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This document consists of lecture notes for a graduate course, which focuses on the relations between Information Theory and Statistical Physics. The course is aimed at EE graduate students in the area of Communications and Information…

Information Theory · Computer Science 2010-06-09 Neri Merhav

In this study, we give the variation of parameters method from a different viewpoint for the Nth order inhomogeneous linear ordinary difference equations with constant coefficient by means of delta exponential function . Advantage of this…

Classical Analysis and ODEs · Mathematics 2019-06-04 Erdal Bas , Ramazan Ozarslan

This is an introductory course on nonlinear integrable partial differential and differential-difference equ\-a\-ti\-ons based on lectures given for students of Moscow Institute of Physics and Technology and Higher School of Economics. The…

Mathematical Physics · Physics 2019-01-03 A. Zabrodin

The paper develops the method for construction of the families of particular solutions to the nonlinear Partial Differential Equations (PDE) without relation to the complete integrability. Method is based on the specific link between…

Exactly Solvable and Integrable Systems · Physics 2007-05-23 A. I. Zenchuk

Partial differential equations (PDEs) are central to scientific modeling. Modern workflows increasingly rely on learning-based components to support model reuse, inference, and integration across large computational processes. Despite the…

Machine Learning · Computer Science 2026-02-20 Yilong Dai , Shengyu Chen , Ziyi Wang , Xiaowei Jia , Yiqun Xie , Vipin Kumar , Runlong Yu

The research in Artificial Intelligence methods with potential applications in science has become an essential task in the scientific community last years. Physics Informed Neural Networks (PINNs) is one of this methods and represent a…

Computational Physics · Physics 2023-07-24 Luis Medrano Navarro , Luis Martín Moreno , Sergio G Rodrigo

Recent advances in operator learning have produced two distinct approaches for solving partial differential equations (PDEs): attention-based methods offering point-level adaptability but lacking spectral constraints, and spectral-based…

Machine Learning · Computer Science 2025-06-24 Xihang Yue , Yi Yang , Linchao Zhu

Many scientific and industrial applications require solving Partial Differential Equations (PDEs) to describe the physical phenomena of interest. Some examples can be found in the fields of aerodynamics, astrodynamics, combustion and many…

Computational Physics · Physics 2019-12-11 Juan B. Pedro , Juan Maroñas , Roberto Paredes

An elementary system leading to the notions of fractional integrals and derivatives is considered. Various physical situations whose description is associated with fractional differential equations of motion are discussed.

Statistical Mechanics · Physics 2007-05-23 Alexander I. Olemskoi

Parabolic partial differential equations (PDEs) appear in many disciplines to model the evolution of various mathematical objects, such as probability flows, value functions in control theory, and derivative prices in finance. It is often…

Machine Learning · Computer Science 2024-07-18 Xingzi Xu , Ali Hasan , Jie Ding , Vahid Tarokh

Partial differential equations (PDEs) are crucial for modeling various physical phenomena such as heat transfer, fluid flow, and electromagnetic waves. In computer-aided engineering (CAE), the ability to handle fine resolutions and large…

Quantum Physics · Physics 2025-01-31 Yuki Sato , Hiroyuki Tezuka , Ruho Kondo , Naoki Yamamoto

The discrete heat equation is worked out in order to illustrate the search of symmetries of difference equations. It is paid an special attention to the Lie structure of these symmetries, as well as to their dependence on the derivative…

Exactly Solvable and Integrable Systems · Physics 2009-10-31 D. Levi , J. Negro , M. A. del Olmo

While there is currently a lot of enthusiasm about "big data", useful data is usually "small" and expensive to acquire. In this paper, we present a new paradigm of learning partial differential equations from {\em small} data. In…

Artificial Intelligence · Computer Science 2018-01-17 Maziar Raissi , George Em Karniadakis

Partial Differential Equations (PDEs) are fundamental tools for modeling physical phenomena, yet most PDEs of practical interest cannot be solved analytically and require numerical approximations. The feasibility of such numerical methods,…

Numerical Analysis · Mathematics 2025-12-03 Juan Esteban Suarez Cardona , Holger Boche , Gitta Kutyniok

INTRODUCTION This papers deals with partial differential equations of second order, linear, with constant and not constant coefficients, in two variables, which admit real characteristics. I face the study of PDEs with the mentality of the…

General Mathematics · Mathematics 2017-11-06 Andrea Pezzi

This set of Montreal lectures is an elementary and sketchy introduction to the general field of random matrices. The first half is devoted to combinatorial models, whereas the second half deals with random matrix questions(GUE, etc...).

Probability · Mathematics 2007-12-27 Pierre van Moerbeke

We present a conceptually clear introduction to quantum theory, deriving the theory from scratch from the point of view of quantum information. Different subsets of these lectures were taught to a wide variety of audiences, including…

Popular Physics · Physics 2025-04-15 Barak Shoshany

In this chapter we provide an introduction to fractional dissipative partial differential equations (PDEs) with a focus on trying to understand their dynamics. The class of PDEs we focus on are reaction-diffusion equations but we also…

This book encompasses both traditional and modern methods treating partial differential equation (PDE) of first order and second order. There is a balance in making a selfcontained mathematical text and introducing new subjects. The Lie…

Analysis of PDEs · Mathematics 2010-04-14 A. D. R. Choudary , Saima Parveen , Constantin Varsan

This dissertation investigates three main topics, all of which dealing with alternative, higher-order gravity theories in four dimensions. Firstly, we study the variational and conformal structure of those theories. Next, we analyse their…

General Relativity and Quantum Cosmology · Physics 2007-05-23 Laurent Querella
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