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Related papers: Quasi-Lie schemes for PDEs

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We give an axiomatic formulation of quantum structures like semilogics and quasilogics which generalize the boolean semirings of events and fuzzy logics. The notions of distributions, states, representations observables and semiobservables…

Logic · Mathematics 2007-05-23 V. P. Belavkin

We introduce a semi-implicit Milstein approximation scheme for some class of non-colliding particle systems modeled by systems of stochastic differential equations with non-constant diffusion coefficients. We show that the scheme converges…

Probability · Mathematics 2019-08-13 Hoang-Long Ngo , Duc-Trong Luong

We review the construction and analysis of numerical methods for strongly nonlinear PDEs, with an emphasis on convex and nonconvex fully nonlinear equations and the convergence to viscosity solutions. We begin by describing a fundamental…

Numerical Analysis · Mathematics 2016-10-26 Michael Neilan , Abner J. Salgado , Wujun Zhang

A rigorous geometric proof of the Lie's Theorem on nonlinear superposition rules for solutions of non-autonomous ordinary differential equations is given filling in all the gaps present in the existing literature. The proof is based on an…

Mathematical Physics · Physics 2008-11-26 José F. Cariñena , Janusz Grabowski , Giuseppe Marmo

In this paper, we explain in more details the modern treatment of the problem of group classification of (systems of) partial differential equations (PDEs) from the algorithmic point of view. More precisely, we revise the classical…

Mathematical Physics · Physics 2013-09-09 Ding-jiang Huang , Nataliya M. Ivanova

We present a generalized quasi-particle theory for bosonic lattice systems, which naturally contains all relevant collective modes, including the Higgs amplitude in the strongly correlated superfluid. In contrast to Bogoliubov theory, this…

Quantum Gases · Physics 2014-01-21 Ulf Bissbort , Michael Buchhold , Walter Hofstetter

In many scientific fields, the generation and evolution of data are governed by partial differential equations (PDEs) which are typically informed by established physical laws at the macroscopic level to describe general and predictable…

Methodology · Statistics 2025-07-01 Ziyuan Chen , Shunxing Yan , Fang Yao

In this study, we propose high-order implicit and semi-implicit schemes for solving ordinary differential equations (ODEs) based on Taylor series expansion. These methods are designed to handle stiff and non-stiff components within a…

Numerical Analysis · Mathematics 2024-09-19 S. Boscarino , E. Macca

A stochastic Lie system on a manifold $M$ is a stochastic differential equation whose dynamics is described by a linear combination with functions depending on $\mathbb{R}^\ell$-valued semi-martigales of vector fields on $M$ spanning a…

Probability · Mathematics 2025-12-02 Javier de Lucas , Marcin Zając

We introduce a general method for the construction of quasiprobability representations for arbitrary notions of quantum coherence. Our technique yields a nonnegative probability distribution for the decomposition of any classical state.…

Quantum Physics · Physics 2018-06-22 J. Sperling , I. A. Walmsley

Quasiprobability distributions (QDs) in open quantum systems are investigated for $SU(2)$, spin like systems, having relevance to quantum optics and information. In this work, effect of both quantum non-demolition (QND) and dissipative open…

Quantum Physics · Physics 2022-06-10 Kishore Thapliyal , Subhashish Banerjee , Anirban Pathak , S. Omkar , V. Ravishankar

We define a pseudo quasi-3 design as a symmetric design with the property that the derived and residual designs with respect to at least one block are quasi-symmetric. Quasi-symmetric designs can be used to construct optimal self…

Combinatorics · Mathematics 2008-04-11 Carl Bracken

We extend to the multidimensional case a Wong-Zakai-type theorem proved by Hu and {\O}ksendal in [7] for scalar quasi-linear It\^o stochastic differential equations (SDEs). More precisely, with the aim of approximating the solution of a…

Probability · Mathematics 2021-03-17 Alberto Lanconelli , Ramiro Scorolli

We develop a framework for estimating unknown partial differential equations from noisy data, using a deep learning approach. Given noisy samples of a solution to an unknown PDE, our method interpolates the samples using a neural network,…

Machine Learning · Computer Science 2019-10-24 Ali Hasan , João M. Pereira , Robert Ravier , Sina Farsiu , Vahid Tarokh

A large system of ordinary differential equations is approximated by a parabolic partial differential equation with dynamic boundary condition and a different one with Robin boundary condition. Using the theory of differential operators…

Functional Analysis · Mathematics 2014-03-26 András Bátkai , Ágnes Havasi , Róbert Horváth , Dávid Kunszenti-Kovács , Péter L. Simon

Families of regimes for discrete control systems are studied possessing a special quasi-controllability property that is similar to the Kalman controllability property. A new approach is proposed to estimate the amplitudes of transient…

Optimization and Control · Mathematics 2009-09-25 V. Kozyakin , N. Kuznetsov , A. Pokrovskii

In this note we survey results in recent research papers on the use of Lie groups in the study of partial differential equations. The focus will be on parabolic equations, and we will show how the problems at hand have solutions that seem…

Analysis of PDEs · Mathematics 2007-05-23 Palle E. T. Jorgensen

Many processes in science and engineering can be described by partial differential equations (PDEs). Traditionally, PDEs are derived by considering first principles of physics to derive the relations between the involved physical quantities…

Machine Learning · Statistics 2019-03-27 Jens Berg , Kaj Nyström

Lie symmetries of systems of second-order linear ordinary differential equations with constant coefficients are exhaustively described over both the complex and real fields. The exact lower and upper bounds for the dimensions of the maximal…

Classical Analysis and ODEs · Mathematics 2014-03-25 Vyacheslav M. Boyko , Roman O. Popovych , Nataliya M. Shapoval

The adaptive quasi-likelihood analysis is developed for a degenerate diffusion process. Asymptotic normality and moment convergence are proved for the quasi-maximum likelihood estimators and quasi-Bayesian estimators, in the adaptive…

Statistics Theory · Mathematics 2024-06-10 Arnaud Gloter , Nakahiro Yoshida