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We revisit the problem of the deformed oscillator with position-dependent mass [da Costa et al., J. Math. Phys. {\bf 62}, 092101 (2021)] in the classical and quantum formalisms, by introducing the effect of the mass function in both kinetic…

Quantum Physics · Physics 2023-02-07 Bruno G. da Costa , Ignacio S. Gomez , Biswanath Rath

Given an arbitrary single-qubit operation, an important task is to efficiently decompose this operation into an (exact or approximate) sequence of fault-tolerant quantum operations. We derive a depth-optimal canonical form for single-qubit…

Quantum Physics · Physics 2012-12-13 Alex Bocharov , Krysta M. Svore

We introduce a new numerical strategy to solve a class of oscillatory transport PDE models which is able to captureaccurately the solutions without numerically resolving the high frequency oscillations {\em in both space and time}.Such PDE…

Numerical Analysis · Mathematics 2016-06-01 Nicolas Crouseilles , Shi Jin , Mohammed Lemou

Partial differential equations (PDEs) govern physical phenomena across the full range of scientific scales, yet their computational solution remains one of the defining challenges of modern science. This critical review examines two mature…

Machine Learning · Computer Science 2026-03-10 Mohammad Nooraiepour , Jakub Wiktor Both , Teeratorn Kadeethum , Saeid Sadeghnejad

This paper focuses on minimizing a smooth function combined with a nonsmooth regularization term on a compact Riemannian submanifold embedded in the Euclidean space under a decentralized setting. Typically, there are two types of approaches…

Optimization and Control · Mathematics 2025-07-16 Lei Wang , Le Bao , Xin Liu

We introduce a novel method for the implementation of shape optimziation in fluid dynamics applications, where we propose to use the shape derivative to determine deformation fields with the help of the $p-$ Laplacian for $p > 2$. This…

Optimization and Control · Mathematics 2021-03-30 Peter Marvin Müller , Niklas Kühl , Martin Siebenborn , Klaus Deckelnick , Michael Hinze , Thomas Rung

Numerical homogenization, i.e. the finite-dimensional approximation of solution spaces of PDEs with arbitrary rough coefficients, requires the identification of accurate basis elements. These basis elements are oftentimes found after a…

Numerical Analysis · Mathematics 2015-05-12 Houman Owhadi

Periodic orbit quantization requires an analytic continuation of non-convergent semiclassical trace formulae. We propose a method for semiclassical quantization based upon the Pade approximant to the periodic orbit sums. The Pade…

chao-dyn · Physics 2009-10-31 J. Main , P. A. Dando , Dz. Belkic , H. S. Taylor

In beam shaping applications, the minimization of the number of necessary optical elements for the beam shaping process can benefit the compactness of the optical system and reduce its cost. The single freeform surface design for input…

Optics · Physics 2017-08-10 Christoph Bösel , Herbert Gross

These notes are issued from a short course given by the author in a summer school in Chamb{\'e}ry in June 2015. We consider general semilinear PDE's and we address the following two questions: 1) How to design an efficient feedback control…

Analysis of PDEs · Mathematics 2015-06-22 Emmanuel Trélat

We observe that, within the effective generating function formalism for the implementation of canonical transformations within wave mechanics, non-trivial canonical transformations which leave invariant the form of the Hamilton function of…

Quantum Physics · Physics 2008-11-26 E. D. Davis , G. I. Ghandour

We study the numerical approximation of a class of degenerate parabolic stochastic partial differential equations on non-compact metric graphs, which naturally arise in the asymptotic analysis of Hamiltonian flows under small noise…

Numerical Analysis · Mathematics 2026-04-14 Jianbo Cui , Mihály Kovács , Derui Sheng

In recent work with Bhatt and Morrow, we defined a new integral p-adic cohomology theory interpolating between etale and de Rham cohomology. An unexpected feature of this cohomology is that in coordinates, it can be computed by a…

Algebraic Geometry · Mathematics 2016-06-07 Peter Scholze

Partial differential equations (PDEs) play a central role in describing many physical phenomena. Various scientific and engineering applications demand a versatile and differentiable PDE solver that can quickly generate solutions with…

In the 2nd version of this note we introduce the notion of viscosity solution for a type of fully nonlinear parabolic path-dependent partial differential equations (P-PDE). We then prove the comparison theorem (or maximum principle) of this…

Probability · Mathematics 2012-02-21 Shige Peng

We derive a canonical form for smooth vector fields on $\Re^{n+1}$. We use this to demonstrate the local multi-Hamiltonian nature of the corresponding flows. Associated with the canonical form is an inhomogenious linear PDE whose solutions…

chao-dyn · Physics 2009-10-22 P. Crehan

Partial Differential Equations (PDEs) have long been recognized as powerful tools for image processing and analysis, providing a framework to model and exploit structural and geometric properties inherent in visual data. Over the years,…

Image and Video Processing · Electrical Eng. & Systems 2024-12-17 Alejandro Garnung Menéndez

A methodology for defining variational principles for a class of PDE models from continuum mechanics is demonstrated, and some of its features explored. The scheme is applied to quasi-static and dynamic models of rate-independent and…

Analysis of PDEs · Mathematics 2024-07-02 Amit Acharya

The projection of the eigenfunctions obtained in standard plane-wave first-principle electronic-structure calculations into atomic-orbital basis sets is proposed as a formal and practical link between the methods based on plane waves and…

Condensed Matter · Physics 2009-10-28 Daniel Sanchez-Portal , Emilio Artacho , Jose M. Soler

We propose a partial differential-integral equation (PDE) framework for deep neural networks (DNNs) and their associated learning problem by taking the continuum limits of both network width and depth. The proposed model captures the…

Optimization and Control · Mathematics 2024-11-12 Peter Markowich , Simone Portaro