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In this paper, we study Lie superalgebras of $2\times 2$ matrix-valued first-order differential operators on the complex line. We first completely classify all such superalgebras of finite dimension. Among the finite-dimensional…

Mathematical Physics · Physics 2016-08-15 Federico Finkel , Artemio González-López , Miguel A. Rodríguez

This paper aims to introduce two systems of nonlinear ordinary differential equations whose solution components generate the graded algebra of quasi-modular forms on Hecke congruence subgroups $\Gamma_0(2)$ and $\Gamma_0(3)$. Using these…

Number Theory · Mathematics 2021-11-04 Younes Nikdelan

Let $A$ be a finite-dimensional, commutative algebra over $\mathbb{R}$ or $\mathbb{C}$. The notion of $A$-differentiable functions on $A$ is extended to the notion of $A$-differentiable functions on a finitely generated $A$-module $B$. Let…

Complex Variables · Mathematics 2022-02-09 Krzysztof Ciosmak

We present a Python module named PyCheb, to solve the ordinary differential equations by using spectral collocation method. PyCheb incorporates discretization using Chebyshev points, barycentric interpolation and iterate methods. With this…

Mathematical Software · Computer Science 2016-11-07 Shaohui Liu , Tianshi Wang , Youran Zhang

We consider a semigroup of operators in the Banach space $C_b(H)$ of uniformly continuous and bounded functions on a separable Hilbert space $H$. In particular, we deal with semigroups that are related to solution of stochastic PDEs in $H$…

Analysis of PDEs · Mathematics 2007-05-23 Luigi Manca

We concisely summarize a method of finding all rational solutions to an inhomogeneous rational ODE system of arbitrary order (but solvable for its highest order terms) by converting it into a finite dimensional linear algebra problem. This…

Mathematical Physics · Physics 2018-01-31 Igor Khavkine

First, we extend the notion of second order differential equations (SODE) on a smooth manifold to anchored Banach vector bundles. Then we define the Banach Lie algebroids as Lie algebroids structures modeled on anchored Banach vector…

Differential Geometry · Mathematics 2010-03-08 Mihai Anastasiei

We consider a perturbation problem for embedded eigenvalues of a self-adjoint differential operator in $L^2(\mathbb R;\mathbb R^n)$. In particular, we study the set of all small perturbations in an appropriate Banach space for which the…

Functional Analysis · Mathematics 2021-06-08 Sara Maad Sasane , Alexia Papalazarou

We study an infinite system of ordinary differential equations that models the evolution of coagulating and fragmenting clusters, which we assume to be composed of identical units. Under very mild assumptions on the coefficients we prove…

Functional Analysis · Mathematics 2026-02-19 Lyndsay Kerr , Matthias Langer

In this paper differential operators on various moduli spaces (e.g. of holomorphic vector bundles) are described in a canonical way in terms of the geometry of a certain distinguished completion of an appropriate configuration space.

High Energy Physics - Theory · Physics 2008-02-03 Victor Ginzburg

Solutions to most nonlinear ordinary differential equations (ODEs) rely on numerical solvers, but this gives little insight into the nature of the trajectories and is relatively expensive to compute. In this paper, we derive analytic…

Dynamical Systems · Mathematics 2024-06-25 Estelle Basor , Rebecca Morrison

The space of linear differential operators on a smooth manifold $M$ has a natural one-parameter family of $Diff(M)$ (and $Vect(M)$)-module structures, defined by their action on the space of tensor-densities. It is shown that, in the case…

High Energy Physics - Theory · Physics 2007-05-23 C. Duval , V. Ovsienko

Ordinary Differential Equations (ODEs) are widely used in physics, chemistry, and biology to model dynamic systems, including reaction kinetics, population dynamics, and biological processes. In this work, we integrate GPU-accelerated ODE…

Machine Learning · Computer Science 2024-12-02 Rakshit Kr. Singh , Aaron Rock Menezes , Rida Irfan , Bharath Ramsundar

Neural networks have the ability to serve as universal function approximators, but they are not interpretable and don't generalize well outside of their training region. Both of these issues are problematic when trying to apply standard…

Machine Learning · Computer Science 2023-08-21 Colby Fronk , Linda Petzold

In this paper we devise a systematic procedure to obtain nonlocal symmetries of a class of scalar nonlinear ordinary differential equations (ODEs) of arbitrary order related to linear ODEs through nonlocal relations. The procedure makes use…

Exactly Solvable and Integrable Systems · Physics 2015-05-30 R. Gladwin Pradeep , V. K. Chandrasekar , M. Senthilvelan , M. Lakshmanan

The method to solve inhomogeneous linear differential equations that is usually taught at school relies on the fact that the right hand side function is the product of a polynomial and an exponential and that the linear spaces of those…

Classical Analysis and ODEs · Mathematics 2016-07-19 Pep Mulet

We introduce a sheaf theoretic viewpoint on functional analysis designed for infinite dimensional Lie group actions. We develop functional calculus for Banach valued functors and, in particular, prove the existence of an exponential map for…

Complex Variables · Mathematics 2023-09-06 Mauricio Garay , Duco van Straten

This paper is concerned with solution in H\"{o}lder spaces of the Cauchy problem for linear and semi-linear backward stochastic partial differential equations (BSPDEs) of super-parabolic type. The pair of unknown variables are viewed as…

Analysis of PDEs · Mathematics 2016-02-10 Shanjian Tang , Wenning Wei

The question is addressed of when a Sobolev type space, built upon a general rearrangement-invariant norm, on an $n$-dimensional domain, is a Banach algebra under pointwise multiplication of functions. A sharp balance condition among the…

Functional Analysis · Mathematics 2015-12-11 Andrea Cianchi , Luboš Pick , Lenka Slavíková

This paper investigates the use of artificial neural networks (ANNs) to solve differential equations (DEs) and the construction of the loss function which meets both differential equation and its initial/boundary condition of a certain DE.…

Machine Learning · Computer Science 2023-01-03 Xiao Xiong