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Optical diffraction tomography relies on solving an inverse scattering problem governed by the wave equation. Classical reconstruction algorithms are based on linear approximations of the forward model (Born or Rytov), which limits their…

Computational Engineering, Finance, and Science · Computer Science 2017-09-01 Emmanuel Soubies , Thanh-An Pham , Michael Unser

This work addresses inverse linear optimization where the goal is to infer the unknown cost vector of a linear program. Specifically, we consider the data-driven setting in which the available data are noisy observations of optimal…

Optimization and Control · Mathematics 2021-12-07 Rishabh Gupta , Qi Zhang

We present a method for linearising classes of matrix-valued nonlinear partial differential equations with local and nonlocal nonlinearities. Indeed we generalise a linearisation procedure originally developed by P\"oppe based on solving…

Analysis of PDEs · Mathematics 2020-10-05 Anastasia Doikou , Simon J. A. Malham , Ioannis Stylianidis

A new approach to solving the Time-Dependent Self-Consistent-Field equations is developed based on the double quotient formulation of Tsiper [J. Phys. B, 34 L401 (2001)]. Dual channel, quasi-independent non-linear optimization of these…

Quantum Physics · Physics 2010-01-19 Matt Challacombe

In this report the emphasis is on an alternative representation of the Magnus series by proper operator (matrix) exponential solutions to differential equations (systems), both linear and nonlinear ODEs and PDEs. The main idea here is in…

Mathematical Physics · Physics 2026-01-06 Yu. N. Kosovtsov

This study applies the RBF wavelet series to the evaluation of analytical solutions of linear time-dependent wave and diffusion problems of any dimensionality and geometry. To the best of the author's knowledge, such analytical solutions…

Numerical Analysis · Mathematics 2025-10-20 W. Chen

Successful applications of the Kruskal-Segur approach to interfacial pattern formation have remained limited due to the necessity of an integral formulation of the problem. This excludes nonlinear bulk equations, rendering convection…

Pattern Formation and Solitons · Physics 2017-03-13 Thomas Fischaleck , Klaus Kassner

This paper presents a Fourier integral pseudospectral (FIPS) method for a general class of nonlinear, periodic optimal control (OC) problems with equality and/or inequality constraints and sufficiently smooth solutions. In this scheme, the…

Optimization and Control · Mathematics 2023-11-14 Kareem T. Elgindy

A new numerical method for solving a scalar ordinary differential equation with a given initial condition is introduced. The method is using a numerical integration procedure for an equivalent integral equation and is called in this paper…

Numerical Analysis · Mathematics 2011-09-06 Alexander Lozovskiy

The Lamperti transform offers a powerful bridge between self-similar processes and stationary dynamics, making it especially useful for analyzing anomalous diffusion models that lack stationary increments. In this paper we examine the…

Probability · Mathematics 2026-01-07 Foad Shokrollahi , Saeed Vahdati

Due to their wide appearance in environmental settings as well as industrial and medical applications, the Stokes-Darcy problems with different sets of interface conditions establish an active research area in the community of mathematical…

Numerical Analysis · Mathematics 2025-04-03 Paula Strohbeck , Marco Discacciati , Iryna Rybak

We propose a decomposition framework for the parallel optimization of the sum of a differentiable function and a (block) separable nonsmooth, convex one. The latter term is typically used to enforce structure in the solution as, for…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-11-12 Francisco Facchinei , Simone Sagratella , Gesualdo Scutari

The problem of developing an arithmetic for continued fractions (in order to perform, e.g., sums and products) does not have a straightforward solution and has been addressed by several authors. In 1972, Gosper provided an algorithm to…

Number Theory · Mathematics 2025-05-13 Piotr Miska , Nadir Murru , Giuliano Romeo

We consider solutions in frequency bands of dispersive equations on the line defined by Fourier multipliers, these solutions being considered as wave packets. In this paper, a refinement of an existing method permitting to expand…

Analysis of PDEs · Mathematics 2020-01-30 Florent Dewez

Using a Fourier spectral method, we provide a detailed numerically investigation of dispersive Schr\"odinger type equations involving a fractional Laplacian. By an appropriate choice of the dispersive exponent, both mass and energy sub- and…

Analysis of PDEs · Mathematics 2015-06-19 C. Klein , C. Sparber , P. Markowich

We consider a time-dependent linear diffusion equation together with a related inverse boundary value problem. The aim of the inverse problem is to determine, based on observations on the boundary, the non-homogeneous diffusion coefficient…

Numerical Analysis · Mathematics 2016-09-21 Lauri Mustonen

We derive a parallel sampling algorithm for computational inverse problems that present an unknown linear forcing term and a vector of nonlinear parameters to be recovered. It is assumed that the data is noisy and that the linear part of…

Numerical Analysis · Mathematics 2022-03-24 Darko Volkov

In computational inverse problems, it is common that a detailed and accurate forward model is approximated by a computationally less challenging substitute. The model reduction may be necessary to meet constraints in computing time when…

Methodology · Statistics 2018-02-14 Daniela Calvetti , Matthew M. Dunlop , Erkki Somersalo , Andrew M. Stuart

An infinite-dimensional bilinear optimal control problem with infinite-time horizon is considered. The associated value function can be expanded in a Taylor series around the equilibrium, the Taylor series involving multilinear forms which…

Optimization and Control · Mathematics 2017-09-14 Tobias Breiten , Karl Kunisch , Laurent Pfeiffer

In stochastic optimization, the population risk is generally approximated by the empirical risk. However, in the large-scale setting, minimization of the empirical risk may be computationally restrictive. In this paper, we design an…

Machine Learning · Statistics 2016-11-22 Murat A. Erdogdu , Mohsen Bayati , Lee H. Dicker
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