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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Dark Energy Studies with LSST using the Photon Simulator (Final Report)

This grant funded the development and dissemination of the Photon Simulator (PhoSim) for the purpose of studying dark energy at high precision with the upcoming Large Synoptic Survey Telescope (LSST) astronomical survey. The work was in collaboration with the Dark Energy Science Collaboration (DESC). Several detailed physics improvements were made in the optics, atmosphere and sensor, a number of validation studies were performed, and a significant number of usability features were implemented. Future work in DESC will use PhoSim as the image simulation tool for data challenges used by the analysis groups.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

A Machine Learning Approach to the Detection of Ghosting Artifacts in Dark Energy Survey Images

Unwanted artifacts that often plague astronomical images arise from a number of sources that include imperfect optics, faulty image sensors, cosmic ray hits, and even airplanes and satellites. One major source that is dicult to avoid is known as ghosting, and is caused by the scattering and internal reflections of light o of the telescope’s mechanical and optical components. Detecting ghosting artifacts eciently in the large cosmological surveys that will acquire petabytes of data can be a daunting task. In this paper, we use data from the Dark Energy Survey to develop, train, and validate a machine learning model to detect ghosts based on convolutional neural networks. The model architecture and training procedure is discussed in detail, and the performance on the training and validation set presented. Testing is performed on data and results are compared with those from a ray-tracing algorithm. A proof-of-principle is demonstrated that shows promise for Stage IV surveys and beyond.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Simulation of the Charge Measurements for the SuperCDMS Soudan Experiment

Astronomical observations lead us to believe that dark matter constitutes the majority of the mass of the Universe, yet it has never been directly observed experimentally. The Super Cryogenic Dark Matter Search Experiment (SuperCDMS) aims to discover the particle nature of dark matter, by developing and using some of the most sensitive detectors ever built. The SuperCDMS detectors are capable of rejecting known particles to search for dark matter interactions, but the discrimination is a complicated analysis task. Previous analyses with SuperCDMS set world leading sensitivity limits to dark matter interactions, but the analysis techniques have not been based on simulations. Now we have developed an efficient simulations infrastructure that will help better understand the detectors, develop a better background model, and optimize the next generation dark matter searches. In this thesis we present the fully-functional simulations infrastructure to produce high quality samples a s well as results for the charge system readout simulations, and comparisons to expectations from data. We show that our simulations well-reproduce dominant features of data, bringing SuperCDMS closer to a robust simulation-based analysis method, much needed for the upcoming SuperCDMS dark matter searches.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Uncertainty in Experimental Data Analysis [Slides]

The talk was presented virtually to the Institute of Fundamental Technological Research, Polish Academy of Sciences in Warsaw, Poland, December 21, 2020. Astronomical observations, unusual medical cases, physics experiments too costly to repeat, natural events like earthquakes, hurricanes – all of them are impossible to repeat yet produce important scientific information not achievable in other way. This data should not be treated as qualitative, anecdotal evidence only. It should be analyzed in a mathematically rigorous way to produce quantitative experimental data. Analysis method for one-of-a-kind event data differs from analysis of a repeated experiment data. For a repeated experiments the experimental error includes a range of true values generated by repetitions of the experiment, and measurement uncertainty caused by detectors. They are independent. Repetitions of any experiment, as similar as achievable, always have built-in differences resulting in a range of the true values rather than in a single true experimental value. Measurement uncertainty depends on the measurement system only. Modern digital measurements have very small uncertainty, frequently smaller than the range of true experimental values resulting from built-in differences in the experiment repetitions. When data from one-of-a-kind experiment are analyzed, only the measurement uncertainty can be reported.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Eject, crash, or survive: Using machine learning to predict orbital instability of exoplanetary systems

Astronomers throughout history, including titans like Kepler and Newton, have tackled planetary dynamics and orbital instability. Despite strides taken in research, understanding the evolution of planetary orbits remains an intricate, computationally expensive, and analytically unsolved problem. I apply machine learning classification methods to numerical simulations of planetary systems in order to predict the long-term fate of the planet - whether the planet remains in a stable orbit or not. My method uses the first 41.1 years (≤ 500 orbits) of data from a planet’s simulation to calculate 17 dynamically-motivated metrics; I trained my classifier on these features to predict a planet’s stability after 107 years. At 84.33%, my classifier was comparable in accuracy to pre-existing literature, despite using significantly less computational power than most other methods. In my research, I found that the standard deviation of eccentricity, mass ratios for neighboring planets, and semi-major axis ratio with the outer planet neighbor to be the most predictive features of instability. I propose reasons for the importance of these features, their role in planetary dynamics, as well as possible explanations for why some planets were misclassified. By understanding the important metrics of instability and reasons for misclassification, we can begin to understand more about system architectures, orbital motion and dynamics, and the formation and evolution of the exoplanetary systems. This is applicable in our own Solar System, and with exoplanet discovery missions such as TESS, this research becomes especially relevant in understanding the new exoplanetary systems we discover.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Eject, crash, or survive: Using machine learning to predict orbital instability of exoplanetary systems

Astronomers throughout history, including titans like Kepler and Newton, have tackled planetary dynamics and orbital instability. Despite strides taken in research, understanding the evolution of planetary orbits remains an intricate, computationally expensive, and analytically unsolved problem. I apply machine learning classification methods to numerical simulations of planetary systems in order to predict the long-term fate of the planet - whether the planet remains in a stable orbit or not. My method uses the first 41.1 years (≤ 500 orbits) of data from a planet’s simulation to calculate 17 dynamically-motivated metrics; I trained my classifier on these features to predict a planet’s stability after 107 years. At 84.33%, my classifier was comparable in accuracy to pre-existing literature, despite using significantly less computational power than most other methods. In my research, I found that the standard deviation of eccentricity, mass ratios for neighboring planets, and semi-major axis ratio with the outer planet neighbor to be the most predictive features of instability. I propose reasons for the importance of these features, their role in planetary dynamics, as well as possible explanations for why some planets were misclassified. By understanding the important metrics of instability and reasons for misclassification, we can begin to understand more about system architectures, orbital motion and dynamics, and the formation and evolution of the exoplanetary systems. This is applicable in our own Solar System, and with exoplanet discovery missions such as TESS, this research becomes especially relevant in understanding the new exoplanetary systems we discover.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Dependence of Dust Formation on the Supernova Explosion and nuDust

Dust is ubiquitous in the interstellar medium, serving as both a source of information and headaches to astronomers, depending on who you ask. The out-flows of core collapse supernovae (CCSNe) serve as a factory for dust nucleation and are one of a few known sources of dust in the universe. From observations of local CCSNe such as 1987A and Cassiopeia A, we know that dust is abundant in CCSN ejecta prior to interacting with the ISM. Furthermore, the explosion energy, explosive engine, metallicity, and progenitor mass of the CCSN will all impact the subsequent dust formation history and composition. Observations of the supernova ejecta probe the detailed composition of the ejecta which, in turn, can be used probe the properties of the progenitor star and the process of the explosion

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Weak Lensing And Cosmology In The Dark Energy Survey

In this PhD Thesis, we present studies which aim at understanding and testing the fundamental assumptions of the $\Lambda$CDM cosmological model. We initially show that weak gravitational lensing can be derived as a consequence of General Relativity, and that it can be applied to astronomical data from the Dark Energy Survey (DES) in order to constrain the amplitude of matter fluctuations in the universe. This constraint can be used as an end-to-end cosmological test when it is compared to inferences from the Cosmic Microwave Background. We further extend the cosmological model to account for non-standard parameters which can point to novel physics, and use DES data to assess their statistical significance. We finally show that the Cold Dark Matter (CDM) paradigm can also be fundamentally tested with observational data using morphological signatures of disk galaxies in cluster environments if CDM is self-interacting.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Understanding Transients: Needs from the Laboratory Astrophysics Community

A growing number of astrophysical transients are pushing astronomers to develop increasingly complex computational tools to model both radiation hydrodynamics and electron transport. Here we review the physics needs and simulation uncertainties associated with modeling these transients. Although this review will focus on theory and simulation aspects of this problem, we also review some experiments designed to study this physics.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Scalable and Energy-Efficient Methods for Interactive Exploration of Scientific Data

The main scientific contributions of this project are the following novel concepts for multidimensional arrays: shape-based similarity join (SIGMOD 2016), incremental view maintenance (SIGMOD 2017), user-defined stencil functions (HPDC 2017), and distributed caching for in-situ processing (SSDBM 2018). Building on our collaboration with the astrophysics group at LBNL, we applied these techniques to the data generated in the Palomar Transient Factory (PTF) astronomical survey. They played a pivotal role in the first-ever observation of a neutron star merger, which produces gravitational waves and turns out to be the origin of heavy elements, including gold. This has lead to a Science magazine article that has received extensive media coverage on ACM TechNews, Slashdot, FiveThirtyEight, and Quanta Magazine, among others. Additionally, two other articles detailing related aspects of the same discovery have been published in the Astrophysical Journal Letters journal. These publications have more than 3,000 citations according to Google Scholar (as of February 2022). This cross-disciplinary collaboration provided very good opportunities to apply database techniques to real-life scientific problems. The fact that they facilitated major discoveries in astrophysics proves the importance of our research. In addition to the work on multidimensional array databases, this project has also developed stochastic gradient descent (SGD) optimization algorithms for training large scale machine learning models, methods for querying in-situ data, and a database query optimizer based on sketch synopses.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Generating and Sustaining Microplasma with Microwaves (Final Report)

Plasma can be generated in spaces ranging in size from astronomical down to the microscopic. The physics that describes the gas breakdown is different at each size scale. The dominant physical phenomenon also depends on the type of electromagnetic field that drives the breakdown – static, AC, RF, microwave, visible. This project, staffed by undergraduate researchers and their mentor, focused on plasma generated in the size range of 10 to 500 micrometers using microwave energy. This project was motivated by the prior observation that plasma can only be generated in microgaps when the gas is above a certain gap-dependent pressure, here called the transition pressure. A microwave-driven microgap was designed and constructed in this project and then used to measure the electric field required to initiate plasma over a wide range of pressures from 0.1 Torr to 760 Torr (1 atmosphere).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Combined Heat Shield and Solar Thermal Propulsion System for an Oberth Maneuver

As humanity continues its exploration of space, many space missions are enabled by increases in speed. Examples include outer planet and dwarf planet exploration missions and missions that travel through our solar system into interstellar space. For many of these applications speeds of >10 astronomical units per year (AU/yr) are desired. A powered gravity assist around the Sun may offer the best option for reaching this goal; however, current heat shields and kick stages are too heavy or generate too little thrust. Solar thermal propulsion overcomes this tradeoff by converting the heat of the Sun into thrust. By tripling the specific impulse relative to chemical propulsion and by enabling a smaller perihelion through active cooling, this approach nearly doubles the escape velocity. Our team has designed and built working solar thermal propulsion prototypes out of materials that can survive 2700 K at a 30 x 30 cm scale. These benchtop-scale demonstrations have thus far validated the simplifying assumptions that underlie our thermal and propulsion models. Despite growing confidence that a full-scale heat shield/heat exchanger can survive an Oberth maneuver, many questions remain regarding the feasibility of long-term cryogenic storage of hydrogen propellant.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Unlocking Autonomous Telescopes through Reinforcement Learning: An Offline Framework and Insights from a Case Study

Optimizing observational astronomy campaigns is becoming a complex and expensive task for next-generation telescopes, where manual planning of observations may tend to reach suboptimal results in terms of optimization.Reinforcement Learning (RL) has been well-demonstrated as a valuable approach for training autonomous systems, and it may provide the basis for self-driving telescopes capable of scanning the sky and optimizing the scheduling for astronomy campaigns.We have developed a framework for the optimization of telescope scheduling using RL techniques, based on a dataset containing data on a discrete set of sky locations that the telescope should visit, and a reward metric. We compared several RL algorithms applied to an offline simulation dataset based at the Stone Edge Observatory, considering a discrete set of sky locations to visit and using “t-effective” as a reward metric, a measure of the quality of the data.Deep Q-Networks (DQNs), belonging to the class of value-based methods, have shown remarkable success in the optimization of astronomical observations in our dataset. In the full environment, the average reward value in each state was found to be 92%±5% of the maximum possible reward, while on the test set it resulted in 87%±9% of the maximum possible reward.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

DarkNESS: Characterization of Space Multi-Chip Module Skipper-CCDs

The DarkNESS mission is to send a 6U CubeSat fitted with an array of skipper-CCDs to see how well these sensors operate in Low Earth Orbit: take measurements of x-rays from the galactic center and strongly interacting sub-GeV dark matter from Cygnus X-1. Skipper-CCDs allow for low-noise astronomical observations which can extend the discovery reach for direct dark matter search experiments. This paper will discuss the characterization of the space Multi-Chip Module (sMCM) equipped with skipper-CCDs, and the challenges it faces during testing in the lab environment.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Dr. Sahar Said Allam (1964-2022): A Memoriam

In this short talk, we memorialize the scientific life of AAS member Dr. Sahar Said Allam (1964-2022), an alumna of Cairo University and the National Research Institute of Astronomy \& Geophysics (NRIAG). Her scientific career took her to the Universitaet Potsdam (Germany), New Mexico State University (USA), the Space Telescope Science Institute (USA), and the Fermi National Accelerator Laboratory (Fermilab; USA), as well as to astronomical observatories in New Mexico, Arizona, Hawaii, Chile, and Australia. Among other projects, she worked on the Sloan Digital Sky Survey (SDSS) and the Dark Energy Survey (DES), achieving the coveted “Builders” status on both these projects. She was the discoverer of the (at the time) brightest known Lyman Break Galaxy, the strongly lensed “8 O’Clock Arc”, and played an important role in the discovery of the optical counterpart to the gravitational wave event GW170817. During her final illness, she began work as a Data Preview 0 (“DP0”) De legate for the Vera C. Rubin Legacy Survey of Space & Time (LSST) and was even the Principal Investigator on a successful observing proposal submitted posthumously. The asteroid “135979 Allam” is named after her.

Tucker, Douglas L.↗
DOE OSTI2023

Pathways to Discovery in Astronomy and Astrophysics for the 2020s

We live in an extraordinary period of discovery in astronomy and astrophysics. Six Nobel Prizes have been awarded over the past decade alone for discoveries based on astronomical data (dark energy, gravitational waves, neutrino oscillations, the discovery of exoplanets, cosmology, and supermassive black holes). Many of the ambitious scientific visions of the 2010 New Worlds, New Horizons (Astro2010)1 decadal survey are being fulfilled, but momentum has only grown. We stand on the threshold of new endeavors that will transform not only our understanding of the universe and the processes and physical paradigms that govern it but also humanity’s place in it. This report of the Committee for a Decadal Survey on Astronomy and Astrophysics 2020 (Astro2020) proposes a broad, integrated plan for space- and ground-based astronomy and astrophysics for the decade 2023–2032.2 It also lays the foundations for further advances in the following decade. This is the seventh in a sequence of decadal survey studies in this field from the National Academies of Sciences, Engineering, and Medicine. This survey examines the program of record, providing advice on the major projects from prior surveys that are yet to be completed. It also lays out priorities for future investments driven by scientific opportunities. The recommendations in this report advance foundational activities that support the people who drive innovation and discovery, and that promote the technologies and tools needed to carry out the science. The report also recommends sustaining activities on a broad range of cost and time scales, as well as activities that enable future visionary projects by maturing them scientifically and technically. Last, the recommendations set in motion the construction of frontier facilities that will change the view and understanding of the cosmos. The survey is bounded by plausible budget scenarios based on briefings from the sponsoring agencies— the Department of Energy (DOE), the National Aeronautics and Space Administration (NASA), and the National Science Foundation (NSF). Within these bounds, the survey aims high, reflecting this time of great scientific promise and progress, with opportunities to pursue some of the most compelling scientific quests of our times.

79 ASTRONOMY AND ASTROPHYSICS↗