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At least 1,207 records · Page 67

Quantitative time-resolved diagnostics of electric field dynamics during individual plasma breakdown events using burst laser pulse electric field induced second harmonic generation

In plasma discharges, the acceleration of electrons by a fast varying electric field and the subsequent collisional electron energy transfer determines the plasma dynamics, chemical reactivity, and breakdown. Current in situ electric field measurements require reconstruction of the temporal profile over many observations. However, such methods are unsuitable for non-repetitive and unstable plasmas. Here, in this paper, we present a method for creating “movies” of dynamic electric fields in a single acquisition at sample rates of 500 × 10 6 fps. This ultrafast diagnostic was demonstrated in radio frequency electric fields between two parallel plates in air, as well as in Ar nanosecond-pulsed single-sided dielectric barrier discharges.

42 ENGINEERING↗

Aluminum relaxation as the source of excess low energy events in low threshold calorimeters

A previously unexplained background called the Low Energy Excess has negatively impacted the reach of a variety of low threshold calorimeters including light dark matter direct detection and coherent elastic neutrino-nucleus scattering experiments. The relaxation of stressed aluminum films as mediated by the motion of dislocations may account for these observations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Transient plasma-detachment events induced by multiple gas puffs in ADITYA-U tokamak

Application of periodic short bursts of gas leads to periodic separation of the plasma column edge from the limiter in the Ohmically heated discharges of ADITYA-U tokamak. After every gas-puff, injecting around 10 17 –10 18 m −3 molecules of fuel gas in the edge of the plasma column, a significant reduction in plasma density, temperature, H α emission intensity and an increase in the H β /H α ratio is observed in the vicinity of the limiter radius for a certain time duration before these parameters regain their pre-gas puff values. A decline in the ion-flux to the limiter is also observed simultaneously. The global confinement of plasma also increases after each gas-puff. These observations, which repeat after each gas-injection, imply that the plasma–neutral interaction occurs further away from the limiters after the gas-injection and indicate a periodic plasma separation from the limiter surface. Further investigation revealed that the gas-injection modifies the radial and toroidal electric field, which may be playing a role in the separation of the plasma column from the limiter surface. It was further demonstrated by an electrode bias experiment in the absence of gas-injection that an application of an external radial electric field can result in obtaining a separated plasma state.

Physics - Plasma physics↗

Correlation of plastic events with local structure in jammed packings across spatial dimensions

Significance Mean-field theories, exact in the limit of infinite spatial dimensions, succeed in describing many features of glasses and amorphous solids in low dimensions, leading to considerable effort to understand how behavior evolves with dimension. Until now, all evidence has supported a picture in which “localized physics,” responsible for deviations from mean-field behavior in low dimensions, fades away with rising dimension. Our work shows that rearrangements, in which particles change relative positions leading to fluid-like response, reveal a different picture of dimensional cross-over. We find that rearrangements, which are localized in two- and three-dimensional systems and correlated with local structure, remain just as correlated with local structure up to five dimensions, suggesting that local structure is important even in high dimensions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A building performance-based approach to determining energy resilience for grocery stores in the event of a power outage

Evaluating progress toward a built environment that is best equipped to serve communities during a regional power outage will require metrics that capture the energy resilience of the unique buildings and businesses most crucial to the well-being of those nearby. We focused on grocery stores as key buildings for which access, and thus energy resilience, is critical during a disaster when power is unavailable. We evaluated the energy resilience of these buildings by offering and testing building-scale metrics that assess business continuity potential during a power outage. Metrics proposed in this study are calculated based on the unique power loads characteristic to grocery stores, primarily refrigeration and maintaining safe indoor environmental conditions. Building simulations based on varying levels of backup power were carried out against occupant safety and comfort parameters to apply these metrics, with additional criteria imposed on grocery stores to capture the inventory and sales loss from food spoilage resulting from a lack of refrigeration power. Findings from this study demonstrate the feasibility of our proposed metrics and methodology to serve as a low-data burden means for stakeholders to evaluate the energy resilience of grocery stores, with greater implications in helping to understand the impact on community-scale energy resilience.

Siegel, Lino Sanchez↗

Operational space and performance limiting events in the first physics campaign of MAST-U

Abstract The MAST-U fusion plasma research device, an upgrade to the Mega Amp Spherical Tokamak, has recently completed its first campaign of physics operation. MAST-U operated with Ohmic, or one or two neutral beams for heating, at 400–800 kA plasma current, in conventional or ‘SuperX’ divertor configurations. Equilibrium reconstructions provide key plasma physics parameters vs. time for each discharge, and diagrams are produced which show where the prevalence of operation occurs as well as the limits in various operational spaces. When compared to stability limits, the operation of MAST-U so far has generally stayed out of the low q , low density instability region, and below the high density Greenwald limit, high beta global stability limit, and high elongation vertical stability limit. MAST-U still has the potential to reach higher elongation, which could benefit the plasma performance. Despite the majority of operations happening below established stability limits, disruptions do occur in the flat-top phase of MAST-U plasmas. The reasons for these disruptions are highlighted, and possible strategies to avoid them and to extend the operational space of MAST-U in future campaigns are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Synergistic effects of W–Ta alloys exposed to various ELM-like fusion events

Abstract Recently tungsten alloys have shown capabilities in suppressing morphological changes when exposed to harsh fusion conditions. Morphological changes due to He + and D + ions at high temperatures (1000–2000 K) can lead to easier erosion and sputtering of tungten (W) particles towards quenching the fusion plasma. This study investigated W–3Ta alloy as potential plasma facing materials (PFMs) exposed to different edge-localized mode (ELM)-like energies and ion loadings. Performance of W–3Ta has been tested as a function of ELM-like energies (0.6–1.5 GW m −2 ) and varying He + and D + ion concentrations (100% He + , 50% He + :50% D + ,10% He + :90% D + (similar ELM-like reactor condition), and 100% D + ions). Early-stage fuzz formation and surface pores were observed during 100% He + ion irradiation and mixed ion loadings but not observed during 100% D + ion loadings. Pores decreased in quantity and increased in size with increasing transient heat loading. Grain boundaries acted as trapping sites of helium and deuterium atoms during dual beam ion irradiations, as observed through increased pore size along the grain boundary. Qualitative erosion estimates were measured using witness plates. Increased erosion was observed with increasing D + ion concentration, which is attributed to D supersaturation in the near surface region affecting thermal and mechanical properties. More erosion was observed for W–3Ta samples compared to pure W, evident through large (>10 µ m) cracks on the surface, and an increase in W metal x-ray photoelectron spectroscopy peaks under similar loading conditions. The slight enhancement in erosion is attributed to the slightly decreased thermal properties, ∼10% thermal diffusivity drop, of W–3Ta at high temperatures. The damage threshold was impacted by ion loading, where distinct cracking was observed for 100% He + at a lower heat loading. This matrix study using reactor-like loading supports the need for extensive studies on future W alloy PFMs before selecting one as an alternative.

Physics↗

A new calibration method for charm jet identification validated with proton-proton collision events at $\sqrt{s}$ =13 TeV

Many measurements at the LHC require efficient identification of heavy-flavour jets, i.e. jets originating from bottom (b) or charm (c) quarks. An overview of the algorithms used to identify c jets is described and a novel method to calibrate them is presented. This new method adjusts the entire distributions of the outputs obtained when the algorithms are applied to jets of different flavours. It is based on an iterative approach exploiting three distinct control regions that are enriched with either b jets, c jets, or light-flavour and gluon jets. Results are presented in the form of correction factors evaluated using proton-proton collision data with an integrated luminosity of 41.5 fb$^{-1}$ at √s = 13 TeV, collected by the CMS experiment in 2017. The closure of the method is tested by applying the measured correction factors on simulated data sets and checking the agreement between the adjusted simulation and collision data. Furthermore, a validation is performed by testing the method on pseudodata, which emulate various mismodelling conditions. The calibrated results enable the use of the full distributions of heavy-flavour identification algorithm outputs, e.g. as inputs to machine-learning models. Thus, they are expected to increase the sensitivity of future physics analyses.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Machine learning on FPGA for event selection

Real-time data processing is a frontier field in experimental particle physics. The application of FPGAs at the trigger level is used by many current and planned experiments (CMS, LHCb, Belle2, PANDA). Usually they use conventional processing algorithms. LHCb has implemented Machine Learning (ML) elements for real-time data processing with a triggered readout system that runs most of the ML algorithms on a computer farm. The work described in this article aims to test the ML-FPGA algorithms for streaming data acquisition. Herein, there are many experiments working in this area and they have a lot in common, but there are many specific solutions for detector and accelerator parameters that are worth exploring further. This report describes the purpose of the work and progress in evaluating the ML-FPGA application.

47 OTHER INSTRUMENTATION↗

Normalizing flows for domain adaptation when identifying Λ hyperon events

Here this study focuses on the application of a normalizing flow as a method of domain adaptation when classifying physics data. Normalizing flows offer a way to transform data points between two different distributions. The present study investigates a novel method of transforming latent representations of physics data to a normal distribution and then to a physics distribution again. The final distribution models a simulated distribution. After being transformed, the data can be classified by a neural network trained on labeled simulation data. The present study succeeds in training two normalizing flows that can transform between data (or simulation) and a Gaussian distribution.

47 OTHER INSTRUMENTATION↗

A new hybrid gadolinium nanoparticles-loaded polymeric material for neutron detection in rare event searches

Experiments aimed at direct searches for WIMP dark matter require highly effective reduction of backgrounds and control of any residual radioactive contamination. In particular, neutrons interacting with atomic nuclei represent an important class of backgrounds due to the expected similarity of a WIMP-nucleon interaction, so that such experiments often feature a dedicated neutron detector surrounding the active target volume. In the context of the development of DarkSide-20k detector at INFN Gran Sasso National Laboratory (LNGS), several R&D projects were conceived and developed for the creation of a new hybrid material rich in both hydrogen and gadolinium nuclei to be employed as an essential element of the neutron detector. Thanks to its very high cross-section for neutron capture, gadolinium is one of the most widely used elements in neutron detectors, while the hydrogen-rich material is instrumental in efficiently moderating the neutrons. In this paper results from one of the R&Ds are presented. In this effort the new hybrid material was obtained as a poly(methyl methacrylate) (PMMA) matrix, loaded with gadolinium oxide in the form of nanoparticles. We describe its realization, including all phases of design, purification, construction, characterization, and determination of mechanical properties of the new material.

Dark Matter detectors (WIMPs, axions, etc.)↗

Machine learning for single-ended event reconstruction in PROSPECT experiment

The Precision Reactor Oscillation and Spectrum Experiment, PROSPECT, was a segmented antineutrino detector that successfully operated at the High Flux Isotope Reactor in Oak Ridge, TN, during its 2018 run. Despite challenges with photomultiplier tube base failures affecting some segments, innovative machine learning approaches were employed to perform position and energy reconstruction, and particle classification. This work highlights the effectiveness of convolutional neural networks and graph convolutional networks in enhancing data analysis. By leveraging these techniques, a 3.3% increase in effective statistics was achieved compared to traditional methods, showcasing their potential to improve analysis performance. Furthermore, these machine learning methodologies offer promising applications for other segmented particle detectors, underscoring their versatility and impact.

47 OTHER INSTRUMENTATION↗