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DOE OSTI2021

Statistical analysis of correlations in the x-ray induced Coulomb explosion of iodopyridine

Coulomb explosion imaging is a promising experimental tool to study individual molecules. Here, in this work simulation data for the x-ray induced Coulomb explosion of 2-iodopyridine is analyzed and the involved fragmentation dynamics are described. It is found that particular final ion momenta show correlations that reflect a collision of two atoms during the explosion. Variations of the proton kinetic energies can be associated with variations in the charge build-up time. Covariances of the forces during the explosion can be utilized to simplify the description of the dynamics in reduced dimensionality using only four collective coordinates.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2017

Phase-space dynamics of runaway electrons in magnetic fields

Dynamics of runaway electrons in magnetic fields are governed by the competition of three dominant physics: parallel electric field acceleration, Coulomb collision, and synchrotron radiation. Examination of the energy and pitch-angle flows reveals that the presence of local vortex structure and global circulation is crucial to the saturation of primary runaway electrons. Models for the vortex structure, which has an O-point to X-point connection, and the bump of runaway electron distribution in energy space have been developed and compared against the simulation data. Lastly, identification of these velocity-space structures opens a new venue to re-examine the conventional understanding of runaway electron dynamics in magnetic fields.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Electron cyclotron drift instability and anomalous transport: two-fluid moment theory and modeling

In the presence of a strong electric field perpendicular to the magnetic field, the electron cross-field (E × B) flow relative to the unmagnetized ions can cause the so-called electron cyclotron drift instability (ECDI) due to resonances of the ion acoustic mode and the electron cyclotron harmonics. This occurs in, for example, collisionless shock ramps in space, and in E × B discharge devices such as Hall thrusters. A prominent feature of ECDI is its capability to induce an electron flow parallel to the background >E field at a speed greatly exceeding predictions by classical collision theory. Such anomalous transport is important due to its role in particle thermalization at space shocks, and in causing plasma flows towards the walls of E × B devices, leading to unfavorable erosion and performance degradation, etc. The development of ECDI and anomalous transport is often considered requiring a fully kinetic treatment. In this work, however, we demonstrate that a reduced variant of this instability, and more importantly, the associated anomalous transport, can be treated self-consistently in a collisionless two-fluid framework without any adjustable collision parameter. By treating both electron and ion species on an equal footing, the free energy due to the inter-species velocity shear allows the growth of an anomalous electron flow parallel to the background E field. We will first present linear analyses of the instability in the two-fluid five- and ten-moment models, and compare them against the fully-kinetic theory. At low temperatures, the two-fluid models predict the fastest-growing mode in good agreement with the kinetic result. Also, by including more (> = 10) moments, secondary (and possibly higher) unstable branches can be recovered. The dependence of the instability on ion-to-electron mass ratio, plasma temperature, and background B field strength is also thoroughly explored. We then carry out direct numerical simulations of the cross-field setup using the five-moment model. The development of the instability, as well as the anomalous transport, is confirmed and in excellent agreement with theoretical predictions. The force balance properties are also studied using the five-moment simulation data. Here this work casts new insights into the nature of ECDI and the associated anomalous transport and demonstrates the potential of the two-fluid moment model in efficient modeling of E × B plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Unorthodox parallelization for Bayesian quantum state estimation

Quantum state tomography (QST) allows for the reconstruction of quantum states through measurements and some inference technique under the assumption of repeated state preparations. Bayesian inference provides a promising platform to achieve both efficient QST and accurate uncertainty quantification, yet is generally plagued by the computational limitations associated with long Markov chains. In this work, we present a novel Bayesian QST approach that leverages modern distributed parallel computer architectures to efficiently sample a D-dimensional Hilbert space. Using a parallelized preconditioned Crank–Nicholson Metropolis–Hastings algorithm, we demonstrate our approach on simulated data and experimental results from IBM Quantum systems up to four qubits, showing significant speedups through parallelization. Although highly unorthodox in pooling independent Markov chains, our method proves remarkably practical, with validation ex post facto via diagnostics like the intrachain autocorrelation time. We conclude by discussing scalability to higher-dimensional systems, offering a path toward efficient and accurate Bayesian characterization of large quantum systems.

Bayesian inference↗

DOE OSTI2017

Prospects for distinguishing dark matter models using annual modulation

It has recently been demonstrated that, in the event of a putative signal in dark matter direct detection experiments, properly identifying the underlying dark matter-nuclei interaction promises to be a challenging task. Given the most optimistic expectations for the number counts of recoil events in the forthcoming Generation 2 experiments, differentiating between interactions that produce distinct features in the recoil energy spectra will only be possible if a strong signal is observed simultaneously on a variety of complementary targets. However, there is a wide range of viable theories that give rise to virtually identical energy spectra, and may only differ by the dependence of the recoil rate on the dark matter velocity. In this work, we investigate how degeneracy between such competing models may be broken by analyzing the time dependence of nuclear recoils, i.e. the annual modulation of the rate. For this purpose, we simulate dark matter events for a variety of interactions and experiments, and perform a Bayesian model-selection analysis on all simulated data sets, evaluating the chance of correctly identifying the input model for a given experimental setup. Lastly, we find that including information on the annual modulation of the rate may significantly enhance the ability of a single target to distinguish dark matter models with nearly degenerate recoil spectra, but only with exposures beyond the expectations of Generation 2 experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

An accurate perturbative approach to redshift space clustering of biased tracers in modified gravity

We extend the scale-dependent Gaussian Streaming Model (GSM) to produce analytical predictions for the anisotropic redshift-space correlation function for biased tracers in modified gravity models. Employing the Convolution Lagrangian Perturbation Theory (CLPT) re-summation scheme, with a local Lagrangian bias schema provided by the peak-background split formalism, we predict the necessary ingredients that enter the GSM, the real-space halo pairwise velocity and the pairwise velocity dispersion. We further consider effective field theory contributions to the pairwise velocity dispersion in order to model correctly its large scale behavior. We apply our method on two widely-considered modified gravity models, the chameleon-screened ƒ(R) Hu-Sawicki model and the nDGP Vainshtein model and compare our predictions against state-of-the-art N-body simulations for these models. We demonstrate that the GSM approach to predict the monopole and the quadrupole of the redshift-space correlation function for halos, gives very good agreement with the simulation data, for a wide range of screening mechanisms, levels of screening and halo masses at z = 0.5 and z = 1. Our work shows the applicability of the GSM, for cosmologies beyond GR, demonstrating that it can serve as a powerful predictive tool for the next stage of cosmological surveys like DESI, Euclid, LSST and WFIRST.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Muon flux measurement at China Jinping Underground Laboratory

China Jinping Underground Laboratory (CJPL) is ideal for studying solar, geo-, and supernova neutrinos. A precise measurement of the cosmic-ray background is essential in proceeding with R&D research for these MeV-scale neutrino experiments. Using a 1-ton prototype detector for the Jinping Neutrino Experiment (JNE), we detected 264 high-energy muon events from a 645.2-day dataset from the first phase of CJPL (CJPL-I), reconstructed their directions, and measured the cosmic-ray muon flux to be $(3.53\pm0.22_{\rm{stat.}}\pm0.07_{\rm{sys.}})\times10^{-10}$ cm $^{-2}$s $^{-1}$. The observed angular distributions indicate the leakage of cosmic-ray muon background and agree with simulation data accounting for Jinping mountain's terrain. A survey of muon fluxes at different laboratory locations, considering both those situated under mountains and those down mine shafts, indicates that the flux at the former is generally a factor of $(4\pm2)$ larger than at the latter, with the same vertical overburden. In conclusion, this study provides a convenient back-of-the-envelope estimation for the muon flux of an underground experiment.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

Simulation of convective transport during frequency chirping of a TAE using the MEGA code

Here, we present a procedure to examine energetic particle phase-space during long range frequency chirping phenomena in tokamak plasmas. To apply the proposed method, we have performed self-consistent simulations using the MEGA code and analyzed the simulation data. We demonstrate a traveling wave in phase-space and that there exist specific slices of phase-space on which the resonant particles lie throughout the wave evolution. For non-linear evolution of an n = 6 toroidicity-induced Alfvén eigenmode (TAE), our results reveal the formation of coherent phase-space structures (holes/clumps) after coarse-graining of the distribution function. These structures cause a convective transport in phase-space which implies a radial drift of the resonant particles. We also demonstrate that the rate of frequency chirping increases with the TAE damping rate. Our observations of the TAE behavior and the corresponding phase-space dynamics are consistent with the Berk–Breizman theory.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Tailoring resonant magnetic perturbation to optimize fast-ion confinement during ELM control in KSTAR

Abstract 3D resonant magnetic perturbation (RMP) is one promising way to control edge localized modes that can cause excessive material erosion of tokamak first walls. However, RMP can lead to undesired degradation of plasma confinement, including fast-particle losses, which can impact the performance and safety of the reactor. This work investigates the optimization of the poloidal spectrum of the 3D field to optimize fast ion confinement during edge localized mode (ELM) suppression. In the initial step, the validity of the modeling framework is tested against experimental data. Simulations successfully replicate an increase in poloidal limiter temperature with different poloidal spectra. Then, the simulation shows improvement of fast ion confinement with a reduction of core resonant response, while edge resonant magnetic fields are maintained above the threshold to sustain the ELM suppression. Reduction of the core resonant fields keeps the Kolmogorov–Arnold–Moser surface and reduces the fast particle losses due to the stochastic magnetic field lines. The results highlight the potential of edge localization of the resonant fields to enhance the performance of fusion reactors, but further investigation is needed to improve the validation of this approach.

3D field↗

DOE OSTI2020

Comparison of Rotor Wake Identification and Characterization Methods for the Analysis of Wake Dynamics and Evolution

Optimal wind power plant design requires understanding of wind turbine wake physics and validation of engineering wake models under wake-controlled operating conditions. In this work, we have developed and investigated several different wake identification and characterization methods for analyzing wake evolution and dynamics. The accuracy and robustness of these methods, based on Gaussian function fitting and adaptive contour identification, have been assessed by application to a large-eddy simulation data set. A new contour-based method based on downstream momentum deficit has been considered. Uncertainties arising from wake-identification errors result in characterizations of the wake expansion, recovery, and meandering motion that differ by 19% of the rotor area, 4% of the freestream, and 15% rotor diameter, respectively.

17 WIND ENERGY↗

DOE OSTI2023

Evaluation of Portable Programming Models to Accelerate LArTPC Detector Simulations

The Liquid Argon Time Projection Chamber (LArTPC) technology is widely used in high energy physics experiments, including the upcoming Deep Underground Neutrino Experiment (DUNE). Accurately simulating LArTPC detector responses is essential for analysis algorithm development and physics model interpretations. Accurate LArTPC detector response simulations are computationally demanding, and can become a bottleneck in the analysis workflow. Compute devices such as General-Purpose Graphics Processing Units (GPGPUs) have the potential to substantially accelerate simulations compared to traditional CPU-only processing. The software development for these compute accelerators often carries the cost of specialized code refactorization and porting to match the target hardware architecture. With the rapid evolution and increased diversity of the computer architecture landscape, it is highly desirable to have a portable solution that also maintains reasonable performance. We report our ongoing effort in evaluating Kokkos as a basis for this portable programming model using LArTPC simulations in the context of the Wire-Cell Toolkit, a C++ library for LArTPC simulations, data analysis, reconstruction and visualization.

47 OTHER INSTRUMENTATION↗

DOE OSTI2017

Application and performance of an ML-EM algorithm in NEXT

The goal of the NEXT experiment is the observation of neutrinoless double beta decay in (136)Xe using a gaseous xenon TPC with electroluminescent amplification and specialized photodetector arrays for calorimetry and tracking. The NEXT Collaboration is exploring a number of reconstruction algorithms to exploit the full potential of the detector. This paper describes one of them: the Maximum Likelihood Expectation Maximization (ML-EM) method, a generic iterative algorithm to find maximum-likelihood estimates of parameters that has been applied to solve many different types of complex inverse problems. In particular, we discuss a bi-dimensional version of the method in which the photosensor signals integrated over time are used to reconstruct a transverse projection of the event. First results show that, when applied to detector simulation data, the algorithm achieves nearly optimal energy resolution (better than 0.5% FWHM at the Q value of (136)Xe) for events distributed over the full active volume of the TPC.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Flow annealed importance sampling bootstrap meets differentiable particle physics

High-energy physics requires the generation of large numbers of simulated data samples from complex but analytically tractable distributions called matrix elements. Surrogate models, such as normalizing flows, are gaining popularity for this task due to their computational efficiency. We adopt an approach based on flow annealed importance sampling bootstrap (FAB) that evaluates the differentiable target density during training and helps avoid the costly generation of training data in advance. We show that FAB reaches higher sampling efficiency with fewer target evaluations in high dimensions in comparison to other methods.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Simulation driven adaptive sampling for neutron-diffraction based strain mapping of additively manufactured parts

Neutron diffraction based strain mapping is a useful technique for measuring residual strains in additively manufactured (AM) metal parts. The measurement is traditionally done by scanning the sample in a point-wise raster pattern to extract the strain at each position. Since the overall scan can span several hours, adaptive sampling approaches using Bayesian optimization based on Gaussian process (BO-GP) regression have been introduced—demonstrating that even with a fraction of the typically made measurements the dominant strain patterns in the sample can be reconstructed. However, the parameters of the BO-GP algorithm have to be carefully chosen for best performance, and the movement time between arbitrary points can offset the time savings from a reduced number of measurement locations. In this paper, we propose algorithms to refine the BO-GP based methods by using simulations of strain patterns in AM parts based on the materials and the process used to print them. We demonstrate that the simulated strain patterns can be used to help choose better parameters for the BO-GP based framework—leading to low reconstruction error for the final strain pattern. Furthermore, we show that the strain mapping experiment can be initialized with a sampling pattern learnt from the simulation data and ordered to reduce movement time, dramatically enabling reduction in the overall time required to run the baseline BO-GP method.

Gaussian process regression↗

DOE OSTI2018

Measuring phylogenetic signal between categorical traits and phylogenies

Abstract Motivation Determining whether a trait and phylogeny share some degree of phylogenetic signal is a flagship goal in evolutionary biology. Signatures of phylogenetic signal can assist the resolution of a broad range of evolutionary questions regarding the tempo and mode of phenotypic evolution. However, despite the considerable number of strategies to measure it, few and limited approaches exist for categorical traits. Here, we used the concept of Shannon entropy and propose the δ statistic for evaluating the degree of phylogenetic signal between a phylogeny and categorical traits. Results We validated δ as a measure of phylogenetic signal: the higher the δ-value the higher the degree of phylogenetic signal between a given tree and a trait. Based on simulated data we proposed a threshold-based classification test to pinpoint cases of phylogenetic signal. The assessment of the test’s specificity and sensitivity suggested that the δ approach should only be applied to 20 or more species. We have further tested the performance of δ in scenarios of branch length and topology uncertainty, unbiased and biased trait evolution and trait saturation. Our results showed that δ may be applied in a wide range of phylogenetic contexts. Finally, we investigated our method in 14 360 mammalian gene trees and found that olfactory receptor genes are significantly associated with the mammalian activity patterns, a result that is congruent with expectations and experiments from the literature. Our application shows that δ can successfully detect molecular signatures of phenotypic evolution. We conclude that δ represents a useful measure of phylogenetic signal since many phenotypes can only be measured in categories. Availability and implementation https://github.com/mrborges23/delta_statistic. Supplementary information Supplementary data are available at Bioinformatics online.

Borges, Rui↗

DOE OSTI2022

Estimating the local dark matter density in a non-axisymmetric wobbling disc

The density of dark matter near the Sun, ρDM, ⊙, is important for experiments hunting for dark matter particles in the laboratory, and for constraining the local shape of the Milky Way’s dark matter halo. Estimates to date have typically assumed that the Milky Way’s stellar disc is axisymmetric and in a steady-state. Yet the Milky Way disc is neither, exhibiting prominent spiral arms and a bar, and vertical and radial oscillations. Here, we assess the impact of these assumptions on determinations of ρDM, ⊙ by applying a free-form, steady-state, Jeans method to two different N-body simulations of Milky Way-like galaxies. In one, the galaxy has experienced an ancient major merger, similar to the hypothesized Gaia–Sausage–Enceladus; in the other, the galaxy is perturbed more recently by the repeated passage and slow merger of a Sagittarius-like dwarf galaxy. We assess the impact of each of the terms in the Jeans–Poisson equations on our ability to correctly extract ρDM, ⊙ from the simulated data. We find that common approximations employed in the literature – axisymmetry and a locally flat rotation curve – can lead to significant systematic errors of up to a factor ~1.5 in the recovered surface mass density ~2 kpc above the disc plane, implying a fractional error on ρDM, ⊙ of the order of unity. However, once we add in the tilt term and the rotation curve term in our models, we obtain an unbiased estimate of ρDM, ⊙, consistent with the true value within our 95 percent confidence intervals for realistic 20 percent uncertainties on the baryonic surface density of the disc. Other terms – the axial tilt, 2nd Poisson and time-dependent terms – contribute less than 10 percent to ρDM, ⊙ (given current data) and can be safely neglected for now. In the future, as more data become available, these terms will need to be included in the analysis.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

A novel approach for calculating galaxy rotation curves using spaxel cross-correlation and iterative smoothing

ABSTRACT Precise measurements of the internal dynamics of galaxies have proven of great importance for understanding the internal dark matter distribution of galaxies. We present a novel method for measuring the line-of-sight (LOS) velocities across the face of galaxies by cross-correlation of spectral pixels (spaxels) and an iterative method of smoothing. On simulated data the method can accurately recover the input LOS velocities for different types of spectra (absorption-line dominated, emission-line dominated, and differing shapes of the continuum), and can handle stellar population radial gradients. Most important of all, it continues to provide reliable measurements of LOS velocities with reasonable uncertainties even when the spectra are very low signal-to-noise ratio (approaching ∼1), which is a challenge for traditional template-fitting approaches. We apply our method to data from a real MaNGA galaxy as a demonstration and find promising results with good precision. This novel approach can be complementary to existing methods primarily based on template fitting.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

KilonovaNet : Surrogate models of kilonova spectra with conditional variational autoencoders

ABSTRACT Detailed radiative transfer simulations of kilonova spectra play an essential role in multimessenger astrophysics. Using the simulation results in parameter inference studies requires building a surrogate model from the simulation outputs to use in algorithms requiring sampling. In this work, we present kilonovanet, an implementation of conditional variational autoencoders (cVAEs) for the construction of surrogate models of kilonova spectra. This method can be trained on spectra directly, removing overhead time of pre-processing spectra, and greatly speeds up parameter inference time. We build surrogate models of three state-of-the-art kilonova simulation data sets and present in-depth surrogate error evaluation methods, which can in general be applied to any surrogate construction method. By creating synthetic photometric observations from the spectral surrogate, we perform parameter inference for the observed light-curve data of GW170817 and compare the results with previous analyses. Given the speed with which kilonovanet performs during parameter inference, it will serve as a useful tool in future gravitational wave observing runs to quickly analyse potential kilonova candidates.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗