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A number of many-body problems can be formulated using Hamiltonians that are quadratic in the creation and annihilation operators. Here, we show how such quadratic Hamiltonians can be efficiently estimated indirectly, employing very few…

Quantum Physics · Physics 2011-01-17 Daniel Burgarth , Koji Maruyama , Franco Nori

We explore the use of Physics Informed Neural Networks to analyse nonlinear Hamiltonian Dynamical Systems with a first integral of motion. In this work, we propose an architecture which combines existing Hamiltonian Neural Network…

Machine Learning · Computer Science 2023-08-09 Vedanta Thapar

Inelastic light scattering from electrons is a symmetry-selective probe of the charge dynamics within correlated materials. Many measurements have been made on correlated insulators, and recent exact solutions in large dimensions explain a…

Strongly Correlated Electrons · Physics 2009-11-07 J. K. Freericks , T. P. Devereaux , R. Bulla , Th. Pruschke

We propose a scheme to construct predictive models for Hamiltonian matrices in atomic orbital representation from ab initio data as a function of atomic and bond environments. The scheme goes beyond conventional tight binding descriptions…

Within the calibration of material models, often the numerical results of a simulation model $y$ are compared with the experimental measurements $y^*$. Usually, the differences between measurements and simulation are minimized using least…

Materials Science · Physics 2024-08-14 Thomas Most

We investigate the problem of determining the Hamiltonian of a locally interacting open-quantum system. To do so, we construct model estimators based on inverting a set of stationary, or dynamical, Heisenberg-Langevin equations of motion…

Quantum Physics · Physics 2020-08-19 Eugene F. Dumitrescu , Pavel Lougovski

Nonresonant inelastic x-ray scattering (NIXS) is a possible tool to detect charge excitations in electron systems. In addition, multipole transitions at high-momentum-transfer region open a new possibility to determine orbital-selective…

Strongly Correlated Electrons · Physics 2015-11-11 Kenji Tsutsui , Eiji Kaneshita , Takami Tohyama

We theoretically and numerically analyze x-ray scattering from asymmetric-top molecules three-dimensionally aligned using elliptically polarized laser light. A rigid-rotor model is assumed. The principal axes of the polarizability tensor…

Atomic Physics · Physics 2010-05-07 Stefan Pabst , Phay J. Ho , Robin Santra

We present a scalable and efficient framework for the inference of spatially-varying parameters of continuum materials from image observations of their deformations. Our goal is the nondestructive identification of arbitrary damage,…

Numerical Analysis · Mathematics 2024-08-21 Joseph Kirchhoff , Dingcheng Luo , Thomas O'Leary-Roseberry , Omar Ghattas

Recent experiments show that indirect resonant inelastic X-ray scattering (RIXS) is a new probe of spin dynamics. Here I derive the cross-section for magnetic RIXS and determine the momentum dependent four-spin correlation function that it…

Strongly Correlated Electrons · Physics 2015-06-25 Jeroen van den Brink

Energy dispersive X-ray (EDX) spectrum imaging yields compositional information with a spatial resolution down to the atomic level. However, experimental limitations often produce extremely sparse and noisy EDX spectra. Under such…

In this work, we address the efficient computation of parameterized systems of linear equations, with possible nonlinear parameter dependence. When the matrix is highly sensitive to the parameters, mean-based preconditioning might not be…

Numerical Analysis · Mathematics 2026-05-29 Wouter Gerrit van Harten , Laura Scarabosio

The dream of machine learning in materials science is for a model to learn the underlying physics of an atomic system, allowing it to move beyond interpolation of the training set to the prediction of properties that were not present in the…

Computational Physics · Physics 2020-08-26 Paul Sinz , Michael W. Swift , Xavier Brumwell , Jialin Liu , Kwang Jin Kim , Yue Qi , Matthew Hirn

The H\"uckel Hamiltonian is an incredibly simple tight-binding model famed for its ability to capture qualitative physics phenomena arising from electron interactions in molecules and materials. Part of its simplicity arises from using only…

In this paper we present a hybrid approach to numerically solve two-dimensional electromagnetic inverse scattering problems, whereby the unknown scatterer is hosted by a possibly inhomogeneous background. The approach is `hybrid' in that it…

Analysis of PDEs · Mathematics 2012-10-22 G. Giorgi , M. Brignone , R. Aramini , M. Piana

To accurately reproduce measurements from the real world, simulators need to have an adequate model of the physical system and require the parameters of the model be identified. We address the latter problem of estimating parameters through…

Robotics · Computer Science 2022-03-01 Eric Heiden , Christopher E. Denniston , David Millard , Fabio Ramos , Gaurav S. Sukhatme

A generalization of the S-parameter retrieval method for finite three-dimensional inhomogeneous objects under arbitrary illumination and observation conditions is presented. The effective permittivity of such objects may be rigorously…

Classical Physics · Physics 2010-02-12 Shreyas B. Raghunathan , Neil V. Budko

We present a fully automated framework for extracting interatomic force constants (IFCs) directly from X-ray thermal diffuse scattering (TDS) data. By formulating scattering intensity as a differentiable function of a symmetry-reduced IFC…

Computational Physics · Physics 2026-03-31 Klara Suchan , Shaswat Mohanty , Hanfeng Zhai , Wei Cai

A long-distance effective theory of hydrogen-like atoms, dubbed the relativistic Ritz approach was recently introduced and some its theoretical consequences were explored. In this article, the relativistic Ritz approach is used to fit…

Atomic Physics · Physics 2022-11-14 David M. Jacobs

The article considers the nonlinear inverse problem of identifying the material parameters in viscoelastic structures based on a generalized Maxwell model. The aim is to reconstruct the model parameters from stress data acquired from a…

Numerical Analysis · Mathematics 2025-03-18 Rebecca Rothermel , Thomas Schuster