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At least 505 records · Page 28

DC and Wave Electric Fields and Other Plasma Parameters Observed on Two Sounding Rockets in the Dark Cusp during IMF BZ North and South Conditions

Two Black Brant IX sounding rockets were launched into the dark, dayside cusp near magnetic noon on December 2 and 3, 1997, from Ny Alesund, Spitzbergen at 79degN reaching altitudes of approximately 450 km. Real-time ground-based and Wind (interplanetary magnetic field) IMF data were used to determine the launch conditions. The first launch, with Bz north conditions, crossed into and back out of an open field region with merging poleward of the projected trajectory. The second flight, into Bz south conditions, was timed to coincide with an enhancement in the merging rate from a increase in the negative Bz, while the (Defense Meteorological Satellite Program) DMSP F13 satellite was situated slightly to the north of the rocket trajectory. Each payload returned DC electric and magnetic fields, plasma waves, energetic particles, photometer data, and thermal plasma data. Data from both flights will be shown, with an emphasis on the DC electric field results. In particular, the data gathered on December 2, 1997 will be used to discuss ionospheric signatures of merging and the open/closed character of the the cusp/low latitude boundary layer. In contrast, the data gathered on December 3, 1997 shows evidence of pulsed electric field structures which will be examined in the context of cusp plasma entry processes. Both data sets returned a rich variety of plasma waves, as well as optical emissions and thermal plasma data.

Pfaff, R. F.↗

Search for charged-lepton flavor violation in the production and decay of top quarks using trilepton final states in proton-proton collisions at $\sqrt{s}$ =13 TeV

A search is performed for charged-lepton flavor violating processes in top quark (𝑡) production and decay. The data were collected by the CMS experiment from proton-proton collisions at a center-of-mass energy of 13 TeV and correspond to an integrated luminosity of 138 fb −1 . The selected events are required to contain one opposite-sign electron-muon pair, a third charged lepton (electron or muon), and at least one jet of which no more than one is associated with a bottom quark. Boosted decision trees are used to distinguish signal from background, exploiting differences in the kinematics of the final states particles. The data are consistent with the standard model expectation. Upper limits at 95% confidence level are placed in the context of effective field theory on the Wilson coefficients, which range between 0.024–0.424 TeV −2 depending on the flavor of the associated light quark and the Lorentz structure of the interaction. These limits are converted to upper limits on branching fractions involving up (charm) quarks, 𝑡 → 𝑒⁢𝜇⁢𝑢 (𝑡 → 𝑒⁢𝜇⁢𝑐), of 0.032⁢(0.498) × 10 −6 , 0.022⁢(0.369) × 10 −6 , and 0.012⁢(0.216) × 10 −6 for tensorlike, vectorlike, and scalarlike interactions, respectively.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Assessment of Particle Drag Models Using L2K and GBK Experimental Data

Properly assessing the drag force is an important element to computing the trajectories of particles traveling through a shock layer. This study will use experimental data in the German Aerospace Center (DLR) L2K arcjet to evaluate the ability of various particle drag models to reproduce the experimental particle velocity data.

particle flows↗

Point-particle drag, lift, and torque closure models using machine learning: Hierarchical approach and interpretability

Developing deterministic neighborhood-informed point-particle closure models using machine learning has garnered interest recently from the dispersed multiphase flow community. The robustness of neural models for this complex multibody problem is hindered by the availability of particle-resolved data. Here, the present work addresses this unavoidable limitation of data paucity by implementing two strategies: (1) by using a rotation and reflection equivariant neural network and (2) by pursuing a physics-based hierarchical machine learning approach. The resulting machine-learned models are observed to achieve a maximum accuracy of 85% and 96% in the prediction of neighbor-induced force and torque fluctuations, respectively, for a wide range of Reynolds number and volume fraction conditions considered. Furthermore, we pursue force and torque network architectures that provide universal prediction spanning a wide range of Reynolds number (0.25 ≤ Re ≤250) and particle volume fraction (0 ≤ φ ≤0.4). The hierarchical nature of the approach enables improved prediction of quantities such as streamwise torque, by going beyond binary interactions to include trinary interactions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Learning new physics from data: A symmetrized approach

Thousands of person years have been invested in searches for new physics (NP), the majority of them motivated by theoretical considerations. Yet, no evidence of beyond the Standard Model physics has been found. This suggests that model-agnostic searches might be an important key to explore NP, and help discover unexpected phenomena which can inspire future theoretical developments. A possible strategy for such searches is identifying asymmetries between data samples that are expected to be symmetric within the Standard Model. We propose exploiting neural networks (NNs) to quickly fit and statistically test the differences between two samples. Our method is based on an earlier work, originally designed for inferring the deviations of an observed dataset from that of a much larger reference dataset. We present a symmetric formalism, generalizing the original one, avoiding fine-tuning of the NN parameters and any constraints on the relative sizes of the samples. Our formalism could be used to detect small symmetry violations, extending the discovery potential of current and future particle physics experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Theory and observation of energetic ions in the lobes of the geomagnetic tail

The Owen et al. (1990) model, which attempts to explain the nature of the pitch angle distributions of energetic ions within the lobes of the distant geomagnetic tail is briefly reviewed. Energetic ion data from the ISEE-3 spacecraft obtained during early 1983, when the spacecraft made several traversals of the distant geomagnetic tail are then presented. The data demonstrate that during quiet periods in which the spacecraft is continuously located in the tail lobes, the pitch angle distribution is observed to be highly anisotropic, being peaked closely perpendicular to the magnetic field direction, but with a small net flow in the antisunward direction, in agreement with the model results. Further predictions of the model, concerning the variation of the lobe energetic ion distributions with position in the lobes, are compared to observations made as the spacecraft performed a traversal of the lobe. Finally, since the model indicates that a more isotropic distribution should exist in the tail lobe during solar particle events, data is presented from such a period for further comparison. In all the above cases, good agreement is demonstrated between the data and the expections of the model.

Owen, C. J.↗

The STARDUST Discovery Mission: Data from the Encounter with Comet Wild 2 and the Expected Sample Return

On January 2,2004, the STARDUST spacecraft made the closest ever flyby (236 km) of the nucleus of a comet - Comet Wild 2. During the fly by the spacecraft collected samples of dust from the coma of the comet. These samples will be returned to Earth on January 15,2006. After a brief preliminary examination to establish the nature of the returned samples, they will be made available to the general scientific community for study. In addition to its aerogel dust collector, the STARDUST spacecraft was also equipped with instruments that made in situ measurements of the comet during the flyby. These included several dust impact monitors, a mass spectrometer, and a camera. The spacecraft's communication system was also used to place dynamical constraints on the mass of the nucleus and the number of impacts the spacecraft had with large particles. The data taken by these instruments indicate that the spacecraft successfully captured coma samples. These instruments, particularly the camera, also demonstrated that Wild 2 is unlike any other object in the Solar System previously visited by a spacecraft. During my talk I will discuss the scientific goals of the STARDUST mission and provide an overview of its design and flight to date. I will then end with a description of the exciting data returned by the spacecraft during the recent encounter with Wild 2 and discuss what these data tell us about the nature of comets. It will probably come as no surprise that the encounter data raise as many (or more) new questions as they answer old ones.

Sandford, Scott A.↗

Theoretical Particle Physics in the Data-Driven Era (Final Report)

DOE award DE-SC0021447 supports theoretical research in high energy physics. PI and students are not a part of any experimental collaboration, even if some works were done in collaboration with experimental colleagues. All research products are in the form of research articles and they are publicly available under inspirehep.net and arxiv.org, which are typical publication methods in high energy physics. No invention or patent is involved with this research. No equipment or hardware is involved with the research under this award. Research outcomes are used by colleagues in high energy physics, including both theorists and experimentalists. Therefore the outcome of research topics under this award supported the High Energy Physics experimental research program, both in understanding the data and in finding new directions for experimental exploration. The research materials are used to train undergraduate students, graduate students and postdoctoral scholars. We summarize research activity under this award in the following section and major products are listed in section 3. Section 4 contains professional presentations given by PI. Other products developed during the award period are in section 5. Students’ activities are summarized in section 6.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Radiation dosimetry measurements with real time radiation monitoring device (RRMD)-II in Space Shuttle STS-79

The real-time measurement of radiation environment was made with an improved real-time radiation monitoring device (RRMD)-II onboard Space Shuttle STS-79 (S/MM#4: 4th Shuttle MIR Mission, at an inclination angle of 51.6 degrees and an altitude of 250-400km) for 199 h during 17-25 September, 1996. The observation of the detector covered the linear energy transfer (LET) range of 3.5-6000 keV/micrometer. The Shuttle orbital profile in this mission was equivalent to that of the currently planned Space Station, and provided an opportunity to investigate variations in count rate and dose equivalent rate depending on altitude, longitude, and latitude in detail. Particle count rate and dose equivalent rate were mapped geographically during the mission. Based on the map of count rate, an analysis was made by dividing whole region into three regions: South Atlantic Anomaly (SAA) region, high latitude region and other regions. The averaged absorbed dose rate during the mission was 39.3 microGy/day for a LET range of 3.5-6000 keV/micrometer. The corresponding average dose equivalent rates during the mission are estimated to be 293 microSv/day with quality factors from International Commission on Radiological Protection (ICRP)-Pub. 60 and 270 microSv/day with quality factors from ICRP-Pub. 26. The effective quality factors for ICRP-Pub. 60 and 26 are 7.45 and 6.88, respectively. From the present data for particles of LET > 3.5keV/micrometer, we conclude that the average dose equivalent rate is dominated by the contribution of galactic cosmic ray (GCR) particles. The dose-detector depth dependence was also investigated.

manned↗

PreMevE‐MEO: Predicting Ultra‐Relativistic Electrons Using Observations From GPS Satellites

Abstract Ultra‐relativistic electrons with energies greater than or equal to two megaelectron‐volt (MeV) pose a major radiation threat to spaceborne electronics, and thus specifying those highly energetic electrons has a significant meaning to space weather communities. Here we report the latest progress in developing our predictive model for MeV electrons in the outer radiation belt. The new version, primarily driven by electron measurements made along medium‐Earth‐orbits (MEO), is called PREdictive MEV Electron (PreMevE)‐MEO model that nowcasts ultra‐relativistic electron flux distributions across the whole outer belt. Model inputs include >2 MeV electron fluxes observed in MEOs by a fleet of GPS satellites as well as electrons measured by one Los Alamos satellite in the geosynchronous orbit. We developed an innovative Sparse Multi‐Inputs Latent Ensemble NETwork (SmileNet) which combines convolutional neural networks with transformers, and we used long‐term in situ electron data from NASA's Van Allen Probes mission to train, validate, optimize, and test the model. It is shown that PreMevE‐MEO can provide hourly nowcasts with high model performance efficiency and high correlation with observations. This prototype PreMevE‐MEO model demonstrates the feasibility of making high‐fidelity predictions driven by observations from longstanding space infrastructure in MEO, thus has great potential of growing into an invaluable space weather operational warning tool.

79 ASTRONOMY AND ASTROPHYSICS↗

Learning to identify electrons

In this report we investigate whether state-of-the-art classification features commonly used to distinguish electrons from jet backgrounds in collider experiments are overlooking valuable information. A deep convolutional neural network analysis of electromagnetic and hadronic calorimeter deposits is compared to the performance of typical features, revealing a ≈ 5% gap which indicates that these lower-level data do contain untapped classification power. To reveal the nature of this unused information, we use a recently developed technique to map the deep network into a space of physically interpretable observables. We identify two simple calorimeter observables which are not typically used for electron identification, but which mimic the decisions of the convolutional network and nearly close the performance gap.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Extraction of the higher-twist parton distribution $e(x)$ from CLAS data

We present the first point-by-point extraction of a twist-3 PDF. The scalar PDF, e(x), is accessed through the analysis of the data for the sin φR-moment of the beam-spin asymmetry for dihadron production in semi-inclusive DIS off proton target at CLAS and CLAS12. The dihadron formalism allows for use of collinear framework, hence calling for a minimal set of approximations and hypotheses. The extracted PDF e(x) carries insights into the physics of the largely-unexplored quark-gluon correlations, and its first Mellin moment is related to the marginally known scalar charge of the nucleon. We show that the proton flavor combination of the scalar PDF is nonzero at more than 74% probability.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Constraining Particle Variation in Lunar Regolith for Simulant Design

Simulants are used by the lunar engineering community to develop and test technologies for In Situ Resource Utilization (ISRU), excavation and drilling, and for mitigation of hazards to machinery and human health. Working with the United States Geological Survey (USGS), other NASA centers, private industry and academia, Marshall Space Flight Center (MSFC) is leading NASA s lunar regolith simulant program. There are two main efforts: simulant production and simulant evaluation. This work requires a highly detailed understanding of regolith particle type, size, and shape distribution, and of bulk density. The project has developed Figure of Merit (FoM) algorithms to quantitatively compare these characteristics between two materials. The FoM can be used to compare two lunar regolith samples, regolith to simulant, or two parcels of simulant. In work presented here, we use the FoM algorithm to examine the variance of particle type in Apollo 16 highlands regolith core and surface samples. For this analysis we have used internally consistent particle type data for the 90-150 m fraction of Apollo core 64001/64002 from station 4, core 60009/60010 from station 10, and surface samples from various Apollo 16 stations. We calculate mean modal compositions for each core and for the group of surface samples and quantitatively compare samples of each group to its mean as a measurement of within-group variance; we also calculate an FoM for every sample against the mean composition of 64001/64002. This gives variation with depth at two locations and between Apollo 16 stations. Of the tested groups, core 60009/60010 has the highest internal variance with an average FoM score of 0.76 and core 64001/64002 has the lowest with an average FoM of 0.92. The surface samples have a low but intermediate internal variance with an average FoM of 0.79. FoM s calculated against the 64001/64002 mean reference composition range from 0.79-0.97 for 64001/64002, from 0.41-0.91 for 60009/60010, and from 0.54-0.93 for the surface samples. Six samples fall below 0.70, and they are also the least mature (i.e., have the lowest I(sub s)/FeO). Because agglutinates are the dominant particle type and the agglutinate population increases with sample maturity (I(sub s)/FeO), the maturity of the sample relative to the reference is a prime determinant of the particle type FoM score within these highland samples.

Schrader, Christian M.↗

Geometric GNNs for charged particle tracking at GlueX

Nuclear physics experiments are aimed at uncovering the fundamental building blocks of matter. The experiments involve high-energy collisions that produce complex events with many particle trajectories. Tracking charged particles resulting from collisions in the presence of a strong magnetic field is critical to enable the reconstruction of particle trajectories and precise determination of interactions. It is traditionally achieved through combinatorial approaches that scale worse than linearly as the number of hits grows. Since particle hit data naturally form a point cloud and can be structured as graphs, graph neural networks (GNNs) emerge as an intuitive and effective choice for this task. In this study, we evaluate the GNN model for track finding on the data from the GlueX experiment at Jefferson Lab. We use simulation data to train the model and test on both simulation and real GlueX measurements. We demonstrate that GNN-based track finding outperforms the currently used traditional method at GlueX in terms of segment-based efficiency at a fixed purity while providing faster inferences. We show that the GNN model can achieve significant speedup by processing multiple events in batches, which exploits the parallel computation capability of graphical processing units (GPUs). Finally, we compare the GNN implementation on GPU and field-programmable gate array and describe the trade-off.

batched GNN pipeline↗

Assessment of Particle Drag Models Using GBK Experimental Data

Developing a simulation capability to model dust-laden flows requires the ability to accurately predict the velocity of a particle as it travels through a shock layer, nozzle plume, or the flow of an experimental facility. The primary mechanism that determines the particle velocity is the drag force acting on the particle. The drag force is typically expressed in terms of the frontal area of the particle, its velocity relative to the surrounding fluid, the density of the surrounding fluid, and a non-dimensional drag coefficient. As part of the ESM project, an integrated CFD-particle trajectory code named US3D-DUST is being developed]. This code uses a Lagrangian-based framework that computes the trajectories of individual particles in the flow. Several of the most commonly-used spherical drag models have been implemented in US3D-DUST. In this study, the US3D-DUST code will be used to simulate particle flows in the GBK facility. Differences in particle velocities predicted using the different drag models will be compared against recent GBK data

Dusty flow↗

Search for top squarks in the four-body decay mode with single lepton final states in proton-proton collisions at $ \sqrt{s} $ = 13 TeV

A search for the pair production of the lightest supersymmetric partner of the top quark, the top squark ($ {\overset{\sim }{\textrm{t}}}_1 $), is presented. The search targets the four-body decay of the $ {\overset{\sim }{\textrm{t}}}_1 $, which is preferred when the mass difference between the top squark and the lightest supersymmetric particle is smaller than the mass of the W boson. This decay mode consists of a bottom quark, two other fermions, and the lightest neutralino ($ {\overset{\sim }{\chi}}_1^0 $), which is assumed to be the lightest supersymmetric particle. The data correspond to an integrated luminosity of 138 fb$^{−1}$ of proton-proton collisions at a center-of-mass energy of 13 TeV collected by the CMS experiment at the CERN LHC. Events are selected using the presence of a high-momentum jet, an electron or muon with low transverse momentum, and a significant missing transverse momentum. The signal is selected based on a multivariate approach that is optimized for the difference between m($ {\overset{\sim }{\textrm{t}}}_1 $) and m($ {\overset{\sim }{\chi}}_1^0 $). The contribution from leading background processes is estimated from data. No significant excess is observed above the expectation from standard model processes. The results of this search exclude top squarks at 95% confidence level for masses up to 480 and 700 GeV for m($ {\overset{\sim }{\textrm{t}}}_1 $) − m($ {\overset{\sim }{\chi}}_1^0 $) = 10 and 80 GeV, respectively.[graphic not available: see fulltext]

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Test of Light-Lepton Universality in the Rates of Inclusive Semileptonic B-Meson Decays at Belle II

We present the first measurement of the ratio of branching fractions of inclusive semileptonic B -meson decays, R ( X e / μ ) = B ( B → X e ν ) / B ( B → X μ ν ) , a precision test of electron-muon universality, using data corresponding to 189 fb - 1 from electron-positron collisions collected with the Belle II detector. In events where the partner B meson is fully reconstructed, we use fits to the lepton momentum spectra above 1.3 GeV / c to obtain R ( X e / μ ) = 1.007 ± 0.009 ( stat ) ± 0.019 ( syst ) , which is the most precise lepton-universality test of its kind and agrees with the standard-model expectation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Measurement of the B + /B 0 production ratio in e + e - collisions at the $\Upsilon$ (4S) resonance using B → J/Ψ($\ell\ell$)K decays at Belle

We measure the ratio of branching fractions for the $\Upsilon$ (4S) decays to B + B - and B 0 $\bar{B}$ 0 using B + → J/Ψ($\ell\ell$)K + and B 0 → J/Ψ($\ell\ell$)K 0 samples, where J/Ψ($\ell\ell$) stands for J/Ψ → $\ell$ + $\ell$ - ($\ell$ = e or μ), with 711 fb -1 of data collected at the $\Upsilon$ (4S) resonance with the Belle detector. We find the decay rate ratio of $\Upsilon$ (4S) → B + B - over $\Upsilon$ (4S) → B 0 $\bar{B}$ 0 to be 1.065 ± 0.012 ± 0.019 ± 0.047, which is the most precise measurement to date. The first and second uncertainties are statistical and systematic, respectively, and the third uncertainty is due to the assumption of isospin symmetry in B → J/Ψ($\ell\ell$) K.

79 ASTRONOMY AND ASTROPHYSICS↗