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The paper presents error estimates within a unified abstract framework for the analysis of FEM for boundary value problems with linear diffusion-convection-reaction equations and boundary conditions of mixed type. Since neither conformity…

Numerical Analysis · Mathematics 2026-02-04 Lutz Angermann , Peter Knabner , Andreas Rupp

Composite fermions provide a simple and unified picture to understand a vast amount of phenomenology in the quantum Hall regime. However it has remained challenging to formulate this concept properly within a single Landau level. Recently a…

Strongly Correlated Electrons · Physics 2022-01-25 Ken K. W. Ma , Kun Yang

In this work we present a detailed study of the Fermion Monte Carlo algorithm (FMC), a recently proposed stochastic method for calculating fermionic ground-state energies [M.H. Kalos and F. Pederiva, Phys. Rev. Lett. vol. 85, 3547 (2000)].…

Strongly Correlated Electrons · Physics 2009-11-11 Roland Assaraf , Michel Caffarel , Anatole Khelif

Diffusion Monte Carlo (DMC) based on fixed-node approximation has enjoyed significant developments in the past decades and become one of the go-to methods when accurate ground state energy of molecules and materials is needed. The remaining…

Chemical Physics · Physics 2023-08-07 Weiluo Ren , Weizhong Fu , Xiaojie Wu , Ji Chen

The present work proposes to use density-functional theory (DFT) to correct for the basis-set error of wave-function theory (WFT). One of the key ideas developed here is to define a range-separation parameter which automatically adapts to a…

We investigate the properties of fermion-boson stars (FBSs), which can be viewed as neutron stars with a bosonic dark matter (DM) admixture. A challenge in studying the impact of DM on neutron stars is the absence of a universally accepted…

High Energy Astrophysical Phenomena · Physics 2025-10-21 Kelvin Ka-Ho Lam , Lap-Ming Lin

In recent years dynamical modelling has been provided with a range of breakthrough methods to perform exact Bayesian inference. However it is often computationally unfeasible to apply exact statistical methodologies in the context of large…

Computation · Statistics 2014-12-24 Umberto Picchini , Julie Lyng Forman

Basis set incompleteness error and finite size error can manifest concurrently in systems for which the two effects are phenomenologically well-separated in length scale. When this is true, we need not necessarily remove the two sources of…

Chemical Physics · Physics 2016-08-03 James J. Shepherd

Diffusion Monte Carlo (DMC) calculations typically yield highly accurate results in solid-state and quantum-chemical calculations. However, operators that do not commute with the Hamiltonian are at best sampled correctly up to second order…

Other Condensed Matter · Physics 2009-11-13 R. Gaudoin , J. M. Pitarke

Full configuration interaction (FCI) solvers are limited to small basis sets due to their expensive computational costs. An optimal orbital selection for FCI (OptOrbFCI) is proposed to boost the power of existing FCI solvers to pursue the…

Chemical Physics · Physics 2020-09-01 Yingzhou Li , Jianfeng Lu

Commercial RGB-D cameras often produce noisy, incomplete depth maps for non-Lambertian objects. Traditional depth completion methods struggle to generalize due to the limited diversity and scale of training data. Recent advances exploit…

Computer Vision and Pattern Recognition · Computer Science 2025-06-30 Wenzhou Lyu , Jialing Lin , Wenqi Ren , Ruihao Xia , Feng Qian , Yang Tang

By combining extrapolated selected configuration interaction (sCI) energies obtained with the CIPSI (Configuration Interaction using a Perturbative Selection made Iteratively) algorithm with the recently proposed short-range…

Chemical Physics · Physics 2020-06-05 Emmanuel Giner , Anthony Scemama , Julien Toulouse , Pierre-François Loos

The quality of astrochemical models is highly dependent on reliable binding energy (BE) values that consider the morphological and energetic variety of binding sites on the surface of ice-grain mantles. Here, we present the Binding Energy…

Instrumentation and Methods for Astrophysics · Physics 2022-08-31 Giulia M. Bovolenta , Stefan Vogt-Geisse , Stefano Bovino , Tommaso Grassi

In this second part of our series on the recently proposed many-body expanded full configuration interaction (MBE-FCI) method, we introduce the concept of multideterminantal expansion references. Through theoretical arguments and numerical…

Chemical Physics · Physics 2019-09-23 Janus J. Eriksen , Jürgen Gauss

Motivated by a recent experiment by ENS group on the mixture of Bose and Fermi superfluids (arxiv:1404.2548), we investigate the effective scattering between a bosonic atom and a molecule(dimer) of fermion atoms. It is found that the…

Quantum Gases · Physics 2014-10-30 Xiaoling Cui

Understanding the applicability and limitations of electronic-structure methods needs careful and efficient comparison with accurate reference data. Knowledge of the quality and errors of electronic-structure calculations is crucial to…

The Slater-type F12 geminal lengthscales originally tuned for the second-order M{\o}ller-Plesset F12 method are too large for higher-order F12 methods formulated using the SP (diagonal fixed-coefficient spin-adapted) F12 ansatz. The new…

Chemical Physics · Physics 2025-10-13 Samuel R. Powell , Kshitijkumar A. Surjuse , Bimal Gaudel , Edward F. Valeev

Unmodeled beyond Standard Model (BSM) physics in neutrino propagation can masquerade as parameter degeneracies in future precision measurements. Because the upcoming DUNE and T2HK experiments will operate at substantially different…

High Energy Physics - Phenomenology · Physics 2026-03-17 João Paulo Pinheiro , Ushak Rahaman

Bayesian model mixing (BMM) is a statistical technique that can combine constraints from different regions of an input space in a principled way. Here we extend our BMM framework for the equation of state (EOS) of strongly interacting…

Nuclear Theory · Physics 2025-05-27 A. C. Semposki , C. Drischler , R. J. Furnstahl , D. R. Phillips

Two of the most significant challenges in uncertainty quantification pertain to the high computational cost for simulating complex physical models and the high dimension of the random inputs. In applications of practical interest, both of…

Computational Engineering, Finance, and Science · Computer Science 2022-09-02 Jonas Nitzler , Jonas Biehler , Niklas Fehn , Phaedon-Stelios Koutsourelakis , Wolfgang A. Wall
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