Distribution functions of probabilistic automata
In this paper we present a detailed study of distribution function of probabilistic automata.
probabilistic↗
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Heating and acceleration of ions with Kappa distribution functions by low‐frequency Alfvén wave
Abstract Heating and acceleration of ions with Kappa distribution functions (with parameter ) in low‐beta plasmas, by a low‐frequency Alfvén wave, is investigated using test‐particle simulations, yielding interesting new results. As long as the Alfvén wave amplitude is sufficiently large, the computed net heating energy of ions becomes independent of the wave frequency and amplitude, always approaching the same value of . The eventual energy of ions is dictated only by the initial ion energy and the ratio of the magnetic field energy density to the plasma density. The heating effect of the Kappa ions increases with . During the heating process, the ions are picked up by the Alfvén wave and pitch angle scattered, forming a quasi‐isotropic spherical shell velocity distribution. The Kappa ions are accelerated in the parallel direction, reaching a bulk flow speed roughly equal to the local Alfvén speed. Higher ‐value in the initial Kappa distribution leads to faster saturation. The above results may explain certain features of the ion heating and acceleration in the solar wind and corona.
Li, Kehua↗
Electron distribution functions associated with electrostatic emissions in the dayside magnetosphere
The analysis deals with electron distribution functions constructed from ISEE-1 dayside observations of low-energy magnetospheric electrons at low latitudes. The discussion covers some examples corresponding to three distinct types of odd half harmonic electrostatic emissions, observed in the plasma wave experiment on ISEE-1, which occur between the electron cyclotron frequency and the upper hybrid frequency.
Sentman, D. D.↗
How Is the Solar Wind Shocked? A Distribution-Function Perspective From the MMS Mission
In this talk, we will discuss how plasma distribution functions from the Magnetospheric Multiscale (MMS) mission transformed the picture on how the solar wind is shocked. For quasi-parallel shocks with typical Alfven Mach numbers, we will examine how ion deceleration, reflection, and thermalization take place, and illustrate how the new picture expands on the framework envisioned by Schwartz and Burgess in 1991. For quasi-perpendicular shocks with the range of Alfven Mach numbers (~1-60) captured by MMS, we will examine examples showing the processes of ion and electron thermalization go beyond the existing paradigm and call for future investigation. The knowledge advanced by MMS measurements provides a ground to understand planetary shocks in our solar system as well as astrophysical shocks arising from stellar wind interaction with exoplanets and supernova remnants.
Li-Jen Chen↗
SAS PDF: pair distribution function analysis of nanoparticle assemblies from small-angle scattering data
SASPDF, a method for characterizing the structure of nanoparticle assemblies (NPAs), is presented. The method is an extension of the atomic pair distribution function (PDF) analysis to the small-angle scattering (SAS) regime. The PDFgetS3 software package for computing the PDF from SAS data is also presented. An application of the SASPDF method to characterize structures of representative NPA samples with different levels of structural order is then demonstrated. The SASPDF method quantitatively yields information such as structure, disorder and crystallite sizes of ordered NPA samples. The method was also used to successfully model the data from a disordered NPA sample. The SASPDF method offers the possibility of more quantitative characterizations of NPA structures for a wide class of samples.
77 NANOSCIENCE AND NANOTECHNOLOGY↗
Reconstruction of Electron and Ion Distribution Functions in a Magnetotail Reconnection Diffusion Region
In the diffusion region of magnetotail reconnection, particle distributions are highly structured, exhibiting triangular shapes and multiple striations that deviate dramatically from the Maxwellian distribution. Fully kinetic simulations have been demonstrated to be capable of producing the essential structures of the observed distribution functions, yet are computationally not feasible for 3D global simulations. The fluid models used for large-scale simulations, on the other hand, do not have the kinetic physics necessary for describing reconnection accurately. Our study aims to bridge fully kinetic and fluid simulations by quantifying the information required to capture the non-Maxwellian features in the distributions underlying the closures used in the fluid code. Here, we compare the results of fully kinetic simulations with observed electron velocity distributions in a magnetotail reconnection diffusion region and use the maximum entropy model to reconstruct electron and ion distributions using various numbers of moments obtained from the simulation. Our results indicate that using only local moments, the maximum entropy model can reproduce many of the features of the distributions: (1) the electron outflow distribution with a tilted triangular structure is reproduced with 21 or more moments in agreement with Ng et al. and (2) counterstreaming distributions can be captured with the 35-moment model when the separation in velocity space between the populations is large.
58 GEOSCIENCES↗
Neural-network analysis of Parton Distribution Functions from Ioffe-time pseudodistributions
In this work, we extract two nonsinglet nucleon Parton Distribution Functions from lattice QCD data for reduced Ioffe-time pseudodistributions. We perform such analysis within the NNPDF framework, considering data coming from different lattice ensembles and dis- cussing in detail the treatment of the different source of systematics involved in the fit. We introduce a recipe for taking care of systematics and use it to perform our extraction of light-cone PDFs.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Major Pathways to Electron Distribution Function Formation in Regions of Diffuse Aurora
This paper discusses the major pathways of electron distribution function formation in the region of diffuse aurora. The diffuse aurora accounts for about of 75% of the auroral energy precipitating into the upper atmosphere, and its origin has been the subject of much discussion. We show that an earthward stream of precipitating electrons initially injected from the Earth's plasma sheet via wave-particle interactions degrades in the atmosphere toward lower energies and produces secondary electrons via impact ionization of the neutral atmosphere. These electrons of magnetospheric origin are then reflected back into the magnetosphere along closed dipolar magnetic field lines, leading to a series of reflections and consequent magnetospheric interactions that greatly augment the initially precipitating flux at the upper ionospheric boundary (700-800 km). To date this, systematic magnetosphere-ionosphere coupling element has not been included in auroral research models, and, as we demonstrate in this article, has a dramatic effect (200-300%) on the formation of the precipitating fluxes that result in the diffuse aurora. It is shown that wave-particle interaction processes that drive precipitating fluxes in the region of diffuse aurora from the magnetospheric altitudes are only the first step in the formation of electron precipitation at ionospheric altitudes, and they cannot be separated from the atmospheric collisional machine that redistributes and transfers their energy inside the magnetosphere-ionosphere-atmosphere coupling system.
magnetospheric↗
A 'skewed' lognormal approximation to the probablility distribution function of the large-scale density field
I propose a method to fit the probability distribution function (PDF) of the large-scale density field rho, motivated by a Lagrangian version of the continuity equation. It consists in applying the Edgeworth expansion to the quantity Phi identical with log rho - mean value of log rho. The method is tested on the matter particle distribution in two cold dark matter N-body simulations of different physical sizes to cover a large dynamic range. It is seen to be very efficient, even in the nonlinear regime, and may thus be used as an analytical tool to study the effect on the PDF of the transition between the weakly nonlinear regime and the highly nonlinear regime.
Colombi, S.↗
The continuum and leading twist limits of parton distribution functions in lattice QCD
In this study, we present continuum limit results for the unpolarized parton distribution function of the nucleon computed in lattice QCD. This study is the first continuum limit using the pseudo-PDF approach with Short Distance Factorization for factorizing lattice QCD calculable matrix elements. Our findings are also compared with the pertinent phenomenological determinations. Inter alia, we are employing the summation Generalized Eigenvalue Problem (sGEVP) technique in order to optimize our control over the excited state contamination which can be one of the most serious systematic errors in this type of calculations. A crucial novel ingredient of our analysis is the parameterization of systematic errors using Jacobi polynomials to characterize and remove both lattice spacing and higher twist contaminations, as well as the leading twist distribution. This method can be expanded in further studies to remove all other systematic errors.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Machine-learning prediction for quasiparton distribution function matrix elements
There have been rapid developments in the direct calculation in lattice QCD (LQCD) of the Bjorken-x dependence of hadron structure through large-momentum effective theory (LaMET). LaMET overcomes the previous limitation of LQCD to moments (that is, integrals over Bjorken x) of hadron structure, allowing LQCD to directly provide the kinematic regions where the experimental values are least known. LaMET requires large-momentum hadron states to minimize its systematics and allow us to reach small- x reliably. This means that very fine lattice spacing to minimize lattice artifacts at order $(P_za)^n$ will become crucial for next-generation LaMET-like structure calculations. Furthermore, such calculations require operators with long Wilson-link displacements, especially in finer lattice units, increasing the communication costs relative to that of the propagator inversion. In this work, we explore whether machine-learning algorithms can make predictions of correlators to reduce the computational cost of these LQCD calculations. We consider two algorithms, gradient-boosting decision tree and linear models, applied to LaMET data, the matrix elements needed to determine the kaon and $η_s$ unpolarized parton distribution functions (PDFs), meson distribution amplitude (DA), and the nucleon gluon PDF. We find that both algorithms can reliably predict the target observables with different prediction accuracy and systematic errors. The predictions from smaller displacement z to larger ones work better than those for momentum p due to the higher correlation among the data.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Evolution of parton distribution functions in the short-distance factorization scheme
Lattice QCD offers the possibility of computing parton distributions from first principles, although not in the usual $\overline{MS}$ factorization scheme. Calculations are therefore matched to $\overline{MS}$ using a perturbative procedure which is the source of significant uncertainty within the currently accessible kinematics. We present the possibility of computing the z 2 evolution of non-singlet pseudo-parton distribution functions within the short factorization scheme in a numerically improvable way. The goal is to have tools to evolve a calculation to a scale where perturbative uncertainties are less pronounced. We compare a numerical extraction of the evolution operator from lattice data to the computation of z 2 dependence in perturbation theory. Finally, we discuss how this numerical work may be extended to address the two-scale problem that arises when the Ioffe time range must be made large to extend the reach of the calculation of the pseudo-PDF to smaller values of the momentum fraction.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Moments of parton distribution functions of any order from lattice QCD
We describe a procedure to determine moments of parton distribution functions of any order in lattice quantum chromodynamics (QCD). The procedure is based on the gradient flow for fermion and gauge fields. The flowed matrix elements of twist-2 operators renormalize multiplicatively, and the matching with the physical matrix elements can be obtained using continuum symmetries and the irreducible representations of Euclidean 4-dimensional rotations. We calculate the matching coefficients at one-loop in perturbation theory for moments of any order in the flavor nonsinglet case. We also give specific examples of operators that could be used in lattice QCD computations. It turns out that it is possible to choose operators with identical Lorentz indices and still have a multiplicative matching. One can thus use twist-2 operators exclusively with temporal indices, thus substantially improving the signal-to-noise ratio in the computation of the hadronic matrix elements.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Approximating Density Probability Distribution Functions Across Cosmologies
Using a suite of self-similar cosmological simulations, we measure the probability distribution functions (PDFs) of real-space density, redshift-space density, and their geometric mean. We find that the real-space density PDF is well-described by a function of two parameters: ns, the spectral slope, and σL, the linear rms density fluctuation. For redshift-space density and the geometric mean of real- and redshift-space densities, we introduce a third parameter, ${s}_{L}=\sqrt{\langle {\left({{dv}}_{\mathrm{pec}}^{L}/{dr}\right)}^{2}\rangle }/H$. We find that density PDFs for the LCDM cosmology is also well-parameterized by these three parameters. As a result, we are able to use a suite of self-similar cosmological simulations to approximate density PDFs for a range of cosmologies. We make the density PDFs publicly available and provide an analytical fitting formula for them.
79 ASTRONOMY AND ASTROPHYSICS↗
Minimum mean square error approximation of unknown probability distribution functions.
Double stochastic approximation algorithm for minimizing mean square error in finite expansion of unknown probability distribution functions
Deuser, L. M.↗
The Compton-Getting effect for cosmic-ray particles and photons and the Lorentz- invariance of distribution functions
Compton-Getting effect for cosmic ray particles and photons and Lorentz-invariance of distribution functions, discussing thermal background radiation, proton spectra, etc
Forman, M. A.↗
Bibliometric review and recent advances in total scattering pair distribution function analysis: 21 years in retrospect
Global research activities have been driven by the quest to develop and characterize novel materials for technological advancements. The total scattering pair distribution function (TSPDF) is a powerful and versatile characterization technique for examining the structural details of diverse complex materials including liquid, amorphous, disordered crystalline, and nanostructured materials. Thus, it is critical to keep track of research progress, identify research gaps, and future research directions of the application of the TSPDF technique in materials development and discovery. In this work, a bibliometric analysis of literature regarding the TSPDF technique between 2000 and 2021 was conducted using datasets retrieved from the Web of Science database. The research trends based on publication outputs, research subject distribution, co-authorships among institutions, countries/regions, co-citation of referenced sources, and keyword co-occurrence are evaluated and discussed herein. The impact of the TSPDF technique is projected to increase due to its importance in probing emerging functional materials, and the advances in specialized facilities and instrumentation among the scientific communities engaged with it. Finally, current and emerging research hotspots related to TSPDF technique such as catalysis, computer modeling and simulation, pharmaceutics, machine learning, hydrogen storage, battery materials, and layered structured materials are also identified and discussed.
36 MATERIALS SCIENCE↗
Recovering non-Maxwellian particle velocity distribution functions from collective Thomson-scattered spectra
Collective optical Thomson scattering (TS) is a diagnostic commonly used to characterize plasma parameters. These parameters are typically extracted by a fitting algorithm that minimizes the difference between a measured scattered spectrum and an analytic spectrum calculated from the velocity distribution function (VDF) of the plasma. However, most existing TS analysis algorithms assume that the VDFs are Maxwellian, and applying an algorithm that makes this assumption does not accurately extract the plasma parameters of a non-Maxwellian plasma due to the effect of non-Maxwellian deviations on the TS spectra. We present new open-source numerical tools for forward modeling analytic spectra from arbitrary VDFs and show that these tools are able to more accurately extract plasma parameters from synthetic TS spectra generated by non-Maxwellian VDFs compared to standard TS algorithms. Estimated posterior probability distributions of fits to synthetic spectra for a variety of example non-Maxwellian VDFs are used to determine uncertainties in the extracted plasma parameters and show that correlations between parameters can significantly affect the accuracy of fits in plasmas with non-Maxwellian VDFs.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗