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We develop techniques at the interface between differential algebra and model theory to study the following problems of exponential algebraicity: Does a given algebraic differential equation admits an exponentially algebraic solution, that…

Logic · Mathematics 2025-10-31 Rémi Jaoui , Jonathan Kirby

Large language models have recently demonstrated advanced capabilities in solving IMO and Putnam problems; yet their role in research mathematics has remained fairly limited. The key difficulty is verification: suggested proofs may look…

Artificial Intelligence · Computer Science 2025-10-17 Ayush Khaitan , Vijay Ganesh

We develop a new tool, namely polynomial and linear algebraic methods, for studying systems of word equations. We illustrate its usefulness by giving essentially simpler proofs of several hard problems. At the same time we prove extensions…

Combinatorics · Mathematics 2015-02-10 Aleksi Saarela

This is the first installment of an exposition of an ACL2 formalization of elementary linear algebra, focusing on aspects of the subject that apply to matrices over an arbitrary commutative ring with identity, in anticipation of a future…

Discrete Mathematics · Computer Science 2025-07-28 David Russinoff

The theme of symbolic computation in algebraic categories has become of utmost importance in the last decade since it enables the automatic modeling of modern algebra theories. On this theoretical background, the present paper reveals the…

Symbolic Computation · Computer Science 2007-05-23 Alina Andreica

Recently deep learning surrogates and neural operators have shown promise in solving partial differential equations (PDEs). However, they often require a large amount of training data and are limited to bounded domains. In this work, we…

Machine Learning · Computer Science 2023-08-25 Zhiwei Fang , Sifan Wang , Paris Perdikaris

Many statistical models are algebraic in that they are defined in terms of polynomial constraints, or in terms of polynomial or rational parametrizations. The parameter spaces of such models are typically semi-algebraic subsets of the…

Statistics Theory · Mathematics 2010-03-04 Mathias Drton , Seth Sullivant

A number of models of linear logic are based on or closely related to linear algebra, in the sense that morphisms are "matrices" over appropriate coefficient sets. Examples include models based on coherence spaces, finiteness spaces and…

Logic in Computer Science · Computer Science 2022-04-25 Takeshi Tsukada , Kazuyuki Asada

We present a Hilbert space perspective to homogenization of standard linear evolutionary boundary value problems in mathematical physics and provide a unified treatment for (non-)periodic homogenization problems in thermodynamics,…

Analysis of PDEs · Mathematics 2016-03-08 Marcus Waurick

We present a comprehensive programme analysing the decomposition of proof systems for non-classical logics into proof systems for other logics, especially classical logic, using an algebra of constraints. That is, one recovers a proof…

Logic in Computer Science · Computer Science 2023-10-20 Alexander V. Gheorghiu , David J. Pym

Let $X$ be a manifold with boundary, and let $L$ be a 0-elliptic operator on X which is semi-Fredholm essentially surjective with infinite-dimensional kernel. Examples include Hodge Laplacians and Dirac operators on conformally compact…

Analysis of PDEs · Mathematics 2024-12-10 Marco Usula

Machine-learning methods are gradually being adopted in a wide variety of social, economic, and scientific contexts, yet they are notorious for struggling with exact mathematics. A typical example is computer algebra, which includes tasks…

Machine Learning · Computer Science 2024-11-06 Lennart Dabelow , Masahito Ueda

We identify a common scheme in several existing algorithms addressing computational problems on linear differential equations with polynomial coefficients. These algorithms reduce to computing a linear relation between vectors obtained as…

Symbolic Computation · Computer Science 2025-05-05 Louis Gaillard

For every algebraically closed field $\boldsymbol k$ of characteristic different from $2$, we prove the following: (1) Generic finite dimensional (not necessarily associative) $\boldsymbol k$-algebras of a fixed dimension, considered up to…

Algebraic Geometry · Mathematics 2015-01-20 Vladimir L. Popov

The task to construct parametrices of elliptic differential operators on a manifold with edges requires a calculus of operators with a two-component principal symbolic hierarchy, consisting of (edge-degenerate) interior and…

Analysis of PDEs · Mathematics 2007-05-23 B. -W. Schulze , A. Volpato

In this article we introduce a simple straightforward and powerful method involving symbolic manipulation, Picard iteration, and auxiliary variables for approximating solutions of partial differential boundary value problems. The method is…

General Mathematics · Mathematics 2016-11-22 Hamid Semiyari

This paper shows how numerical methods on a regular grid in a box can be used to generate numerical schemes for problems in general smooth domains contained in the box with no need for a domain specific discretization. The focus is mainly…

Numerical Analysis · Mathematics 2016-04-14 Patrick Guidotti

In this paper we introduce a working generalization of the theory of Gr\"obner bases for algebras of partial difference polynomials with constant coefficients. One obtains symbolic (formal) computation for systems of linear or non-linear…

Rings and Algebras · Mathematics 2013-07-24 Roberto La Scala

We consider the problem of symbolic-numeric integration of symbolic functions, focusing on rational functions. Using a hybrid method allows the stable yet efficient computation of symbolic antiderivatives while avoiding issues of…

Symbolic Computation · Computer Science 2018-10-26 Robert M. Corless , Robert H. C. Moir , Marc Moreno Maza , Ning Xie

Recent work in deep learning has opened new possibilities for solving classical algorithmic tasks using end-to-end learned models. In this work, we investigate the fundamental task of solving linear systems, particularly those that are…

Machine Learning · Computer Science 2025-11-19 Pietro Sittoni , Francesco Tudisco