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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Automated detector simulation and reconstruction parametrization using machine learning

Rapidly applying the effects of detector response to physics objects (e.g. electrons, muons, showers of particles) is essential in high energy physics. Presently available tools for the transformation from truth-level physics objects to reconstructed detector-level physics objects involve manually defining resolution functions. These resolution functions are typically derived in bins of variables that are correlated with the resolution (e.g. pseudorapidity and transverse momentum). This process is time consuming, requires manual updates when detector conditions change, and can miss important correlations. Machine learning offers a way to automate the process of building these truth-to-reconstructed object transformations and can capture complex correlation for any given set of input variables. Such machine learning algorithms, with sufficient optimization, could have a wide range of applications: improving phenomenological studies by using a better detector representation, allowing for more efficient production of Geant4 simulation by only simulating events within an interesting part of phase space, and studies on future experimental sensitivity to new physics.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Measurement of the muon spin precession frequency using the straw tracking detectors at the Fermilab Muon g-2 experiment

The measurement of the anomalous magnetic dipole moment of the muon ($a_{\mu}$) has long stood as an excellent precision test of the Standard Model (SM). The Fermilab Muon g-2 experiment has recently finished data-taking and in July 2023 published its latest determination of $a_\mu$ with a world-leading precision of 0.2\,ppm. In this publication, it surpassed the systematic uncertainty goal defined in the TDR. The analyses of a dataset approximately four times larger than this recent publication is now underway. The principle measurement of the Muon g-2 experiment measures $a_{\mu}$ by taking the ratio of two frequencies; the anomalous precession frequency ($\omega_a$) and the muon-weighted magnetic field of the experiment's storage ring measured from the precession frequency of protons in water using nuclear magnetic resonance (NMR) probes. In all publications to date, $\omega_a$ has been determined using energy deposits in the 24 calorimeters. However, the Fermilab experiment has t wo straw tracker detectors measuring the time and momentum of charged particles which can in principle also be used to to measure $\omega_a$ and such a measurement can provide an invaluable cross-check of the calorimeter result with different, and reduced, systematic uncertainties. This thesis presents the first (blinded) determination of $\omega_a$ using just charged tracks from the straw tracking detectors as opposed to calorimeter energy deposits. This analysis was undertaken using the Run-2/3 dataset which represents approximately 25\% of the final dataset. A total uncertainty of 2.19\,ppm on $\omega_a$ was obtained which is dominated by the statistical uncertainty of 2.16\,ppm. Additionally two new methodologies important to the analysis of the straw tracking data have been developed: one to better determine the track arrival time ($t_0$) and one to determine the level of pileup in the tracking detectors. The new $t_0$ algorithm which incorporates angular information improves t he resolution on the determination of the $t_0$ by a factor of two and results in 19\% more tracks being successfully reconstructed. The data from the trackers is also used to determine the beam profile that weights the magnetic field in the determination of $a_\mu$ and in determining several of the systematic uncertainties in the calorimeter-based $\omega_a$ analysis. A detailed study of the impact of the internal alignment of the tracker, the $t_0$ and pileup on the determination of the beam position was undertaken and propagated through to an uncertainty in the $\omega_a$ determination. These uncertainties were used in the Fermilab Muon g-2 experiment's recent publication in Phys. Rev. Lett.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2000

Charge Detector Study for a Thin Sampling Calorimeter for ACCESS

Advanced Cosmic ray Composition Experiment for Space Station (ACCESS) is a NASA's new mission concept that is now being studied. The scientific objective is to measure cosmic ray elemental energy spectra in the energy range from I TeV up to 1000 TeV. ACCESS will carry two instruments and measure the energy and charge of incoming particles. One of these will be a calorimeter with a charge detector. The charge detector will see not only signals from the incident cosmic rays but also signals from radiation backscattered from the calorimeter. In that case, bias information on particle identification is unavoidable. This study shows how much the charge detector will be affected by backscatter and how it can be designed with a minimized effect.

Lee, Jeongin↗
DOE OSTI2025

A gravity-based mounting approach for large-scale cryogenic calorimeter arrays

Cryogenic calorimeters are among the leading technologies for searching for rare events. The CUPID experiment is exploiting this technology to deploy a tonne-scale detector to search for neutrinoless double-beta decay of 100 Mo. The CUPID collaboration proposed an innovative approach to assembling cryogenic calorimeters in a stacked configuration, held in position solely by gravity. This gravity-based assembly method is unprecedented in the field of cryogenic calorimeters and offers several advantages, including relaxed mechanical tolerances and simplified construction. To assess and optimize its performance, we constructed a medium-scale prototype hosting 28 Li 2 MoO 4 crystals and 30 Ge light detectors, both operated as cryogenic calorimeters at the Laboratori Nazionali del Gran Sasso (Italy). Despite an unexpected excess of noise in the light detectors, the results of this test proved (i) a thermal stability better than ±0.5 mK at 10 mK, (ii) a good energy resolution of Li 2 MoO 4 cryogenic calorimeters, (6.6 ± 2.2) keV FWHM at 2615 keV, and (iii) a Li 2 MoO 4 light yield measured by the closest light detector of 0.36 keV/MeV, sufficient to guarantee the particle identification requested by CUPID.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2001

Low power, lightweight vapor sensing using arrays of conducting polymer composite chemically-sensitive resistors

Arrays of broadly responsive vapor detectors can be used to detect, identify, and quantify vapors and vapor mixtures. One implementation of this strategy involves the use of arrays of chemically-sensitive resistors made from conducting polymer composites. Sorption of an analyte into the polymer composite detector leads to swelling of the film material. The swelling is in turn transduced into a change in electrical resistance because the detector films consist of polymers filled with conducting particles such as carbon black. The differential sorption, and thus differential swelling, of an analyte into each polymer composite in the array produces a unique pattern for each different analyte of interest, Pattern recognition algorithms are then used to analyze the multivariate data arising from the responses of such a detector array. Chiral detector films can provide differential detection of the presence of certain chiral organic vapor analytes. Aspects of the spaceflight qualification and deployment of such a detector array, along with its performance for certain analytes of interest in manned life support applications, are reviewed and summarized in this article.

NASA Discipline Life Sciences Technologies↗
DOE OSTI2020

Neutrino identification with scintillation light in MicroBooNE

MicroBooNE is a neutrino experiment which employs a liquid argon (LAr) time projection chamber (TPC) to record neutrino interactions from Fermilab's neutrino beamlines. The experiment's primary objective is to study low-energy νe interactions from the Booster Neutrino Beamline (BNB). Located on the surface, the detector is affected by a continuous rate of cosmic-rays. This leads to one neutrino interaction for every 104 cosmic rays observed in the TPC, making it difficult to isolate neutrino interactions in the detector using charge alone. MicroBooNE's trigger makes use of prompt scintillation light and plays an essential role in both performing strong background rejection and significantly reducing data-rates. Furthermore, a series of novel techniques relying on scintillation light are used to isolate beam-induced activity. This document briefly presents MicroBooNE's scintillation-light based trigger and novel Flash-Matching pattern recognition techniques for cosmic-rejection. This work serves as the foundation of neutrino analyses in LArTPC detectors and is therefore of interest to the broader short- and long-baseline neutrino programs being launched at Fermilab.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Development of a novel, windowless, amorphous selenium based photodetector for use in liquid noble detectors

Detection of the vacuum ultraviolet (VUV) scintillation light produced by liquid noble elements is a central challenge in order to fully exploit the available timing, topological, and calorimetric information in detectors leveraging these media. Here in this paper, we characterize a novel, windowless amorphous selenium based photodetector with direct sensitivity to VUV light. We present here the manufacturing and experimental setup used to operate this detector at low transport electric fields (2.7–5.2 V/μm) and across a wide range of temperatures (77 K–290 K). This work shows that the first proof-of-principle windowless amorphous selenium device is robust under cryogenic conditions, responsive to VUV light at cryogenic temperatures, and preserves argon purity. These findings motivate a continued exploration of amorphous selenium devices for simultaneous detection of scintillation light and ionization charge in noble element detectors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Deuteron Evaporation from N = Z Compound Nuclei

Deuteron evaporation was observed from the N = Z compound nuclei 52 Fe ⋆ , 56 Ni ⋆ , and 64 Ge ⋆ in an experiment conducted at Argonne National Laboratory, USA. The experiment included a novel combination of two highly pixelated double-sided Si-strip detectors inside the Microball chargedparticle detection array, allowing for unequivocal discrimination of evaporated deuterons from protons and α particles. In conjunction with the Gammasphere array, Neutron Shell, and additional ancillary detectors, decay paths into various residual nuclei were investigated. The study provides insights into the competition of deuteron vs. proton-neutron evaporation as a function of available excitation energy and populated angular momentum. Results are interpreted using a statistical evaporation formalism for multiple subsequent particle emissions. The decisive factor in the comparison appears to be the available excitation energy in the residual system, with single nucleon evaporation preferred over deuteron evaporation for higher excitation energies.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1975

Flux of high-LET cosmic-ray particles in manned space flight

On the Apollo and Skylab missions the high-energy heavy ion (HZE) flux was measured by means of plastic nuclear track detectors. Measurements involved the fluxes of high linear energy transfer (LET), particles with Z between 6 and 26 incident on astronauts and on several biological experiments. Partial results of these measurements are presented; the effects of shielding and solar modulation are discussed.-

Benton, E. V.↗
DOE OSTI2024

Search for a Long-Lived $\mu\mu$ Resonance in the NuMI Beam at ICARUS

The ICARUS detector in the Short-Baseline Neutrino program at Fermilab is sensitive to “long-lived” new physics particles that would be produced in the Neutrinos at the Main Injector (NuMI) beam and decay inside the ICARUS liquid argon time projection chamber (LArTPC). We show results from a new analysis in ICARUS which searched for di-muon decays from a long-lived particle produced in kaon decay in the NuMI beam. The search is sensitive to new areas of parameter space for the Higgs portal scalar and an axion-like particle model. The sensitivity is also presented in a model-independent way applicable to any new physics model predicting the process $K \to \pi+S(\to\mu\mu)$, for a long-lived particle S. This is the first search for new physics performed with the ICARUS detector at Fermilab. It paves the way for the future program of long-lived particle searches at ICARUS.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Reweighting simulated events using machine-learning techniques in the CMS experiment

Data analyses in particle physics rely on an accurate simulation of particle collisions and a detailed simulation of detector effects to extract physics knowledge from the recorded data. Event generators together with a GEANT -based simulation of the detectors are used to produce large samples of simulated events for analysis by the LHC experiments. These simulations come at a high computational cost, where the detector simulation and reconstruction algorithms have the largest CPU demands. This article describes how machine-learning (ML) techniques are used to reweight simulated samples obtained with a given set of parameters to samples with different parameters or samples obtained from entirely different simulation programs. The ML reweighting method avoids the need for simulating the detector response multiple times by incorporating the relevant information in a single sample through event weights. Results are presented for reweighting to model variations and higher-order calculations in simulated top quark pair production at the LHC. This ML-based reweighting is an important element of the future computing model of the CMS experiment and will facilitate precision measurements at the High-Luminosity LHC.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Track Seeding and Labelling with Embedded-space Graph Neural Networks

To address the unprecedented scale of HL-LHC data, the Exa.TrkX project is investigating a variety of machine learning approaches to particle track reconstruction. The most promising of these solutions, graph neural networks (GNN), process the event as a graph that connects track measurements (detector hits corresponding to nodes) with candidate line segments between the hits (corresponding to edges). Detector information can be associated with nodes and edges, enabling a GNN to propagate the embedded parameters around the graph and predict node-, edge- and graph-level observables. Previously, message-passing GNNs have shown success in predicting doublet likelihood, and we here report updates on the state-of-the-art architectures for this task. In addition, the Exa.TrkX project has investigated innovations in both graph construction, and embedded representations, in an effort to achieve fully learned end-to-end track finding. Hence, we present a suite of extensions to the original model, with encouraging results for hitgraph classification. In addition, we explore increased performance by constructing graphs from learned representations which contain non-linear metric structure, allowing for efficient clustering and neighborhood queries of data points. We demonstrate how this framework fits in with both traditional clustering pipelines, and GNN approaches. The embedded graphs feed into high-accuracy doublet and triplet classifiers, or can be used as an end-to-end track classifier by clustering in an embedded space. A set of post-processing methods improve performance with knowledge of the detector physics. Finally, we present numerical results on the TrackML particle tracking challenge dataset, where our framework shows favorable results in both seeding and track finding.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Design and implementation of the cosmic ray tagger system for the ICARUS detector at FNAL

The ICARUS-T600 Liquid Argon Time Projection Chamber is operating at Fermilab at shallow depth and thus exposed to a high flux of cosmic rays that can fake neutrino interactions. A cosmic ray tagging (CRT) system (∼ 1100 m 2 ), surrounding the cryostat with two layers of fiber embedded plastic scintillators, was developed to mitigate the cosmic ray induced background. Using nanosecond-level timing information, the CRT can distinguish incoming cosmic rays from outgoing particles from neutrino interactions in the TPC. In this paper an overview of the CRT system, its installation and commissioning at Fermilab, and its performance are discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

The track-length extension fitting algorithm for energy measurement of interacting particles in liquid argon TPCs and its performance with ProtoDUNE-SP data

This paper introduces a novel track-length extension fitting algorithm for measuring the kinetic energies of inelastically interacting particles in liquid argon time projection chambers (LArTPCs). The algorithm finds the most probable offset in track length for a track-like object by comparing the measured ionization density as a function of position with a theoretical prediction of the energy loss as a function of the energy, including models of electron recombination and detector response. The algorithm can be used to measure the energies of particles that interact before they stop, such as charged pions that are absorbed by argon nuclei. The algorithm's energy measurement resolutions and fractional biases are presented as functions of particle kinetic energy and number of track hits using samples of stopping secondary charged pions in data collected by the ProtoDUNE-SP detector, and also in a detailed simulation. Additional studies describe the impact of the dE/dx model on energy measurement performance. The method described in this paper to characterize the energy measurement performance can be repeated in any LArTPC experiment using stopping secondary charged pions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Measurement of the Muon Flux at the Sanford Underground Research Facility with the LUX-ZEPLIN Dark Matter Detector

High-energy cosmic-ray muons reaching deep underground laboratories can cause events in detectors that mimic signals expected from dark matter particles, neutrinos, or rare decays. Knowledge of the muon flux and energy spectrum is important for evaluating the background rate caused by muons and their secondaries. In this paper, we report the measurement of the cosmic-ray muon flux in the Davis Campus of the Sanford Underground Research Facility with the LUX-ZEPLIN detector. Using 366.4~days of exposure, the muon rate through the detector was measured as $10.94\pm0.17_\textrm{stat.}~\textrm{day}^{-1}$ with energy thresholds of 20~MeV in the inner xenon detector and 8 MeV in the outer liquid scintillator detector. This rate corresponds to a muon flux of $(5.09\pm0.08_\textrm{stat.}\pm0.10_\textrm{sys.})\times10^{-9}~\textrm{cm}^{-2}\textrm{s}^{-1}$ in the Davis Cavern.

Akerib, D. S. [SLAC; Stanford U., Phys. Dept.; KIP↗
DOE OSTI2023

Design of a Cryogenic Scintillation Neutrino Detector at the Spallation Neutron Source

We successfully verified in the following three aspects the feasibility of using a cryogenic scintillating crystal-based neutrino detector at the Spallation Neutron Source (SNS), Oak Ridge National Laboratory, for the detection of low-mass dark matter particles and non-standard neutrino interactions (NSIs), as part of the detector R&D effort of the COHERENT experiment. First, we demonstrated the possibility of using silicon photomultipliers (SiPMs) at cryogenic temperatures to replace traditional photomultiplier tubes (PMTs) as light sensors. Second, we verified that the high light yield of undoped CsI crystals measured above 13 keVee at 77 K still holds down to 5.9 keVee. Third, we successfully measured nuclear quenching factor of undoped cryogenic CsI at the Triangle Universities Nuclear Laboratory with the help from our Duke collaborators. The first achievement resulted in a publication in European Physics Journal C. The second resulted in an arXiv pre-print, which is under journal review. The last one indicates that the performance of the proposed detector may be better than what was assumed in the literature. The analysis is in the final stage and will result in another journal publication. In addition, two graduate students involved in this project graduated with master’s degrees during the project period. Both decided to continue their research as PhD students. One open-source data analysis code package was created and is publicly available on GitHub. A set of tutorials about Monte Carlo simulation of radiation interacting with detectors were created on YouTube, receiving more than 100,000 views.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Improving ProtoDUNE pion cross-section measurements with NuGraph Michel-electron tagging

Understanding hadron-argon interactions is essential for precise neutrino energy reconstruction and final-state interaction modeling in liquid-argon time projection chamber (LArTPC) experiments such as DUNE. In particular, pion absorption and charge-exchange processes constitute significant sources of systematic uncertainty in neutrino oscillation measurements. ProtoDUNE-SP, a large-scale LArTPC prototype operated at the CERN Neutrino Platform and exposed to charged-particle test beams in the few-GeV range, enables direct measurements of these processes. This work focuses on the measurement of differential cross sections for pion absorption and charge exchange using the 2 GeV/c pion beam data from the ProtoDUNE-SP run. A key component of this analysis is the identification of Michel electrons from $\pi \rightarrow \mu \rightarrow e$ decay chains, which helps separate different interaction topologies and improves background rejection. Michel electron identification will also assist in reliably calibrating the electromagnetic response in ProtoDUNE-SP data and for the future DUNE detectors. In this analysis, we apply NuGraph to identify Michel electrons. NuGraph is a graph neural network that models detector hits as nodes connected by spatial and temporal edges for particle and topology classification in LArTPC detectors. We first benchmark NuGraph’s Michel electron classification performance using ICEBERG data, a small-scale LArTPC prototype used for DUNE electronics and reconstruction development, and then transfer the approach to ProtoDUNE-SP. This poster presents the analysis strategy, NuGraph-based classification studies, and discusses how these developments are expected to improve the pion cross-section measurement.

Razafinime, Soamasina Herilala [Cincinnati U.] (OR↗