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A generalization of the maximum noise fraction (MNF) transform is proposed. Powers of each band are included as new bands before the MNF transform is performed. The generalized MNF (GMNF) is shown to perform better than the MNF on a time…

Data Analysis, Statistics and Probability · Physics 2009-11-06 Christopher Gordon

In the present work, a machine learning based constitutive model for electro-mechanically coupled material behavior at finite deformations is proposed. Using different sets of invariants as inputs, an internal energy density is formulated…

Computational Engineering, Finance, and Science · Computer Science 2022-08-30 Dominik K. Klein , Rogelio Ortigosa , Jesús Martínez-Frutos , Oliver Weeger

We give a simple and explicit description of the Bernstein-Szego type measures associated with Jacobi matrices which differ from the Jacobi matrix of the Chebyshev measure in finitely many entries. We also introduce a class of measures M…

Classical Analysis and ODEs · Mathematics 2017-05-09 Jeffrey S. Geronimo , Plamen Iliev

We consider the problem of estimating a signal from noisy circularly-translated versions of itself, called multireference alignment (MRA). One natural approach to MRA could be to estimate the shifts of the observations first, and infer the…

Information Theory · Computer Science 2018-02-14 Tamir Bendory , Nicolas Boumal , Chao Ma , Zhizhen Zhao , Amit Singer

Scalable interferometers lie at the heart of photonic quantum technologies, but their expansion has been fundamentally limited by optical losses that grow with circuit depth. Here, we introduce and experimentally demonstrate a…

Quantum Physics · Physics 2025-12-22 Abhinav Verma , Jacob Hastrup , Jonas S. Neergaard-Nielsen , Ulrik L. Andersen

We present a novel numerical framework that integrates the modified Langevin noise formalism into the multimode Jaynes- and Tavis-Cummings models, enabling a first-principles, non-Markovian analysis of atom-field interactions in dissipative…

Quantum Physics · Physics 2025-04-04 Hyunwoo Choi , Weng Cho Chew , Dong-Yeop Na

Resonant inelastic x-ray scattering (RIXS) is a well-established tool for studying electronic, nuclear and collective dynamics of excited atoms, molecules and solids. An extension of this powerful method to a time-resolved probe technique…

Chemical Physics · Physics 2015-11-03 Victor Kimberg , Nina Rohringer

We compare several different ways of measuring the energy resolution for meV-resolved inelastic x-ray scattering (IXS): using scattering from poly(methyl methacrylate), PMMA, using scattering from borosilicate glass (Tempax), and using…

Materials Science · Physics 2021-03-17 Daisuke Ishikawa , Alfred Q. R. Baron

We present calculations of the millielectronvolt-scale x-ray scattering spectra of multilayered dynamic-compression targets comprising an unstructured ablator layer and a crystalline, textured sample layer. Our model builds on the classic…

Applied Physics · Physics 2026-05-21 P. G. Heighway , J. S. Wark

We consider the problem in Electrical Impedance Tomography (EIT) of identifying one or multiple inclusions in a background-conducting body $\Omega\subset\mathbb{R}^2$, from the knowledge of a finite number of electrostatic measurements…

Numerical Analysis · Mathematics 2025-02-07 Romina Gaburro , Patrick Healy , Shraddha Naidu , Clifford Nolan

In this paper we consider the geodesic X-ray transform with attenuation coefficient as a combination of smooth complex function and 1-form. We show that attenuated X-ray transform applied to the pair of tensors is injective modulo the…

Differential Geometry · Mathematics 2017-03-07 Yernat M. Assylbekov

When a well-localized photon is incident on a spatially superposed absorber but is not absorbed, the photon can still deliver energy to the absorber. It is shown that when the transferred energy is small relative to the energy uncertainty…

Quantum Physics · Physics 2020-09-07 Mordecai Waegell , Cyril Elouard , Andrew N. Jordan

Two-dimensional Hamiltonian systems admitting second invariants which are quartic in the momenta are investigated using the Jacobi geometrization of the dynamics. This approach allows for a unified treatment of invariants at both arbitrary…

Exactly Solvable and Integrable Systems · Physics 2009-11-07 Max Karlovini , Giuseppe Pucacco , Kjell Rosquist , Lars Samuelsson

Iterative Monte Carlo algorithm has been constructed and tested for quantification of X-ray fluorescence analysis in order to determine the atomic composition of solid materials. The calculation model uses simulation code MCNP6 that…

Computational Physics · Physics 2019-06-14 I. Szaloki , A. Gerenyi , G. Radocz

X-ray grating interferometry allows for the simultaneous acquisition of attenuation, differential-phase contrast, and dark-field images, resulting from X-ray attenuation, refraction, and small-angle scattering, respectively. The modulated…

For adaptive mixed finite element methods (AMFEM), we first introduce the data oscillation to analyze, without the restriction that the inverse of the coefficient matrix of the partial differential equations (PDEs) is a piecewise polynomial…

Numerical Analysis · Mathematics 2011-01-07 Shaohong Du , Xiaoping Xie

Full waveform inversion is an ill-posed inverse problem whose solution non-uniqueness -- i.e., arising from band-limited, finite-aperture, noisy data -- calls for uncertainty quantification to avoid overconfident geological interpretations.…

Geophysics · Physics 2026-03-27 Kamal Aghazade , Ali Siahkoohi , Ali Gholami

Finite, lossy waveguides are ubiquitous: distributed attenuation with partial reflections produces feedback, resonance, delays and decay across electromagnetic, acoustic, photonic, quantum-transport and electrochemical interfaces. Yet…

Optics · Physics 2026-02-05 Huayang Cai , Bishuang Chen

In this work, the inverse problem of quantitative thermoacoustic tomography is studied. In quantitative thermoacoustic tomography, dielectric parameters of an imaged target are estimated from an absorbed energy density induced by an…

Computational Physics · Physics 2024-10-10 Teemu Sahlström , Timo Lähivaara , Tanja Tarvainen

The purpose of this note is to show how the method of maximum entropy in the mean (MEM) may be used to improve parametric estimation when the measurements are corrupted by large level of noise. The method is developed in the context on a…

Machine Learning · Computer Science 2021-08-23 Henryk Gzyl , Enrique ter Horst
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