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At least 19 records

Calibrated particle identification for Belle II

We present several efforts aimed at improving charged particle identification at the Belle II experiment. We define an ablation test to quantify and evaluate the impact of each sub-detector on the global particle identification performance. We demonstrate that the performance of the identification scheme can be improved via a simple calibration of the sub-detector likelihoods through a set of per hypothesis, per sub-detector weights. Finally, we present preliminary results on an improved definition of the likelihoods contributed by the electromagnetic calorimeter. A set of multiclass boosted decision trees is trained to exploit the shape of energy depositions of different particle species. In simulated $B\bar{B}$ events, the pion-to-electron and muon fake rates are reduced by 55% and 31% respectively at low-medium momentum.

Hohmann, Marcel [Univ. of Melbourne, Parkville, VI

Coupling of TIGRESS and EMMA with Auxiliary Array TIP at TRIUMF

The combination of a germanium detector array and recoil mass spectrometer allows for high-sensitivity experiments in nuclear structure and astrophysics by enabling high-energy-resolution -ray spectroscopy and reaction measurements of weak fusion-evaporation, transfer or radiative-capture reactions in the presence of dominant background reaction channels. The TIGRESS -ray spectrometer with an upgraded data acquisition system has been coupled with the EMMA mass spectrometer alongside a suite of auxiliary detectors housed within TIGRESS such as TIP. This paper reviews the unique combination of radioactive beams at TRIUMF with the capabilities of TIGRESS and EMMA in the context of fusion-evaporation with TIP and radiative-capture reactions without an auxiliary array.

A/Q identification

Real-Time event reconstruction for Nuclear Physics Experiments using Artificial Intelligence

Charged track reconstruction is a critical task in nuclear physics experiments, enabling the identification and analysis of particles produced in high-energy collisions. Machine learning (ML) has emerged as a powerful tool for this purpose, addressing the challenges posed by complex detector geometries, high event multiplicities, and noisy data. Traditional methods rely on pattern recognition algorithms like the Kalman filter, but ML techniques, such as neural networks, graph neural networks (GNNs), and recurrent neural networks (RNNs), offer improved accuracy and scalability. By learning from simulated and real detector data, ML models can identify and classify tracks, predict trajectories, and handle ambiguities caused by overlapping or missing hits. Moreover, ML-based approaches can process data in near-real-time, enhancing the efficiency of experiments at large-scale facilities like the Large Hadron Collider (LHC) and Jefferson Lab (JLAB). As detector technologies and computational resources evolve, ML-driven charged track reconstruction continues to push the boundaries of precision and discovery in nuclear physics. In these proceedings, we highlight advancements in charged track identification leveraging Artificial Intelligence within the CLAS12 detector, achieving a notable enhancement in experimental statistics compared to traditional methods. Additionally, we showcase real-time event reconstruction capabilities, including the inference of charged particle properties, such as momentum, direction, and species identification, at speeds matching data acquisition rates. These innovations enable the extraction of physics observables directly from the experiment in real-time.

Gavalian, Gagik (ORCID:0000000267385457)

Measurements of hadron production in 90 GeV/𝑐 proton-carbon interactions

This paper presents the multiplicity of neutral and charged hadrons produced in 90 GeV/𝑐 proton-carbon interactions from a dataset taken by the NA61/SHINE experiment in 2017. Particle identification via d⁢𝐸/d⁢𝑥 was performed for the charged hadrons 𝜋 ± , 𝐾 ± , and $p/\bar{p}$; the neutral hadrons $K^0_S$, $Λ$, and $\bar{Λ}$ were identified via an invariant mass analysis of their decays to charged hadrons. Double-differential multiplicity results as a function of laboratory momentum and polar angle are presented for each particle species; these results provide vital constraints on the predicted neutrino beam flux for current and future long-baseline neutrino oscillation experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS

Charged-hadron identification at Belle II

The Belle II experiment’s ability to identify particles critically affects the sensitivity of its measurements. We describe Belle II’s algorithms for identifying charged particles and evaluate their performance in separating pions, kaons, and protons using $426\,\text {fb}^{-1}$ of data collected at the energy-asymmetric $e^{+}e^{-}$ collider SuperKEKB in 2019–2022 at center-of-mass energies at and near the mass of the $\Upsilon$ (4S).

Adachi, I. (ORCID:0000000322870173)

First observation of antiproton annihilation at rest on argon in the LArIAT experiment

We report the first observation and measurement of antiproton annihilation at rest on argon track and shower multiplicities and particle identification conducted with the LArIAT experiment. Stopping antiprotons from the Fermilab Test Beam Facility’s charged particle test beam are identified using beamline instrumentation and LArIAT’s liquid argon time projection chamber (LArTPC). The charged particle multiplicity from the annihilation vertex is manually evaluated via hand scanning, yielding a mean of 3.2 ± 0.4 tracks and a standard deviation of 1.3 tracks, consistent with a semiautomated reconstruction resulting in 2.8 ± 0.4 tracks and a standard deviation of 1.2 tracks. Both methods are consistent with Monte Carlo simulations within statistical uncertainty. The shower multiplicities and particle identification for outgoing tracks are also consistent with eant4 model predictions. These results, obtained from a low-statistics sample, provide a foundation for higher-statistics studies in larger LArTPCs, which could refine modeling of intranuclear annihilation on argon and inform scenarios such as neutron-antineutron oscillations. Published by the American Physical Society 2025

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS

MEASURING CLAS12 D(E, E′Π±) CROSS SECTIONS FOR E4NU

Neutrino experiments need neutrino event generators such as GENIE to simulate neutrinonucleus (¿A) interactions in order to measure neutrino oscillations. We need eA data to validate GENIE. GENIE d(e, e') cross sections do not match data in the pion production region. Further analysis of this region can help constrain GENIE models. The goal of this project was to compare 4.244 GeV CLAS12 d(e, e'p±) cross sections to GENIE predictions. We analyzed data from the Fall 2019 run period of Run Group B (RG-B). We applied particle identification, fiducial, and vertex cuts on electron and charged pion candidates. We compared the measured data with events generated with GENIE and another generator called onepigen. We used onepigen to simulate single charged pion production and to calculate radiative corrections for the data. We submitted GENIE and onepigen events to the GEant4 Monte-Carlo (GEMC) simulation of CLAS12 and applied the same cuts we used on the data. We plotted cross sections as functions of W and binned the events in Q2, ¿pq, and Pp. We used 2D (Q2), 3D (Q2 with ¿pq or Pp), and 4D (Q2, ¿pq, and Pp) binning schemes. We found GENIE describes d(e, e'p±) cross sections better than expected. GENIE describes the data remarkably well in the 2D bins and some 3D and 4D bins. There are many discrepancies between GENIE and data in the other 3D and 4D bins. The results show that, relative to data, GENIE cross sections increase as Q2 increases, decrease as Pp increases, and fit best at low ¿pq. These results will help guide improvements to GENIE in order to reduce the systematic uncertainties in neutrino-oscillation experiments.

Fogler, Caleb [Old Dominion Univ., Norfolk, VA (Un

Searching for heavy charged relics in the Earth

We propose a method for detecting an ambient density of heavy, electrically-charged particles. Such particles would impact the Earth, lose energy in terrestrial matter, and become trapped. We study the accumulation of these rare particles in multiple target materials that provide large exposure, such as water and geological rocks. We discuss strategies for concentrating the particles by centrifugation or gravitational settling, along with particle identification using mass spectrometry. This method enables the discovery of charged relics with masses $1-10^{12}\,{\rm TeV}$ comprising a tiny fraction of the local dark matter density, reaching down to $f_X\sim 10^{-20}$ at the lowest masses. A pathfinder experiment using only a liter of water and one centrifuge (or $\sim \text{m}^3$ and no centrifuge) operating for a month can already reach $f_X\sim 10^{-10}$ and probe new parameter space.

Ebadi, Reza [Johns Hopkins U.; Delaware U.] (ORCID

The SHMS 11 GeV/c spectrometer in Hall C at Jefferson Lab

The Super High Momentum Spectrometer (SHMS) has been built for Hall C at the Thomas Jefferson National Accelerator Facility (Jefferson Lab). With a momentum capability reaching 11 GeV/ c , the SHMS provides measurements of charged particles produced in electron-scattering experiments using the maximum available beam energy from the upgraded Jefferson Lab accelerator. The SHMS is an ion-optics magnetic spectrometer comprised of a series of new superconducting magnets which transport charged particles through an array of triggering, tracking, and particle-identification detectors that measure momentum, energy, angle and position in order to allow kinematic reconstruction of the events back to their origin at the scattering target. The detector system is protected from background radiation by a sophisticated shielding enclosure. The entire spectrometer is mounted on a rotating support structure which permits measurements to be taken with a large acceptance over laboratory scattering angles from 5.5° to 40°, thus allowing a wide range of low cross-section experiments to be conducted. Finally, these experiments complement and extend the previous Hall C research program to higher energies.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS

The sweeper spectrometer for neutron invariant-mass spectroscopy at FRIB

Neutron invariant-mass spectroscopy (NIMS) is a key technique for studying unbound and weakly bound nuclei at the limits of stability. At the Facility for Rare Isotope Beams (FRIB), such measurements are performed using the Sweeper spectrometer, a large-gap, high-rigidity dipole system coupled to the MoNA-LISA neutron detector arrays. To meet the demands imposed by higher beam energies (>130 MeV/u) and the broad cocktail-beam selection available at FRIB, the spectrometer has recently been upgraded to improve particle-identification and detection performance. Upstream of the reaction target, a plastic scintillator with Silicon photomultiplier (SiPM) readout provides the global trigger and time reference, two parallel plate avalanche counters (PPACs) track the trajectories of incoming beam particles, and a silicon PIN detector measures the energy loss, ΔE, for charge (Z) identification. After the Sweeper magnet, the trajectories of the reaction products are tracked by two micro-pattern drift chambers (MPDCs), their charge (Z) is identified by a Frisch-grid ionization chamber (FG-IC), and their mass-to-charge ratio (A/Q) is deduced by time-of-flight measurement using a fast plastic scintillator read out by an array of photomultiplier tubes (PMTs). The detection system also incorporates the Modular Neutron Array (MoNA) for neutron detection and the CAESium-iodide scintillator ARray (CAESAR) for high-efficiency γ-ray measurements to enable full kinematic reconstruction. Performance was evaluated using a cocktail beam around 37 Al accelerated at E ≈ 130 MeV/u during the first FRIB campaign, demonstrating the readiness of the upgraded system for future studies of nuclei at and beyond the neutron drip line.

Particle identification methods

Discovery of new isotopes in the fragmentation of 82 Se and insights into their production

The production cross sections of neutron-rich nuclei for elements just above 60 Ca were measured at the Facility for Rare Isotope Beams (FRIB). Four previously unobserved isotopes ( 63 Sc, 65,66 Ti, and 68 V) were produced, separated, and identified for the first time using the Advanced Rare Isotope Separator (ARIS). One event was found to be consistent with 61 Ca . The new isotopes were created through the interaction of an 82 Se beam with a carbon target at an energy of 228 MeV/𝑢 and a primary beam current of 1.07 p⁢µ⁢A. The event-by-event particle identification of the mass number (𝐴), atomic number (𝑍), and ionic charge state (𝑞) for the reaction products was achieved by combining measurements of energy loss, time of flight, magnetic rigidity, and total kinetic energy. This successful search for new isotopes, conducted at the beginning of FRIB's third year of operation, highlights the facility's discovery potential, which will continue to grow as the beam current increases. The production cross sections were analyzed in the context of the newly developed Δ⁢𝐵⁢𝐸 systematics that provides trends in neutron-rich regions and increased sensitivity to nuclear binding, an important nuclear structure observable. Furthermore, the new systematics addresses gaps in 𝑄 𝑔 -based methods commonly used to interpret the production cross sections of light neutron-rich elements, and provides an efficient empirical approach to describe cross-section trends across isotopic chains. Good agreement with the measured data was obtained when the Δ⁢𝐵⁢𝐸 systematics and abrasion-ablation calculations were performed using the Hartree-Fock-Bogoliubov (HFB-22) mass table.

59 ≤ A ≤ 89

Advancing Artificial Intelligence with Liquid Argon Neutrino Experiments (Technical Report)

The grant allowed two main contributions: 1) The development of a first successful demonstration of the employment of Optimal Transport in liquid argon time projection chamber neutrino detectors. Optimal Transport, used in other contexts and specifically with LHC calorimetric data, was adapted to address a key particle identification challenge in LArTPCs: the separation of pi0 backgrounds from single-electrons produced in charged-current electron neutrino interactions. The work, leveraging ML methods such as k-nearest-neighbor (kNN) and support-vector-machine (SVM), showed an increase in background rejection of a factor of two or more. Work is now ongoing to incorporate this development in physics analyses for LArTPC experiments and more broadly expand the use of OT in LArTPC detectors including DUNE. This work was done in collaboration with the phenomenology group led by Nathaniel Craig at UCSB. 2) The deployment of NuGraph2, a graph neural network developed for LArTPC reconstruction, in the MicroBooNE experiment. NuGraph2 uses novel graph-neural-network methods on the rather simple LArTPC inputs of reconstructed hits, greatly simplifying the workflow compared to the use of waveform or signal-deconvolved wire ROIs. The network performed particle classification and was shown to address many challenging problems in LArTPC imaging including track-shower separation and the identification of protons and charged pions from primary muons. Our group collaborated with Giuseppe Cerati (FNAL scientist) who is one of the core developers of NuGraph2 to integrate this tool in MicroBooNE’s analysis framework. This consisted in tow key contributions: a) Studying performance on real data, which came with several months of iterations because the MC-trained version of the network was found to show significant bias that our group investigated and addressed. b) Integrating the output hit labeling of NuGraph2 into the existing particle tracking and shower reconstruction code. As a result of this work led by our team NuGraph2 is now enabling a suite of new analyses which benefit from enhanced capabilities and thus broader physics reach. The grant supported primarily the salary of UCSB graduate student Chuyue “Michaelia” Fang as well as partial summer salary support for PI Caratelli. Some funds were used for travel by Michaelia to ML related schools and conferences.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS

Performance of the Particle-Identification Silicon-Telescope Array coupled with the VAMOS++ magnetic spectrometer

The Particle-Identification Silicon-Telescope Array (PISTA) is a new detection system designed for high-resolution studies of fission process induced by multi-nucleon transfer in inverse kinematics. It is specifically optimized for experiments with the VAMOS++ magnetic spectrometer at GANIL (Grand Accélérateur National d’Ions Lourds). The array comprises eight trapezoidal ΔE-E silicon telescopes arranged in a lamp shade configuration. Each telescope integrates two single-sided stripped silicon detectors, enabling target-like recoil identification, energy loss measurements, and trajectory reconstruction. Positioned in close proximity to the target, PISTA’s compact geometry achieves high-efficiency tracking of target-like recoils produced in multi-nucleon transfer reactions at Coulomb barrier energies. The spatial segmentation of the array allows precise determination of the mass and charge of the target-like nucleus, and excitation energy of fissioning systems. This work presents the particle identification and excitation energy reconstruction performances for the interactions of 238 U beam with 12 C target. An excitation energy resolution of 800 keV (FWHM) was determined together with mass resolution of 1.1% (FWHM). The combination of PISTA and VAMOS++ magnetic spectrometer enables unprecedented investigations of the fission process as a function of the excitation energy of the fissioning nucleus, particularly for exotic systems produced in transfer-induced reactions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND

First Measurement of Charged Current Muon Neutrino-Induced Kaon Production on Argon

The Micro Booster Neutrino Experiment (MicroBooNE) is a liquid argon time projection chamber (LArTPC) neutrino detector with an 85-ton active volume, located on-axis to the Booster Neutrino Beamline (BNB) at Fermilab. The detector is exposed to a neutrino flux with average energy of 800 MeV and was designed to study neutrino interactions on argon, particularly in the 1 GeV energy range. Among its main goals is the investigation of neutrino-induced strange particle production at final-state, with a specific interest on charged kaons ($K^{+}$). The understanding of this neutrino interaction is crucial for refining background models in future nucleon decay searches on others LArTPCs experiments such as the Deep Underground Neutrino Experiment (DUNE). Additionally, the techniques developed for the identification of neutrino-induced $K^{+}$ will contribute to improving particle identification methods in LArTPC-based detectors. This thesis is reporting the first-ever measurement of the flux-integrated cross section for charged-current muon neutrino-induced $K^{+}$ production on argon, determined to be $7.93 \pm 3.27(\text{stat.}) \pm 2.92(\text{syst.}) \times 10^{-42}$ cm$^2$/nucleon, based on the MicroBooNE dataset corresponding to $6.88 \times 10^{20}$ Protons on Target (POT).

Rodriguez Rondon, Jairo H. [South Dakota Sch. Mine

Multiscale electro-chemo-mechanical model of high-capacity amorphous silicon anode material in sodium-ion batteries

The growing interest in sodium-ion batteries (SIBs) is fueled by their abundant resources and environmentally friendly nature, with amorphous silicon (a-Si) emerging as a promising anode material for enhancing capacity. However, the key challenge lies in sustaining reversible capacity during cycling. Here, in this work, we developed a multiscale electrochemical model incorporating an a-Si anode to elucidate the performance parameters of SIBs. Additionally, we integrated an electro-chemo-mechanical model at the particle level to capture stress generation, an essential factor in the degradation of high-capacity electrodes. Unlike existing models, our approach accounts for large-deformation chemo-mechanics at the particle scale and includes simulations under varying charge rates to explore multiscale behavior. The results reveal that coupled sodiation significantly prolongs complete cycling times and influences discharge dynamics, indicating that neglecting this coupling leads to an underestimation of actual capacity. Furthermore, we observed pronounced polarization effects at higher charge rates, resulting in heterogeneous stress distributions across the anode. With the identification of critical failure parameters for both active particles and binder materials, offering novel insights for mitigating degradation in high-capacity electrode systems.

Amorphous silicon anode

First Measurement of Charged Current Muon Neutrino-Induced Kaon Production on Argon using the MicroBooNE Detector

MicroBooNE is an 85-tonne active mass liquid argon time projection chamber (LArTPC) neutrino detector exposed to the Booster Neutrino Beamline (BNB) at Fermilab. One of the key physics goals is the precise measurement of neutrino interactions on argon in the 1 GeV energy regime. The study of strange and heavier meson production in neutrino interactions, in particular final states containing $K^{+}$, will help to improve the background estimates for future nucleon decay searches in experiments such as DUNE, provide valuable input for improving neutrino generator models, and will allow the development of techniques to enhance the particle identification capabilities of LArTPCs. In this work, we present the first-ever cross-section measurements of charged current muon neutrino-induced kaon production on argon at MicroBooNE.

Rodriguez Rondon, Jairo H. [South Dakota Sch. Mine

First Measurement of Sub-GeV nu_mu Charged-Current Coherent Pion Production on Argon in MicroBooNE

Coherent pion production, characterized by a neutrino interacting with an entire nucleus without breaking it apart, results in a forward-going muon, pion, and a low-momentum recoil nucleus. This process provides a sensitive probe of neutrino-nucleus interactions and offers a potential standard candle for neutrino-flux normalization in neutrino-oscillation experiments. We present the first measurement of the flux-averaged charged-current coherent pion production cross section on argon nucleus using the MicroBooNE liquid argon time projection chamber. The analysis employs particle identification together with a data-driven background parameterization to isolate the coherent signal. This measurement uses the full MicroBooNE dataset collected from the Fermilab Booster Neutrino Beam, corresponding to an exposure of 1.26E10^21 protons on target and an average neutrino energy of approximately 0.8 GeV. The result provides the first constraint on charged-current coherent pion production on argon nucleus at sub-GeV energies and supplies important input for improving neutrino interaction modeling in current and future experiments such as DUNE.

Hussain, Adil [Kansas State U.] (ORCID:00000001621

Likelihood-Based Particle Identification in the Short-Baseline Near Detector

Accurate particle identification is crucial in any high-energy physics experiment, allowing scientists to understand the unique interactions and mechanisms at play in a detector. In this project, I develop and study a new particle identification (PID) algorithm for the Short-Baseline Near Detector, a likelihood-based approach, different from out current $\chi^2$ method. A likelihood estimation offers a more physically motivated strategy for PID. The distribution random energy losses of charged particles traveling through a medium are described by the Vavilov probability density function. By using this model, we can account for random energy losses and construct likelihood functions specific to each particle type, potentially enabling a more accurate method for PID.

Vanderwaal, Sophia [U. Alabama, Huntsville] (ORCID