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Two self-consistent schemes involving Hedin's $GW$ approximation are studied for a set of sixteen different atoms and small molecules. We compare results from the fully self-consistent $GW$ approximation (SC$GW$) and the quasi-particle…

Materials Science · Physics 2015-06-19 Peter Koval , Dietrich Foerster , Daniel Sánchez-Portal

We study the effectiveness of stationary-phase approximated post-Newtonian waveforms currently used by ground-based gravitational-wave detectors to search for the coalescence of binary black holes by comparing them to an accurate waveform…

General Relativity and Quantum Cosmology · Physics 2009-06-10 Michael Boyle , Duncan A. Brown , Larne Pekowsky

The interaction of electromagnetic waves with metallic nanostructures generates resonant oscillations of the conduction-band electrons at the metal surface. These resonances can lead to large enhancements of the incident field and to the…

Optics · Physics 2018-05-09 Ferran Vidal-Codina , Ngoc-Cuong Nguyen , Jaime Peraire

This manuscript explores a variational quantum formulation for nonlinear elasticity problems arising from hyperelastic material models, targeting near term noisy intermediate scale quantum (NISQ) devices. The approach leverages the…

Quantum Physics · Physics 2026-05-29 Uditnarayan Kouskiya , Caglar Oskay

Kohn-Sham DFT with optimally tuned range-separated hybrid (RSH) functionals provides accurate and nonempirical fundamental gaps for a wide variety of finite-size systems. The standard tuning procedure relies on calculation of total energies…

Materials Science · Physics 2021-03-05 Wenfei Li , Vojtech Vlcek , Helen Eisenberg , Eran Rabani , Roi Baer , Daniel Neuhauser

Quantum simulation of the electronic structure problem is one of the most researched applications of quantum computing. The majority of quantum algorithms for this problem encode the wavefunction using $N$ Gaussian orbitals, leading to…

Fault-tolerant quantum computing typically requires the transpilation of arbitrary quantum circuits into a finite, universal gate set, such as Clifford+T. As a baseline, Diagonal approximation can be used for synthesizing single-qubit Pauli…

Quantum Physics · Physics 2026-05-12 Gilad Kishony , Avi Elazari , Ron Cohen , Lior Gazit

A grid-based real-space implementation of the Projector Augmented Wave (PAW) method of P. E. Blochl [Phys. Rev. B 50, 17953 (1994)] for Density Functional Theory (DFT) calculations is presented. The use of uniform 3D real-space grids for…

Materials Science · Physics 2009-11-10 J. J. Mortensen , L. B. Hansen , K. W. Jacobsen

In this work we combine the framework of the Reduced Basis method (RB) with the framework of the Localized Orthogonal Decomposition (LOD) in order to solve parametrized elliptic multiscale problems. The idea of the LOD is to split a high…

Numerical Analysis · Mathematics 2015-05-20 Assyr Abdulle , Patrick Henning

Neural operators (NOs) struggle with high-contrast multiscale partial differential equations (PDEs), where fine-scale heterogeneities cause large errors. To address this, we use the Generalized Multiscale Finite Element Method (GMsFEM) that…

Following earlier work [Mehta, N.; Martin, J. M. L.; J. Chem. Theory Comput. 2022, 18, acs.jctc.2c00426] that showed how the slow basis set convergence of double hybrid density functional theory can be obviated by the use of F12 explicit…

Chemical Physics · Physics 2022-10-04 Nisha Mehta , Jan M. L. Martin

We present an algorithm for the approximate decomposition of diagonal operators, focusing specifically on decompositions over the Clifford+$T$ basis, that minimize the number of phase-rotation gates in the synthesized approximation circuit.…

Quantum Physics · Physics 2016-06-13 Jonathan Welch , Alex Bocharov , Krysta M. Svore

This paper presents a generalized weak Galerkin (gWG) finite element method for linear elasticity problems on general polygonal and polyhedral meshes. The proposed framework is flexible and efficient, allowing for the use of nonpolynomial…

Numerical Analysis · Mathematics 2026-01-27 Junping Wang , Yue Wang

Operator learning offers a powerful paradigm for solving parametric partial differential equations (PDEs), but scaling probabilistic neural operators such as the recently proposed Gaussian Processes Operators (GPOs) to high-dimensional,…

Machine Learning · Statistics 2025-06-23 Sawan Kumar , Tapas Tripura , Rajdip Nayek , Souvik Chakraborty

For many-body methods such as MCSCF and CASSCF, in which the number of one-electron orbitals are optimized and independent of basis set used, there are no problems with using plane-wave basis sets. However, for methods currently used in…

Computational Physics · Physics 2020-09-02 Eric J. Bylaska , Duo Song , Nicholas P. Bauman , Karol Kowalski , Daniel Claudino , Travis S. Humble

Full waveform inversion (FWI) is a large-scale nonlinear ill-posed problem for which computationally expensive Newton-type methods can become trapped in undesirable local minima, particularly when the initial model lacks a low-wavenumber…

Geophysics · Physics 2024-02-23 Ali Gholami

LiDAR-Inertial Odometry (LIO) is widely used for autonomous navigation, but its deployment on Size, Weight, and Power (SWaP)-constrained platforms remains challenging due to the computational cost of processing dense point clouds.…

Robotics · Computer Science 2025-03-12 Boyang Lou , Shenghai Yuan , Jianfei Yang , Wenju Su , Yingjian Zhang , Enwen Hu

In the Kohn-Sham orbital basis imaginary-time path integral for electrons in a semiconductor nanoparticle has a mild Fermion sign problem and is amenable to evaluation by the standard stochastic methods. This is evidenced by the simulations…

Strongly Correlated Electrons · Physics 2021-06-09 Andrei Kryjevski , Thomas Luu , Valentin Karasiev

This chapter provides a comprehensive review of fundamental concepts related to approximate natural orbital functionals (NOFs), emphasizing their significance in quantum chemistry and physics. Focusing on fermions, the discussion excludes…

Chemical Physics · Physics 2023-12-13 Mario Piris

We give a technique to reduce the error probability of quantum algorithms that determine whether its input has a specified property of interest. The standard process of reducing this error is statistical processing of the results of…

Computational Complexity · Computer Science 2019-07-24 Debajyoti Bera , Tharrmashastha P.