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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Measurement of anti- 3 He nuclei absorption in matter and impact on their propagation in the Galaxy

In our Galaxy, light antinuclei composed of antiprotons and antineutrons can be produced through high-energy cosmic-ray collisions with the interstellar medium or could also originate from the annihilation of dark-matter particles that have not yet been discovered. On Earth, the only way to produce and study antinuclei with high precision is to create them at high-energy particle accelerators. Although the properties of elementary antiparticles have been studied in detail, the knowledge of the interaction of light antinuclei with matter is limited. We determine the disappearance probability of 3 $\overline{He}$ when it encounters matter particles and annihilates or disintegrates within the ALICE detector at the Large Hadron Collider. We extract the inelastic interaction cross section, which is then used as an input to the calculations of the transparency of our Galaxy to the propagation of 3 $\overline{He}$ stemming from dark-matter annihilation and cosmic-ray interactions within the interstellar medium. For a specific dark-matter profile, we estimate a transparency of about 50%, whereas it varies with increasing 3 $\overline{He}$ momentum from 25% to 90% for cosmic-ray sources. The results indicate that 3 $\overline{He}$ nuclei can travel long distances in the Galaxy, and can be used to study cosmic-ray interactions and dark-matter annihilation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Measurement of the inclusive isolated-photon production cross section in pp and Pb–Pb collisions at $\mathbf {\sqrt{\textit{s}_{NN }} = 5.02}$ TeV

The ALICE Collaboration at the CERN LHC has measured the inclusive production cross section of isolated photons at midrapidity as a function of the photon transverse momentum (p$^{γ}_{T}$), in Pb–Pb collisions in different centrality intervals, and in pp collisions, at centre-of-momentum energy per nucleon pair of $\sqrt{s_{NN}}$ = 5.02 TeV. The photon transverse momentum range is between 10–14 and 40–140 GeV/c, depending on the collision system and on the Pb–Pb centrality class. The result extends to lower p$^{γ}_{T}$ than previously published results by the ATLAS and CMS experiments at the same collision energy. The covered pseudorapidity range is |η γ | < 0.67. The isolation selection is based on a charged particle isolation momentum threshold p$^{iso, ch}_{T}$ GeV/c within a cone of radii R = 0.2 and 0.4. The nuclear modification factor is calculated and found to be consistent with unity in all centrality classes, and also consistent with the HG-PYTHIA model, which describes the event selection and geometry biases that affect the centrality determination in peripheral Pb–Pb collisions. The measurement is compared to next-to-leading order perturbative QCD calculations and to the measurements of isolated photons and Z 0 bosons from the CMS experiment, which are all found to be in agreement.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Temperature measurement of Quark-Gluon plasma at different stages

In a Quark-Gluon Plasma (QGP), the fundamental building blocks of matter, quarks and gluons, are under extreme conditions of temperature and density. A QGP could exist in the early stages of the Universe, and in various objects and events in the cosmos. The thermodynamic and hydrodynamic properties of the QGP are described by Quantum Chromodynamics (QCD) and can be studied in heavy-ion collisions. Despite being a key thermodynamic parameter, the QGP temperature is still poorly known. Thermal lepton pairs (e + e − and μ + μ − ) are ideal penetrating probes of the true temperature of the emitting source, since their invariant-mass spectra suffer neither from strong final-state interactions nor from blue-shift effects due to rapid expansion. Here we measure the QGP temperature using thermal e+e− production at the Relativistic Heavy Ion Collider (RHIC). The average temperature from the low-mass region (in-medium ρ 0 vector-meson dominant) is (2.01 ± 0.23) × 10 12 K, consistent with the chemical freeze-out temperature from statistical models and the phase transition temperature from Lattice QCD. The average temperature from the intermediate mass region (above the ρ0 mass, QGP dominant) is significantly higher at (3.25 ± 0.60) × 10 12 K. This work provides essential experimental thermodynamic measurements to map out the QCD phase diagram and understand the properties of matter under extreme conditions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Measurement of the Generalized Spin Polarizabilities of the Neutron in the Low-Q{sup 2} Region

Understanding the nucleon spin structure in the regime where the strong interaction becomes truly strong poses a challenge to both experiment and theory. At energy scales below the nucleon mass of about 1 GeV, the intense interaction among the quarks and gluons inside the nucleon makes them highly correlated. Their coherent behaviour causes the emergence of effective degrees of freedom, requiring the application of non-perturbative techniques such as chiral effective field theory1. Here we present measurements of the neutron’s generalized spin polarizabilities that quantify the neutron’s spin precession under electromagnetic fields at very low energy-momentum transfer squared down to 0.035 GeV2. In this regime, chiral effective field theory calculations2–4 are expected to be applicable. Our data, however, show a strong discrepancy with these predictions, presenting a challenge to the current description of the neutron’s spin properties.

Sulkosky, Vincent↗
DOE OSTI2023

Pattern of global spin alignment of ϕ and K*0 mesons in heavy-ion collisions

The strong force, as one of the four fundamental forces at work in the universe, governs interactions of quarks and gluons, and binds together the atomic nucleus. Notwithstanding decades of progress since Yukawa first developed a description of the force between nucleons in terms of meson exchange 1 , a full understanding of the strong interaction remains a major challenge in modern science. One remaining difficulty arises from the non-perturbative nature of the strong force, which leads to the phenomenon of quark confinement at distance scales on the order of the size of the proton. Here we show that in relativistic heavy-ion collisions, where quarks and gluons are set free over an extended volume, two species of produced vector (spin-1) mesons, namely φ and K∗0 , emerge with a surprising pattern of global spin alignment. In particular, the global spin alignment for φ is unexpectedly large, while that for K∗0 is consistent with zero. The observed spin-alignment pattern and magnitude for the φ cannot be explained by conventional mechanisms, while a model with strong force fields2, 3 accommodates the current data. This is the first time that the strong force field is experimentally supported as a key mechanism that leads to global spin alignment. We extract a quantity proportional to the intensity of the field of the strong force. Within the framework of the Standard Model, where the strong force is typically described in the quark and gluon language of Quantum Chromodynamics, the field being considered here is an effective proxy description. This is a qualitatively new class of measurement, which opens a new avenue for studying the behaviour of strong force fields via their imprint on spin alignment.

Abdallah, M. S.↗
DOE OSTI2021

Accurate prediction of mega-electron-volt electron beam properties from UED using machine learning

To harness the full potential of the ultrafast electron diffraction (UED) and microscopy (UEM), we must know accurately the electron beam properties, such as emittance, energy spread, spatial-pointing jitter, and shot-to-shot energy fluctuation. Owing to the inherent fluctuations in UED/UEM instruments, obtaining such detailed knowledge requires real-time characterization of the beam properties for each electron bunch. While diagnostics of these properties exist, they are often invasive, and many of them cannot operate at a high repetition rate. Here, we present a technique to overcome such limitations. Employing a machine learning (ML) strategy, we can accurately predict electron beam properties for every shot using only parameters that are easily recorded at high repetition rate by the detector while the experiments are ongoing, by training a model on a small set of fully diagnosed bunches. Applying ML as real-time noninvasive diagnostics could enable some new capabilities, e.g., online optimization of the long-term stability and fine single-shot quality of the electron beam, filtering the events and making online corrections of the data for time-resolved UED, otherwise impossible. This opens the possibility of fully realizing the potential of high repetition rate UED and UEM for life science and condensed matter physics applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

The detection of marine microseismic activity with the CUORE tonne-scale cryogenic experiment

Vibrations from experimental setups and the environment are a persistent source of noise for low-temperature calorimeters searching for rare events, including neutrinoless double beta ( 0νββ ) decay or dark matter interactions. Such noise can significantly limit experimental sensitivity to the physics case under investigation. Here, we report the detection of marine microseismic vibrations using mK-scale calorimeters. This study employs a multi-device analysis correlating data from CUORE, the leading experiment in the search for 0νββ decay with mK-scale calorimeters, and the Copernicus Earth Observation program, revealing the seasonal impact of Mediterranean Sea activity on CUORE’s energy thresholds, resolution, and sensitivity over four years. The detection of marine microseisms underscores the need to address faint environmental noise in ultra-sensitive experiments. Understanding how such noise couples to the detector and developing mitigation strategies is essential for next-generation experiments. We demonstrate one such strategy: a noise decorrelation algorithm implemented in CUORE using auxiliary sensors, which reduces vibrational noise and improves detector performance. Enhancing sensitivity to 0νββ decay and to rare events with low-energy signatures requires identifying unresolved noise sources, advancing noise reduction methods, and improving vibration suppression systems, all of which inform the design of next-generation rare event experiments.

experimental nuclear physics↗
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 OSTI2021

Response to Andrew Fowlie’s Comments

This Letter to the Editor of Harvard Data Science Review is a rejoinder to a Letter to the Editor by Andrew Fowlie, titled “Comment on Reproducibility and Replication of Experimental Particle Physics Results”.

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↗