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Neutrino-nucleus cross section uncertainties are expected to be a dominant systematic in future accelerator neutrino experiments. The cross sections are determined by the linear response of the nucleus to the weak interactions of the…

Quantum Physics · Physics 2020-05-06 Alessandro Roggero , Andy C. Y. Li , Joseph Carlson , Rajan Gupta , Gabriel N. Perdue

In this paper, a novel QR decomposition-based compression scheme is combined with a volume integral equations method for the fast and efficient numerical computation of the scattering of electromagnetic fields from large scale metasurfaces,…

Using classical electrodynamics we determine the angular dependence of the light intensities radiated in second and third harmonic generation by spherical metal clusters. Forward and backward scattering is analyzed in detail. Also resonance…

Condensed Matter · Physics 2007-05-23 J. Dewitz , W. Hubner , K. H. Bennemann

The shapes of Stokes profiles contain much information about the atmospheric conditions that produced them. However, a variety of different atmospheric structures can produce very similar profiles. Thus, it is important for proper…

Solar and Stellar Astrophysics · Physics 2023-07-12 Thore Espedal Moe , Tiago M. D. Pereira , Flavio Calvo , Jorrit Leenaarts

In this paper, numerical simulations of four-mode continuous-variable cluster states with different topologies in the framework of measurement-based quantum computation are presented. By utilizing the symplectic representation and…

Quantum Physics · Physics 2026-04-28 Amin Ahadi , Saman Sarshar

Wide-angle x-ray scattering (WAXS) is emerging as a powerful tool for increasing the resolution of solution structure measurements of biomolecules. Compared to its better known complement, small angle x-ray scattering (SAXS), WAXS targets…

The prospects of extracting new physics signals in coherent elastic neutrino--nucleus scattering (CE$\nu$NS) processes are limited by the precision with which the underlying nuclear structure physics, embedded in the weak nuclear form…

Nuclear Theory · Physics 2023-04-27 N. Van Dessel , V. Pandey , H. Ray , N. Jachowicz

There is intense interest in uncovering design rules that govern the formation of various structural phases as a function of chemical composition in multi-principal element alloys (MPEAs). In this paper, we develop a machine learning (ML)…

Materials Science · Physics 2022-06-22 Kyungtae Lee , Mukil Ayyasamy , Paige Delsa , Timothy Q. Hartnett , Prasanna V. Balachandran

Distributed scatterers in InSAR (DS-InSAR) processing are essential for retrieving surface deformation in areas lacking strong point targets. Conventional workflows typically involve selecting statistically homogeneous pixels based on…

Applications · Statistics 2025-09-17 Shuyi Yao , Alejandro C. Frery , Timo Balz

Small angle X-ray scattering (SAXS) is extensively used in materials science as a way of examining nanostructures. The analysis of experimental SAXS data involves mapping a rather simple data format to a vast amount of structural models.…

Machine Learning · Computer Science 2021-11-17 Piotr Tomaszewski , Shun Yu , Markus Borg , Jerk Rönnols

Uncertainty quantification (UQ) plays a critical role in verifying and validating forward integrated computational materials engineering (ICME) models. Among numerous ICME models, the crystal plasticity finite element method (CPFEM) is a…

Materials Science · Physics 2023-01-27 Anh Tran , Pieterjan Robbe , Tim Wildey , David Montes de Oca Zapiain , Hojun Lim

Charge-current quasielastic (CCQE) (anti)neutrino scattering cross sections on a $^{12}$C target are analyzed using a spectral function $S(p,{\cal E})$ that gives a scaling function in accordance with the ($e,e'$) scattering data. The…

Rigorous quantum dynamics calculations provide essential insights into complex scattering phenomena across atomic and molecular physics, chemical reaction dynamics, and astrochemistry. However, the application of the gold-standard quantum…

Chemical Physics · Physics 2026-01-06 Hubert J. Jóźwiak , Md Muktadir Rahman , Timur V. Tscherbul

Retrosynthesis prediction is fundamental to drug discovery and chemical synthesis, requiring the identification of reactants that can produce a target molecule. Current template-free methods struggle to capture the structural invariance…

Machine Learning · Computer Science 2025-10-21 Jiaxi Zhuang , Yu Zhang , Aimin Zhou , Ying Qian

We present a new approach to jet definition alternative to clustering methods, such as the anti-$k_T$ scheme, that exploit kinematic data directly. Instead the new method uses kinematic information to represent the particles in a…

High Energy Physics - Phenomenology · Physics 2022-03-09 G. Cerro , S. Dasmahapatra , H. A. Day-Hall , B. Ford , S. Moretti , C. H. Shepherd-Themistocleous

Inverting scattering experiments to obtain effective interparticle interactions is generally a poorly conditioned problem. L. Reatto (Phil. Mag. A 58, 37 (1986)) showed that for atomic liquids close to the triple point, inversions are hard…

Soft Condensed Matter · Physics 2012-01-24 Ard A. Louis

We present a novel application of the multi-modal, multi-level quantum complex exponential least squares (MM-QCELS) algorithm, a state-of-the-art, early fault-tolerant quantum phase estimation (QPE) technique, to the simulation and analysis…

Quantum Physics · Physics 2026-03-04 Antonio Marquez Romero , Josh J. M. Kirsopp , Giuseppe Buonaiuto , Michal Krompiec

Modeling the relationship between chemical structure and molecular activity is a key goal in drug development. Many benchmark tasks have been proposed for molecular property prediction, but these tasks are generally aimed at specific,…

Quantitative Methods · Quantitative Biology 2020-10-05 Samuel G. Finlayson , Matthew B. A. McDermott , Alex V. Pickering , Scott L. Lipnick , Isaac S. Kohane

Small-angle scattering (SAS) intensities observed experimentally are often characterized by the presence of successive power-law regimes with various scattering exponents whose values vary from -4 to -1. This usually indicates multiple…

Statistical Mechanics · Physics 2014-01-31 A. Yu. Cherny , E. M. Anitas , V. A. Osipov , A. I. Kuklin

Sparse principal component analysis (sparse PCA) aims at finding a sparse basis to improve the interpretability over the dense basis of PCA, meanwhile the sparse basis should cover the data subspace as much as possible. In contrast to most…

Machine Learning · Computer Science 2014-05-02 Zhenfang Hu , Gang Pan , Yueming Wang , Zhaohui Wu
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