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A Detector Response Matrix (DRM) is a discrete representation of an instrument’s Detector Response Function (DRF), which quantifies how many discrete energy depositions occur in a detector volume for a given distribution of particles incident on the detector.
The BUTTON-30 detector is a 30-tonne technology demonstrator designed to evaluate the potential of hybrid event detection, simultaneously exploiting both Cherenkov and scintillation light to detect particles produced in neutrino interactions. The detector is installed at a depth of 1.1 km in the Boulby Underground Laboratory allowing to test the performance of this new technology underground in a low background environment. This paper describes the design and construction of the experiment.
In this article we examine recent developments in the research area concerning the creation of end-to-end models for the complete optimization of measuring instruments. The models we consider rely on differentiable programming methods and on the specification of a software pipeline including all factors impacting performance — from the data-generating processes to their reconstruction and the inference on the parameters of interest — along with the careful specification of a utility function well aligned with the end goals of the experiment. Building on previous studies originated within the MODE Collaboration, we focus specifically on applications involving instruments for particle physics experimentation, as well as industrial and medical applications that share the detection of radiation as their data-generating mechanism. This report illustrates the most recent advancements in the area, and outlines, for each of the discussed applications as well as for automatic differentiation itself, ongoing and future work.
Additive manufacturing offers efficient production of plastic scintillators with nontrivial geometries using vat polymerization, allowing fabrication of geometries which would be difficult or even impossible to produce using conventional subtractive manufacturing. This work presents a novel photocurable scintillator formula that includes coumarin 450 as a tertiary dye to enable high-resolution 3D printing via the manipulation of the 405 nm cure light. Bulk photocured and 3D printed (with and without tertiary dye) samples were compared through observational assessment and spectral response. All samples showed pulse shape discrimination between neutron and gamma events. Inclusion of the tertiary dye has minimal impact on emission spectrum and light output, but significant impact on print resolution as shown by comparison of printed high-complexity geometries and feature resolution test objects. With the use of a cure-limiting dye, unsupported features — such as freestanding pillars — were resolvable down to 0.7 mm. Even finer resolution at or below 0.1 mm was achieved in fully supported, integrated structures printed with off-the-shelf 405 nm desktop 3D printer. Scintillators demonstrated a light output up to 50% of EJ-200 with a PSD figure of merit up to 1.35 at 0.9–1.1 MeVee.
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This R&D project, initiated by the DOE Nuclear Physics AI-Machine Learning initiative in 2022, leverages AI to address data processing challenges in high-energy nuclear experiments (RHIC, LHC, and future EIC). Our focus is on developing a demonstrator for real-time processing of high-rate data streams from sPHENIX experiment tracking detectors. The limitations of a 15 kHz maximum trigger rate imposed by the calorimeters can be negated by intelligent use of streaming technology in the tracking system. The approach efficiently identifies low momentum rare heavy flavor events in high-rate p+p collisions (3MHz), using Graph Neural Network (GNN) and High Level Synthesis for Machine Learning (hls4ml). Success at sPHENIX promises immediate benefits, minimizing resources and accelerating the heavy-flavor measurements. The approach is transferable to other fields. For the EIC, we develop a DIS-electron tagger using Artificial Intelligence - Machine Learning (AI-ML) algorithms for real-time identification, showcasing the transformative potential of AI and FPGA technologies in high-energy nuclear and particle experiments real-time data processing pipelines.
Online reconstruction plays a crucial role in monitoring and in real-time analysis of high energy and nuclear physics experiments. A vital aspect of reconstruction algorithms is particle identification, which combines information from various detector components to determine the type of particle. Electron identification is particularly significant in electro-production nuclear physics experiments like the CLAS12 spectrometer at Jefferson Laboratory as it is essential in data recording. A machine learning approach has been developed for CLAS12 experiments to reconstruct and identify electrons by combining raw signals from multiple detector components at the data acquisition level. This method achieves high electron identification purity while maintaining nearly 100% efficiency. Furthermore, the machine learning tools operate at rates exceeding data acquisition speed, enabling the real-time electron reconstruction. This advancement significantly improves online analyses and monitoring capabilities for CLAS12 experiments.
A simulation-based method has been developed to prototype new detector designs for nuclear data measurements utilizing neutron scattering. This method uses representative physics inputs for signal and background generation, full detector resolution smearing benchmarked by experimental data, and a neutron beam timing simulation to produce analyzable output like a physical measurement. A test case has been studied using a hybrid time-of-flight calorimeter detector for scattering cross-section measurements on 239 Pu with 1-5 MeV incident monoenergetic neutrons. Data analysis methods have been developed to perform event-level particle reconstruction and reaction channel discrimination. This analysis has been used to estimate the capability of the test detector to perform simultaneous scattering and fission cross section measurements, as well as its ability to provide neutron spectra and particle angular information.
Online reconstruction is key for monitoring purposes and real time analysis in High Energy and Nuclear Physics experiments. A necessary component of reconstruction algorithms is particle identification that combines information left by a particle passing through several detector components to identify the particle’s type. Of particular interest to electro-production Nuclear Physics experiments such as CLAS12 is electron identification which is used to trigger data recording. A machine learning approach was developed for CLAS12 to reconstruct and identify electrons by combining raw signals at the data acquisition level from several detector components. Here, this approach achieves an electron identification purity above 75% whilst retaining an efficiency close to 100%. The machine learning tools are capable of running at high rates exceeding the data acquisition rates and will allow electron reconstruction in real-time. This work enhances online analyses and monitoring and can contribute to improved triggering at CLAS12. This machine learning driven approach will also be crucial for experiments aiming to transition to streaming readout operations where online reconstruction will be a key component of the data taking paradigm.
Ultra-Fast timing detectors, having a time resolution of 10pSec or less, are becoming increasingly important for many scientific disciplines, including High Energy Physics, Nuclear Physics, Medical Imaging and more. When developing ultra-fast detectors such as MCPs, LAPPDs, LGADs, SNSPDs, it is necessary to have access to a readout system that is low power, can support many channels and is cost effective. The PSEC5 chip was an application specific integrated circuit (ASIC) developed by the pioneering group of Prof. Henry Frisch at University of Chicago and micro electronic engineers at Fermi National Accelerator Laboratory. Three boards were designed, two to implement the readout system for an LAPPD and one to only characterize the PSEC1 chip. The main goal of the project shifted to setting up a testing environment to focus on the characterization of the chip. My student and I tested and characterized this ASIC using the third chip-on-board printed circuit board. Results show the successful fabrication and operation of some of the key building blocks and lead to the suggestions on modification for the second iteration of the chip.
Micro Pattern Gaseous Detectors (MPGDs) are used for tracking in High Energy Physics and Nuclear Physics because of their large area, excellent spatial resolution capabilities and low cost. However, for high energy charged particles impacting at a large angle with respect to the axis perpendicular to detector plane, the spatial resolution degrades significantly because of the long trail of ionization charges produced in clusters all along the track in the drift region of the detector. The long ionization charge trail results in registering hits from large number of strips in the readout plane which makes it challenging to precisely reconstruct the particle’s position using simple center of gravity algorithm. As a result, the larger the drift gap, the more severe the deterioration of spatial resolution for inclined tracks. For the same reason, the position resolution is also severely degraded in a large magnetic field, where the Lorentz E x B effect causes the ionization charges to follow a curved and longer path in the detector gas volume. In this paper, we report on the development of thin-gap MPGDs as a way to maintain excellent spatial resolution capabilities of MPGD detectors over a wide angular range of incoming particles. In a thin-gap MPGD, the thickness of the gas volume in the drift region is reduced from typically 3 mm to 1 mm or less. We present preliminary test beam results demonstrating the improvement in spatial resolution from 400 m with a standard 3 mm gap μ RWELL prototype to ~140 μ m with a double amplification GEM- μ RWELL thin-gap hybrid detector. Here, we also discuss the impact of a thin-gap drift volume on other aspects of the performance of MPGD technologies such as the efficiency and detector stability.
Low gain avalanche diodes with DC- and AC-coupled readout were exposed to ionizing and non-ionizing radiation at levels relevant to future experiments in particle, nuclear, and medical physics and to astrophysics. Damage-related change in their acceptor removal constants and in the resistivity of the region between the guard ring and the active area are reported, as is change in the leakage current and depletion voltages of the active volumes.
The LEGEND experiment is looking for the extremely rare neutrinoless double beta (0νββ) decay of 76 Ge using isotopically-enriched high-purity germanium (HPGe) detectors. The detection of this process would imply that the neutrino is a Majorana particle and the total lepton number would not be conserved, which could be related to the cosmological asymmetry between matter and antimatter through leptogenesis. The long-term goal of the collaboration is LEGEND-1000: a 1-ton detector array planned to run for 10 years, with a projected half-life sensitivity exceeding 10 28 years, fully covering the inverted neutrino mass hierarchy. A first search for the 0νββ decay has been carried out by LEGEND-200 building on the experience gained from GERDA and the MAJORANA DEMONSTRATOR. The experiment has been collecting physics data for a year at the Gran Sasso National Laboratory in Italy with 140 kg of HPGe detectors. With a total exposure of 61 kg yr, LEGEND-200 has achieved a background index of $5_{−2}^{+3}$ × 10 −4 counts/(keV kg yr) in the 0νββ decay signal region from the highest performing detectors. After combining the results from GERDA, the MAJORANA Demonstrator and LEGEND-200, an exclusion sensitivity > 2.8 × 10 26 yr has been obtained at 90% confidence level for the 0νββ decay half-life, with no evidence for a signal. A new observed lower limit of $T_{1/2}^{0v} >$ 1.9 × 10 26 yr at 90% confidence level has been established.
Here, this manuscript describes an innovative method to tag muons using the baseline information of the Flash ADC (FADC) waveform of PMTs in the JSNS 2 (J-PARC Sterile Neutrino Search at J-PARC Spallation Neutron Source) experiment. The experiment is designed to search for evidence of sterile neutrinos, and a reliable method for muon tagging is an essential component for background rejection because the detector is located above ground, on the 3rd floor of the J-PARC Material and Life Science Experimental Facility (MLF). Cosmogenic muons that stop within the detector volume and produce a Michel electron are a particularly important background that must be rejected for our sterile neutrino search. Utilizing this innovative method, more than 99.8 % of Michel electrons can be rejected even without using information from the detector’s veto region PMTs. This technique can be employed by any experiments which uses a similar detector configuration.
The Accelerator Neutrino Neutron Interaction Experiment (ANNIE) was designed to reconstruct neutrino events from the Fermilab Booster Neutrino Beam (BNB) with the parallel goals of measuring neutron production in interactions with oxygen and serving as a testbed for new technology. The ANNIE detector consists of a 26-ton water Cherenkov target tank instrumented with conventional photomultiplier tubes (PMTs), a downstream tracking muon spectrometer, and an upstream double wall of plastic scintillator to serve to veto charged particles incoming from neutrino events that occur upstream of the experimental setup. ANNIE has also deployed multiple Large-Area Picosecond PhotoDetectors (LAPPDs) and a test vessel of water-based liquid scintillator (WbLS). This paper describes the event reconstruction performance of the detector before implementation of these novel technologies, which will serve as a baseline against which their impact can be measured. That said, even the techniques used for event reconstruction using only the conventional PMT array and muon spectrometer are significantly different than those used in other water Cherenkov detectors due to the small size of ANNIE (which makes nanosecond-scale timing not as useful as in a large detector) and the availability of reconstruction information from the tracking muon spectrometer. We demonstrate that combining the information from these two elements into a single fit using only pattern recognition yields a muon vertex uncertainty of 60 cm, a directional uncertainty of 13.2 degrees, and energy reconstruction uncertainty of about 10% for BNB muon neutrino Charged Current Zero Pion (CC0π) events.
The design, fabrication, and demonstration of a novel Silicon Carbide Low Gain Avalanche Detector (4HSiC LGAD), exhibiting an ultra-fast time response and excellent time resolution, are reported. Here, the use of field plates is proposed to suppress the high electric field caused by the negative bevel-etched angle in 4H-SiC LGADs based on TCAD simulations. Experimental measurements confirm that the field plate significantly increases the breakdown voltage of the 4H-SiC LGADs. Gain and time resolution are measured by using the ultraviolet transient current technique (UV-TCT) showing that 4H-SiC LGADs possess excellent timing performance, with a time resolution better than 35 ps for the injected laser signal with single minimum ionizing particle (MIP) charges generation at room temperature. Additionally, the gain suppression effect in a 4H-SiC LGAD is observed for the first time.
The Electron-Ion Collider (EIC) is an upcoming accelerator facility aimed at exploring the properties of quarks and gluons in nucleons and nuclei, shedding light on their structure and dynamics. The inaugural experimental apparatus, ePIC (electron-Proton and Ion Collider), is designed as a general-purpose detector to address the National Academy of Sciences and the Nuclear Science Advisory Committee physics program at the EIC. The wider EIC community is strongly supporting a second interaction region and an associated second detector to enhance the full science program. In this study, we evaluate how this second interaction region and detector can be complementary to ePIC. The layout of an interaction region for the second detector offers a secondary focus that provides better forward detector acceptance at scattering angles near θ ~ 0 mrad, which can specifically enhance the exclusive, tagging, and diffractive physics program. Here, this article presents an analysis of a tagging program using the second interaction region layout with incoherent diffractive vector meson production. The current design of the second EIC interaction region is evaluated for its vetoing capabilities of incoherent events required for the study of coherent diffractive measurements. We find an increased vetoing performance compared to the ePIC interaction region, thus improving measurements which are important for the spatial imaging of nucleons and nuclei.
A neutrino detector is proposed to be developed for use on a space probe in close orbit of the Sun. The detector will also be protected from radiation by a tungsten shield Sun shade, active veto array and passive cosmic shielding. With the intensity of solar neutrinos substantially greater in a close solar orbit than on the Earth only a small 250 kg detector is needed. It is expected that this detector and space probe studying the core of the Sun, its nuclear furnace and particle physics basic properties will bring new knowledge beyond what is currently possible for Earth bound solar neutrino detectors.