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A linear functional of an object from a convex symmetric set can be optimally estimated, in a worst-case sense, by a linear functional of observations made on the object. This well-known fact is extended here to a nonlinear setting: other…

Functional Analysis · Mathematics 2025-12-25 Simon Foucart

We use tensor network techniques to obtain high order perturbative diagrammatic expansions for the quantum many-body problem at very high precision. The approach is based on a tensor train parsimonious representation of the sum of all…

We present a method to extract temporal hypergraphs from sequences of 2-dimensional functions obtained as solutions to Optimal Transport problems. We investigate optimality principles exhibited by these solutions from the point of view of…

Discrete Mathematics · Computer Science 2023-01-10 Diego Baptista , Caterina De Bacco

Lambeks Syntactic Calculus, commonly referred to as the Lambek calculus, was innovative in many ways, notably as a precursor of linear logic. But it also showed that we could treat our grammatical framework as a logic (as opposed to a…

Computation and Language · Computer Science 2015-06-19 Richard Moot

Many edge and contour detection algorithms give a soft-value as an output and the final binary map is commonly obtained by applying an optimal threshold. In this paper, we propose a novel method to detect image contours from the extracted…

Computer Vision and Pattern Recognition · Computer Science 2021-05-12 Zahra Mousavi Kouzehkanan , Reshad Hosseini , Babak Nadjar Araabi

We introduce a new form of Lagrangian and propose a simple first-order algorithm for nonconvex optimization with nonlinear equality constraints. We show the algorithm generates bounded dual iterates, and establish the convergence to KKT…

Optimization and Control · Mathematics 2023-05-10 Jong Gwang Kim

Recently, we proposed a non-local relativistic formulation of MOND (Modified Newtonian Dynamics). The equations of motion were not derived, rather they were inferred from the result one would obtain by using the Schwinger-Keldysh formalism.…

High Energy Physics - Theory · Physics 2007-05-23 Marc Soussa

In this work we present recent results on application of low-rank tensor decompositions to modelling of aggregation kinetics taking into account multi-particle collisions (for three and more particles). Such kinetics can be described by…

Numerical Analysis · Mathematics 2020-08-18 Daniil A. Stefonishin , Sergey A. Matveev , Dmitry A. Zheltkov

Orbital motion of a body can be found from Newtonian equation of motion. However, it is useful to express the motion through time derivatives of Keplerian orbital elements, mainly if the motion is perturbed by small perturbing force. The…

Instrumentation and Methods for Astrophysics · Physics 2009-07-27 P. Pastor

We review our perturbative techniques for improved heavy quark actions. A new procedure for computing improvement coefficients is suggested, where the continuum limit of a lattice-regularized theory provides the matching conditions.We also…

High Energy Physics - Lattice · Physics 2009-11-10 Matthew Nobes , Howard Trottier

Many of the technical complications associated with the general theory of relativity ultimately stem from the nonlinearity of Einstein's equation. It is shown here that an appropriate choice of dynamical variables may be used to eliminate…

General Relativity and Quantum Cosmology · Physics 2015-01-07 Abraham I. Harte

We propose a new framework for deriving screening rules for convex optimization problems. Our approach covers a large class of constrained and penalized optimization formulations, and works in two steps. First, given any approximate point,…

Optimization and Control · Mathematics 2016-09-26 Anant Raj , Jakob Olbrich , Bernd Gärtner , Bernhard Schölkopf , Martin Jaggi

We extend the recently developed real-time Diagrammatic Monte Carlo method, in its hybridization expansion formulation, to the full Kadanoff-Baym-Keldysh contour. This allows us to study real-time dynamics in correlated impurity models…

Strongly Correlated Electrons · Physics 2015-05-14 Marco Schiró

We study the utility of a complex Langevin (CL) equation as an alternative for the Monte Carlo (MC) procedure in the evaluation of expectation values occurring in fermionic many-body problems. We find that a CL approach is natural in cases…

Nuclear Theory · Physics 2009-11-06 Chris Adami , Steven E. Koonin

We report on the first results for the second-order perturbation theory correction to the ground-state energy of a nuclear many-body system in a continuum quantum Monte Carlo calculation. Second-order (and higher) perturbative corrections…

Nuclear Theory · Physics 2023-11-10 Ryan Curry , Joel E. Lynn , Kevin E. Schmidt , Alexandros Gezerlis

The tractions that cells exert on a gel substrate from the observed displacements is an increasingly attractive and valuable information in biomedical experiments. The computation of these tractions requires in general the solution of an…

Computational Physics · Physics 2016-08-30 Jose J Munoz

We propose an alternative formulation of Many-Body Perturbation Theory that uses the density-functional concept. Instead of the usual four-point integral equation for the polarizability, we obtain a two-point one, that leads to excellent…

Other Condensed Matter · Physics 2010-07-01 Fabien Bruneval , Francesco Sottile , Valerio Olevano , Rodolfo Del Sole , Lucia Reining

We extend many theorems from the context of solid angle sums over rational polytopes to the context of solid angle sums over real polytopes. Moreover, we consider any real dilation parameter, as opposed to the traditional integer dilation…

Combinatorics · Mathematics 2007-08-02 David DeSario , Sinai Robins

In a previous paper, the general approach for treatment of algebraic equations of different order in gravity theory was exposed, based on the important distinction between covariant and contravariant metric tensor components. In the present…

Mathematical Physics · Physics 2009-11-06 Bogdan G. Dimitrov

In model extraction attacks, the goal is to reveal the parameters of a black-box machine learning model by querying the model for a selected set of data points. Due to an increasing demand for explanations, this may involve counterfactual…

Optimization and Control · Mathematics 2026-03-04 Daan Otto , Jannis Kurtz , Dick den Hertog , Ilker Birbil
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