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Measures of discrepancy between probability distributions (statistical distance) are widely used in the fields of artificial intelligence and machine learning. We describe how certain measures of statistical distance can be implemented as…

Accelerator Physics · Physics 2022-12-21 Chad E. Mitchell , Robert D. Ryne , Kilean Hwang

Since the particles such as molecules, atoms and nuclei are composite particles, it is important to recognize that physics must be invariant for the composite particles and their constituent particles, this requirement is called particle…

High Energy Physics - Theory · Physics 2007-05-23 H. Y. Cui

Most of our knowledge of the physical processes in distant plasmas is obtained through measurement of the radiation they produce. Here we provide an overview of the main collisional and radiative processes and examples of diagnostics…

Solar and Stellar Astrophysics · Physics 2013-03-20 Stephen J. Bradshaw , John C. Raymond

Sphere packings are essential to the development of physical models for powders, composite materials, and the atomic structure of the liquid state. There is a strong scientific need to be able to assess the fit of packing models to data,…

Methodology · Statistics 2009-10-31 Jeffrey Picka

We use the PyNeb 1.1.16 Python package to evaluate the atomic datasets available for the spectral modeling of [Fe II] and [Fe III], which list level energies, A-values, and effective collision strengths. Most datasets are reconstructed from…

The Axelrod approximation is widely used in astrophysical modelling codes to evaluate electron-impact excitation effective collision strengths for forbidden transitions. Approximate methods such as this are a necessity for many heavy…

High Energy Astrophysical Phenomena · Physics 2025-09-17 Leo P. Mulholland , Steven J. Bromley , Connor P. Ballance , Stuart A. Sim , Catherine A. Ramsbottom

This paper addresses different aspects of "coupled" model descriptions in computational electromagnetics. This includes domain decomposition, multiscale problems, multiple or hybrid discrete field formulation and multi-physics problems.…

Computational Engineering, Finance, and Science · Computer Science 2023-03-16 Markus Clemens , Sebastian Schöps , Carsten Cimala , Nico Gödel , Simon Runke , Daniel Schmidthäusler , Thomas Timm

In this paper we develop tools for observers to use when analysing nebular spectra for temperatures and metallicities, with two goals: to present a new, simple method to calculate equilibrium electron temperatures for collisionally excited…

Astrophysics of Galaxies · Physics 2013-07-18 David C. Nicholls , Michael A. Dopita , Ralph S. Sutherland , Lisa J. Kewley , Ethan Palay

Thermal fission energy is one of the basic parameters needed in the calculation of antineutrino flux for reactor neutrino experiments. It is useful to improve the precision of the thermal fission energy calculation for current and future…

Nuclear Experiment · Physics 2013-08-09 X. B. Ma , W. L. Zhong , L. Z. Wang , Y. X. Chen , J. Cao

In Starrett and Saumon [Phys. Rev. E 87, 013104 (2013)] a model for the calculation of electronic and ionic structures of warm and hot dense matter was described and validated. In that model the electronic structure of one "atom" in a…

Plasma Physics · Physics 2015-06-22 C. E. Starrett , D. Saumon , J. Daligault , S. Hamel

The negative ion density and temperature are the two fundamental parameters that are necessary to quantify the properties of electronegative discharges. However, determining these parameters by means of electrostatic probes can be quite…

Plasma Physics · Physics 2021-09-21 Pawandeep Singh , Shantanu Kumar Karkari

Atomic frequency standards are used to generate accurate and precise time and frequency, enabling many communications, synchronization, and navigation systems in modern life. GPS and other satellite navigation systems, voice and data…

Atomic Physics · Physics 2020-04-22 Bonnie L. Schmittberger , David R. Scherer

Statistical learning algorithms are finding more and more applications in science and technology. Atomic-scale modeling is no exception, with machine learning becoming commonplace as a tool to predict energy, forces and properties of…

Chemical Physics · Physics 2020-12-09 Félix Musil , Michele Ceriotti

We prescribe the minimal set of experimental data and parameters that should be reported for random-laser experiments and models. This prescript allows for a quantitative comparison between different experiments, and for a criterion whether…

Disordered Systems and Neural Networks · Physics 2009-11-11 Karen L. van der Molen , Allard P. Mosk , Ad Lagendijk

We discuss the use of the Born and Markov approximations in describing the dynamics of an atom laser. In particular, we investigate the applicability of the quantum optical Born-Markov master equation for describing output coupling. We…

Quantum Physics · Physics 2009-10-31 G. M. Moy , J. J. Hope , C. M. Savage

Plasma accelerators are rapidly evolving toward user-relevant machines with increasing repetition rates, particle energies and average beam powers. Despite their compact size, the operational characteristics of plasma accelerators are…

In this report, we present a wide variety of ways in which information from multiple probes of dark energy may be combined to obtain additional information not accessible when they are considered separately. Fundamentally, because all major…

Cosmology and Nongalactic Astrophysics · Physics 2014-03-14 J. Rhodes , S. Allen , B. A. Benson , T. Chang , R. de Putter , S. Dodelson , O. Dore , K. Honscheid , E. Linder , B. Menard , J. Newman , B. Nord , E. Rozo , A. Vallinotto , D. Weinberg

We present a detailed model of the discrete X-ray spectroscopic features expected from steady-state, low-density photoionized plasmas. We apply the Flexible Atomic Code (FAC) to calculate all of the necessary atomic data for the full range…

Astrophysics · Physics 2007-05-23 A. Kinkhabwala , E. Behar , M. Sako , M. F. Gu , S. M. Kahn , F. B. S. Paerels

Computer simulation models are widely used to study complex physical systems. A related fundamental topic is the inverse problem, also called calibration, which aims at learning about the values of parameters in the model based on…

Methodology · Statistics 2024-01-03 Yang Li , Shifeng Xiong

Achieving the ultimate precisions for multiple parameters simultaneously is an outstanding challenge in quantum physics, because the optimal measurements for incompatible parameters cannot be performed jointly due to the Heisenberg…

Quantum Physics · Physics 2023-10-12 Binke Xia , Jingzheng Huang , Hongjing Li , Han Wang , Guihua Zeng