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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Tremaine-Gunn limit with mass-varying particles

General classical arguments on the time evolution of the phase-space density can be used to derive constraints on the mass of particle candidates for the cosmological dark matter (DM). The resulting Tremaine-Gunn limit is extremely useful in constraining particle DM models. In certain models, however, the DM particle mass varies appreciably over time. In this work, we generalize the phase-space limits on possible DM particle masses to these scenarios. We then examine the ensuing cosmological implications on the effective DM equation of state and indirect DM detection.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Pseudorapidity densities of charged particles with transverse momentum thresholds in pp collisions at $\sqrt{s} = 5.02$ and 13 TeV

The pseudorapidity density of charged particles with minimum transverse momentum (p T ) thresholds of 0.15, 0.5, 1, and 2 GeV/c is measured in pp collisions at the center of mass energies of $\sqrt{s}$ = 5.02 and 13 TeV with the ALICE detector. The study is carried out for inelastic collisions with at least one primary charged particle having a pseudorapidity (η) within ± 0.8 and p T larger than the corresponding threshold. In addition, measurements without p T - thresholds are performed for inelastic and nonsingle-diffractive events as well as for inelastic events with at least one charged particle having |η| < 1 in pp collisions at $\sqrt{s}$ = 5.02 TeV for the first time at the LHC. These measurements are compared to the pythia 6, pythia 8, and epos-lhc models. In general, the models describe the η dependence of particle production well. However, discrepancies are observed for the highest transverse momentum threshold (p T > 2 GeV/c), highlighting the importance of such measurements for tuning event generators. The new measurements agree within uncertainties with results from the ATLAS and CMS experiments obtained at $\sqrt{s}$ =13 TeV .

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Absorption of charged particles in perfectly matched layers by optimal damping of the deposited current

Perfectly matched layers (PMLs) are widely used in particle-in-cell simulations, in order to absorb electromagnetic waves that propagate out of the simulation domain. However, when charged particles cross the interface between the simulation domain and the PMLs, a number of numerical artifacts can arise. Here, in order to mitigate these artifacts, we introduce a PML algorithm whereby the current deposited by the macroparticles in the PML is damped by an analytically derived optimal coefficient. The benefits of this algorithm are illustrated in practical simulations. In particular, it is shown that this algorithm is well suited for particles exiting the box in near-normal incidence, in the sense that the fields behave as if the exiting particle is propagating in an infinite vacuum.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Confinement and Collective Escape of Active Particles

Active matter broadly covers the dynamics of self-propelled particles. While the onset of collective behavior in homogenous active systems is relatively well understood, the effect of inhomogeneities such as obstacles and traps lacks overall clarity. Here, we study how interacting, self-propelled particles become trapped and released from a trap. We have found that captured particles aggregate into an orbiting condensate with a crystalline structure. As more particles are added, the trapped condensates escape as a whole. Our results shed light on the effects of confinement and quenched disorder in active matter.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Charged particle motion and radiation in strong electromagnetic fields

The dynamics of charged particles in electromagnetic fields is an essential component of understanding the most extreme environments in our Universe. In electromagnetic fields of sufficient magnitude, radiation emission dominates the particle motion and effects of quantum electrodynamics (QED) in strong fields are crucial, which triggers electron-positron pair cascades and counterintuitive particle-Trapping phenomena. As a result of recent progress in laser technology, high-power lasers provide a platform to create and probe such fields in the laboratory. With new large-scale laser facilities on the horizon and the prospect of investigating these hitherto unexplored regimes, this review explores the basic physical processes of radiation reaction and QED in strong fields, how they are treated theoretically and in simulation, the new collective dynamics they unlock, recent experimental progress and plans, and possible applications for high-flux particle and radiation sources.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Decay of Electrostatic Force of Dust Particles on Photovoltaic Modules

Photovoltaic (PV) energy yield loss due to solar module soiling has become increasingly important as solar module deployment is now at the hundreds of gigawatts scale and continues to grow rapidly. We have reported on direct measurements-using atomic force microscopy (AFM)-of strong electric-field-induced attraction and adhesion force (Fes) of dust particles onto solar panel that are 1 to 2 orders of magnitude stronger than the van der Waals and water capillary forces, corroborated by observing the increase in system voltage-induced soiling rate. Here, we report another characteristic of Fes on soiling-long lasting or slow decay after turning off the high voltage applied to solar panels. The Fes decay time varies in a wide time range of 1 to 10 hours, depending on two factors: 1) either/both the cell or/and particle were charged with high voltage before the voltages were turned off; and 2) how the cell was connected to the ground after the voltage was turned off-either connected through the power supply electronics, directly connected to the ground, or electrically floated. The Fes decay is understood in terms of 1) net electrical charge dissipations in both particle and cell, 2) thermal disordering of dipole polarization in the module glass dielectrics, and 3) charge redistribution by the electrostatic interaction of particle and module glass. This long-lasting Fes for hours can significantly affect the solar panel soiling after sunset, especially combined with water condensation.

14 SOLAR ENERGY↗
DOE OSTI2023

Reinforcement Learning for Load-balanced Parallel Particle Tracing

We explore an online reinforcement learning (RL) paradigm to dynamically optimize parallel particle tracing performance in distributed-memory systems. Our method combines three novel components: (1) a work donation algorithm, (2) a high-order workload estimation model, and (3) a communication cost model. First, we design an RL-based work donation algorithm. Our algorithm monitors workloads of processes and creates RL agents to donate data blocks and particles from high-workload processes to low-workload processes to minimize program execution time. The agents learn the donation strategy on the fly based on reward and cost functions designed to consider processes' workload changes and data transfer costs of donation actions. Second, we propose a workload estimation model, helping RL agents estimate the workload distribution of processes in future computations. Third, we design a communication cost model that considers both block and particle data exchange costs, helping RL agents make effective decisions with minimized communication costs. We demonstrate that our algorithm adapts to different flow behaviors in large-scale fluid dynamics, ocean, and weather simulation data. Our algorithm improves parallel particle tracing performance in terms of parallel efficiency, load balance, and costs of I/O and communication for evaluations with up to 16,384 processors.

Distributed and parallel particle tracing↗
DOE OSTI2021

Pseudorapidity distributions of charged particles as a function of mid- and forward rapidity multiplicities in pp collisions at $\sqrt{s}$ = 5.02, 7 and 13 TeV

The multiplicity dependence of the pseudorapidity density of charged particles in proton–proton (pp) collisions at centre-of-mass energies √s = 5.02, 7 and 13 TeV measured by ALICE is reported. The analysis relies on track segments measured in the midrapidity range (|η| < 1.5). Results are presented for inelastic events having at least one charged particle produced in the pseudorapidity interval |η| < 1. The multiplicity dependence of the pseudorapidity density of charged particles is measured with mid- and forward rapidity multiplicity estimators, the latter being less affected by autocorrelations. A detailed comparison with predictions from the PYTHIA 8 and EPOS LHC event generators is also presented. The results can be used to constrain models for particle production as a function of multiplicity in pp collisions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Investigating charm production and fragmentation via azimuthal correlations of prompt D mesons with charged particles in pp collisions at $\mathbf {\sqrt{ s} = 13}$ TeV

Angular correlations of heavy-flavour and charged particles in high-energy proton–proton collisions are sensitive to the production mechanisms of heavy quarks and to their fragmentation as well as hadronisation processes. The measurement of the azimuthal-correlation function of prompt D mesons with charged particles in proton–proton collisions at a centre-of-mass energy of \(\sqrt{s} = 13\) TeV with the ALICE detector is reported, considering \(\mathrm D^{0} \) , \(\mathrm D^{+} \) , and \(\mathrm D^{*+} \) mesons in the transverse-momentum interval \(3< p_{\mathrm{T}} < 36\) GeV/ \(c\) at midrapidity ( \(|y| < 0.5\) ), and charged particles with \(p_{\mathrm{T}} > 0.3\) GeV/ \(c\) and pseudorapidity \(|\eta | < 0.8\) . This measurement has an improved precision and provides an extended transverse-momentum coverage compared to previous ALICE measurements at lower energies. The study is also performed as a function of the charged-particle multiplicity, showing no modifications of the correlation function with multiplicity within uncertainties. The properties and the transverse-momentum evolution of the near- and away-side correlation peaks are studied and compared with predictions from various Monte Carlo event generators. Among those considered, PYTHIA8 and POWHEG+PYTHIA8 provide the best description of the measured observables. The obtained results can provide guidance on tuning the generators.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Multiplicity dependence of charged-particle jet production in pp collisions at $\sqrt{s}$ = 13 TeV

The multiplicity dependence of jet production in pp collisions at the centre-of-mass energy of $\sqrt{s}$ = 13 TeV is studied for the first time. Jets are reconstructed from charged particles using the anti-$k_T$ algorithm with resolution parameters $\textit{R}$ varying from 0.2 to 0.7. The jets are measured in the pseudorapidity range |$η_{\text{jet}}$| < 0.9 – $\textit{R}$ and in the transverse momentum range 5 < $p^{ch}_{\text{T,jet}}$ < 140 GeV/c. The multiplicity intervals are categorised by the ALICE forward detector V0. The $p_T$ differential cross section of charged-particle jets are compared to leading order (LO) and next-to-leading order (NLO) perturbative quantum chromodynamics (pQCD) calculations. It is found that the data are better described by the NLO calculation, although the NLO prediction overestimates the jet cross section below 20 GeV/c. The cross section ratios for different $\textit{R}$ are also measured and compared to model calculations. These measurements provide insights into the angular dependence of jet fragmentation. The jet yield increases with increasing self-normalised charged-particle multiplicity. This increase shows only a weak dependence on jet transverse momentum and resolution parameter at the highest multiplicity. While such behaviour is qualitatively described by the present version of PYTHIA, quantitative description may require implementing new mechanisms for multi-particle production in hadronic collisions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Reproducibility and Replication of Experimental Particle Physics Results

Recently, much attention has been focused on the replicability of scientific results, causing scientists, statisticians, and journal editors to examine closely their methodologies and publishing criteria. Experimental particle physicists have been aware of the precursors of non-replicable research for many decades and have many safeguards to ensure that the published results are as reliable as possible. The experiments require large investments of time and effort to design, construct, and operate. Large collaborations produce and check the results, and many papers are signed by more than three thousand authors. This paper gives an introduction to what experimental particle physics is and to some of the tools that are used to analyze the data. It describes the procedures used to ensure that results can be computationally reproduced, both by collaborators and by non-collaborators. It describes the status of publicly available data sets and analysis tools that aid in reproduction and recasting of experimental results. It also describes methods particle physicists use to maximize the reliability of the results, which increases the probability that they can be replicated by other collaborations or even the same collaborations with more data and new personnel. Examples of results that were later found to be false are given, both with failed replication attempts and one with alarmingly successful replications. While some of the characteristics of particle physics experiments are unique, many of the procedures and techniques can be and are used in other fields.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Water mass age structures the auxiliary metabolic gene content of free-living and particle-attached deep ocean viral communities

Viruses play important roles in the ocean’s biogeochemical cycles. Yet, deep ocean viruses are one of the most under-explored fractions of the global biosphere. Little is known about the environmental factors that control the composition and functioning of their communities or how they interact with their free-living or particle-attached microbial hosts. We analysed 58 viral communities associated with size-fractionated free-living (0.2–0.8 μm) and particle-attached (0.8–20 μm) cellular metagenomes from bathypelagic (2150–4018 m deep) microbiomes obtained during the Malaspina expedition. These metagenomes yielded 6631 viral sequences, 91% of which were novel, and 67 represented high-quality genomes. Taxonomic classification assigned 53% of the viral sequences to families of tailed viruses from the order Caudovirales. Computational host prediction associated 886 viral sequences to dominant members of the deep ocean microbiome, such as Alphaproteobacteria (284), Gammaproteobacteria (241), SAR324 (23), Marinisomatota (39), and Chloroflexota (61). Free-living and particle-attached viral communities had markedly distinct taxonomic composition, host prevalence, and auxiliary metabolic gene content, which led to the discovery of novel viral-encoded metabolic genes involved in the folate and nucleotide metabolisms. Water mass age emerged as an important factor driving viral community composition. We postulated this was due to changes in quality and concentration of dissolved organic matter acting on the host communities, leading to an increase of viral auxiliary metabolic genes associated with energy metabolism among older water masses. These results shed light on the mechanisms by which environmental gradients of deep ocean ecosystems structure the composition and functioning of free-living and particle-attached viral communities.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Skyrmion soliton motion on periodic substrates by atomistic and particle-based simulations

Abstract We compare the dynamical behavior of magnetic skyrmions interacting with square and triangular defect arrays just above commensuration using both atomistic and particle-based models. Under applied drives, the initial motion is a kink traveling through the pinned skyrmion lattice. For the square defect array, both models agree well and show a regime in which the soliton motion is locked along 45°. The atomistic model also produces locking of a soliton along 30°, which is absent in the particle-based model. For the triangular defect array, the atomistic model exhibits 30° soliton motion over a wide region of external current values. In contrast, the particle-based model gives 45° soliton motion over a small range of external driving force values. The difference arises because the nondeforming particle model facilitates meandering skyrmion orbits while the deformable atomistic model enables stronger skyrmion-skyrmion interactions that reduce the meandering. Our results indicate that soliton motion through pinned skyrmion lattices on a periodic substrate is a robust effect.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Improving High-Energy Particle Detectors with Machine Learning

Microseconds after the Big Bang, the universe existed in a state called the quark-gluon plasma (QGP). To experimentally study its properties, the QGP is recreated in high-energy nuclear collisions at the LHC, and the particles produced from the QGP are reconstructed from their energy deposition in the ATLAS calorimeter. This requires both classifying the particles and calibrating their deposited energy. The objective of this project is to improve the reconstruction by using machine learning techniques, where the energy depositions of clusters of cells, formed by ATLAS topo-clustering methods, are treated as three-dimensional images when inputted to neural networks. This approach significantly improves the calibration of deposited energies when cross-validating while training, and models trained on idealized data predict the calibrated energies of particles in more complex data sets well. Additionally, implementation of a data generator using uproot allows the program to load input data into memory as needed while training or predicting, significantly reducing the amount of memory used. The data generator also allows for use of multiprocessing to speed up training and evaluating. This work illustrates that using machine learning methods for both classification and calibration has the potential to significantly improve particle reconstruction.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Two bright, optically clear, intrinsic fast-neutron and charged-particle detector materials for neutron imaging and other applications

Two optically clear, bright, scintillating ZnS materials have been identified that, like previous opaque ZnS scintillators, are excellent charged particle detectors. We show that ZnS is a good fast-neutron-to charged-particle converter making optically clear ZnS an intrinsic fast-neutron detector that does not require layering or mixing of converter materials and scintillator materials, and removes the limitations imposed by opaque ZnS scintillator materials used for more than a century. Thermal neutron detection using optically clear 6 LiF or 10 BN and clear ZnS may benefit from improved spatial resolution and light transmission. Properties and tests of clear scintillating ZnS are described. Fast-neutron imaging applications benefit from increased efficiency of these scintillators, minimal scattering in the scintillator, and increased useful detector volume. Charged particle and fast-neutron detectors have numerous applications in nuclear non-proliferation and security, nuclear and particle physics, and non-destructive testing and environmental measurements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Energetic Particles - microturbulence interaction thrust (EP SIWG white paper)

This white paper outlines a strategic approach to Energetic Particle (EP) research, aimed at applying the results to the future burning devices such as ITER. Our goal is to deepen the understanding of the interplay between plasma background microturbulence and diverse species of energetic ions in burning plasma devices. This strategy is poised to advance our knowledge in this crucial area of fusion science, paving the way for significant breakthroughs in plasma physics and fusion energy research. We consider the confinement of energetic ions such as auxiliary heating beams, minority ions from ICRH, and fusion product alpha particles. Recent studies have underscored the potential of EP/microturbulence interaction to enhance fusion plasma performance by stabilizing microturbulence. However, it also poses risks, such as exacerbating Alfvénic eigenmode (AE) instabilities, which could compromise the sustainability of plasma discharge by causing EP losses. The interplay between EPs and background microturbulence is evident in the phenomenon of effective pitch angle scattering, a crucial aspect of the quasilinear (QL) theory. This theory is integral to developing numerically-efficient yet comprehensive and self-consistent approaches, recently employed to investigate the relaxation of energetic particle populations in the holistic modeling of fusion-grade plasmas. The primary objectives of this white paper thrust encompass a dual focus. First is that we need to delve into the mechanisms through which microturbulence engenders effective pitch angle scattering. This investigation will entail the examination of the presence of known or self-consistently predicted spectra of modes accountable for microturbulence. In these explorations, electrostatic microturbulence serves as a logical initial stride towards achieving the trust's objectives. This endeavor is anticipated to yield formulations expressing the parametric dependencies of the effective pitch angle scattering frequency on variables such as thermal plasma electron and/or ion temperatures, as well as their respective thermal conductivities. In our second objective, we aim to delve into the intricate formation of zonal flow (ZF) structures amidst the complex interplay of microturbulence and Alfvenic eigenmodes (AEs). This endeavor poses greater challenges as we seek to unravel the macroscopic manifestations influenced by microturbulence, termed as zonal structures (ZS), stemming from microturbulence-induced ZF. Drawing from this understanding, we anticipate employing a QL approach to yield comprehensive insights into the distribution function of energetic particles (EP) within phase space. This method entails resolving the dominant multidimensional phase space diffusion processes while effectively averaging over the rapid ballistic responses. Nevertheless, substantial strides remain imperative to realize a comprehensive whole-device modeling framework. This entails meticulous verification and validation exercises against experimental observations, as well as rigorous benchmarking against theoretical frameworks and numerical simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Real-Time Artificial Intelligence for Particle Reconstruction and Higgs Physics

With the discovery of the Higgs boson at the CERN LHC, the world's highest-energy particle accelerator complex, scientists have acquired an important tool to study the fundamental building blocks of the universe. Precision measurements of Higgs bosons produced with large momentum allow for unique insights into the structure of the interactions of the Higgs boson with other particles that may shed light on physics beyond the standard model. While experimentally challenging, exploring such interactions with novel artificial intelligence (AI) methods can advance our understanding of the Higgs sector, including the Higgs boson's self-interaction. Moreover, the LHC is undergoing a major upgrade to further increase its particle collision rate and thereby operate for an additional decade. The experimental detectors at the upgraded facility must process at least a factor of ten more data at rates of hundreds of terabytes per second all under challenging conditions. New AI techniques are required to reconstruct and select, or trigger on, the most physics-sensitive events in real-time to handle the resulting avalanche of data. The proposed research will achieve the goals of the LHC program at the CMS experiment by developing a sub-microsecond event reconstruction system using real-time AI algorithms that employ field-programmable gate array technologies. By harnessing sophisticated AI techniques, this research focuses on measuring the production of Higgs bosons at large momentum while enhancing particle reconstruction methods in the trigger and beyond. Overall, the proposed research has broader implications for the use of AI in resource-constrained, low-latency embedded applications across all fields of science.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Tritium Betavoltaic Powered Sensor Platforms: Power Augmentation with Scintillating Particles

Betavoltaics (BV) are long-life power sources that typically convert beta particle radiation into electricity. Largely, the radioactive decays within the source go unharvested by the device. This work seeks to augment the power generation of BV devices by integration of scintillating particles within the radiative getter to convert beta emission which would otherwise not leave the getter into usable light for power generation. Silica-covered barium fluoride scintillating particles were integrated into a tritiated water getter. Power generation was increased from 100s of nW to µW levels with the addition of 0.2 wt. % particles into the getter. Nanowatt-scale sensor platforms were demonstrated with the µW BV devices and the maximum possible lifetime of such platforms was estimated. As this technique enables higher power density BV devices from conventional Si semiconductors (compared to wider bandgap BVs), the further implementation may lower the barrier-to-deployment of these long-life power/sensor platforms.

42 ENGINEERING↗