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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Machine learning on FPGA for event selection

Real-time data processing is a frontier field in experimental particle physics. The application of FPGAs at the trigger level is used by many current and planned experiments (CMS, LHCb, Belle2, PANDA). Usually they use conventional processing algorithms. LHCb has implemented Machine Learning (ML) elements for real-time data processing with a triggered readout system that runs most of the ML algorithms on a computer farm. The work described in this article aims to test the ML-FPGA algorithms for streaming data acquisition. Herein, there are many experiments working in this area and they have a lot in common, but there are many specific solutions for detector and accelerator parameters that are worth exploring further. This report describes the purpose of the work and progress in evaluating the ML-FPGA application.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Deep probabilistic direction prediction in 3D with applications to directional dark matter detectors

Abstract We present the first method to probabilistically predict 3D direction in a deep neural network model. The probabilistic predictions are modeled as a heteroscedastic von Mises-Fisher distribution on the sphere S 2 , giving a simple way to quantify aleatoric uncertainty. This approach generalizes the cosine distance loss which is a special case of our loss function when the uncertainty is assumed to be uniform across samples. We develop approximations required to make the likelihood function and gradient calculations stable. The method is applied to the task of predicting the 3D directions of electrons, the most complex signal in a class of experimental particle physics detectors designed to demonstrate the particle nature of dark matter and study solar neutrinos. Using simulated Monte Carlo data, the initial direction of recoiling electrons is inferred from their tortuous trajectories, as captured by the 3D detectors. For 40 keV electrons in a 70% He 30% CO 2 gas mixture at STP, the new approach achieves a mean cosine distance of 0.104 (26 ∘ ) compared to 0.556 (64 ∘ ) achieved by a non-machine learning algorithm. We show that the model is well-calibrated and accuracy can be increased further by removing samples with high predicted uncertainty. This advancement in probabilistic 3D directional learning could increase the sensitivity of directional dark matter detectors.

Computer Science↗
DOE OSTI2024

Training toward significance with the decorrelated event classifier transformer neural network

Experimental particle physics uses machine learning for many tasks, where one application is to classify signal and background events. This classification can be used to bin an analysis region to enhance the expected significance for a mass resonance search. In natural language processing, one of the leading neural network architectures is the transformer. In this work, an event classifier transformer is proposed to bin an analysis region, in which the network is trained with special techniques. The techniques developed here can enhance the significance and reduce the correlation between the network’s output and the reconstructed mass. It is found that this trained network can perform better than boosted decision trees and feed-forward networks. Published by the American Physical Society 2024

Astronomy & Astrophysics↗
DOE OSTI2023

Development of ML FPGA Filter for Particle Identification and Tracking in Real Time

Real-time data processing is a frontier field in experimental particle physics. Machine Learning methods are widely used and have proven to be very powerful in particle physics. The growing computational power of modern FPGA boards allows us to add more sophisticated algorithms for real time data processing. Many tasks could be solved using modern Machine Learning (ML) algorithms which are naturally suited for FPGA architectures. The FPGA-based machine learning algorithm provides an extremely low, sub-microsecond, latency decision and makes information-rich data sets for event selection. We report work has started to evaluate an FPGA based Machine Learning (ML) algorithm for a real-time particle identification and tracking with Transition Radiation Detector (TRD) and e/m calorimeter. The first target is the GlueX experiment, with a plan to build a TRD based on GEM technology. GlueX trigger latency is 3.3 μs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

A Beamdump facility at Jefferson Lab

The potential of the intense secondary muon, neutrino, and (hypothetical) light dark matter beams at the Thomas Jefferson National Accelerator Facility (Jefferson Lab) is explored. These are produced in the high-power dumps with high-current electron beams. Light dark matter searches with the approved Beam Dump eXperiment (BDX) are driving the realization of a new underground vault behind Hall A that could be extended to a Beamdump Facility with little additional installations. High-energy muons created via the Bethe–Heitler process uniquely do not proceed through the more common pion production and decay channels. Several possible muon physics applications are highlighted. Neutrino detector technologies and experiments suitable for a beamdump facility are outlined.

Accelerator Physics↗
DOE OSTI2024

Search for CP-violating Neutrino Non-Standard Interactions with the NOvA Experiment

The phenomenon of neutrino oscillations is the most significant evidence in experimental particle physics that points to the existence of Physics Beyond the Standard Model, and it opened a window for several and interesting new investigations in the field of neutrino physics. Among the possibilities, Non-Standard Interactions (NSI) are an extension of the neutrino matter effect leading to a rich phenomenology. These NSI are expected to modify the propagation of neutrinos through matter. The current open questions in the neutrino oscillation model rely heavily on how neutrinos interact with matter, and NSI could induce possible effects. This talk reports the preliminary search for CP-violating NSI of neutrinos with matter at the NOvA Experiment. Data from $\nu_{\mu}(\bar{\nu}_{\mu})\rightarrow\nu_{\mu}(\bar{\nu}_{\mu})$ and $\nu_{\mu}(\bar{\nu}_{\mu})\rightarrow\nu_{e}(\bar{\nu}_{e})$ oscillation channels are used to measure the effect of the NSI parameters $\varepsilon_{e\mu}$ or $\v arepsilon_{e\tau}$ over the 810 km baseline of the experiment.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Progress of the CHILLAX Experiment (HEPCAT Year 1 Report)

A significant facet of modern experimental particle physics research is that of searching for hypothetical rare events. In this context, “rare” means “unusual to detect in the laboratory”, and can be a confirmed phenomenon (e.g. coherent elastic neutrino-nucleus scattering, which has a high cross section at low, difficult to detect energies), or an as-of-yet unobserved phenomenon that may not exist (e.g. dark matter - standard model matter non-gravitational interaction). A salient challenge for experimentalists is to devise detectors optimized for observing such rare events.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Flexible Pilot Jobs Framework for Distributed High Throughput Computing

Experimental particle physics has been at the forefront of analyzing the world’s largest datasets for decades. The high-energy physics (HEP) community was among the first to develop suitable software and computing tools for this purpose. GlideinWMS is a Glidein-based workload management system whose purpose is to provide experiments like CMS at CERN, DUNE at Fermilab, and others, a way to access and efficiently use vast amounts of computing resources. This system wants to provide a simple way to submit jobs to a set of computing resources, that will be provided to users behind the scenes. Glideins are the pilot jobs executed on the worker nodes at the grid sites, performing operations such as hardware detection, environment setup, and error handling. After all these operations, they will launch the actual user job. Many grid sites are supported, such as shared clusters, Google CE, and AWS. My internship aimed to design and code a flexible pilot jobs framework that will replace the one used by GlideinWMS, developing a modular and flexible skeleton of the Glidein and adding further functionalities. My project also focused on the application of machine learning techniques as support to this management system.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Direct neutrino-mass measurement based on 259 days of KATRIN data

That neutrinos carry a nonvanishing rest mass is evidence of physics beyond the Standard Model of elementary particles. Their absolute mass holds relevance in fields from particle physics to cosmology. We report on the search for the effective electron antineutrino mass with the KATRIN experiment. KATRIN performs precision spectroscopy of the tritium β-decay close to the kinematic endpoint. On the basis of the first five measurement campaigns, we derived a best-fit value of $m^{2}_{v} = -0.14^{+0.13}_{-0.15}$ eV 2 , resulting in an upper limit of m ν < 0.45 eV at 90% confidence level. Stemming from 36 million electrons collected in 259 measurement days, a substantial reduction of the background level, and improved systematic uncertainties, this result tightens KATRIN’s previous bound by a factor of almost two.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Research in Elementary Particle Physics

The Experimental High Energy Physics group in the Department of Physics & Astronomy at Louisiana State University (LSU) is composed of faculty, postdocs and students. We perform research in experimental neutrino physics at the Intensity Frontier (DUNE, ProtoDUNE and T2K). The group continues their principal research efforts on the T2K and DUNE projects to measure neutrino oscillation parameters and study neutrino properties.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Five-body systems with Bethe-Salpeter equations

We extend the Bethe-Salpeter formalism to systems made of five valence particles. Restricting ourselves to two-body interactions, we derive the subtraction terms necessary to prevent overcounting. We solve the five-body Bethe-Salpeter equation numerically for a system of five scalar particles interacting by a scalar exchange boson. To make the calculations tractable, we implement properties of the permutation group S 5 and construct an approximation based on intermediate two- and three-body poles. We extract the five-body ground and excited states along with the spectra obtained from the two-, three-, and four-body equations. In the limit of a massless exchange particle, the two-, three, four- and five-body states coexist within a certain range of the coupling strength, whereas for heavier exchange particles the five-body system becomes Borromean. Our study serves as a building block for the calculation of pentaquark properties using functional methods.

Eichmann, Gernot [Univ. of Graz (Austria)] (ORCID:↗
DOE OSTI2025

Measurement of the mean number of muons with energies above 500 GeV in air showers detected with the IceCube Neutrino Observatory

We present a measurement of the mean number of muons with energies larger than 500 GeV in near-vertical extensive air showers initiated by cosmic rays with primary energies between 2.5 and 100 PeV. The measurement is based on events detected in coincidence between the surface and in-ice detectors of the IceCube Neutrino Observatory. Air showers are recorded on the surface by IceTop, while a bundle of high-energy muons (TeV muons) from the shower can subsequently produce a tracklike event in the IceCube in-ice array. Results are obtained assuming the hadronic interaction models Sibyll 2.1, QGSJet-II.04, and EPOS-LHC. The measured number of TeV muons is found to be in agreement with predictions from air-shower simulations. The results have also been compared to a measurement of low-energy muons by IceTop, indicating an inconsistency between the predictions for low- and high-energy muons in simulations based on the EPOS-LHC model.

Abbasi, R. [Loyola University Chicago]↗
DOE OSTI2025

Seasonal variations of the atmospheric muon neutrino spectrum measured with IceCube

This study presents an analysis of seasonal variations in the atmospheric muon neutrino flux, using 11.3 years of data from the IceCube Neutrino Observatory. By leveraging a novel spectral unfolding method, we explore the energy range from 125 GeV to 10 TeV for zenith angles from 90° to 110°, corresponding to the Antarctic atmosphere. Our findings reveal that the differential measurement of the amplitudes of the seasonal variation is consistent with an energy-dependent decrease reaching (-4.5 ± 1.2)% during Austral winter and increase to (+ 3.9 ± 1.3)% during Austral summer relative to the annual average at 10 TeV. While the unfolded flux exceeds the model predictions by up to 30%, the differential measurement of the seasonal to annual average flux remains unaffected. The measured seasonal variations of the muon neutrino spectrum are consistent with theoretical predictions using the MCEq code and the NRLMSISE-00 atmospheric model.

Astroparticle Physics and High-Energy Cosmic Pheno↗
DOE OSTI2025

Deciphering spin-parity assignments of nuclear levels

Spin-parity assignments of nuclear levels are critical for understanding nuclear structure and reactions. However, inconsistent notation conventions and ambiguous reporting in research papers often lead to confusion and misinterpretations. Here, this paper examines the policies of the Evaluated Nuclear Structure Data File (ENSDF) and the evaluations by Endt and collaborators, highlighting key differences in their approaches to spin-parity notation. Sources of confusion are identified, including ambiguous use of strong and weak arguments and the conflation of new experimental results with prior constraints. Recommendations are provided to improve clarity and consistency in reporting spin-parity assignments, emphasizing the need for explicit notation conventions, clear differentiation of argument strengths, community education, and separate reporting of new findings. These steps aim to enhance the accuracy and utility of nuclear data for both researchers and evaluators.

Experimental Nuclear Physics↗
DOE OSTI2023

Observation of the effect of gravity on the motion of antimatter

Einstein’s general theory of relativity from 1915 remains the most successful description of gravitation. From the 1919 solar eclipse to the observation of gravitational waves, the theory has passed many crucial experimental tests. However, the evolving concepts of dark matter and dark energy illustrate that there is much to be learned about the gravitating content of the universe. Singularities in the general theory of relativity and the lack of a quantum theory of gravity suggest that our picture is incomplete. It is thus prudent to explore gravity in exotic physical systems. Antimatter was unknown to Einstein in 1915. Dirac’s theory appeared in 1928; the positron was observed in 1932. There has since been much speculation about gravity and antimatter. The theoretical consensus is that any laboratory mass must be attracted by the Earth, although some authors have considered the cosmological consequences if antimatter should be repelled by matter. In the general theory of relativity, the weak equivalence principle (WEP) requires that all masses react identically to gravity, independent of their internal structure. Here we show that antihydrogen atoms, released from magnetic confinement in the ALPHA-g apparatus, behave in a way consistent with gravitational attraction to the Earth. Repulsive ‘antigravity’ is ruled out in this case. This experiment paves the way for precision studies of the magnitude of the gravitational acceleration between anti-atoms and the Earth to test the WEP.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Review of Particle Physics

Abstract The Review summarizes much of particle physics and cosmology. Using data from previous editions, plus 2,143 new measurements from 709 papers, we list, evaluate, and average measured properties of gauge bosons and the recently discovered Higgs boson, leptons, quarks, mesons, and baryons. We summarize searches for hypothetical particles such as supersymmetric particles, heavy bosons, axions, dark photons, etc. Particle properties and search limits are listed in Summary Tables. We give numerous tables, figures, formulae, and reviews of topics such as Higgs Boson Physics, Supersymmetry, Grand Unified Theories, Neutrino Mixing, Dark Energy, Dark Matter, Cosmology, Particle Detectors, Colliders, Probability and Statistics. Among the 120 reviews are many that are new or heavily revised, including a new review on Machine Learning, and one on Spectroscopy of Light Meson Resonances. The Review is divided into two volumes. Volume 1 includes the Summary Tables and 97 review articles. Volume 2 consists of the Particle Listings and contains also 23 reviews that address specific aspects of the data presented in the Listings. The complete Review (both volumes) is published online on the website of the Particle Data Group (pdg.lbl.gov) and in a journal. Volume 1 is available in print as the PDG Book. A Particle Physics Booklet with the Summary Tables and essential tables, figures, and equations from selected review articles is available in print, as a web version optimized for use on phones, and as an Android app.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

The critical importance of software for HEP

Particle physics has an ambitious and broad global experimental programme for the coming decades. Large investments in building new facilities are already underway or under consideration. Scaling the present processing power and data storage needs by the foreseen increase in data rates in the next decade for HL-LHC is not sustainable within the current budgets. As a result, a more efficient usage of computing resources is required in order to realise the physics potential of future experiments. Software and computing are an integral part of experimental design, trigger and data acquisition, simulation, reconstruction, and analysis, as well as related theoretical predictions. A significant investment in computing and software is therefore critical. Advances in software and computing, including artificial intelligence (AI) and machine learning (ML), will be key for solving these challenges. Making better use of new processing hardware such as graphical processing units (GPUs) or ARM chips is a growing trend. This forms part of a computing solution that makes efficient use of facilities and contributes to the reduction of the environmental footprint of HEP computing. The HEP community already provided a roadmap for software and computing for the last EPPSU, and this paper updates that, with a focus on the most resource critical parts of our data processing chain.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Energy Spectrum of Ultrahigh-Energy Cosmic Rays across Declinations -90° to +44.8° as Measured at the Pierre Auger Observatory

The energy spectrum of cosmic rays above 2.5 EeV has been measured across the declination range - 9 0 ° ≤ δ ≤ + 44.8 ° using ∼ 310 000 events accrued at the Pierre Auger Observatory from an exposure of ( 104 900 ± 3 100 ) km 2 sr yr . No significant variations of energy spectra with declination are observed, after allowing or not for nonuniformities across the sky arising from the well-established dipolar anisotropies in the arrival directions of ultrahigh-energy cosmic rays. Here, the instep feature in the spectrum at ≃ 10 EeV reported previously is now established at a significance above 5 σ . Within the statistics, the energy spectra are indistinguishable across declinations so disfavoring an origin for the instep from a few distinctive sources.

Abdul Halim, A. [University of Adelaide]↗