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Neural architectures trained with losses inspired by differential conditions are the basis for PINN models. Since many constructions in differential geometry may be framed as minimisation of a differential functional, these functionals can…

Differential Geometry · Mathematics 2026-04-29 Edward Hirst

FiniteFlow is a public framework for defining and executing numerical algorithms over finite fields and reconstructing multivariate rational functions. The framework allows to build complex algorithms by combining basic building blocks into…

High Energy Physics - Phenomenology · Physics 2019-12-09 Tiziano Peraro

Finite difference schemes are here solved by means of a linear matrix equation. The theoretical study of the related algebraic system is exposed, and enables us to minimize the error due to a finite difference approximation.

Analysis of PDEs · Mathematics 2007-05-23 Claire David

Topology optimization for large scale problems continues to be a computational challenge. Several works exist in the literature to address this topic, and all make use of iterative solvers to handle the linear system arising from the Finite…

Numerical Analysis · Mathematics 2020-10-21 Darin Peetz , Ahmed Elbanna

Let $\mathbb{F}_q$ be a finite field. Given two irreducible polynomials $f,g$ over $\mathbb{F}_q$, with $\mathrm{deg} f$ dividing $\mathrm{deg} g$, the finite field embedding problem asks to compute an explicit description of a field…

Symbolic Computation · Computer Science 2020-01-07 Ludovic Brieulle , Luca De Feo , Javad Doliskani , Jean-Pierre Flori , Éric Schost

\textsc{Pykat} is a Python package which extends the popular optical interferometer modelling software \textsc{Finesse}. It provides a more modern and efficient user interface for conducting complex numerical simulations, as well as…

Instrumentation and Methods for Astrophysics · Physics 2020-04-16 Daniel D. Brown , Philip Jones , Samuel Rowlinson , Andreas Freise , Sean Leavey , Anna C. Green , Daniel Toyra

We study computing geometric problems on uncertain points. An uncertain point is a point that does not have a fixed location, but rather is described by a probability distribution. When these probability distributions are restricted to a…

Computational Geometry · Computer Science 2012-05-03 Allan Jorgensen , Maarten Löffler , Jeff M. Phillips

Functional integrals are central to modern theories ranging from quantum mechanics and statistical thermodynamics to biology, chemistry, and finance. In this work we present a new method for calculating functional integrals based on a…

Mathematical Physics · Physics 2023-09-22 Amos A. Hari , Sefi Givli

We describe spaces of essential finite height (measured) laminations in a surface $S$ using a parameter space we call $\mathbb S$, an ordered semi-ring. We show that for every finite height essential lamination $L$ in $S$, there is an…

Geometric Topology · Mathematics 2014-04-15 Ulrich Oertel

In this paper, we present Ginkgo, a modern C++ math library for scientific high performance computing. While classical linear algebra libraries act on matrix and vector objects, Ginkgo's design principle abstracts all functionality as…

In this paper we compute the set of point modules of finitely semi-graded rings. In particular, from the parametrization of the point modules for the quantum affine n-space, the set of point modules for some important examples of non…

Rings and Algebras · Mathematics 2019-08-15 Oswaldo Lezama

We introduce PINGS (Physics-Informed Neural Network for Fast Generative Sampling), a framework that amortizes diffusion sampling by training a physics-informed network to approximate reverse-time probability-flow dynamics, reducing sampling…

The great success of Physics-Informed Neural Networks (PINN) in solving partial differential equations (PDEs) has significantly advanced our simulation and understanding of complex physical systems in science and engineering. However, many…

Numerical Analysis · Mathematics 2024-09-10 Hao Zhang , Longxiang Jiang , Xinkun Chu , Yong Wen , Luxiong Li , Yonghao Xiao , Liyuan Wang

In this article, a new generic higher-order finite-element framework for massively parallel simulations is presented. The modular software architecture is carefully designed to exploit the resources of modern and future supercomputers.…

Mathematical Software · Computer Science 2018-05-28 Nils Kohl , Dominik Thönnes , Daniel Drzisga , Dominik Bartuschat , Ulrich Rüde

The topological space of the stack of $G$-zips can be computed using a refinement process. We extend this refinement process to a more general framework and show that in many situations this process can be used to compute the equivalence…

Algebraic Topology · Mathematics 2025-05-20 Christopher Lang

Fidimag is an open-source scientific code for the study of magnetic materials at the nano- or micro-scale using either atomistic or finite difference micromagnetic simulations, which are based on solving the Landau-Lifshitz-Gilbert…

Mesoscale and Nanoscale Physics · Physics 2020-02-12 Marc-Antonio Bisotti , David Cortés-Ortuño , Ryan A. Pepper , Weiwei Wang , Marijan Beg , Thomas Kluyver , Hans Fangohr

In this paper we will look at the connection of frames and finite dimensionality. A main focus is to present simple algorithms and make them available online. The main result is a way to 'switch' between different frames, giving an…

Functional Analysis · Mathematics 2009-02-12 Peter Balazs

What is computable with limited resources? How can we verify the correctness of computations? How to measure computational power with precision? Despite the immense scientific and engineering progress in computing, we still have only…

Other Computer Science · Computer Science 2016-10-20 Attila Egri-Nagy

The finite section method is a classical scheme to approximate the solution of an infinite system of linear equations. We present quantitative estimates for the rate of the convergence of the finite section method on weighted $\ell…

Functional Analysis · Mathematics 2007-05-23 Karlheinz Gröchenig , Ziemowit Rzeszotnik , Thomas Strohmer

NIFTY, "Numerical Information Field Theory", is a software package designed to enable the development of signal inference algorithms that operate regardless of the underlying spatial grid and its resolution. Its object-oriented framework is…

Instrumentation and Methods for Astrophysics · Physics 2013-06-06 Marco Selig , Michael R. Bell , Henrik Junklewitz , Niels Oppermann , Martin Reinecke , Maksim Greiner , Carlos Pachajoa , Torsten A. Enßlin
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