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In non-private stochastic convex optimization, stochastic gradient methods converge much faster on interpolation problems -- problems where there exists a solution that simultaneously minimizes all of the sample losses -- than on…

Machine Learning · Computer Science 2022-11-01 Hilal Asi , Karan Chadha , Gary Cheng , John Duchi

We present a low-complexity algorithm to calculate the correlation energy of periodic systems in second-order M\o ller-Plesset perturbation theory (MP2). In contrast to previous approximation-free MP2 codes, our implementation possesses a…

Chemical Physics · Physics 2017-03-16 Tobias Schäfer , Benjamin Ramberger , Georg Kresse

Detectability of failures of linear programming (LP) decoding and its potential for improvement by adding new constraints motivate the use of an adaptive approach in selecting the constraints for the LP problem. In this paper, we make a…

Information Theory · Computer Science 2007-07-13 Mohammad H. Taghavi N. , Paul H. Siegel

Thin surfaces, such as the leaves of a plant, pose a significant challenge for implicit surface reconstruction techniques, which typically assume a closed, orientable surface. We show that by approximately interpolating a point cloud of the…

Numerical Analysis · Mathematics 2023-09-19 Riley M. Whebell , Timothy J. Moroney , Ian W. Turner , Ravindra Pethiyagoda , Scott W. McCue

Transition intensities for small molecules such as water and CO$_2$ can now be computed with such high accuracy that they are being used to systematically replace measurements in standard databases. These calculations use high accuracy ab…

A two-user downlink network aided by a reconfigurable intelligent surface is considered. The weighted sum signal to interference plus noise ratio maximization and the sum rate maximization models are presented, where the precoding vectors…

Signal Processing · Electrical Eng. & Systems 2022-02-15 Cong Sun , Xian Liu , Bile Peng , Eduard Jorswieck

This article initiates the study of space-time adaptive mesh refinements for time-dependent boundary element formulations of wave equations. Based on error indicators of residual type, we formulate an adaptive boundary element procedure for…

Numerical Analysis · Mathematics 2025-11-07 Alessandra Aimi , Giulia Di Credico , Heiko Gimperlein , Chiara Guardasoni

The use of adaptive mesh refinement (AMR) techniques is crucial for accurate and efficient simulation of higher dimensional spacetimes. In this work we develop an adaptive algorithm tailored to the integration of finite difference…

General Relativity and Quantum Cosmology · Physics 2009-11-10 Frans Pretorius , Luis Lehner

Efficient simulation of quantum computers is essential for the development and validation of near-term quantum devices and the research on quantum algorithms. Up to date, two main approaches to simulation were in use, based on either full…

Computational Complexity · Computer Science 2020-05-06 Roman Schutski , Danil Lykov , Ivan Oseledets

We study the performance of our previously proposed Projective Quantum Eigensolver (PQE) on IBM's quantum hardware in conjunction with error mitigation techniques. For a single qubit model of H$_2$, we find that we are able to obtain…

Quantum Physics · Physics 2023-10-10 Jonathon P. Misiewicz , Francesco A. Evangelista

We study dendritic microstructure evolution using an adaptive grid, finite element method applied to a phase-field model. The computational complexity of our algorithm, per unit time, scales linearly with system size, rather than the…

Materials Science · Physics 2009-10-30 Nikolas Provatas , Nigel Goldenfeld , Jonathan Dantzig

Invariant-based models for incompressible isotropic hyperelasticity are typically formulated as functions of the first and second invariants, $W = W(\bar{I}_1, \bar{I}_2)$. A widely used class of models employs separable representations of…

Computational Engineering, Finance, and Science · Computer Science 2026-04-14 Simon Wiesheier , Miguel Angel Moreno-Mateos , Paul Steinmann

In this work we investigate the computation of dispersion relation (i.e., band functions) for three-dimensional photonic crystals, formulated as a parameterized Maxwell eigenvalue problem, using a novel hp-adaptive sampling algorithm. We…

Numerical Analysis · Mathematics 2024-06-18 Yueqi Wang , Richard Craster , Guanglian Li

Considering recent advancements and successes in the development of efficient quantum algorithms for electronic structure calculations --- alongside impressive results using machine learning techniques for computation --- hybridizing…

Quantum Physics · Physics 2018-10-24 Rongxin Xia , Sabre Kais

Adaptive variational quantum simulation algorithms use information from the quantum computer to dynamically create optimal trial wavefunctions for a given problem Hamiltonian. A key ingredient in these algorithms is a predefined operator…

Deep learning based methods have recently pushed the state-of-the-art on the problem of Single Image Super-Resolution (SISR). In this work, we revisit the more traditional interpolation-based methods, that were popular before, now with the…

Computer Vision and Pattern Recognition · Computer Science 2017-12-19 Xu Jia , Hong Chang , Tinne Tuytelaars

We propose a new formulation for integrating over smooth curves and surfaces that are described by their closest point mappings. Our method is designed for curves and surfaces that are not defined by any explicit parameterization and is…

Numerical Analysis · Mathematics 2015-10-16 Catherine Kublik , Richard Tsai

A multilevel approach to sample the potential energy surface in a path integral formalism is proposed. The purpose is to reduce the required number of ab initio evaluations of energy and forces in ab initio path integral molecular dynamics…

Computational Physics · Physics 2014-12-22 Hua Y. Geng

We consider regular polynomial interpolation algorithms on recursively defined sets of interpolation points which approximate global solutions of arbitrary well-posed systems of linear partial differential equations. Convergence of the…

Numerical Analysis · Mathematics 2008-07-10 Joerg Kampen

Adaptive Finite Element Method (adaptivity) is known to be an effective numerical tool for some ill-posed problems. The key advantage of the adaptivity is the image improvement with local mesh refinements. A rigorous proof of this property…

Mathematical Physics · Physics 2012-10-30 Larisa Beilina , Michael V. Klibanov
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