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This paper argues that the requirement of applicableness of quantum linearity to any physical level from molecules and atoms to the level of macroscopic extensional world, which leads to a main foundational problem in quantum theory…

Quantum Physics · Physics 2014-06-25 Arkady Bolotin

This paper is devoted to studying a type of contact problems modeled by hemivariational inequalities with small periodic coefficients appearing in PDEs, and the PDEs we considered are linear, second order and uniformly elliptic. Under the…

Numerical Analysis · Mathematics 2021-11-15 Changqing Ye , Junzhi Cui

The goal of this paper is to develop a numerical algorithm that solves a two-dimensional elliptic partial differential equation in a polygonal domain using tensor methods and ideas from isogeometric analysis. The proposed algorithm is based…

Numerical Analysis · Mathematics 2018-02-09 L. Markeeva , I. Tsybulin , I. Oseledets

The "quantum complexity" of a unitary operator measures the difficulty of its construction from a set of elementary quantum gates. While the notion of quantum complexity was first introduced as a quantum generalization of the classical…

Quantum Physics · Physics 2021-11-02 Vir B. Bulchandani , S. L. Sondhi

We present a new solver for coupled nonlinear elliptic partial differential equations (PDEs). The solver is based on pseudo-spectral collocation with domain decomposition and can handle one- to three-dimensional problems. It has three…

General Relativity and Quantum Cosmology · Physics 2009-11-07 Harald P. Pfeiffer , Lawrence E. Kidder , Mark A. Scheel , Saul A. Teukolsky

This paper is the companion article to [Ann. Probab. 39 (2011) 779--856]. We consider a discrete elliptic equation on the $d$-dimensional lattice $\mathbb{Z}^d$ with random coefficients $A$ of the simplest type: They are identically…

Probability · Mathematics 2012-03-06 Antoine Gloria , Felix Otto

We study quasilinear elliptic double obstacle problems with a variable exponent growth when the right-hand side is a measure. A global Calder\'{o}n-Zygmund estimate for the gradient of an approximable solution is obtained in terms of the…

Analysis of PDEs · Mathematics 2021-05-25 Sun-Sig Byun , Yumi Cho , Jung-Tae Park

The outcomes of quantum mechanical experiments are inherently random. It is therefore necessary to develop stringent methods for quantifying the degree of statistical uncertainty about the results of quantum experiments. For the…

Quantum Physics · Physics 2017-10-11 Daniel Suess , Łukasz Rudnicki , Thiago O. Maciel , David Gross

We introduce a new method for studying stochastic homogenization of elliptic equations in nondivergence form. The main application is an algebraic error estimate, asserting that deviations from the homogenized limit are at most proportional…

Analysis of PDEs · Mathematics 2019-12-10 Scott N. Armstrong , Charles K. Smart

In this note we investigate the relationship between worst-case quantum query complexity and average-case classical query complexity. Specifically, we show that if a quantum computer can evaluate a total Boolean function f with bounded…

Computational Complexity · Computer Science 2012-01-19 Scott Aaronson

In this work we consider the regularization of a supervised learning problem by partial differential equations (PDEs) and derive error bounds for the obtained approximation in terms of a PDE error term and a data error term. Assuming that…

Numerical Analysis · Mathematics 2020-03-17 Carsten Gräser , Prem Anand Alathur Srinivasan

We use entropy numbers in combination with the polynomial method to derive a new general lower bound for the n-th minimal error in the quantum setting of information-based complexity. As an application, we improve some lower bounds on…

Quantum Physics · Physics 2007-05-23 Stefan Heinrich

This article presents a three-step framework for learning and solving partial differential equations (PDEs) using kernel methods. Given a training set consisting of pairs of noisy PDE solutions and source/boundary terms on a mesh, kernel…

Machine Learning · Statistics 2023-04-03 Da Long , Nicole Mrvaljevic , Shandian Zhe , Bamdad Hosseini

We consider the forward problem of uncertainty quantification for the generalised Dirichlet eigenvalue problem for a coercive second order partial differential operator with random coefficients, motivated by problems in structural…

Numerical Analysis · Mathematics 2019-05-20 Alexander D. Gilbert , Ivan G. Graham , Frances Y. Kuo , Robert Scheichl , Ian H. Sloan

We study iterative finite element approximations for the numerical approximation of semilinear elliptic boundary value problems with monotone nonlinear reactions of subcritical growth. The focus of our contribution is on an optimal a priori…

Numerical Analysis · Mathematics 2025-08-18 Florian Spicher , Thomas P. Wihler

This paper introduces a multilevel kernel-based approximation method to estimate efficiently solutions to elliptic partial differential equations (PDEs) with periodic random coefficients. Building upon the work of Kaarnioja, Kazashi, Kuo,…

Numerical Analysis · Mathematics 2025-04-23 Alexander D. Gilbert , Michael B. Giles , Frances Y. Kuo , Ian H. Sloan , Abirami Srikumar

Quantum state tomography (QST) is one of the fundamental problems in quantum information. Among various metrics, sample complexity is widely used to evaluate QST algorithms. While multi-copy measurements are known to achieve optimal sample…

Quantum Physics · Physics 2025-09-17 Gyungmin Cho , Dohun Kim

We study a class of fractional semilinear elliptic equations and formulate the corresponding Calder\'on problem. We determine the nonlinearity from the exterior partial measurements of the Dirichlet-to-Neumann map by using first order…

Analysis of PDEs · Mathematics 2021-06-10 Li Li

We prove a rate of convergence for the $N$-particle approximation of a second-order partial differential equation in the space of probability measures, like the Master equation or Bellman equation of mean-field control problem under common…

Optimization and Control · Mathematics 2021-11-17 Maximilien Germain , Huyên Pham , Xavier Warin

Quantum computers are known for their potential to achieve up-to-exponential speedup compared to classical computers for certain problems. To exploit the advantages of quantum computers, we propose quantum algorithms for linear stochastic…

Quantum Physics · Physics 2025-06-26 Shi Jin , Nana Liu , Wei Wei
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