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Generative adversarial networks (GANs) are promising for a range of applications, including image translation and denoising, as well as synthetic data generation. These applications can be mapped to memristive crossbar arrays (MCAs) for ultra-high energy efficiency and portability. However, conductance variation within analog crossbars degrades the quality of the GAN outputs and necessitates robust post-manufacturing testing. We propose a two-stage adaptive test framework for compute-in-memory (CiM) based GANs, comprising an exhaustive test and a compact test. The exhaustive test measures the inception score of a device under test (DUT) by applying a large number of noise vectors, called the exhaustive noise set. To reduce test time, a compact test estimates the inception score of a DUT from a carefully chosen subset of these vectors, called the compact noise set. The compact noise set is determined by a binary mask optimized with a novel backpropagation-guided algorithm to minimize the difference between the estimated and true inception scores of the DUTs. Finally, to leverage both the accuracy of the exhaustive test and the speed of the compact test, the proposed adaptive test framework first applies the compact test to every DUT. Only the DUTs that yield low confidence in classifications are then subjected to the exhaustive test. Experiments show that this adaptive approach achieves less than 1% test escapes while offering up to 7.26× speedup compared to exhaustive test. 

This paper reports on research that is part of a broader National Science Foundation (NSF)-funded, Innovations in Graduate Education (IGE) project. The project aims to enhance the research culture and broaden the participation in research of underrepresented groups within graduate engineering programs at a mid-sized historically black college or university. The project includes three initiatives that seek to assist in the development of a “research engineer identity” among the graduate students pursuing research-based degrees in the college. One of the three initiatives of the project, and focus of this paper, involves the development of a survey-based Research Engineer Identity Scale (REIS). A two stage sequential mixed-method research design is being used to develop the scale. This paper focuses on the first stage in the design which involved conducting focus groups with research engineers to gain insight into the content, character, and complications associated with internalizing a Research Engineer Identity (REI) in general and among people from underrepresented groups in particular. We report on four semi-structured focus groups that each lasted approximately 90 minutes in Fall 2019. Each focus group included about 6 to 9 faculty members, industry professionals, or graduate students who actively engaged in engineering research in the Southeastern United States. Focus group participants represented various academic disciplines within engineering as well as a range of demographic characteristics such as sex, race, ethnicity, and citizenship status. The focus group conversations were transcribed and transcriptions were entered into NVivo for coding and analysis. Inter-rater reliability procedures were used to ensure consistency of coding. This paper reports on the themes that emerged within the focus group discussions regarding what it means to “be a research engineer.” The findings describe similarities and differences across demographic characteristics in regard to the content, character, and complications associated with efforts to develop a Research Engineer Identity. The paper concludes by briefly describing the process that will be used to transform the emergent themes into pool of items to be included in a web-based questionnaire designed to measure Research Engineer Identity. 

We present the measurement of ${\pi }^{+}$-argon inelastic cross sections using the ProtoDUNE single-phase liquid argon time projection chamber in the incident ${\pi }^{+}$kinetic energy range of 500–800 MeV in multiple exclusive channels (absorption, charge exchange, and the remaining inelastic interactions). The results of this analysis are important inputs to simulations of liquid argon neutrino experiments such as the Deep Underground Neutrino Experiment and the Short Baseline Neutrino program at Fermi National Accelerator Laboratory. They will be employed to improve the modeling of final state interactions within neutrino event generators used by these experiments, as well as the modeling of ${\pi }^{+}$-argon secondary interactions within the liquid argon. This is the first measurement of ${\pi }^{+}$-argon absorption at this kinetic energy range as well as the first ever measurement of ${\pi }^{+}$-argon charge exchange. 

Neutrinoless double beta decay is one of the most sensitive probes for new physics beyond the Standard Model of particle physics. One of the isotopes under investigation is ${}^{136}\mathrm{Xe}$, which would double beta decay into ${}^{136}\mathrm{Ba}$. Detecting the single ${}^{136}\mathrm{Ba}$daughter provides a sort of ultimate tool in the discrimination against backgrounds. Previous work demonstrated the ability to perform single atom imaging of Ba atoms in a single-vacancy site of a solid xenon matrix. In this paper, the effort to identify signal from individual barium atoms is extended to Ba atoms in a hexa-vacancy site in the matrix and is achieved despite increased photobleaching in this site. Abrupt fluorescence turn-off of a single Ba atom is also observed. Significant recovery of fluorescence signal lost through photobleaching is demonstrated upon annealing of Ba deposits in the Xe ice. Following annealing, it is observed that Ba atoms in the hexa-vacancy site exhibit antibleaching while Ba atoms in the tetra-vacancy site exhibit bleaching. This may be evidence for a matrix site transfer upon laser excitation. Our findings offer a path of continued research toward tagging of Ba daughters in all significant sites in solid xenon. Published by the American Physical Society2024 

The 2x2 Demonstrator, a prototype for the Deep Underground Neutrino Experiment (DUNE) liquid argon (LAr) Near Detector, was exposed to the Neutrinos from the Main Injector (NuMI) neutrino beam at Fermi National Accelerator Laboratory (Fermilab). This detector is a prototype of a new modular design for a liquid argon time-projection chamber (LArTPC), comprising a two-by-two array of four modules, each further segmented into two optically isolated LArTPCs. The 2x2 Demonstrator features a number of pioneering technologies, including a low-profile resistive field shell to establish drift fields, native 3D ionization pixelated imaging, and a high-coverage dielectric light readout system. The 2.4-tonne active mass detector is flanked upstream and downstream by supplemental solid-scintillator tracking planes, repurposed from the MINERvA experiment, which track ionizing particles exiting the argon volume. The antineutrino beam data collected by the detector over a 4.5 day period in 2024 include over 30,000 neutrino interactions in the LAr active volume—the first neutrino interactions reported by a DUNE detector prototype. During its physics-quality run, the 2x2 Demonstrator operated at a nominal drift field of 500 V/cm and maintained good LAr purity, with a stable electron lifetime of approximately 1.25 ms. This paper describes the detector and supporting systems, summarizes the installation and commissioning, and presents the initial validation of collected NuMI beam and off-beam self-triggers. In addition, it highlights observed interactions in the detector volume, including candidate muon antineutrino events. 

The Deep Underground Neutrino Experiment (DUNE) is a next-generation neutrino experiment with a rich physics program that includes searches for the hypothetical phenomenon of proton decay. Utilizing liquid-argon time-projection chamber technology, DUNE is expected to achieve world-leading sensitivity in the proton decay channels that involve charged kaons in their final states. The first DUNE demonstrator, ProtoDUNE Single-Phase, was a 0.77 kt detector that operated from 2018 to 2020 at the CERN Neutrino Platform, exposed to a mixed hadron and electron test-beam with momenta ranging from 0.3 to $7\mathrm{GeV}/\mathrm{c}$. We present a selection of low-energy kaons among the secondary particles produced in hadronic reactions, using data from the 6 and $7\mathrm{GeV}/\mathrm{c}$beam runs. The selection efficiency is 1% and the sample purity 92%. The initial energies of the selected kaon candidates encompass the expected energy range of kaons originating from proton decay events in DUNE (below $\sim 200\mathrm{MeV}$). In addition, we demonstrate the capability of this detector technology to discriminate between kaons and other particles such as protons and muons, and provide a comprehensive description of their energy loss in liquid argon, which shows good agreement with the simulation. These results pave the way for future proton decay searches at DUNE. 

We present details on a new measurement of the muon magnetic anomaly, $a_{\mu }=(g_{\mu }-2)/2$. The result is based on positive muon data taken at Fermilab’s Muon Campus during the 2019 and 2020 accelerator runs. The measurement uses $3.1\mathrm{GeV}/c$polarized muons stored in a 7.1-m-radius storage ring with a 1.45 T uniform magnetic field. The value of $a_{\mu }$is determined from the measured difference between the muon spin precession frequency and its cyclotron frequency. This difference is normalized to the strength of the magnetic field, measured using nuclear magnetic resonance. The ratio is then corrected for small contributions from beam motion, beam dispersion, and transient magnetic fields. We measure $a_{\mu }=116592057\left(25\right)\times {10}^{-11}$(0.21 ppm). This is the world’s most precise measurement of this quantity and represents a factor of 2.2 improvement over our previous result based on the 2018 dataset. In combination, the two datasets yield $a_{\mu }\left(\mathrm{FNAL}\right)=116592055\left(24\right)\times {10}^{-11}$(0.20 ppm). Combining this with the measurements from Brookhaven National Laboratory for both positive and negative muons, the new world average is $a_{\mu }\left(\exp \right)=116592059\left(22\right)\times {10}^{-11}$(0.19 ppm). Published by the American Physical Society2024 

Abstract Liquid argon time projection chambers (LArTPCs) rely on highly pure argon to ensure that ionization electrons produced by charged particles reach readout arrays. ProtoDUNE Single-Phase (ProtoDUNE-SP) was an approximately 700-ton liquid argon detector intended to prototype the Deep Underground Neutrino Experiment (DUNE) Far Detector Horizontal Drift module. It contains two drift volumes bisected by the cathode plane assembly, which is biased to create an almost uniform electric field in both volumes. The DUNE Far Detector modules must have robust cryogenic systems capable of filtering argon and supplying the TPC with clean liquid. This paper will explore comparisons of the argon purity measured by the purity monitors with those measured using muons in the TPC from October 2018 to November 2018. A new method is introduced to measure the liquid argon purity in the TPC using muons crossing both drift volumes of ProtoDUNE-SP. For extended periods on the timescale of weeks, the drift electron lifetime was measured to be above 30 ms using both systems. A particular focus will be placed on the measured purity of argon as a function of position in the detector. 

We present a new measurement of the positive muon magnetic anomaly, 𝑎𝜇≡(𝑔𝜇−2)/2, from the Fermilab Muon 𝑔−2 Experiment using data collected in 2019 and 2020. We have analyzed more than 4 times the number of positrons from muon decay than in our previous result from 2018 data. The systematic error is reduced by more than a factor of 2 due to better running conditions, a more stable beam, and improved knowledge of the magnetic field weighted by the muon distribution, 𝜔𝑝, and of the anomalous precession frequency corrected for beam dynamics effects, 𝜔𝑎. From the ratio 𝜔𝑎/𝜔𝑝, together with precisely determined external parameters, we determine 𝑎𝜇=116 592 057⁢(25)×10−11 (0.21 ppm). Combining this result with our previous result from the 2018 data, we obtain 𝑎𝜇⁡(FNAL)=116 592 055⁢(24)×10−11 (0.20 ppm). The new experimental world average is 𝑎𝜇⁡(exp)=116 592 059⁢(22)×10−11 (0.19 ppm), which represents a factor of 2 improvement in precision.