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In this work, the authors introduce a generalized weak Galerkin (gWG) finite element method for the time-dependent Oseen equation. The generalized weak Galerkin method is based on a new framework for approximating the gradient operator.…

Numerical Analysis · Mathematics 2022-09-14 Wenya Qi , Padmanabhan Seshaiyer , Junping Wang

Excellent variational approximations to Gaussian process posteriors have been developed which avoid the $\mathcal{O}\left(N^3\right)$ scaling with dataset size $N$. They reduce the computational cost to $\mathcal{O}\left(NM^2\right)$, with…

Machine Learning · Statistics 2019-09-05 David R. Burt , Carl E. Rasmussen , Mark van der Wilk

The Gromov-Wasserstein (GW) problem provides a framework for aligning heterogeneous datasets by matching their intrinsic geometry, but its statistical and computational scaling remains an issue for high-dimensional problems. Slicing…

Machine Learning · Statistics 2026-05-12 Xiaoyun Gong , Gabriel Rioux , Ziv Goldfeld

The renormalization group plays an essential role in many areas of physics, both conceptually and as a practical tool to determine the long-distance low-energy properties of many systems on the one hand and on the other hand search for…

Statistical Mechanics · Physics 2021-05-10 N. Dupuis , L. Canet , A. Eichhorn , W. Metzner , J. M. Pawlowski , M. Tissier , N. Wschebor

Common G$_0$W$_0$ implementations rely on numerical or analytical frequency integration to determine the G$_0$W$_0$ self-energy, which results in a variety of practical complications. Recently, we demonstrated an exact connection between…

Chemical Physics · Physics 2023-12-01 Johannes Tölle , Garnet Kin-Lic Chan

Recently used in various machine learning contexts, the Gromov-Wasserstein distance (GW) allows for comparing distributions whose supports do not necessarily lie in the same metric space. However, this Optimal Transport (OT) distance…

Machine Learning · Statistics 2022-10-21 Titouan Vayer , Rémi Flamary , Romain Tavenard , Laetitia Chapel , Nicolas Courty

We consider the problem of approximating $[0,1]^{d}$-periodic functions by convolution with a scaled Gaussian kernel. We start by establishing convergence rates to functions from periodic Sobolev spaces and we show that the saturation rate…

Numerical Analysis · Mathematics 2022-02-28 Simon Hubbert , Janin Jäger , Jeremy Levesley

We study the problem of estimating frequency response functions of systems of coupled, classical harmonic oscillators using a quantum computer. The functional form of these response functions can be mapped to a corresponding eigenproblem of…

Quantum Physics · Physics 2025-11-14 Sven Danz , Mario Berta , Stefan Schröder , Pascal Kienast , Frank K. Wilhelm , Alessandro Ciani

We present an implementation of the $GW$ space-time approach that allows cubic-scaling all-electron calculations with standard Gaussian basis sets without exploiting any localization nor sparsity considerations. The independent-electron…

Computational Physics · Physics 2021-04-29 Ivan Duchemin , Xavier Blase

Projection-free optimization via different variants of the Frank-Wolfe (FW) method has become one of the cornerstones in large scale optimization for machine learning and computational statistics. Numerous applications within these fields…

Optimization and Control · Mathematics 2021-08-03 Pavel Dvurechensky , Kamil Safin , Shimrit Shtern , Mathias Staudigl

The representation of subgrid-scale orography is a challenge in the physical parameterization of orographic gravity-wave sources in weather forecasting. A significant hurdle is encoding as much physical information with as simple a…

Atmospheric and Oceanic Physics · Physics 2025-01-16 Ray Chew , Stamen Dolaptchiev , Maja-Sophie Wedel , Ulrich Achatz

We investigate the performance of the GW approximation by comparison to exact results for small model systems. The role of the chemical potentials in Dyson's equation as well as the consequences of numerical resonance broadening are…

Materials Science · Physics 2007-05-23 Thomas J. Pollehn , Arno Schindlmayr , R. W. Godby

Ab initio many-body perturbation theory within the $GW$ approximation is a Green's function formalism widely used in the calculation of quasiparticle excitation energies of solids. In what has become an increasingly standard approach,…

Overlapping gravitational wave (GW) signals are expected in the third-generation (3G) GW detectors, leading to one of the major challenges in GW data analysis. Inference of overlapping GW sources is complicated - it has been reported that…

General Relativity and Quantum Cosmology · Physics 2025-07-08 Qian Hu

Spectral data is routinely broadened in order to improve appearance, approximate a higher sampling level or model experimental measurement effects. While there has been extensive work in the signal processing field to develop efficient…

Materials Science · Physics 2023-09-22 Jessica Farmer , Adam J. Jackson

Modern 4-wave mixing spectroscopies are expensive to obtain experimentally and computationally. In certain cases, the unfavorable scaling of quantum dynamics problems can be improved using a generalized quantum master equation (GQME)…

Chemical Physics · Physics 2024-05-16 Thomas Sayer , Andrés Montoya-Castillo

We describe a finite-field approach to compute density response functions, which allows for efficient $G_0W_0$ and $G_0W_0\Gamma_0$ calculations beyond the random phase approximation. The method is easily applicable to density functional…

Chemical Physics · Physics 2018-12-19 He Ma , Marco Govoni , Francois Gygi , Giulia Galli

The speedup of heavy numerical tasks by quantum computing is now actively investigated in various fields including data analysis in physics and astronomy. In this paper, we propose a new quantum algorithm for matched filtering in…

Instrumentation and Methods for Astrophysics · Physics 2022-05-13 Koichi Miyamoto , Gonzalo Morrás , Takahiro S. Yamamoto , Sachiko Kuroyanagi , Savvas Nesseris

The GW method, which can describe accurately electronic excitations, is one of the most widely used ab initio electronic structure technique and allows the physics of both molecular and condensed phase materials to be studied. However, the…

Quasiparticle (QP) excitations are extremely important for understanding and predicting charge transfer and transport in molecules, nanostructures and extended systems. Since density functional theory (DFT) within the Kohn-Sham (KS)…

Chemical Physics · Physics 2017-07-18 Vojtech Vlcek , Eran Rabani , Daniel Neuhauser , Roi Baer