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At least 433 records · Page 24

Former Central Heat Plant SWMU 045 Year 2 Air Sparge System Performance Monitoring Report

This Air Sparge (AS) Performance Monitoring (PM) Report (PMR) presents Year 2 operation, maintenance, and monitoring (OM&M) activities, PM results, and monitoring well installations supporting the AS Interim Measure (IM) at the Former Central Heat Plant (CHP) at Kennedy Space Center (KSC), Florida. CHP has been designated Solid Waste Management Unit 045 under the KSC Resource Conservation and Recovery Act Corrective Action Program. An AS IM was installed at CHP between 2019 and 2021, which included the installation of an AS system to treat a chlorinated solvent groundwater plume. Contaminants of concern (COCs) identified at CHP for the AS IM include tetrachloroethene (PCE), trichloroethene (TCE), cis-1,2-dichloroethene (cDCE), and vinyl chloride (VC). The completed AS system includes a network of 267 AS wells, which treat approximately 1.3 acres of contaminated groundwater. “Hot” compressor technology is used to treat the source zone, while a “cold” compressor is used to treat two hot spot (HS) areas (HS1 and HS2) and the high concentration plume (HCP). The AS system began operation in June-July 2021 and this document includes Year 2 of operation. The overall runtimes for the AS system for the Year 2 reporting period (October 2022 to September 2023) were approximately 69 percent for the cold trailer and 71 percent for the hot trailer. Air samples and vapor screening results collected during the reporting period showed concentrations less than applicable human health and air emissions permit criteria. Groundwater performance monitoring results show that AS treatment continues to be effective in reducing COC concentrations at CHP. At the shallow interval, COC concentrations were all non-detect, less than, or met their respective State of Florida Groundwater Cleanup Target Levels (GCTLs) at the end of Year 2 in September 2023. In the deep interval, 10 of the 15 PM wells detected COCs greater than their respective GCTLs, with two of these wells also exceeding the Natural Attenuation Default Concentration for VC. Based on Year 2 OM&M and PM results, continued operation of the AS system is required to meet the IM objective. It is therefore recommended to continue with AS IM operations at CHP with the following plan for Year 3.

Kevin Alex Murphy↗

Cryogenic Behavior of the High Temperature Crystal Oscillator PX-570

Microprocessors, data-acquisition systems, and electronic controllers usually require timing signals for proper and accurate operation. These signals are, in most cases, provided by circuits that utilize crystal oscillators due to availability, cost, ease of operation, and accuracy. Stability of these oscillators, i.e. crystal characteristics, is usually governed, amongst other things, by the ambient temperature. Operation of these devices under extreme temperatures requires, therefore, the implementation of some temperature-compensation mechanism either through the manufacturing process of the oscillator part or in the design of the circuit to maintain stability as well as accuracy. NASA future missions into deep space and planetary exploration necessitate operation of electronic instruments and systems in environments where extreme temperatures along with wide-range thermal swings are countered. Most of the commercial devices are very limited in terms of their specified operational temperature while very few custom-made and military-grade parts have the ability to operate in a slightly wider range of temperature. Thus, it is becomes mandatory to design and develop circuits that are capable of operation efficiently and reliably under the space harsh conditions. This report presents the results obtained on the evaluation of a new (COTS) commercial-off-the-shelf crystal oscillator under extreme temperatures. The device selected for evaluation comprised of a 10 MHz, PX-570-series crystal oscillator. This type of device was recently introduced by Vectron International and is designed as high temperature oscillator [1]. These parts are fabricated using proprietary manufacturing processes designed specifically for high temperature and harsh environment applications [1]. The oscillators have a wide continuous operating temperature range; making them ideal for use in military and aerospace industry, industrial process control, geophysical fields, avionics, and engine control. They exhibit low jitter and phase noise, consume little power, and are suited for high shock and vibration applications. The unique package design of these crystal oscillators offers a small ceramic package footprint, as well as providing both through-hole mounting and surface mount options.

Patterson, Richard↗

Evaluation of Deep Learning Model Architectures for Point-of-Care Ultrasound Diagnostics

Point-of-care ultrasound imaging is a critical tool for patient triage during trauma for diagnosing injuries and prioritizing limited medical evacuation resources. Specifically, an eFAST exam evaluates if there are free fluids in the chest or abdomen but this is only possible if ultrasound scans can be accurately interpreted, a challenge in the pre-hospital setting. In this effort, we evaluated the use of artificial intelligent eFAST image interpretation models. Widely used deep learning model architectures were evaluated as well as Bayesian models optimized for six different diagnostic models: pneumothorax (i) B- or (ii) M-mode, hemothorax (iii) B- or (iv) M-mode, (v) pelvic or bladder abdominal hemorrhage and (vi) right upper quadrant abdominal hemorrhage. Models were trained using images captured in 27 swine. Using a leave-one-subject-out training approach, the MobileNetV2 and DarkNet53 models surpassed 85% accuracy for each M-mode scan site. The different B-mode models performed worse with accuracies between 68% and 74% except for the pelvic hemorrhage model, which only reached 62% accuracy for all model architectures. These results highlight which eFAST scan sites can be easily automated with image interpretation models, while other scan sites, such as the bladder hemorrhage model, will require more robust model development or data augmentation to improve performance. With these additional improvements, the skill threshold for ultrasound-based triage can be reduced, thus expanding its utility in the pre-hospital setting.

47 OTHER INSTRUMENTATION↗

Orion Abort Flight Test

The purpose of NASA's Constellation project is to create the new generation of spacecraft for human flight to the International Space Station in low-earth orbit, the lunar surface, as well as for use in future deep-space exploration. One portion of the Constellation program was the development of the Orion crew exploration vehicle (CEV) to be used in spaceflight. The Orion spacecraft consists of a crew module, service module, space adapter and launch abort system. The crew module was designed to hold as many as six crew members. The Orion crew exploration vehicle is similar in design to the Apollo space capsules, although larger and more massive. The Flight Test Office is the responsible flight test organization for the launch abort system on the Orion crew exploration vehicle. The Flight Test Office originally proposed six tests that would demonstrate the use of the launch abort system. These flight tests were to be performed at the White Sands Missile Range in New Mexico and were similar in nature to the Apollo Little Joe II tests performed in the 1960s. The first flight test of the launch abort system was a pad abort (PA-1), that took place on 6 May 2010 at the White Sands Missile Range in New Mexico. Primary flight test objectives were to demonstrate the capability of the launch abort system to propel the crew module a safe distance away from a launch vehicle during a pad abort, to demonstrate the stability and control characteristics of the vehicle, and to determine the performance of the motors contained within the launch abort system. The focus of the PA-1 flight test was engineering development and data acquisition, not certification. In this presentation, a high level overview of the PA-1 vehicle is given, along with an overview of the Mobile Operations Facility and information on the White Sands tracking sites for radar & optics. Several lessons learned are presented, including detailed information on the lessons learned in the development of wind placards for flight. PA-1 flight data is shown, as well as a comparison of PA-1 flight data to nonlinear simulation Monte Carlo data.

Hayes, Peggy Sue↗

Deep-learning-enhanced assessment of wellbore barrier effectiveness in geologic storage systems with intermediate aquifers

For geologic systems where carbon dioxide (CO 2 ) is injected underground, existing wells represent potential pathways for fluid migration. Here, this study introduces a novel deep learning model to quantify the likelihood and potential magnitude of fluid migration through wellbores at sites with intermediate aquifers or thief zones between the injection units and underground drinking water sources. Synthetic datasets, generated using reservoir simulations, captured a wide range of subsurface conditions, well attributes, operational parameters, and fluid migration scenarios. Among the regression models developed to predict brine and CO 2 leakage rates and CO 2 saturations along leaky wellbores, convolutional neural network (CNN) outperformed both Light Gradient Boosting Machine and deep neural network. Additionally, a CNN-based classification model was created to predict whether brine and CO 2 would leak along a wellbore, further improving performance over regression alone. The best models were integrated into the National Risk Assessment Partnership Open-source Integrated Assessment Model for rapid, stochastic assessment of storage system containment and leakage risks. A case study demonstrated the model’s ability to simulate fluid migration through existing wells with multiple intermediate aquifers. This computationally efficient wellbore model offers value in support of site performance evaluation and risk-informed decision making by stakeholders.

CO2 leakage↗

An adaptive and stability-promoting layerwise training approach for sparse deep neural network architecture

This work presents a two-stage adaptive framework for progressively developing deep neural network (DNN) architectures that generalize well for a given training data set. In the first stage, a layerwise training approach is adopted where a new layer is added each time and trained independently by freezing parameters in the previous layers. We impose desirable structures on the DNN by employing manifold regularization, sparsity regularization, and physics-informed terms. We introduce a ε – δ – stability-promoting concept as a desirable property for a learning algorithm and show that employing manifold regularization yields a ε – δ stability-promoting algorithm. Further, we also derive the necessary conditions for the trainability of a newly added layer and investigate the training saturation problem. In the second stage of the algorithm (post-processing), a sequence of shallow networks is employed to extract information from the residual produced in the first stage, thereby improving the prediction accuracy. Numerical investigations on prototype regression and classification problems demonstrate that the proposed approach can outperform fully connected DNNs of the same size. Moreover, by equipping the physics-informed neural network (PINN) with the proposed adaptive architecture strategy to solve partial differential equations, we numerically show that adaptive PINNs not only are superior to standard PINNs but also produce interpretable hidden layers with provable stability. As a result, we also apply our architecture design strategy to solve inverse problems governed by elliptic partial differential equations.

42 ENGINEERING↗

Space Launch System Spacecraft and Payload Elements: Making Progress Toward First Launch

Significant and substantial progress continues to be accomplished in the design, development, and testing of the Space Launch System (SLS), the most powerful human-rated launch vehicle the United States has ever undertaken. Designed to support human missions into deep space, SLS is one of three programs being managed by the National Aeronautics and Space Administration's (NASA's) Exploration Systems Development directorate. The Orion spacecraft program is developing a new crew vehicle that will support human missions beyond low Earth orbit, and the Ground Systems Development and Operations (GSDO) program is transforming Kennedy Space Center (KSC) into next-generation spaceport capable of supporting not only SLS but also multiple commercial users. Together, these systems will support human exploration missions into the proving ground of cislunar space and ultimately to Mars. SLS will deliver a near-term heavy-lift capability for the nation with its 70 metric ton Block 1 configuration, and will then evolve to an ultimate capability of 130 metric tons. The SLS program marked a major milestone with the successful completion of the Critical Design Review in which detailed designs were reviewed and subsequently approved for proceeding with full-scale production. This marks the first time an exploration class vehicle has passed that major milestone since the Saturn V vehicle launched astronauts in the 1960s during the Apollo program. Each element of the vehicle now has flight hardware in production in support of the initial flight of the SLS - Exploration Mission-1 (EM-1), an uncrewed mission to orbit the moon and return, and progress in on track to meet the initial targeted launch date in 2018. In Utah and Mississippi, booster and engine testing are verifying upgrades made to proven shuttle hardware. At Michoud Assembly Facility (MAF) in Louisiana, the world's largest spacecraft welding tool is producing tanks for the SLS core stage. This paper will particularly focus on work taking place at Marshall Space Flight Center (MSFC) and United Launch Alliance (ULA) in Alabama, where upper stage and adapter elements of the vehicle are being constructed and tested. Providing the Orion crew capsule/launch vehicle interface and in-space propulsion via a cryogenic upper stage, the Spacecraft/Payload Integration and Evolution (SPIE) Element serves a key role in achieving SLS goals and objectives. The SPIE element marked a major milestone in 2014 with the first flight of original SLS hardware, the Orion Stage Adapter (OSA) which was used on Exploration Flight Test-1 with a design that will be used again on EM-1. Construction is already underway on the EM-1 Interim Cryogenic Propulsion Stage (ICPS), an in-space stage derived from the Delta Cryogenic Second Stage. Manufacture of the Orion Stage Adapter and the Launch Vehicle Stage Adapter is set to begin at the Friction Stir Facility located at MSFC while structural test articles are either completed (OSA) or nearing completion (Launch Vehicle Stage Adapter). An overview is provided of the launch vehicle capabilities, with a specific focus on SPIE Element qualification/testing progress, as well as efforts to provide access to deep space regions currently not available to the science community through a secondary payload capability utilizing CubeSat-class satellites.

Schorr, Andrew A.↗

Space Launch System Spacecraft and Payload Elements: Making Progress Toward First Launch

Significant and substantial progress continues to be accomplished in the design, development, and testing of the Space Launch System (SLS), the most powerful human-rated launch vehicle the United States has ever undertaken. Designed to support human missions into deep space, SLS is one of three programs being managed by the National Aeronautics and Space Administration's (NASA's) Exploration Systems Development directorate. The Orion spacecraft program is developing a new crew vehicle that will support human missions beyond low Earth orbit, and the Ground Systems Development and Operations program is transforming Kennedy Space Center into next-generation spaceport capable of supporting not only SLS but also multiple commercial users. Together, these systems will support human exploration missions into the proving ground of cislunar space and ultimately to Mars. SLS will deliver a near-term heavy-lift capability for the nation with its 70 metric ton (t) Block 1 configuration, and will then evolve to an ultimate capability of 130 t. The SLS program marked a major milestone with the successful completion of the Critical Design Review in which detailed designs were reviewed and subsequently approved for proceeding with full-scale production. This marks the first time an exploration class vehicle has passed that major milestone since the Saturn V vehicle launched astronauts in the 1960s during the Apollo program. Each element of the vehicle now has flight hardware in production in support of the initial flight of the SLS -- Exploration Mission-1 (EM-1), an un-crewed mission to orbit the moon and return. Encompassing hardware qualification, structural testing to validate hardware compliance and analytical modeling, progress in on track to meet the initial targeted launch date in 2018. In Utah and Mississippi, booster and engine testing are verifying upgrades made to proven shuttle hardware. At Michoud Assembly Facility in Louisiana, the world's largest spacecraft welding tool is producing tanks for the SLS core stage. This paper will particularly focus on work taking place at Marshall Space Flight Center (MSFC) and United Launch Alliance in Alabama, where upper stage and adapter elements of the vehicle are being constructed and tested. Providing the Orion crew capsule/launch vehicle interface and in-space propulsion via a cryogenic upper stage, the Spacecraft/Payload Integration and Evolution (SPIE) Element serves a key role in achieving SLS goals and objectives. The SPIE element marked a major milestone in 2014 with the first flight of original SLS hardware, the Orion Stage Adapter (OSA) which was used on Exploration Flight Test-1 with a design that will be used again on EM-1. Construction is already underway on the EM-1 Interim Cryogenic Propulsion Stage (ICPS), an in-space stage derived from the Delta Cryogenic Second Stage. Manufacture of the Orion Stage Adapter and the Launch Vehicle Stage Adapter is set to begin at the Friction Stir Facility located at MSFC while structural test articles are either completed (OSA) or nearing completion (Launch Vehicle Stage Adapter). An overview is provided of the launch vehicle capabilities, with a specific focus on SPIE Element qualification/testing progress, as well as efforts to provide access to deep space regions currently not available to the science community through a secondary payload capability utilizing CubeSat-class satellites.

Schorr, Andrew A.↗

Exposing Process‐Level Biases in a Global Cloud Permitting Model With ARM Observations

The emergence of global convective‐permitting models (GCPMs) represents a significant advancement in climate modeling, offering improved representation of deep convection and complex precipitation patterns. In this study, we evaluate the performance of the Simple Cloud‐Resolving E3SM Atmosphere Model (SCREAM) using its doubly periodic configuration (DP‐SCREAM) against large eddy simulations and modern observational data sets from the Atmospheric Radiation Measurement program. We introduce several new transitional cloud regime cases, such as the transition from shallow to deep convection and from stratocumulus to cumulus, as well as cold‐air outbreak scenarios. The results reveal both strengths and limitations of SCREAM, particularly in the accurate simulation of cloud transitions and midlevel convection, with varying degrees of sensitivity to horizontal and vertical resolution. Despite improvements at higher resolutions, key biases remain, including the abrupt transition from shallow to deep convection and the lack of congestus clouds. These findings underscore the need for further refinement in turbulence parameterizations and vertical grid resolution in GCPMs.

Bogenschutz, Peter A. [Lawrence Livermore National↗

BioSentinel: An Adaptable Platform for Studying the Biological Effects of Deep Space Radiation

NASA's BioSentinel mission is a 6U nanosatellite with autonomous life support that will utilize the budding yeast Saccharomyces cerevisiae to study the DNA damage response to the deep space radiation environment. BioSentinel is planned to launch in 2019 as a secondary payload on the Space Launch System's first Exploration Mission (EM-1), and will undergo a lunar fly-by and enter heliocentric orbit after deployment. As the first biological mission beyond Low Earth Orbit (LEO) in nearly half a century, this mission will help fill critical gaps in knowledge about the effects of uniquely composed, chronic, low-flux deep space radiation on biological systems. Yeast is well-suited for this mission due to its desiccation tolerance and space-flight heritage. As a eukaryotic model organism, it also serves as a robust analog for human cells. Data gathered on this mission will thus inform us of the hazards involved in long-duration human exploration in deep space, and the protections necessary to mitigate them. Due to its low-cost, flexible and advanced technology, the 4U BioSensor payload contained within the nanosatellite is adaptable to other model microorganisms, exploration platforms and environments relevant to human exploration, such as the ISS, the Lunar Orbital Platform - Gateway and future lunar landers. In order to query the DNA damage response to deep space radiation, BioSentinel contains a wild type yeast strain as a positive control, and a radiation sensitive rad51 mutant strain that is defective for DNA repair. Yeast cells are desiccated in microfluidic cards, and rehydrated with growth medium and metabolic indicator dye at the desired time points during the mission. A thermal control system supports these stasis and growth states, and an optical system continuously measures cell growth and metabolism. An onboard radiation spectrometer and dosimeter allows us to correlate the dose, energy and particle-type of deep space radiation to the biological response. Data received from the deep space biosensor will be compared to control payloads on Earth and the ISS. Ongoing science testing for the BioSentinel project includes optimization for cell viability, desiccation tolerance, and long-term biocompatibility, as well as radiation experiments to understand the sensitivity and responsiveness of cells to varying radiation doses and particle types.

BioSentinel↗

Gluon double-spin asymmetry in the longitudinally polarized p + p collisions

We derive the first-ever small-x expression for the inclusive gluon production cross section in the central rapidity region of the longitudinally polarized proton-proton collisions. The cross section depends on the polarizations of both protons, therefore comprising the numerator of the longitudinal double-spin asymmetry ALL for the produced gluons. The cross section is calculated in the shock wave formalism and is expressed in terms of the polarized dipole scattering amplitudes on the projectile and target protons. We show that the small-x evolution corrections are included into our cross section expression if one evolves these polarized dipole amplitudes using the double-logarithmic helicity evolution derived in [1–4]. Our calculation is performed for the gluon sector only, with the quark contribution left for future work. When that work is complete, the resulting formula will be applicable to longitudinally polarized proton-proton and proton-nucleus collisions, as well as to polarized semi-inclusive deep inelastic scattering (SIDIS) on a proton or a nucleus. Our results should allow one to extend the small-x helicity phenomenology analysis of [5] to the jet/hadron production data reported for the longitudinally polarized proton-proton collisions at RHIC and to polarized SIDIS measurements at central rapidities to be performed at the EIC.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Search for vector-like leptons coupling to first- and second-generation Standard Model leptons in pp collisions at s = 13 TeV with the ATLAS detector

A search for pair production of vector-like leptons coupling to first- and second-generation Standard Model leptons is presented. The search is based on a dataset of proton-proton collisions at s$$ \sqrt{s} $$ = 13 TeV recorded with the ATLAS detector during Run 2 of the Large Hadron Collider, corresponding to an integrated luminosity of 140 fb−1. Events are categorised depending on the flavour and multiplicity of leptons (electrons or muons), as well as on the scores of a deep neural network targeting particular signal topologies according to the decay modes of the vector-like leptons. In each of the signal regions, the scalar sum of the transverse momentum of the leptons and the missing transverse momentum is analysed. The main background processes are estimated using dedicated control regions in a simultaneous fit with the signal regions to data. No significant excess above the Standard Model background expectation is observed and limits are set at 95% confidence level on the production cross-sections of vector-like electrons and muons as a function of the vector-like lepton mass, separately for SU(2) doublet and singlet scenarios. The resulting mass lower limits are 1220 GeV (1270 GeV) and 320 GeV (400 GeV) for vector-like electrons (muons) in the doublet and singlet scenarios, respectively.

Aad, G↗

Automated segmentation of porous thermal spray material CT scans with predictive uncertainty estimation

Abstract Thermal sprayed metal coatings are used in many industrial applications, and characterizing the structure and performance of these materials is vital to understanding their behavior in the field. X-ray computed tomography (CT) enables volumetric, nondestructive imaging of these materials, but precise segmentation of this grayscale image data into discrete material phases is necessary to calculate quantities of interest related to material structure. In this work, we present a methodology to automate the CT segmentation process as well as quantify uncertainty in segmentations via deep learning. Neural networks (NNs) have been shown to excel at segmentation tasks; however, memory constraints, class imbalance, and lack of sufficient training data often prohibit their deployment in high resolution volumetric domains. Our 3D convolutional NN implementation mitigates these challenges and accurately segments full resolution CT scans of thermal sprayed materials with maps of uncertainty that conservatively bound the predicted geometry. These bounds are propagated through calculations of material properties such as porosity that may provide an understanding of anticipated behavior in the field.

Martinez, Carianne↗

Quantum Simulation of Molecular Dynamics Processes─A Benchmark Study Using a Classical Simulator and Present-Day Quantum Hardware

Here, we explore how the fundamental problems in quantum molecular dynamics can be modeled using classical simulators (emulators) of quantum computers and the actual quantum hardware available to us today. The list of problems we tackle includes propagation of a free wave packet, vibration of a harmonic oscillator, and tunneling through a barrier. Each of these problems starts with the initial wave packet setup. Although Qiskit provides a general method for initializing wave functions, in most cases it generates deep quantum circuits. While these circuits perform well on noiseless simulators, they suffer from excessive noise on quantum hardware. To overcome this issue, we designed a shallower quantum circuit for preparing a Gaussian-like initial wave packet, which improves the performance of real hardware. Next, quantum circuits are implemented to apply the kinetic and potential energy operators for the evolution of a wave function over time. The results of our modeling on classical emulators of quantum hardware agree perfectly with the results obtained using the traditional (classical) methods. This serves as a benchmark and demonstrates that the quantum algorithms and Qiskit codes we developed are accurate. However, the results obtained on the actual quantum hardware available today, such as IBM’s superconducting qubits and IonQ’s trapped ions, indicate large discrepancies due to hardware limitations. This work highlights both the potential and challenges of using quantum computers to solve fundamental quantum molecular dynamics problems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Potential Link Between 2020 Mentone, West Texas M5 Earthquake and Nearby Wastewater Injection: Implications for Aquifer Mechanical Properties

Abstract The M5 Mentone earthquake that occurred on March 26, 2020, was the largest event recorded over the last 2 decades in West Texas within the Delaware Basin, a U.S. major petroleum‐producing area. Also, numerous hydrofracturing and wastewater disposal wells are spread across this region. Within a 30 km distance to mainshock, eight class‐II injection wells for industrial wastewater disposal target the deep porous Ellenburger aquifer at an average rate of 1.36 × 10 6 barrel (BBL) per month during 2012–2020. Poroelastic models of fluid diffusion show these nearby injectors collectively imparted up to 80.5 kPa of Coulomb stress at the mainshock location, capable of triggering this M5 event. Assuming the Mentone event occurs when pore‐pressure increase is maximum, the time delay between peak injection and the M5 occurrence corresponds with an optimal permeability of 6.76 × 10 ‐14 m 2 for the Ellenburger aquifer layer, in agreement with independent estimates.

15 GEOTHERMAL ENERGY↗

Kilopower Project: The KRUSTY Fission Power Experiment and Potential Missions

The Kilopower Project was initiated by NASA’s Space Technology Mission Directorate/Game Changing Development Program in fiscal year 2015 to demonstrate subsystem-level technology readiness of small space fission power in a relevant environment (Technology Readiness Level 5) for space science and human exploration power needs. The Kilopower Project centerpiece is the Kilowatt Reactor Using Stirling TechnologY (KRUSTY) test, which consists of the development and testing of a ground technology demonstrator of a 1-kW(electric)–class fission power system (FPS). The technologies to be developed and validated by KRUSTY are extensible to space FPSs from 1 to 10 kW(electric), which can enable modular surface FPSs for human exploration as well as higher-power future potential deep space science missions. The KRUSTY demonstration is cofunded by NASA and the U.S. Department of Energy National Nuclear Security Administration. The KRUSTY demonstration in the National Critical Experiment Research Center’s Device Assembly Facility was completed in the first quarter of 2018.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Tree-based algorithms for weakly supervised anomaly detection

Weakly supervised methods have emerged as a powerful tool for model-agnostic anomaly detection at the Large Hadron Collider (LHC). While these methods have shown remarkable performance on specific signatures such as dijet resonances, their application in a more model-agnostic manner requires dealing with a larger number of potentially noisy input features. In this paper, we show that using boosted decision trees as classifiers in weakly supervised anomaly detection gives superior performance compared to deep neural networks. Boosted decision trees are well known for their effectiveness in tabular data analysis. Our results show that they not only offer significantly faster training and evaluation times, but they are also robust to a large number of noisy input features. By using advanced gradient boosted decision trees in combination with ensembling techniques and an extended set of features, we significantly improve the performance of weakly supervised methods for anomaly detection at the LHC. This advance is a crucial step toward a more model-agnostic search for new physics. Published by the American Physical Society 2024

Astronomy & Astrophysics↗

Nuclear matter effects on jet production at electron-ion colliders

In these proceedings we report recent progress on understanding hadron and jet production in electron-nucleus collisions at the future Electron-Ion Collider [1,2]. These processes will play an essential role in the exploration of the partonic structure of nuclei and the study of parton shower evolution in strongly-interacting matter. We employ the framework of soft-collinear effective theory, generalized to include in-medium interactions, to present the first theoretical results for inclusive hadron and jet cross sections, as well as the jet charge modification in deep inelastic scattering on nuclei. We further demonstrate how to separate initial-state and final-state effects.

Li, Hai Tao↗