The pursuit of knowledge in particle physics requires constant learning. As new tools become available, new theories are developed, and physicists search for new answers with ever-evolving methods. However, it is the case that formal educational systems serve as the primary training grounds for particle physicists. Graduate school (and undergraduate school to a lesser extent) is where researchers learn most of the technical skills required for research, develop scientific problem-solving abilities, learn how to establish themselves in their field, and begin developing their career. It is unfortunate, then, that the skills gained by physicists during their formal education are often mismatched with the skills actually required for a successful career in physics. We performed a survey of the U.S. particle physics community to determine the missing elements of graduate and undergraduate education and to gauge how to bridge these gaps. In this contributed paper, part of the 2021-22 Snowmass Community Planning Exercise, we report the results of this survey. We also recommend several specific community actions to improve the quality of particle physics education; the "community" here refers to physics departments, national labs, professional societies, funding agencies, and individual physicists.

We present measurements of the angular distribution of re-emitted light from tetraphenyl butadiene thin films when exposed to 128 nm light, which is the peak of the liquid Argon (LAr) scintillation spectrum, in vacuum. Films ranging from 250 nm to 5.5 μm in thickness are measured. All films were fabricated by evaporation deposition on ultraviolet transmitting (UVT) acrylic substrates. Preliminary comparisons of the angular distribution to that produced by a detailed Monte Carlo model are also presented. The current shortcomings of the model are discussed and future plans briefly outlined.

We have built and operated a crystalline/vapor xenon TPC, with the goal of improving searches for dark matter. The motivation for this instrument is the fact that beta decays from the radon decay chain to the ground state presently limit the state-of-the-art liquid/vapor xenon experiments. In contrast, a crystalline xenon target has the potential to exclude, or tag and reject radon-chain backgrounds. As a preamble to demonstrating such capabilities, the present article makes a first demonstration of the operation of a crystalline/vapor xenon TPC with electroluminescence (gas gain) for the electron signal readout. It also shows that the scintillation yield in crystalline xenon appears to be identical to that in liquid xenon, in contrast to previous results.

We report the first measurement of discrimination between low-energy helium recoils and electron recoils in liquid xenon. This result is relevant to proposed low-mass dark matter searches which seek to dissolve light target nuclei in the active volume of liquid-xenon time projection chambers. Low-energy helium recoils were produced by degrading α particles from ^{210}Po with a gold foil situated on the cathode of a liquid xenon time-projection chamber. The resulting population of helium recoil events is well separated from electron recoils and is also offset from the expected position of xenon nuclear recoil events.

As noble liquid time projection chambers grow in size their high voltage requirements increase, and detailed, reproducible studies of dielectric breakdown and the onset of electroluminescence are needed to inform their design. The Xenon Breakdown Apparatus (XeBrA) is a 5-liter cryogenic chamber built to characterize the DC high voltage breakdown behavior of liquid xenon and liquid argon. Electrodes with areas up to 33 cm2 were tested while varying the cathode-anode separation from 1 to 6 mm with a voltage difference up to 75 kV. A power-law relationship between breakdown field and electrode area was observed. The breakdown behavior of liquid argon and liquid xenon within the same experimental apparatus was comparable.

Liquid xenon particle detectors rely on excellent light collection efficiency for their performance. This depends on the high reflectivity of polytetrafluoroethylene (PTFE) at the xenon scintillation wavelength of 178 nm, but the angular dependence of this reflectivity is not well-understood. IBEX is designed to directly measure the angular distribution of xenon scintillation light reflected off PTFE in liquid xenon. These measurements are fully described by a microphysical reflectivity model with few free parameters. Dependence on PTFE type, surface finish, xenon pressure, and wavelength of incident light is explored. Total internal reflection is observed, which results in the dominance of specular over diffuse reflection and a reflectivity near 100% for high angles of incidence.

Maintaining the electric fields necessary for the current generation of noble liquid time projection chambers (TPCs), with drift lengths exceeding 1 m, requires a large negative voltage applied to their cathode. Delivering such high voltage is associated with an elevated risk of electrostatic discharge and electroluminescence, which would be detrimental to the performance of the experiment. The Xenon Breakdown Apparatus (XeBrA) is a 5-l, high voltage test chamber built to investigate the contributing factors to electrical breakdown in noble liquids. In this work, we present the main findings after conducting scans over stressed electrode areas, surface finish, pressure, and high voltage ramp speed in the medium of liquid xenon. Area scaling and surface finish were observed to be the dominant factors affecting breakdown, whereas no significant changes were observed with varying pressure or ramp speed. A general rise in both the anode current and photon rate was observed in the last 30 s, leading up to a breakdown, with a marked increase in the last couple of seconds. In addition, the position of breakdowns was reconstructed with a system of high-speed cameras and a moderate correlation with the Fowler-Nordheim field emission model was found. Tentative evidence for bubble nucleation being the originating mechanism of breakdown in the liquid was also observed. We deem the results presented in this work to be of particular interest for the design of future, large TPCs, and practical recommendations are provided.

Superfluid He4 is a promising target material for direct detection of light (<1 GeV) dark matter. Possible signal channels available for readout in this medium include prompt photons, triplet excimers, and roton and phonon quasiparticles. The relative yield of these signals has implications for the sensitivity and discrimination power of a superfluid He4 dark matter detector. Using a 16 cm3 volume of 1.75 K superfluid He4 read out by six immersed photomultiplier tubes, we measured the scintillation from electronic recoils ranging between 36.3 and 185 keVee, yielding a mean signal size of 1.25-0.03+0.03 phe/keVee, and nuclear recoils from 53.2 to 1090 keVnr. We compare the results of our relative scintillation yield measurements to an existing semiempirical model based on helium-helium and electron-helium interaction cross sections. We also study the behavior of delayed scintillation components as a function of recoil type and energy, a further avenue for signal discrimination in superfluid He4.

The dual-phase xenon time projection chamber (TPC) is a powerful tool for direct-detection experiments searching for WIMP dark matter, other dark matter models, and neutrinoless double-beta decay. Successful operation of such a TPC is critically dependent on the ability to hold high electric fields in the bulk liquid, across the liquid surface, and in the gas. Careful design and construction of the electrodes used to establish these fields is therefore required. We present the design and production of the LUX-ZEPLIN (LZ) experiment's high-voltage electrodes, a set of four woven mesh wire grids. Grid design drivers are discussed, with emphasis placed on design of the electron extraction region. We follow this with a description of the grid production process and a discussion of steps taken to validate the LZ grids prior to integration into the TPC.

Purpose

The ongoing lack of data standardization severely undermines the potential for automated learning from the vast amount of information routinely archived in electronic health records (EHRs), Radiation Oncology Information Systems (ROIS), treatment planning systems (TPSs), and other cancer care and outcomes databases. The effort sought to create a standardized ontology for clinical data, social determinants of health (SDOH), and other radiation oncology concepts and interrelationships.

Methods and materials

The American Association of Physicists in Medicine's (AAPM's) Big Data Science Committee (BDSC) was initiated July of 2019 to explore common ground from the stakeholders' collective experience of issues that typically compromise the formation of large inter- and intra- institutional databases from EHRs. The BDSC adopted an iterative, cyclical approach to engaging stakeholders beyond its membership to optimize the integration of diverse perspectives from the community.

Results

We developed the Operational Ontology for Oncology (O3) which identified 42 key elements, 359 attributes, 144 value sets, and 155 relationships ranked in relative importance of clinical significance, likelihood of availability in EHRs, or the ability to modify routine clinical processes to permit aggregation. Recommendations are provided for best use and development of the O3 to four constituencies: device manufacturers, centers of clinical care, researchers, and professional societies.

Conclusions

O3 is designed to extend and interoperate with existing global infrastructure and data science standards. The implementation of these recommendations will lower the barriers for aggregation of information that could be used creating large, representative, findable, accessible, interoperable and reusable (FAIR) datasets supporting the scientific objectives of grant programs. The construction of comprehensive "real world" datasets and application of advanced analytic techniques, including artificial intelligence (AI), holds the potential to revolutionize patient management and improve outcomes by leveraging increased access to information derived from larger, more representative datasets.