Manned space flight network performance analysis for the sa-8 mission
Orbital mission of Pegasus B payload with Apollo boilerplate spacecraft, launched by Saturn SA-8 - summary
PEGASUS SATELLITE↗
SEARCH · Engineering Papers
Results for “Pegasus”
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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Large Magnetic Environments
Large magnetic field coils to cancel earth magnetic field - magnetic properties of Pegasus satellite
PEGASUS SATELLITE↗
Preparation of S-13 experimental coatings Final report, Oct. 29, 1963 - Aug. 31, 1965
Elastomeric methyl silicone polymer thermal control coating evaluation with Pegasus spacecraft
SILICONE↗
Power Systems Research at MSFC
Power system developments for rockets and space flights - fuel cells, improved zinc-silver oxide battery, brushless dc motors, switching transformer regulator, and Pegasus electricity
ELECTRIC MOTOR↗
Structural Design and Data Systems of Spacecraft
Structural design and data acquisition systems of Pegasus satellite
STRUCTURAL DESIGN↗
Thermal design considerations
Thermal environment factors affecting electronic canister design for Pegasus satellite
THERMAL ENVIRONMENT↗
Research Achievements Review, volume II
Thermophysics, emissivity physics, thermal similitude, ultraviolet interactions with control surface materials, Pegasus satellite measurements, and infrared instrumentation
INFRARED INSTRUMENT↗
Thermally isolated temperature sensor for space application
Thermally isolated temperature sensor for space application Pegasus satellite
PEGASUS SATELLITE↗
Recent NASA meteoroid penetration results from satellites
Meteoroid penetration measurements by Explorer XVI and XXIII satellites and Pegasus satellites for application to spacecraft design
EXPLORER XXIII SATELLITE↗
Microspacecraft Secondary Payload Mission Opportunities
Worldwide secondary payload launch capabilities and future opportunities have been studied at the Jet Propulsion Laboratory (JPL). Launch vehicles have been identified as having near-term secondary payload opportunities for launching microspacecraft include: Pegasus, Taurus, LMLV-1, Delta II, Atlas II, Space Shuttle, Ariane 5, HIA, Molniya, Cosmos, and Proton.
Pegasus Taurus Delta II Atlas II Space Shuttle Ari↗
SHarD: A beam dynamics simulation code for dielectric laser accelerators based on spatial harmonic field expansion
In order to demonstrate acceleration of electrons to relativistic scales by an on chip dielectric laser accelerator (DLA), a ponderomotive focusing scheme capable of capturing and transporting electrons through nanometer-scale apertures over extended interaction lengths has been proposed. Here we present a Matlab-based numerical code (SHarD) utilizing a spatial harmonic expansion of the fields within the dielectric structure to simulate the evolution of the beam phase space distribution in this scheme. The code can be used to optimize key-parameters for the accelerator performance such as the final energy, transverse spot size evolution and total number of electrons accelerated through currently fabricated structures. Eventually, the simulation model will be applied to inform the phase mask profile to be added to a pulse front tilt drive laser pulse using a liquid crystal mask in the experimental setup being assembled at UCLA Pegasus Laboratory.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Experimental study of energy-dependent angular broadening of MeV electron beams for high-resolution imaging in thick samples
In scanning transmission electron microscopy (STEM), spatial resolution is primarily influenced by the projected size of the electron probe within the specimen. In thin samples, a large semi-convergence angle enables a tightly focused beam and sub-nanometer resolution. However, in thick specimens, resolution is fundamentally limited by transverse beam broadening from multiple large-angle scattering events—for example, a probe with 10 mrad angular divergence can broaden by ∼100 nm over a 10 μm path. Since this broadening scales inversely with beam energy, MeV-STEM offers a promising route for high-resolution imaging in thick materials. To quantitatively assess this effect, we performed high-precision measurements at UCLA’s PEGASUS beamline, characterizing beam divergence and intensity profiles for 3–8 MeV electrons transmitted through a wedged-silicon sample of varying thickness. Our results reconcile discrepancies among analytical models and validate Monte Carlo simulations. Here, we find that increasing beam energy from 3.0 to 5.8 MeV reduces angular broadening by a factor of 2.6, with diminishing returns observed at 7.6 MeV. These findings provide a quantitative framework for optimizing MeV-STEM parameters in high-resolution imaging of thick biological and microelectronic specimens, and for guiding beam energy selection in other advanced imaging modes beyond STEM.
36 MATERIALS SCIENCE↗
Conditioned quantum-assisted deep generative surrogate for particle-calorimeter interactions
Particle collisions at accelerators like the Large Hadron Collider (LHC), recorded by experiments such as ATLAS and CMS, enable precise standard model measurements and searches for new phenomena. Simulating these collisions significantly influences experiment design and analysis but incurs immense computational costs, projected at millions of CPU-years annually during the high luminosity LHC (HL-LHC) phase. Currently, simulating a single event with Geant4 consumes around 1000 CPU seconds, with calorimeter simulations especially demanding. To address this, we propose a conditioned quantum-assisted generative model, integrating a conditioned variational autoencoder (VAE) and a conditioned restricted Boltzmann machine (RBM). Our RBM architecture is tailored for D-Wave’s Pegasus-structured advantage quantum annealer for sampling, leveraging the flux bias for conditioning. This approach combines classical RBMs as universal approximators for discrete distributions with quantum annealing’s speed and scalability. We also introduce an adaptive method for efficiently estimating effective inverse temperature, and validate our framework on Dataset 2 of CaloChallenge.
97 MATHEMATICS AND COMPUTING↗
Comparing quantum annealing and spiking neuromorphic computing for sampling binary sparse coding QUBO problems
We consider the problem of computing a sparse binary representation of an image. Given an image and an overcomplete, non-orthonormal basis, we aim to find a sparse binary vector indicating the minimal set of basis vectors that when added together best reconstruct the given input. We formulate this problem with an L 2 loss on the reconstruction error, and an L 0 loss on the binary vector enforcing sparsity. First, we solve the sparse representation QUBOs by solving them both on a D-Wave quantum annealer with Pegasus chip connectivity, as well as on the Intel Loihi 2 spiking neuromorphic processor using a stochastic Non-equilibrium Boltzmann Machine (NEBM). Second, using Quantum Evolution Monte Carlo with Reverse Annealing and iterated warm starting on Loihi 2 to evolve the solution quality from the respective machines. We demonstrate that both quantum annealing and neuromorphic computing are suitable for solving binary sparse coding QUBOs.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Identification of blood protein biomarkers associated with prostate cancer risk using genetic prediction models: analysis of over 140,000 subjects
Prostate cancer (PCa) brings huge public health burden in men. A growing number of conventional observational studies report associations of multiple circulating proteins with PCa risk. However, the existing findings may be subject to incoherent biases of conventional epidemiologic studies. To better characterize their associations, herein, we evaluated associations of genetically predicted concentrations of plasma proteins with PCa risk. In this study, we developed comprehensive genetic prediction models for protein levels in plasma. After testing 1308 proteins in 79 194 cases and 61 112 controls of European ancestry included in the consortia of BPC3, CAPS, CRUK, PEGASUS, and PRACTICAL, 24 proteins showed significant associations with PCa risk, including 16 previously reported proteins and eight novel proteins. Of them, 14 proteins showed negative associations and 10 showed positive associations with PCa risk. For 18 of the identified proteins, potential functional somatic changes of encoding genes were detected in PCa patients in The Cancer Genome Atlas (TCGA). Genes encoding these proteins were significantly involved in cancer-related pathways. We further identified drugs targeting the identified proteins, which may serve as candidates for drug repurposing for treating PCa. In conclusion, this study identifies novel protein biomarker candidates for PCa risk, which may provide new perspectives on the etiology of PCa and improve its therapeutic strategies.
59 BASIC BIOLOGICAL SCIENCES↗
Tomography of longitudinal phase space linearization for the generation of attosecond electron bunches
The generation of electron bunches on the attosecond timescale is important for a multitude of accelerator-based applications. Here, we report on a tomographic measurement of the (pre)linearized longitudinal phase space of a low charge 3 MeV electron bunch generated with the 1.6 cell Pegasus photoinjector for the generation of attosecond bunches. The nonlinear correlations in the longitudinal phase space induced by space charge at the photocathode, radiofrequency field curvature of the gun, and vacuum dispersion are compensated using a compact X-band linearizer. Then, the initial and compensated phase of the picosecond electron bunch is precisely reconstructed by neural network assisted tomographic reconstruction from momentum spectra at varying buncher linac phase. Finally, we combine the measured phase space shape with particle tracking simulations to show that electron bunches as short as 941 as develop downstream the beamline.
Beam control↗
WIRE: Resource-efficient Scaling with Online Prediction for DAG-based Workflows
This paper introduces WIRE that manages resources for the DAG-based workflows on IaaS clouds. WIRE predicts and plans resources over the MAPE (Monitor-Analyze-Plan-Execute) loops to: 1) Estimate task performance with online data, 2) Conduct simulations to predict the upcoming loads based on online estimates and workflow DAGs, 3) Apply a resource-steering policy to size cloud instance pools for the maximal parallelism that is consistent with low cost. We implement WIRE on Pegasus WMS/HTCondor and evaluate its performance on the ExoGENI network cloud. The results show that WIRE attains low resource cost with the performance that is typically within a factor of two of optimal.
Xie, Bing↗
Emerging Frameworks for Advancing Scientific Workflows Research, Development, and Education
Lightning talks of the Workflows in Support of Large-Scale Science (WORKS) workshop are a venue where the workflow community (researchers, developers, and users) can discuss work in progress, emerging technologies and frameworks, and training and education materials. This paper summarizes the WORKS 2021 lightning talks, which cover four broad topics: (i) libEnsemble, a Python library to coordinate the concurrent evaluation of dynamic ensembles of calculations; (ii) Edu WRENCH, a set of online pedagogic modules that provides simulation-driven hands-on activity in the browser; (iii) VisDict, an envisioned visual dictionary framework that will translate terms, jargon, and concepts between research domains and workflow providers; and (iv) Pegasus Kickstart, a lightweight tool for capturing workflow tasks' performance, including performance metrics from Nvidia GPUs.
Casanova, Henri↗