2007-09-24 Fatma Tasdelen , Ali Olgun , Gulen Bascanbaz-Tunca

We consider approximation of functions of $s$ variables, where $s$ is very large or infinite, that belong to weighted anchored spaces. We study when such functions can be approximated by algorithms designed for functions with only very…

Numerical Analysis · Mathematics 2016-10-11 Peter Kritzer , Friedrich Pillichshammer , G. W. Wasilkowski

Weak-coupling expansions (conserving approximations) are carried out for the attractive Holstein and Hubbard models (on an infinite-dimensional hypercubic lattice) that include all bandstructure and vertex correction effects. Quantum…

Condensed Matter · Physics 2009-10-22 J. K. Freericks , D. J. Scalapino

In our present investigation we propose to study and develop the I-function of two variables analogous to the I-function of one variable introduced and studied by one of the authors[24]. The conditions for convergence, series…

Complex Variables · Mathematics 2013-01-01 Shantha Kumari. K. , Vasudevan Nambisan T. M. , Arjun K. Rathie

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

Multivariate functions emerge naturally in a wide variety of data-driven models. Popular choices are expressions in the form of basis expansions or neural networks. While highly effective, the resulting functions tend to be hard to…

Machine Learning · Statistics 2022-06-15 Jan Decuyper , Koen Tiels , Siep Weiland , Mark C. Runacres , Johan Schoukens