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At least 145 records · Page 8

Inter-Comparison of Lightning Trends from Ground-Based Networks During Severe Weather: Applications Toward GLM

The planned GOES-R Geostationary Lightning Mapper (GLM) will provide total lightning data on the location and intensity of thunderstorms over a hemispheric spatial domain. Ongoing GOES-R research activities are demonstrating the utility of total flash rate trends for enhancing forecasting skill of severe storms. To date, GLM total lightning proxy trends have been well served by ground-based VHF systems such as the Northern Alabama Lightning Mapping Array (NALMA). The NALMA (and other similar networks in Washington DC and Oklahoma) provide high detection efficiency (> 90%) and location accuracy (< 1 km) observations of total lightning within about 150 km from network center. To expand GLM proxy applications for high impact convective weather (e.g., severe, aviation hazards), it is desirable to investigate the utility of additional sources of continuous lightning that can serve as suitable GLM proxy over large spatial scales (order 100 s to 1000 km or more), including typically data denied regions such as the oceans. Potential sources of GLM proxy include ground-based long-range (regional or global) VLF/LF lightning networks such as the relatively new Vaisala Global Lightning Dataset (GLD360) and Weatherbug Total Lightning Network (WTLN). Before using these data in GLM research applications, it is necessary to compare them with LMAs and well-quantified cloud-to-ground (CG) lightning networks, such as Vaisala s National Lightning Detection Network (NLDN), for assessment of total and CG lightning location accuracy, detection efficiency and flash rate trends. Preliminary inter-comparisons from these lightning networks during selected severe weather events will be presented and their implications discussed.

Carey, Lawrence D.↗

Probing and controlling oxygen impurity diffusion in h -BN semi-bulk crystals

Combining its unique features of ultrawide bandgap (UWBG) and two-dimensional nature, h-BN has been explored for emerging applications such as deep ultraviolet optoelectronic devices and single photon emitters. One of the unusual applications of h-BN is for solid-state neutron detectors by utilizing the property of high thermal neutron capture cross section of B-10 as well as its UWBG properties. Although a record high detection efficiency of 59% has been attained by h-BN detectors, the understanding/minimization of defects and impurities is still needed to further advance the h-BN material and detector technologies. We report metal organic chemical vapor deposition growth and oxygen (O) impurity diffusion in thick h-BN. The diffusion coefficient (D) of O impurities has been measured via the evolution of an oxygen related emission with the etching depth, providing a value of D of ∼ 2 × 10−13 cm2/s at 1450 °C and supporting the interpretation that oxygen in h-BN is a substitutional donor. A multiple-buffer-layer approach was employed to mitigate to a certain degree the issue of oxygen diffusion from sapphire substrate during growth. It was demonstrated that the performance of h-BN neutron detectors fabricated from the wafer incorporating multiple buffer layers was significantly improved, as manifested by the enhanced thermal neutron detection efficiency. The advancement of the crystal growth technology of h-BN semi-bulk crystals creates applications in optoelectronic and power electronic devices utilizing the UWBG semiconductor properties of h-BN, while high efficiency h-BN neutron detectors have the potential to supplant the traditional He-3 gas detectors in various application areas by offering the obvious advantages of UWBG semiconductor technologies.

Physics↗

DeepMerge – II. Building robust deep learning algorithms for merging galaxy identification across domains

In astronomy, neural networks are often trained on simulation data with the prospect of being used on telescope observations. Unfortunately, training a model on simulation data and then applying it to instrument data leads to a substantial and potentially even detrimental decrease in model accuracy on the new target dataset. Simulated and instrument data represent different data domains, and for an algorithm to work in both, domain-invariant learning is necessary. Here we employ domain adaptation techniques— Maximum Mean Discrepancy (MMD) as an additional transfer loss and Domain Adversarial Neural Networks (DANNs)— and demonstrate their viability to extract domain-invariant features within the astronomical context of classifying merging and non-merging galaxies. Additionally, we explore the use of Fisher loss and entropy minimization to enforce better in-domain class discriminability. We show that the addition of each domain adaptation technique improves the performance of a classifier when compared to conventional deep learning algorithms. We demonstrate this on two examples: between two Illustris-1 simulated datasets of distant merging galaxies, and between Illustris-1 simulated data of nearby merging galaxies and observed data from the Sloan Digital Sky Survey. The use of domain adaptation techniques in our experiments leads to an increase of target domain classification accuracy of up to ~20%. With further development, these techniques will allow astronomers to successfully implement neural network models trained on simulation data to efficiently detect and study astrophysical objects in current and future large-scale astronomical surveys.

galaxies: interactions↗

Quantum sensing of paramagnetic analytes by nanodiamonds in levitated microdroplets and aqueous solutions

Nanodiamonds (ND) hosting negatively charged nitrogen-vacancy (NV-) color centers have received attention for applications in magnetic field, electric field, chemical, and bio-sensing. The versatility of these probes is their excellent room-temperature optical and spin properties, along with their small size, functionalized surfaces and resistance to bleaching, making them ideal as nanoscopic sensors in picoliter volumes (e.g. single cells, but also microcompartments and aerosols). For quantitative ND-NV- sensing of paramagnetic analytes in such contexts, however, there remains an incomplete understanding of how factors related to the aqueous phase environment control detection efficiency. To address this, optically detected magnetic resonance (ODMR) is measured in bulk macroscale solutions and single levitated microdroplets as a function of Gd+3 concentration (340 nM to 1.5 mM), nanodiamond size, pH, competitor ions, and ligands. The ODMR response to [Gd+3] is found to be nonlinear, and pH, ND and sample volume dependent; indicating the detection of Gd+3 requires efficient adsorption of the analyte to the diamond surface. Langmuir adsorption isotherms embedded in a quantitative photophysical model links the ODMR response to adsorption thermodynamics of Gd+3. The equilibrium constant for Gd+3 adsorption to a carboxylated ND surface is determined to be (1 ± 0.5) x 105 M-1 corresponding to a free energy of adsorption of (-28 ± 1) kJ mol-1. These results provide general insight into how complex aqueous and microscale environments impact nanodiamond based quantum sensing modalities, and portend their application as quantitative chemical sensors in microenvironments.

Brown, Emily K↗

Geant4 Simulation of Cherenkov Photons in Perovskite CsPbBr 3 Gamma-Ray Detectors

Perovskite materials have recently attracted significant attention for hard X-ray and gamma-ray detection. Cherenkov light generated by fast electrons due to gamma-ray interaction with the material can be used to provide fast timing information. Here, in this study, we report Geant4 simulation results of Cherenkov photon generation, transport, and detection within perovskite CsPbBr3. The Cherenkov photon yield, energy spectrum and temporal distribution are investigated under different gamma-ray energy deposition within CsPbBr3. CsPbBr 3 has a similar Cherenkov photon yield as of TlBr that has demonstrated fast-timing capability based on Cherenkov light. The effect of crystal volume, surface finish and SiPM photon detection efficiency on the Cherenkov detection is also discussed. This work provides insights into Cherenkov processes of CsPbBr3.

Cherenkov photon↗

BROOD: Bilevel and Robust Optimization and Outlier Detection for Efficient Tuning of High-Energy Physics Event Generators

The parameters in Monte Carlo (MC) event generators are tuned on experimental measurements by evaluating the goodness of fit between the data and the MC predictions. The relative importance of each measurement is adjusted manually in an often time-consuming, iterative process to meet different experimental needs. In this work, we introduce several optimization formulations and algorithms with new decision criteria for streamlining and automating this process. These algorithms are designed for two formulations: bilevel optimization and robust optimization. Both formulations are applied to the datasets used in the ATLAS A14 tune and to the dedicated hadronization datasets generated by the SHERPA generator, respectively. The corresponding tuned generator parameters are compared using three metrics. We compare the quality of our automatic tunes to the published ATLAS A14 tune. Moreover, we analyze the impact of a pre-processing step that excludes data that cannot be described by the physics models used in the MC event generators.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Calibrating LArPix for TinyTPC

LArTPCs provide sensitivity to GeV signals, such as accelerator neutrinos and part of the supernova neutrino spectrum. TinyTPC is a LArTPC test stand for R&D of LAr doping to expand the reach of LArTPCs down to the 1-10 MeV range, which would substantially enhance the flagship analyses of experiments like DUNE, while enabling low energy analyses. We aim to dope LAr with Xe and pho- tosensitive dopants to expand the LArTPC range by converting hard-to-detect scintillation light to efficiently detected ionization charge. A critical element of the data analysis in TinyTPC is calibrating the readout. This poster will cover the calibration of TinyTPC, a pixelated liquid argon detector, where we find the distance a muon travels through each pixel. We then calculate the energy loss of muons traveling through the detector from cosmic data. We can reconstruct the path of the particles through the TPC using a density-based clustering algorithm designed to sort straight cosmic muon tracks from low energy radioactive decay curled paths and electronic noise

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Reassessment of PHDS Fulcrum40h High Purity Germanium (HPGe) Detector System Performance

This report presents a comprehensive evaluation of the updated PHDS Fulcrum40h High Purity Germanium (HPGe) detector system, benchmarking its performance, usability, and software capabilities against the current National Nuclear Security Administration (NNSA) Nuclear Emergency Support Team (NEST) HPGe Detector System Requirements Document. Systematic measurements were conducted using a single Fulcrum40h detector to assess key parameters including gamma efficiency and resolution, neutron detection efficiency, gamma pulse-pileup response, and gamma-to-neutron crosstalk. The Fulcrum40h system, acquired in August 2022, has undergone recent updates by PHDS to address deficiencies identified following the initial NEST requirements release. The results provide critical insights into the detector’s operational capabilities and compliance with NNSA NEST standards.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

High-Collection-Efficiency Fluorescence Detection Cell

A new fluorescence cell has been developed for the laser induced fluorescence (LIF) detection of formaldehyde. The cell is used to sample a flow of air that contains trace concentrations of formaldehyde. The cell provides a hermetically sealed volume in which a flow of air containing formaldehyde can be illuminated by a laser. The cell includes the optics for transmitting the laser beam that is used to excite the formaldehyde and for collecting the resulting fluorescence. The novelty of the cell is its small size and simple design that provides a more robust and cheaper alternative to the state of the art. Despite its simplicity, the cell provides the same sensitivity to detection as larger, more complicated cells.

Hanisco, Thomas↗

Assessing the Impact of Lightning NOx Emissions in CMAQ Using Lightning Flash Data from WWLLN over the Contiguous United States

Comparison of lightning flash data from the National Lightning Detection Network (NLDN) and from the World Wide Lightning Location Network (WWLLN) over the contiguous United States (CONUS) for the 2016–2018 period reveals temporally and spatially varying flash rates that would influence lightning NO x (LNO x ) production due to known detection efficiency differences especially during summer months over land (versus over ocean). However, the lightning flash density differences between the two networks show persistent seasonal patterns over geographical regions (e.g., land versus ocean). Since the NLDN data are considered to have higher accuracy (lightning detection with >95% efficiency), we developed scaling factors for the WWLLN flash data based on the ratios of WWLLN to NLDN flash data over time (months of year) and space. In this study, sensitivity simulations using the Community Multiscale Air Quality (CMAQ) model are performed utilizing the original data sets (both NLDN and WWLLN) and the scaled WWLLN flash data for LNO x production over the CONUS. The model performance of using the different lightning flash datasets for ambient O 3 and NO x mixing ratios that are directly impacted by LNO x emissions and the wet and dry deposition of oxidized nitrogen species that are indirectly impacted by LNO x emissions is assessed based on comparisons with ground-based observations, vertical profile measurements, and satellite products. During summer months, the original WWLLN data produced less LNO x emissions (due to its lower lightning detection efficiency) compared to the NLDN data, which resulted in less improvement in model performance than the simulation using NLDN data as compared to the simulation without any LNO x emissions. However, the scaled WWLLN data produced LNO x estimates and model performance comparable with the NLDN data, suggesting that scaled WWLLN may be used as a substitute for the NLDN data to provide LNO x estimates in air quality models when the NLDN data are not available (e.g., due to prohibitive cost or lack of spatial coverage).

54 ENVIRONMENTAL SCIENCES↗

Enhanced Surface Passivation by Atomic Layer Deposited Al 2 O 3 for Ultraviolet Sensitive Silicon Photomultipliers

Here, we describe a superior passivation of p-type (p + ) Si surface by Al 2 O 3 thin film that is synthesized by plasma-assisted atomic layer deposition for ultraviolet sensitive silicon photomultipliers (SiPM), compared to conventional SiO 2 and SiN x passivation schemes. The superiority of Al 2 O 3 passivation is due to not only a sufficiently low interface defect density but also a high density of built-in negative charges. A 7 nm thin Al 2 O 3 film can yield an emitter saturation current density of ~8 fA/cm 2 on high sheet resistance p + layer, compared to ~60 and ~1480 fA/cm 2 for thermal SiO 2 and SiN x passivation. This superior surface passivation allows the photon-generated carriers to have higher probabilities to reach the high-field region to trigger an avalanche event. In addition, Al 2 O 3 thin film provides very low values of effective surface recombination velocity on low resistivity n-type and p-type Si surfaces, which can lead to well-passivated surface features on guard ring and trench isolation regions of SiPM. These demonstrate the potential of Al 2 O 3 thin film passivation to improve quantum efficiency and thus photo-detection efficiency of ultraviolet sensitive SiPM with p + /n - /n/n + structure.

36 MATERIALS SCIENCE↗

Systems and methods for detecting large network flows

In a system for efficiently detecting large/elephant flows in a network, the rate at which the received packets are sampled is adjusted according to the measured heavy tailedness of the arriving traffic, such that the measured heavy tailedness reaches a specified target level. The heavy tailedness is measured using the estimated sizes of different flows associated with the arriving packets. When the measured heavy tailedness reaches and remains at the specified target level, the flows having the largest estimated sizes are likely to be the largest/elephant flows in the network.

Ros-Giralt, Jordi↗

Single-Photon Counting Detector Scalability for High Photon Efficiency Optical Communications Links

For high photon-efficiency deep space or low power optical communications links, such as the Orion Artemis-2 Optical Communications System (O2O) project, the received optical signal is attenuated to the extent that single- photon detectors are required. For direct-detection receivers operating at 1.55 µm wavelength, single-photon detectors including Geiger-mode InGaAs avalanche photon diodes (APDs), and in particular superconducting nanowire single-photon detectors (SNSPDs) offer the highest sensitivity and fastest detection speeds. However, these photon detectors exhibit a recovery time between registered input pulses, effectively reducing the detection efficiency over the recovery interval, resulting in missed photon detections, reduced count rate, and ultimately limiting the achievable data rate. A method to overcome this limitation is to divide the received optical signal into multiple detectors in parallel. Here we analyze this approach for a receiver designed to receive a high photon efficiency serially concatenated pulse position modulation (SCPPM) input waveform. From measured count rate and efficiency data using commercial SNSPDs, we apply a model from which we determine the effective detection efficiency, or blocking loss, for different input signal rates. We analyze the scalability of adding detectors in parallel for different modulation orders and background levels to achieve desired data rates. Finally we show tradeoffs between the number of detectors and the required received optical power, useful for real link design considerations.

Vyhnalek, Brian E.↗

Radioxenon Detection for Monitoring Subsurface Nuclear Explosion

The Comprehensive Nuclear-Test-Ban Treaty (CTBT) bans the testing of nuclear weapons anywhere on the earth (atmospheric, surface, underwater and subsurface). Identification of nuclear explosions in the atmosphere, surface, and underwater is relatively straightforward considering a wide range of signatures resulting from such an event. However, for a subsurface explosion, most of the signatures traditionally associated with a nuclear explosion are not readily available. Therefore, the international community has increasingly relied on the atmospheric measurement of noble gases to identify subsurface nuclear weapon explosions. This chapter initially covers the basic principles of subsurface nuclear explosion identification and the importance of detecting radioxenon. This is followed by reviewing some of the early radioxenon detection systems that were developed by research groups around the world in the late 1990s and early 2000s. The detection media employed, results from laboratory and field testing, and some challenges/drawbacks for these systems are detailed. The next section of the chapter is dedicated to innovative detector concepts that have emerged in the past ten to fifteen years using novel detection material, algorithms, and signal readout techniques. The advances achieved in terms of energy resolution, coincidence detection efficiencies, system performance, and the minimum detectable concentration are covered. The final section goes over some of the potential improvements that can be incorporated in the design to enhance detector sensitivity and new detection material that can be explored in the field of radioxenon detection.

Gadey, Harish Reddy↗