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The nonlinear wave and Schrodinger equations on Euclidean space of any dimension, with general power nonlinearity and with both the focusing and defocusing signs, are proved to be ill-posed in the Sobolev space of index s whenever the…

Analysis of PDEs · Mathematics 2007-05-23 Michael Christ , James Colliander , Terence Tao

We consider the stability analysis of a large class of linear 1-D PDEs with polynomial data. This class of PDEs contains, as examples, parabolic and hyperbolic PDEs, PDEs with boundary feedback and systems of in-domain/boundary coupled…

Systems and Control · Computer Science 2017-09-19 Aditya Gahlawat , Giorgio Valmorbida

We formulate a smoothed-particle hydrodynamics numerical method, traditionally used for the Euler equations for fluid dynamics in the context of astrophysical simulations, to solve the non-linear Schrodinger equation in the Madelung…

Computational Physics · Physics 2016-11-09 Philip Mocz , Sauro Succi

The purpose of this paper is to illustrate the I-method by studying low-regularity solutions of the nonlinear Schr\'[o]dinger equation in two space dimensions. By applying this method, together with the interaction Morawetz estimate, (see…

Analysis of PDEs · Mathematics 2015-12-09 Changxing Miao , Jiqiang Zheng

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

A new explicit stabilized scheme of weak order one for stiff and ergodic stochastic differential equations (SDEs) is introduced. In the absence of noise, the new method coincides with the classical deterministic stabilized scheme (or…

Numerical Analysis · Mathematics 2018-06-28 Assyr Abdulle , Ibrahim Almuslimani , Gilles Vilmart

We provide here global Schauder-type estimates for a chain of integro-partial differential equations (IPDE) driven by a degenerate stable Ornstein-Uhlenbeck operator possibly perturbed by a deterministic drift, when the coefficients lie in…

Analysis of PDEs · Mathematics 2019-10-10 Lorenzo Marino

In this paper, we construct quantum circuits for the Black-Scholes equations, a cornerstone of financial modeling, based on a quantum algorithm that overcome the cure of high dimensionality. Our approach leverages the Schr\"odingerisation…

Quantum Physics · Physics 2025-05-08 Shi Jin , Zihao Tang , Xu Yin , Lei Zhang

In this paper, we integrate neural networks and Gaussian wave packets to numerically solve the Schr\"odinger equation with a smooth potential near the semi-classical limit. Our focus is not only on accurately obtaining solutions when the…

Computational Physics · Physics 2025-09-08 Jizu Huang , Rukang You , Tao Zhou

In this paper, we study the local well-posedness of the cubic Schr\"odinger equation: \[ (i \partial_t - \mathscr{L}) u = \pm |u|^2 u \quad \text{ on } I \times \mathbb{R}^d, \] with randomized initial data, and $\mathscr{L}$ being an…

Analysis of PDEs · Mathematics 2023-03-02 Jean-Baptiste Casteras , Juraj Foldes , Gennady Uraltsev

In this work we employ a recently proposed bifurcation analysis technique, the deflated continuation algorithm, to compute steady-state solitary waveforms in a one-component, two dimensional nonlinear Schr\"odinger equation with a parabolic…

Pattern Formation and Solitons · Physics 2017-07-06 E. G. Charalampidis , P. G. Kevrekidis , P. E. Farrell

We establish sharp-in-time kernel and dispersive estimates for the Schr\"odinger equation on non-compact Riemannian symmetric spaces of any rank. Due to the particular geometry at infinity and the Kunze-Stein phenomenon, these properties…

Analysis of PDEs · Mathematics 2023-02-14 Jean-Philippe Anker , Stefano Meda , Vittoria Pierfelice , Maria Vallarino , Hong-Wei Zhang

As a typical application of deep learning, physics-informed neural network (PINN) {has been} successfully used to find numerical solutions of partial differential equations (PDEs), but how to improve the limited accuracy is still a great…

Machine Learning · Computer Science 2022-08-09 Zhi-Yong Zhang , Hui Zhang , Li-Sheng Zhang , Lei-Lei Guo

A detailed exposition of highly efficient and accurate method for the propagation of the time-dependent Schr\"odinger equation is presented. The method is readily generalized to solve an arbitrary set of ODE's. The propagation is based on a…

Quantum Physics · Physics 2017-05-12 Ido Schaefer , Hillel Tal-Ezer , Ronnie Kosloff

In these notes we propose and analyze an inertial type method for obtaining stable approximate solutions to nonlinear ill-posed operator equations. The method is based on the Levenberg-Marquardt (LM) iteration. The main obtained results…

Numerical Analysis · Mathematics 2024-06-12 Antonio Leitão , Joel C. Rabelo , Dirk A. Lorenz , Maximilian Winkler

We prove global well-posedness for the cubic, defocusing, nonlinear Schr{\"o}dinger equation on $\mathbf{R}^{2}$ with data $u_{0} \in H^{s}(\mathbf{R}^{2})$, $s > 1/4$. We accomplish this by improving the almost Morawetz estimates in [9].

Analysis of PDEs · Mathematics 2009-09-07 Benjamin Dodson

We study the Allen-Cahn equation with a cubic-quintic nonlinear term and a stochastic $Q$-trace-class stochastic forcing in two spatial dimensions. This stochastic partial differential equation (SPDE) is used as a test case to understand,…

Dynamical Systems · Mathematics 2017-02-28 Christian Kuehn

We establish local and global well-posedness for the initial value problem associated to the one-dimensional Schrodinger-Debye (SD) system for data in the Sobolev spaces with low regularity. To obtain local results we prove two new sharp…

Analysis of PDEs · Mathematics 2008-11-10 Adan Corcho , Carlos Matheus

In this work we shall consider the initial value problem associated to the generalized derivative Schr\"odinger equations \begin{equation*} \p_tu=i\p_x^2u + \mu\,|u|^{\a}\p_xu, \hskip10pt x,t\in\R, \hskip5pt 0<\a \le 1\;\, {\rm and}\;\,…

Analysis of PDEs · Mathematics 2017-12-05 Felipe Linares , Gustavo Ponce , Gleison N. Santos

Traditional data-driven deep learning models often struggle with high training costs, error accumulation, and poor generalizability in complex physical processes. Physics-informed deep learning (PiDL) addresses these challenges by…

Machine Learning · Computer Science 2024-01-17 Xin-Yang Liu , Min Zhu , Lu Lu , Hao Sun , Jian-Xun Wang