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At least 433 records · Page 24

Differentiable Simulation of a Liquid Argon Time Projection Chamber

Liquid argon time projection chambers (LArTPCs) are widely used in particle detection for their tracking and calorimetric capabilities. The particle physics community actively builds and improves high-quality simulators for such detectors in order to develop physics analyses in a realistic setting. The ability of these simulators to mimic real, measured data is limited by the modeling of the physical detectors used for data collection. This modeling can be improved by performing dedicated calibration measurements. Conventional approaches calibrate individual detector parameters or processes one at a time. However, the impact of detector processes is entangled, making this a poor description of the underlying physics. We introduce a differentiable simulator that enables a gradient-based optimization, allowing for the first time a simultaneous calibration of all detector parameters. We describe the procedure of making a differentiable simulator, highlighting the challenges of retaining the physics quality of the standard, non-differentiable version while providing meaningful gradient information. We further discuss the advantages and drawbacks of using our differentiable simulator for calibration. Finally, we provide a starting point for extensions to our approach, including applications of the differentiable simulator to physics analysis pipelines.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Exotic Dark Matter Search with the Majorana Demonstrator

With excellent energy resolution and ultralow-level radiogenic backgrounds, the high-purity germanium detectors in the enable searches for several classes of exotic dark matter (DM) models. In this work, we report new experimental limits on keV-scale sterile neutrino DM via the transition magnetic moment from conversion to active neutrinos ν s → ν a . We report new limits on fermionic dark matter absorption ( χ + A → ν + A ) and sub-GeV DM-nucleus 3 → 2 scattering ( χ + χ + A → ϕ + A ), and new exclusion limits for bosonic dark matter (axionlike particles and dark photons). These searches utilize the (1–100)-keV low-energy region of a 37.5-kg y exposure collected by the between May 2016 and November 2019 using a set of Ge 76 -enriched detectors whose surface exposure time was carefully controlled, resulting in extremely low levels of cosmogenic activation. Published by the American Physical Society 2024

47 OTHER INSTRUMENTATION↗

Reflectance and fluorescence characteristics of PTFE coated with TPB at visible, UV, and VUV as a function of thickness

Polytetrafluoroethylene (PTFE) is an excellent diffuse reflector widely used in light collection systems for particle physics experiments. In noble element systems, it is often coated with tetraphenyl butadiene (TPB) to allow detection of vacuum ultraviolet scintillation light. Here, in this work this dependence is investigated for PTFE coated with TPB in air for light of wavelengths of 200 nm, 260 nm, and 450 nm. The results show that TPB-coated PTFE has a reflectance of approximately 92% for thicknesses ranging from 5 mm to 10 mm at 450 nm, with negligible variation as a function of thickness within this range. A cross-check of these results using an argon chamber supports the conclusion that the change in thickness from 5 mm to 10 mm does not affect significantly the light response at 128 nm. Our results indicate that pieces of TPB-coated PTFE thinner than the typical 10 mm can be used in particle physics detectors without compromising the light signal.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Magnetic Detection of Chemical Threats

Los Alamos researchers have developed a technology to quickly detect chemical threats using a fieldable detector that provides real-time detection to ensure safety for warfighters, agricultural workers, and the general public. Traditional laboratory-based detection does not allow for agile response to threats on the battlefield or to our food supply chain. Our portable detector brings the laboratory to the field for real-time detection of chemical agents in samples without needing to send the samples to a remote location for analysis. This technology fits a market need in public safety, military sensor design, and pesticide detection. We have proven that this technology works on the benchtop, and are working to miniaturize the system to enable deployment. We are seeking qualified licensing or CRADA partners to finalize development of this system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Low power implementation of high frequency SiPM readout for Cherenkov and scintillation detectors in TOF-PET

State-of-the-art (SoA) electronic readout for silicon photomultiplier (SiPM)-based scintillation detectors that demonstrate experimental limits in achievable coincidence time resolution (CTR) leverage low noise, high frequency signal processing to facilitate a single photon time response that is near the limit of the SiPMs architecture. This readout strategy can optimally exploit fast luminescence and prompt photon populations, and promising measurements show detector concepts employing this readout can greatly advance PET detector CTR, relative to SoA in clinical systems. However, the technique employs power hungry components which make the electronics chain impractical for channel-dense time-of-flight (TOF)-PET detectors. We have developed and tested a low noise and high frequency readout circuit which is performant at low power and consists of discrete elements with small footprints, making it feasible for integration into TOF-PET detector prototypes. A 3 × 3 mm 2 Broadcom SiPM with this readout chain exhibited sub-100 ps single photon time resolution at 10 mW of power consumption, with a relatively minor performance degradation to 120 ± 2 ps FWHM at 5 mW. CTR measurements with 3 × 3 × 20 mm 3 LYSO and fast LGSO scintillators demonstrated 127 ± 3 ps and 113 ± 2 ps FWHM at optimal power operation and 133 ± 2 ps and 121 ± 3 ps CTR at 5 mW. BGO crystals 3 × 3 × 20 mm 3 in size show 271 ± 5 ps FWHM CTR (1174 ± 14 ps full-width-at-tenth-maximum (FWTM)) at optimal power dissipation and 289 ± 8 ps (1296 ± 33 ps FWTM) at 5 mW. The compact and low power readout topology that achieves this performance thereby offers a platform to greatly advance PET system CTR and also opportunities to provide high performance TOF-PET at reduced material cost.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Low-cost, constrained-motion dynamometer for milling force measurement

This paper describes the design and testing of a low-cost dynamometer for milling force measurement. The monolithic design is based on constrained-motion/flexure-based kinematics, where force is inferred from displacement measured using a low-cost optical interrupter (i.e., a knife edge that partially interrupts the beam in an emitter-detector pair). The time-dependent displacement of the dynamometer’s moving platform caused by the milling force is converted to the frequency domain, multiplied by the inverse of the single degree of freedom frequency response, and converted back to the time domain to obtain the time dependent cutting force. Lastly, comparisons with commercially available, piezoelectric-based force measurement are provided.

47 OTHER INSTRUMENTATION↗

Extracting low energy signals from raw LArTPC waveforms using deep learning techniques — A proof of concept

Here, we investigate the feasibility of using deep learning techniques, in the form of a one-dimensional convolutional neural network (1D-CNN), for the extraction of signals from the raw waveforms produced by the individual channels of liquid argon time projection chamber (LArTPC) detectors. A minimal generic LArTPC detector model is developed to generate realistic noise and signal waveforms used to train and test the 1D-CNN, and evaluate its performance on low-level signals. We demonstrate that our approach overcomes the inherent shortcomings of traditional cut-based methods by extending sensitivity to signals with ADC values below their imposed thresholds. This approach exhibits great promise in enhancing the capabilities of future generation neutrino experiments like DUNE to carry out their low-energy neutrino physics programs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Accelerating quantum optics experiments with statistical learning

Quantum optics experiments, involving the measurement of low-probability photon events, are known to be extremely time-consuming. We present a methodology for accelerating such experiments using physically motivated ansatzes together with simple statistical learning techniques such as Bayesian maximum a posteriori estimation based on few-shot data. We show that it is possible to reconstruct time-dependent data using a small number of detected photons, allowing for fast estimates in under a minute and providing a one-to-two order of magnitude speed-up in data acquisition time. We test our approach using real experimental data to retrieve the second order intensity correlation function, G (2) ($τ$), as a function of time delay τ between detector counts, for thermal light as well as anti-bunched light emitted by a quantum dot driven by periodic laser pulses. The proposed methodology has a wide range of applicability and has the potential to impact the scientific discovery process across a multitude of domains.

36 MATERIALS SCIENCE↗

Inferring thermal ion temperature and residual kinetic energy from nuclear measurements in inertial confinement fusion implosions

In inertial con finement fusion implosion experiments, the presence of residual anisotropic fluid motion within the stagnating hot spot leads to signifi cant variations in ion-temperature measurements using neutron time- of-flight detectors along different lines of sight. The minimum ion-temperature measurement is typically used as representative of the thermal temperature. In the presence of isotropic flows, however, even the minimum DT neutron-inferred ion temperature can be well above the plasma thermal temperature. Using both DD and DT neutron-inferred ion-temperature measurements, we show that it is possible to determine the contribution of isotropic flows and infer the DT burn-averaged thermal ion temperature. The contribution of large isotropic flows on driving the ratio of DD to DT neutron-inferred ion temperatures well below unity and approaching the lower bound of 0.8 is demonstrated in multimode simulations. The minimum DD neutron- inferred ion temperature is determined from the velocity variance analysis, accounting for the presence of isotropic flows. Being close to the DT burn-averaged thermal ion temperature, the inferred DD minimum ion temperatures demonstrate a strong correlation with the experimental yields in the OMEGA implosion database. An analytical expression is also derived to explain the effect of mode ℓ = 1 ion-temperature measurement asymmetry on yield degradations caused by the anisotropic flows.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Application of an energy-dependent instrument response function to analysis of nTOF data from cryogenic DT experiments

Neutron time-of-flight (nTOF) detectors are used to diagnose the conditions present in inertial confinement fusion (ICF) experiments and basic laboratory physics experiments performed on an ICF platform. The instrument response function (IRF) of these detectors is constructed by convolution of two components: an x-ray IRF and a neutron interaction response. The shape of the neutron interaction response varies with incident neutron energy, changing the shape of the total IRF. Analyses of nTOF data that span a broad range of energies must account for this energy-dependence in order to accurately infer plasma parameters and nuclear properties in ICF experiments. This work briefly reviews a matrix multiplication approach to convolution which allows for an energy-dependent change in the shape of the IRF. This method is applied to synthetic data resembling symmetric cryogenic DT implosions to examine the effect of the energy-dependent IRF on the inferred areal density. Here, results of forward fits that infer ion temperatures and areal densities from nTOF data collected during cryogenic DT experiments on OMEGA are also discussed.

47 OTHER INSTRUMENTATION↗

Investigation of low gain avalanche detectors exposed to proton fluences beyond 10 15 n eq cm -2

Abstract Low gain avalanche detectors (LGADs) deliver excellent timing resolution, which can mitigate mis-assignment of vertices associated with pileup at the High Luminosity LHC and other future hadron colliders. The most highly irradiated LGADs will be subject to 2.5 × 10 15 n eq cm -2 of hadronic fluence during HL-LHC operation; their performance must tolerate this. Hamamatsu Photonics K.K. and Fondazione Bruno Kessler LGADs have been irradiated with 400 and 500 MeV protons respectively in several steps up to 1.5 × 10 15 n eq cm -2 . Measurements of the acceptor removal constants of the gain layers, evolution of the timing resolution and charge collection with damage, and inter-channel isolation characteristics, for a variety of design options, are presented here.

Instruments & Instrumentation↗

A novel liquid argon purity monitor based on 207 Bi

A novel liquid argon purity monitor based on a 207 Bi radioactive source, emitting monochromatic internal-conversion electrons, is presented. This new monitor allows for a very precise and fast measurement of the electronegative impurities concentration in liquid argon. It can be operated continuously in liquid argon TPC experiments without interfering with the main detector operation. Different drift lengths can be assembled for the proposed device, to assess a large range of liquid argon purities while minimizing systematic uncertainties. Two prototypes have been built and successfully operated in dedicated test stands. The results and performance are reported.

double-phase↗

Optimal transport for 𝑒/𝜋 0 particle classification in LArTPC neutrino experiments

The efficient classification of electromagnetic activity from 𝜋 0 and electrons remains an open problem in the reconstruction of neutrino interactions in liquid argon time projection chamber (LArTPC) detectors. We address this problem using the mathematical framework of optimal transport (OT), which has been successfully employed for event classification in other high energy physics contexts and is ideally suited to the high-resolution calorimetry of LArTPCs. Using a publicly available simulated dataset from the MicroBooNE Collaboration, we show that OT methods achieve state-of-the-art reconstruction performance in 𝑒/𝜋 0 classification. The success of this first application indicates the broader promise of OT methods for LArTPC-based neutrino experiments.

Neutrino detection↗

Precision pulse shape simulation for proton detection at the Nab experiment

The Nab experiment at Oak Ridge National Laboratory, USA, aims to measure the beta-antineutrino angular correlation following neutron β decay to an anticipated precision of approximately 0.1%. The proton momentum is reconstructed through proton time-of-flight measurements, and potential systematic biases in the timing reconstruction due to detector effects must be controlled at the nanosecond level. In conclusion, we present a thorough and detailed semiconductor and quasiparticle transport simulation effort to provide precise pulse shapes, and report on relevant systematic effects and potential measurement schemes.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Graph neural network for neutrino physics event reconstruction

Liquid argon time projection chamber (LArTPC) detector technology offers a wealth of high-resolution information on particle interactions, and leveraging that information to its full potential requires sophisticated automated reconstruction techniques. Here, this article describes NUGRAPH 2, a graph neural network for low-level reconstruction of simulated neutrino interactions in a LArTPC detector. Simulated neutrino interactions in the MicroBooNE detector geometry are described as heterogeneous graphs, with energy depositions on each detector plane forming nodes on planar subgraphs. The network utilizes a multihead attention message-passing mechanism to perform background filtering and semantic labeling on these graph nodes, identifying those associated with the primary physics interaction with 98.0% efficiency and labeling them according to particle type with 94.9% efficiency. The network operates directly on detector observables across multiple two-dimensional representations but utilizes a three-dimensional-context-aware mechanism to encourage consistency between these representations. Model inference takes 0.12 s / event on a CPU and 0.005 s / event batched on a GPU. This architecture is designed to be a general-purpose solution for particle reconstruction in neutrino physics, with the potential for deployment across a broad range of detector technologies, and offers a core convolution engine that can be leveraged for a variety of tasks beyond the two described in this paper.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Improving neutrino energy estimation of charged-current interaction events with recurrent neural networks in MicroBooNE

We present a deep learning-based method for estimating the neutrino energy of charged-current neutrino-argon interactions. We employ a recurrent neural network (RNN) architecture for neutrino energy estimation in the MicroBooNE experiment, utilizing liquid argon time projection chamber (LArTPC) detector technology. Traditional energy estimation approaches in LArTPCs, which largely rely on reconstructing and summing visible energies, often experience sizable biases and resolution smearing because of the complex nature of neutrino interactions and the detector response. The estimation of neutrino energy can be improved after considering the kinematics information of reconstructed final-state particles. Utilizing kinematic information of reconstructed particles, the deep learning-based approach shows improved resolution and reduced bias for the muon neutrino Monte Carlo simulation sample compared to the traditional approach. In order to address the common concern about the effectiveness of this method on experimental data, the RNN-based energy estimator is further examined and validated with dedicated data-simulation consistency tests using MicroBooNE data. We also assess its potential impact on a neutrino oscillation study after accounting for all statistical and systematic uncertainties and show that it enhances physics sensitivity. This method has good potential to improve the performance of other physics analyses. Published by the American Physical Society 2024

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗