Radiation-Tolerant, High Thermal Conductivity Adhesives for High Energy Physics Detector Applications
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The LUX-ZEPLIN (LZ) detector is a dual-phase liquid xenon time projection chamber (TPC) installed at the Sanford Underground Research Facility (Lead, South Dakota) at a depth of 1478 meters. Although the main objective of LZ is the direct detection of dark matter, its low background environment allows for the search of other rare processes, such as the neutrinoless double beta decay of xenon isotopes 134 Xe and 136 Xe with the respective Q-values of 826 keV and 2458 keV. The sensitivity of the detector to these decays is directly determined by the energy resolution, which, in turn, is degraded by non-uniformities in detector response. In this work, we present a novel method to correct, in the data, the non-uniformity of the light collected by an array of photosensors in a scintillation detector. This method is based on the knowledge of the light response functions of individual photosensors. With these techniques, we report, at a very early phase of the detector operations, a state-of-the-art energy resolution (σ/μ) of (0.67 ± 0.01)% at 2614 keV for the fiducial volume of 5.6 tonnes of liquid xenon.
The software program, OnTheFly, was developed at Idaho National Laboratory (INL) to keep high-purity germanium (HPGe) detectors energy calibrated during very long experiments. Over time, spectra produced from a HPGe detector will slowly stretch or contract, causing the energy calibration to change. If the energy calibration changes too much, it will cause energy lines to be misidentified. The higher the energy line the more affected they are by this change. OnTheFly tracks and adjusts the slowly changing energy calibrations so the energy lines will not be misidentified. OnTheFly was used with the Fission Product Monitoring System (FPMS) during the AGR-5/6/7 irradiation experiment performed at INL’s Advanced Test Reactor (ATR). Five HPGe detectors were used to monitor the five capsules in AGR-5/6/7. There were also two extra HPGe detectors that were maintained as spares. Before each ATR cycle of the experiment, the HPGe detectors were energy calibrated with a thorium radioactive source. During each ATR cycle, each detector would acquire data for 8 hours and then reset and acquire data for another 8 hours. After each 8-hour run, the spectra would be saved and analyzed autonomously. The results were then read by OnTheFly and used to produce a new energy calibration for each detector. The new energy calibrations were compared to the current energy calibrations and, if certain criteria were met, the new energy calibration would replace the current energy calibration. The new energy calibration would be used for future spectra. OnTheFly was run at least every couple of days but could be run as much as after each 8-hour run. OnTheFly kept the spectra energy calibrated during the ATR cycles over the 2 years and 5 months that the AGR-5/6/7 experiment ran.
Silicon radiation detectors are an integral component of current and planned collider experiments in high energy physics. Simulations of these detectors are essential for deciding operational configurations, for performing precise data analysis, and for developing future detectors. In this white paper, we briefly review the existing tools and discuss challenges for the future that will require research and development to be able to cope with the foreseen extreme radiation environments of the High Luminosity runs of the Large Hadron Collider and future hadron colliders like FCC-hh and SPPC.
Noble liquid time projection chambers (TPCs) are some of the most sensitive particle detectors ever developed. They see use in searches for new physics with neutrinos, or for new particles like dark matter. They work by sensing light and charge signals left behind by particle interactions in a volume of liquified xenon or argon. TPCs are so sensitive that even a single electron liberated in an interaction can be readily detected. However this sensitivity to signals comes with a sensitivity to background noise, with one example being single electrons that arrive long after the signals from a true particle interaction. This type of noise has been the subject of multiple studies, which have concluded that single electron backgrounds are well correlated with prior events in the TPC, as well as impurities in the detection medium. At Lawrence Livermore National Laboratory (LLNL), the XeNu TPC is a testbed for a novel study of these backgrounds by generating data with new components made of aluminum and Shapal--the latter being an exotic ceramic which can be machined using standard tools. These materials were selected to replace plastic components which introduce impurities in the TPC during operation. Without plastic, the hope is that electron backgrounds will be reduced, leaving new opportunities for studying their origins and dependence on impurities. The SCGSR fellowship served as a springboard to help meet these objectives. Over the course of a year, the new components were designed, fabricated, and installed in XeNu. Following their installation, data was taken for use in a future study that will enable the electron background contributions from plastic components to be studied directly. In the interim, preliminary analysis results indicate that electron backgrounds with the new components are roughly 50% lower. This has established the efficacy of Shapal as a low-background replacement for plastic components where electrical and thermal stability are needed
We discuss fluxes of long-lived supersymmetric (SUSY) particles produced in the atmosphere from ultra-high energy cosmic-ray interactions with air nuclei. We consider long-lived particle production which proceeds first via the on-shell formation of heavier particles in the SUSY spectrum and then their decays. Specifically, we focus on the production of stau pairs from the decays of squarks produced in the initial cosmic ray-air collision under the purview of gauge-mediated symmetry breaking models that have the stau as the next-to-lightest SUSY particle. The calculation of the resulting stau flux schematically mirrors that of prompt atmospheric neutrino production, however, with the energy scale of initial hadronic collision set to EeV energy scales of the incident cosmic rays rather than the PeV energies where the prompt atmospheric neutrino fluxes dominate over neutrino fluxes from pions and kaons, and with the appropriate stau production cross section. We show the effect of accounting for the energy distribution of the staus relative to the squark energy distributions. We discuss the potential for future ultra-high energy detectors similar in scope to IceCube-Gen2 to detect atmospheric staus via tracks going through the detector volume. Current collider constraints on stau pair production within the SUSY framework considered here are more constraining than those from a detector like IceCube-Gen2 over ten years.
Autonomous algorithms use energy detectors to find template waveforms for repeating sources. These template waveforms parameterize pattern matching detectors. Template extracting is upstream of all template matching efforts. Operations must adaptively quantify performance of template methods
The mass calibration of fission product distributions measured with the energy–velocity (E-v) method constitutes a technical challenge. The energy loss of the fission fragments in the various dead layers of the spectrometer and other sources of pulse-height defects of the energy detectors are a significant source of systematic uncertainty in the mass calculations used to determine the measured fission product yields. Here, in this study, the absolute calibration of the fission mass distributions is accomplished by measuring prompt γ-rays in coincidence with the fission fragments. This allows for the direct calibration of the mass spectra and eliminates any dependence on potentially complicated energy corrections. The first test measurement was performed at the Los Alamos Neutron Science Center employing the SPectrometer for Ion DEtermination in fission Research (SPIDER). SPIDER is a 2E-2v spectrometer designed for measuring independent fission product yields from neutron-induced fission. In this test, the single-arm SPIDER (E-v) system and an array of 252 Cf sources were used. The single-arm system consisted of two time pick-off detectors for measuring the time-of-flight of the fission fragments and a double-sided silicon strip detector (DSSD) for measuring the kinetic energy. Characteristic γ-rays from fission fragments were detected using three high-purity germanium (HPGe) detectors. For the mass calibration, γ–mass coincidence events from twelve product isotopes were used. The measured FPYs from 252 Cf spontaneous fission were found to be in excellent agreement with the evaluated data after applying the absolute mass calibration. From the γ–mass coincidence events, the mass resolution of the system was also extracted. An average mass resolution of ~1.4 AMU (FWHM) for the light fragments and ~2.4 AMU (FWHM) for the heavy fragments were found. This was the first in-situ calibration and characterization of the SPIDER spectrometer, which paves the way for high-quality FPY measurements with this instrument.
To date, antineutrino experiments built for the purpose of demonstrating a nonproliferation capability have typically employed organic scintillators situated as close to the core as possible (typically at a distance of a few meters to tens of meters) and have not exceeded a few tons in size. One problem with this approach is that proximity to the reactor core requires accommodation by the host facility. Water Cherenkov detectors located offsite, at distances of a few kilometers or greater, may facilitate nonintrusive monitoring and verification of reactor activities over a large area. As the standoff distance increases, the detector target mass must scale accordingly. This paper quantifies the degree to which a kiloton-scale gadolinium-doped water Cherenkov detector can exclude the existence of undeclared reactors within a specified distance, and remotely detect the presence of a hidden reactor in the presence of declared reactors, by verifying the operational power and standoff distance using a Feldman-Cousins-based likelihood analysis. A 1-kton scale (fiducial) water Cherenkov detector can exclude gigawatt-scale nuclear reactors up to tens of kilometers within a year. In conclusion, when attempting to identify the specific range and power of a reactor, the detector energy resolution is not sufficient to delineate between the two.
We discuss here future neutrino detectors with physics goals ranging from the eV to the EeV scale. The focus is on future enabling technologies for such detectors, rather than existing detectors or those under construction. The report includes methodologies across the broad spectrum of neutrino physics: liquid noble and other cryogenic detectors, including LAr and LXe TPCs; photon-based detectors including technologies enabling hybrid Cherenkov/scintillation detectors; low-threshold detectors which use a wide variety of technologies to probe physics like coherent neutrino-nucleus scattering or detection of cosmic background neutrinos; and ultra-high energy detectors including optical and radio detectors, as well as tracking detectors for use at the forward physics facility of the LHC.
Despite advances in the programmable logic capabilities of modern trigger systems, a significant bottleneck remains in the amount of data to be transported from the detector to off-detector logic where trigger decisions are made. We demonstrate that a neural network (NN) autoencoder model can be implemented in a radiation-tolerant application-specific integrated circuit (ASIC) to perform lossy data compression alleviating the data transmission problem while preserving critical information of the detector energy profile. For our application, we consider the high-granularity calorimeter from the Compact Muon Solenoid (CMS) experiment at the CERN Large Hadron Collider. The advantage of the machine learning approach is in the flexibility and configurability of the algorithm. By changing the NN weights, a unique data compression algorithm can be deployed for each sensor in different detector regions and changing detector or collider conditions. To meet area, performance, and power constraints, we perform quantization-aware training to create an optimized NN hardware implementation. The design is achieved through the use of high-level synthesis tools and the hls4ml framework and was processed through synthesis and physical layout flows based on a low-power (LP)-CMOS 65-nm technology node. The flow anticipates 200 Mrad of ionizing radiation to select gates and reports a total area of 3.6 mm 2 and consumes 95 mW of power. The simulated energy consumption per inference is 2.4 nJ. Furthermore, this is the first radiation-tolerant on-detector ASIC implementation of an NN that has been designed for particle physics applications.
Here the performance characteristics of single-crystalline diamond detectors at varying rates of heavy-ions below 50 MeV/u have been investigated. When tested with a 228 Th source, the energy resolution of these detectors is better than 1.0% FWHM for 8.8 MeV α-particles. With a slight reduction in the energy resolution, simultaneous timing resolution of 314 ps has been achieved. Isotopic resolution has been achieved up to magnesium using a diamond telescope at low rates with a 20 MeV/u 20 Ne + 12 C reaction. At moderate rates of direct 7.5 MeV/u 78 Kr, polarization effects are observed, though this effect can be diminished by increasing the applied voltage on the detector up to a limit. After an accumulated dose of 6.9 × 10 8 direct 78 Kr particles transmitting through the detector, a degradation in the energy resolution of the 8.8 MeV peak from 1.6% to 5.3% is observed, indicating that permanent damage has been done to the detector.
A parametric study was simulated in MCNP to investigate the impact of spontaneous fission neutron energy on neutron detector response. A total of 880 configurations were simulated by varying 3 He pressure and polyethylene reflector thickness for 8 different isotopes. Results showed that deviations between the simulated isotopes become more prevalent at higher energies with 238 U showing the greatest deviation. It was also observed that configurations comparable to most detection setups, 10 atm and 6 - 8 cm polyethylene, were closer to the upper bound of deviations from a 252 Cf. 240 Pu, a common spontaneous fission source of interest, ranged from 2% - 3% within this space. This suggests that further investigation is required to determine exact correction factors when calibrating neutron detectors with a 252 Cf. Although demonstrated here for a 4π-detection system, future plans include simulating a more detailed model of the MC-15 detection setup to determine exact correction factors for future experiments.
Machine learning has been found to be ubiquitously useful across many industries, presenting an opportunity to improve radiation detection performance using data-driven algorithms. Improved detector resolution can aid in the detection, identification, and quantification of radionuclides. Here, in this work, a novel, data-driven, unsupervised learning approach is developed to improve detector spectral characteristics by learning, and subsequently rejecting, poorly performing regions of the pixelated detector. Feature engineering is used to fit individual characteristic photo peaks to a Doniach lineshape with a linear background model. Then, principal component analysis is used to learn a lower-dimension latent space representation of each photo peak where the pixels are clustered, and subsequently ranked, based on the cluster mean distance to an optimal point. Pixels within the worst cluster(s) are rejected to improve the full-width at half-maximum (FWHM) by 10% to 15% (relative to the bulk detector) at 50% net efficiency when applied to training data obtained from measurements of a 100 μCi 154 Eu source using a H3D M400i pixelated cadmium zinc telluride detector. These results compare well with, but do not outperform, a greedy algorithm that accumulates pixels in order of FWHM from lowest to highest used as a benchmark. In the future, this approach can be extended to include the detector energy and angular response. Finally, the model is applied to newly seen natural and enriched uranium spectra relevant for nuclear safeguards applications.
Conclusions: We present an updated neutrino oscillation analysis with: 50% more neutrino beam data, updated simulation and reconstruction, including a new GENIE 3 cross-section model, updated extrapolation which mitigates differing detector acceptances. New 3-Jlavor oscillation results: Δm²₃₂ = (2.41±0.07)×10⁻³ eV², sin²θ₂₃ = 0.57 +0.04 -0.03 , exclude IH, δ = π/2 at > 3σ, disfavor NH, δ = 3π/2 at ~2σ. Looking ahead: We can reach 3σ hierarchy sensitivity for 30-50% of δ values, with the full dataset and an upgraded beam. Plan to reduce our largest systematics, those related to detector energy scale, with the results of our test beam experiment.
Following the report from last quarter where we reported the experimental procedures, data acquisition and filtering process for the beta decay of 156 Eu, in the past quarter we have worked on establishing the efficiency for detecting the radiation emitted from this isotope with simulations of the HPGe detector and we have started investigating the beta detector energy deposition spectra.
For safe and reliable use of computer codes by the community, accuracy must be clearly evaluated. In particular, the nuclear reactor engineering and licensing field needs accurate tools for radiation shielding modeling. Monaco with Automated Variance Reduction using Importance Calculations (MAVRIC) is one such tool, with built-in variance reduction methods distributed within the SCALE code, and its validity is demonstrated in this report for the released version 6.2.4. Representative benchmarks corresponding to shielding analysis are selected for the validation study. Typical experimental results analyzed from those benchmarks include neutron fluxes, detector count rates, detector energy response functions, neutron and gamma doses, foil neutron activation rates and activities, neutron leakage fluxes, and skyshine dose rates. Thousands of points of comparison between experiment and calculation are presented in this work. Other than rare outliers typically explained by either a lack of information or large uncertainties in the experiment conditions, material, or dimensions, MAVRIC agrees well with the experiment results. MAVRIC is also compared to Monte Carlo N-Particle (MCNP) calculations when available, and both codes generally produce good agreements within estimated uncertainties. The selected benchmarks are obtained from reliable sources such as the International Criticality Safety Benchmark Evaluation Project Handbook (ICSBEP Handbook), the Shielding Integral Benchmark Archive & Database (SINBAD), and other shielding validation work found in the literature. Additional datapoints and benchmarks will be added to future versions of this report to incrementally expand the shielding validation suite incrementally.