Results for “Computer Science - Distributed” — Page 52

NASA NTRS2018

Validation of Slosh Modeling Approach Using STAR-CCM+

Without an adequate understanding of propellant slosh, the spacecraft attitude control system may be inadequate to control the spacecraft or there may be an unexpected loss of science observation time due to higher slosh settling times. Computational fluid dynamics (CFD) is used to model propellant slosh. STAR-CCM+ is a commercially available CFD code. This paper presents a comparison between STAR-CCM+ liquid slosh modeling results and experimental, empirically, and analytically derived results. The geometries examined are a bare right cylinder tank and a right cylinder

Benson, David↗

NASA NTRS2018

LiveCheckHSI: a Hardware/Software Co-verification Tool for Hyperspectral Imaging Systems with Embedded System-on-Chip Instrument Avionics

The emergent technology of system-on-chip (SoC) devices promises lighter, smaller, cheaper, and more capable and reliable space electronic systems that could help to unveil some of the most treasured secrets in our universe. This technology is an improvement over the technology that is currently used in space applications, which lags behind state-of-the-art commercial-off-the-shelf (COTS) equipment by several generations. SoC technology integrates all computational power required by next-generation space exploration science instruments onto a single chip. This paper describes hardware/software co-verification tools for the Xilinx Zynq-based control and data handling system that have been developed at the Jet Propulsion Laboratory (JPL) for visible-infrared imaging spectrometers. The system acquires and compresses images in real-time, in addition to programming the spectrometer (frame rate, exposure time), focus step motor, and heaters and reporting telemetry.

Dolman, David↗

NASA NTRSDate not supplied

Model Assisted Probability of Detection for NASA Space Missions

Model assisted probability of detection (MAPOD) uses data from simulations to improve a traditional probability of detection (POD) study. This could include extending the parameter space to reduce uncertainty or substituting experimental data with simulated data to reduce the time and cost of a POD study. In the past MAPOD was difficult due to limited computational resources, but recent innovations in simulation tools and high-performance computing have made this type of high-degree-of-freedom modeling possible, and complex structures have made it necessary. This presentation will summarize the work done by the computational nondestructive evaluation (CNDE) specialists within the Nondestructive Evaluation Sciences branch at NASA Langley Research Center (LaRC) to complete a MAPOD study for phased array ultrasound testing (PAUT) of a friction stir welding (FSW) method to be used on Space Launch System (SLS) structures. The three critical needs for a MAPOD study are a validated and verified model of the inspection technique for the structure being inspected, some experimental POD data, and an uncertainty model for both the model and the experimental data. PAUT was simulated using Extende CIVA’s UT module. The model was validated using laboratory inspection data from NASA Marshall Space Flight Center (MSFC) for a Hit/Miss POD for FSW in 2219-T87 aluminum panels representative of those used in the SLS. This model was then used to simulate flaw sizes that were originally omitted from the original POD study. The results of this new MAPOD study will be presented along with a discussion of the methods and processes used to analyze the original data, selected simulation parameters, and development of the uncertainty model used for the statistical analysis. The goal of this effort is not just to improve the POD study but to demonstrate the value of MAPOD and provide a roadmap for application of MAPOD on future projects.

Elizabeth Gregory↗

NASA NTRS2015

HIFiRE-1 Turbulent Shock Boundary Layer Interaction - Flight Data and Computations

The Hypersonic International Flight Research Experimentation (HIFiRE) program is a hypersonic flight test program executed by the Air Force Research Laboratory (AFRL) and Australian Defence Science and Technology Organisation (DSTO). This flight contained a cylinder-flare induced shock boundary layer interaction (SBLI). Computations of the interaction were conducted for a number of times during the ascent. The DPLR code used for predictions was calibrated against ground test data prior to exercising the code at flight conditions. Generally, the computations predicted the upstream influence and interaction pressures very well. Plateau pressures on the cylinder were predicted well at all conditions. Although the experimental heat transfer showed a large amount of scatter, especially at low heating levels, the measured heat transfer agreed well with computations. The primary discrepancy between the experiment and computation occurred in the pressures measured on the flare during second stage burn. Measured pressures exhibited large overshoots late in the second stage burn, the mechanism of which is unknown. The good agreement between flight measurements and CFD helps validate the philosophy of calibrating CFD against ground test, prior to exercising it at flight conditions.

Turbulence↗

NASA NTRS2004

The EO-1 Autonomous Science Agent Architecture

An Autonomous Science Agent is currently flying onboard the Earth Observing One Spacecraft. This software enables the spacecraft to autonomously detect and respond to science events occurring on the Earth. The package includes software systems that perform science data analysis, deliberative planning, and run-time robust execution. Because of the deployment to a remote spacecraft, this Autonomous Science Agent has stringent constraints of autonomy, reliability, and limited computing resources. We describe these constraints and how they are reflected in our agent architecture.

Earth Observing One (EO-1)↗

NASA NTRS1990

Time-accurate Navier-Stokes computations of self-excited two-dimensional unsteady cavity flows

Time-accurate Navier Stokes computations were performed to study self-excited oscillatory shear layer behavior over a two-dimensional rectangular cavity and to gain insight into the vortex-acoustic coupling that sustains these oscillations. Results were obtained solving the full, unsteady compressible Navier-Stokes equations for Reynolds-averaged turbulent air flow past a cavity with L/d = 2. Conditions duplicated test conditions in experiments by Rossiter at Mach numbers varied from 0.6 to 1.2. The computational scheme was the USA 2D series code developed by Rockwell's Science Center with an algebraic turbulence model for the shear layer and recirculating region. Two physical conditions were simulated: an isolated cavity situated (1) in an infinite plane wall and (2) in an infinite channel with an opposing parallel wall. Computed results for (1) showed excellent agreement with Rossiter's measured amplitudes and frequencies. A tuned acoustic duct resonance effect was observed in (2), demonstrating a controlled change in the acoustic feedback mechanism and resultant amplification in computed oscillations.

Dougherty, N. Sam↗

NASA NTRS2021

Core-Plasma Refilling and Erosion: Science Justification

Global magnetospheric models do not currently couple dynamic plasmaspheric plasma due to computational limitations that will be overcome by 2050. A true GGCM will need to include a dynamic plasmasphere for both physics and space weather prediction. Such inclusion requires that we answer longstanding, fundamental questions about the life cycle of core (<10 eV, plasmaspheric) plasma: how it gets into the inner magnetosphere, and how it is eroded. Erosion and refilling are processes controlling a fundamental space plasma population. During every geomagnetic disturbance, tens of metric tons of plasma are rapidly eroded away, then slowly and unevenly replenished. After several decades we still do not understand the cross-scale mechanisms proposed to be responsible for these 2 processes. Removal and replacement of this enormous plasma mass is as important to the dynamics of the magnetosphere as solar-wind driving. Our community must dedicate the resources and effort needed to solve this enduring puzzle. Other white papers submitted in response to the HP2050 call are discussing cold plasma and ionospheric outflow in more general contexts. This white paper deals specifically with the science justification for studying refilling and erosion.

Plasmasphere, core-plasma, erosion, refilling↗

NASA NTRS2010

Photometric Analysis in the Kepler Science Operations Center Pipeline

We describe the Photometric Analysis (PA) software component and its context in the Kepler Science Operations Center (SOC) pipeline. The primary tasks of this module are to compute the photometric flux and photocenters (centroids) for over 160,000 long cadence (~thirty minute) and 512 short cadence (~one minute) stellar targets from the calibrated pixels in their respective apertures. We discuss the science algorithms for long and short cadence PA: cosmic ray cleaning; background estimation and removal; aperture photometry; and flux-weighted centroiding. We discuss the end-to-end propagation of uncertainties for the science algorithms. Finally, we present examples of photometric apertures, raw flux light curves, and centroid time series from Kepler flight data. PA light curves, centroid time series, and barycentric timestamp corrections are exported to the Multi-mission Archive at Space Telescope [Science Institute] (MAST) and are made available to the general public in accordance with the NASA/Kepler data release policy.

Twicken, Joseph D.↗

NASA NTRS2022

Application Table: A Bridge Connecting the Designing “With-The-Material” and “The-Material” Paradigms

Over the last few decades, advances in high-performance computing, new material characterization methods, and, more recently, an emphasis on integrated computational materials engineering (ICME) have been a catalyst for multiscale modeling and simulation-based design of materials and structures in the aerospace industry. In 2016 NASA sponsored a 2040 Vision study (which appeared in 2018) to define the potential 25-year future state required for integrated multiscale modeling of materials and systems (e.g., load-bearing structures) to accelerate the pace and reduce the expense of innovation in future aerospace and aeronautical systems. The study envisions a cyber-physical-social ecosystem comprised of experimentally verified and validated (V & V) computational models, tools, and techniques, along with the associated digital tapestry, that impacts the entire supply chain to enable cost-effective, rapid, and revolutionary design of “fit-for-purpose” materials, components, and systems. Consequently, the development of a robust information management system that incorporates (across the full life cycle) both experimental (real data) and virtual data resulting from the application of various simulation tools (at single or multiple length scales), therefore enabling the virtual design and optimization of materials throughout their processing – internal structure – property – performance envelope, has become critical. This need is also fueled by the demands for higher efficiency in material testing; consistency, quality, and traceability of data; product design; engineering analysis; as well as control of access to proprietary or sensitive information. This is particularly true when attempting to merge ICME practices with recent additive manufacturing technology which will enable production of the resulting 2040 Vision material and structural designs. At NASA Glenn Research Center we are exploring the future of material science through the use of novel characterization methodologies, high performance computing, and recently an emphasis on integrated computational materials engineering (ICME). Herein, recent efforts to incorporate an Application Table within NASA Glenn Research Center’s ICME Granta MI database is presented. The goal is to provide a place where material and structural application information/requirements can be linked so as to marry the “design the-material” and the “design-with-material” paradigms and thereby enable application-driven design and optimization of materials and structures by providing a central location that links material processing at various length scales to the application’s performance requirements. This paper discusses the specifics of this Application Table as well as best practices and key principles for the development of a robust materials information management system to enable the 2040 Vision integrated materials and structures ecosystem. Furthermore, it presents the intended role of the Application Table in the future of ICME design of “fit-for-purpose” materials, showing the need for a well-established framework that can successfully bridge the gap between the design “the material” and design “with-the-material” paradigms.

Materials↗

NASA NTRSDate not supplied

Application Table: A Bridge Connecting the Designing “With-the-Material” and “the-Material”

Over the last few decades, advances in high-performance computing, new material characterization methods, and, more recently, an emphasis on integrated computational materials engineering (ICME) have been a catalyst for multiscale modeling and simulation-based design of materials and structures in the aerospace industry. In 2016 NASA sponsored a 2040 Vision study (which appeared in 2018) to define the potential 25-year future state required for integrated multiscale modeling of materials and systems (e.g., load-bearing structures) to accelerate the pace and reduce the expense of innovation in future aerospace and aeronautical systems. The study envisions a cyber-physical-social ecosystem comprised of experimentally verified and validated (V & V) computational models, tools, and techniques, along with the associated digital tapestry, that impacts the entire supply chain to enable cost-effective, rapid, and revolutionary design of “fit-for-purpose” materials, components, and systems. Consequently, the development of a robust information management system that incorporates (across the full life cycle) both experimental (real data) and virtual data resulting from the application of various simulation tools (at single or multiple length scales), therefore enabling the virtual design and optimization of materials throughout their processing – internal structure – property – performance envelope, has become critical. This need is also fueled by the demands for higher efficiency in material testing; consistency, quality, and traceability of data; product design; engineering analysis; as well as control of access to proprietary or sensitive information. This is particularly true when attempting to merge ICME practices with recent additive manufacturing technology which will enable production of the resulting 2040 Vision material and structural designs. At NASA Glenn Research Center we are exploring the future of material science through the use of novel characterization methodologies, high performance computing, and recently an emphasis on integrated computational materials engineering (ICME). Herein, recent efforts to incorporate an Application Table within NASA Glenn Research Center’s ICME Granta MI database is presented. The goal is to provide a place where material and structural application information/requirements can be linked so as to marry the “design the-material” and the “design-with-material” paradigms and thereby enable application-driven design and optimization of materials and structures by providing a central location that links material processing at various length scales to the application’s performance requirements. This paper discusses the specifics of this Application Table as well as best practices and key principles for the development of a robust materials information management system to enable the 2040 Vision integrated materials and structures ecosystem. Furthermore, it presents the intended role of the Application Table in the future of ICME design of “fit-for-purpose” materials, showing the need for a well-established framework that can successfully bridge the gap between the design “the material” and design “with-the-material” paradigms.

Materials↗

NASA NTRS2011

Fault-Tolerant, Radiation-Hard DSP

Commercial digital signal processors (DSPs) for use in high-speed satellite computers are challenged by the damaging effects of space radiation, mainly single event upsets (SEUs) and single event functional interrupts (SEFIs). Innovations have been developed for mitigating the effects of SEUs and SEFIs, enabling the use of very-highspeed commercial DSPs with improved SEU tolerances. Time-triple modular redundancy (TTMR) is a method of applying traditional triple modular redundancy on a single processor, exploiting the VLIW (very long instruction word) class of parallel processors. TTMR improves SEU rates substantially. SEFIs are solved by a SEFI-hardened core circuit, external to the microprocessor. It monitors the health of the processor, and if a SEFI occurs, forces the processor to return to performance through a series of escalating events. TTMR and hardened-core solutions were developed for both DSPs and reconfigurable field-programmable gate arrays (FPGAs). This includes advancement of TTMR algorithms for DSPs and reconfigurable FPGAs, plus a rad-hard, hardened-core integrated circuit that services both the DSP and FPGA. Additionally, a combined DSP and FPGA board architecture was fully developed into a rad-hard engineering product. This technology enables use of commercial off-the-shelf (COTS) DSPs in computers for satellite and other space applications, allowing rapid deployment at a much lower cost. Traditional rad-hard space computers are very expensive and typically have long lead times. These computers are either based on traditional rad-hard processors, which have extremely low computational performance, or triple modular redundant (TMR) FPGA arrays, which suffer from power and complexity issues. Even more frustrating is that the TMR arrays of FPGAs require a fixed, external rad-hard voting element, thereby causing them to lose much of their reconfiguration capability and in some cases significant speed reduction. The benefits of COTS high-performance signal processing include significant increase in onboard science data processing, enabling orders of magnitude reduction in required communication bandwidth for science data return, orders of magnitude improvement in onboard mission planning and critical decision making, and the ability to rapidly respond to changing mission environments, thus enabling opportunistic science and orders of magnitude reduction in the cost of mission operations through reduction of required staff. Additional benefits of COTS-based, high-performance signal processing include the ability to leverage considerable commercial and academic investments in advanced computing tools, techniques, and infra structure, and the familiarity of the science and IT community with these computing environments.

Czajkowski, David↗

NASA NTRSDate not supplied

Expanding Repository Data Available For Sharing And Knowledge Discovery

Some of the hardest space biology and space health challenges require data-intensive, bioinformatic, meta-analytical, and computer-assisted research approaches. These challenges include examining interdisciplinary space life science research across experiments and across interacting spaceflight hazards (radiation, altered gravity, confinement, hostile-closed environments, distance-duration from Earth). The approaches to confront these challenges involve mining multiple datasets simultaneously from various hierarchical organizations of biological complexity, all while concurrently evaluating how experimental design factors affect endpoints of standard assays. To enable this field, it is essential that principal investigators (PIs) submit data in a structure so it can be maximally re-used. The purpose of the NASA Ames Life Sciences Data Archive (ALSDA) is to collect, curate, and make publicly available all non-human space-relevant biological data. ALSDA must also ensure data are open-access, and maximally findable, accessible, interoperable, and reusable (FAIR). The scope of ALSDA data collected and submitted by PIs include subject and study design metadata, assay metadata parameters, raw and processed assay data, assay imagery/video, and subject-experienced mission data telemetry (radiation, temperature, humidity, acoustics, vibrations, etc.). ALSDA recently integrated into a collaborative group of Open Science projects to facilitate a suite of new tools and workflows that will improve data submission, accessibility, and reusability by implementing digital data submission agreements, and adopting the data management system originally developed by NASA GeneLab. ALSDA intends to bring current biological repository data and all future collected data into this new scientific data reuse reality. This new suite of tools will enable ALSDA to deploy a science curation system using scientific assay configurations for the data submission portal. It will capture essential assay parameters according to established standards in each sub-field within biology. The submission portal expedites data collection by enhancing ease of PI data submission, providing a user interface and specificity for which data is to be submitted. Data submissions can be brought into cutting-edge informatic analysis portals to enable mining of physiological, behavioral, biochemical, and imaging datasets in conjunction with ‘omics-level datasets. As ALSDA datasets are submitted, curated, and published (e.g., micro-computed tomography, histology, pulse oximetry, serum metabolites, magnetic resonance imaging, intraocular pressure, novel object recognition, etc.), the merging together of spaceflight data along this multi-hierarchical complexity of biology will enable informatics and data-intensive approaches resulting in knowledge discoveries across missions, space hazards, and biological disciplines.

life science↗

NASA NTRSDate not supplied

Expanding Repository Data Available For Sharing and Knowledge Discovery

Some of the hardest space biology and space health challenges require data-intensive, bioinformatic, meta-analytical, and computer-assisted research approaches. These challenges include examining interdisciplinary space life science research across experiments and across interacting spaceflight hazards (radiation, altered gravity, confinement, hostile-closed environments, distance-duration from Earth). The approaches to confront these challenges involve mining multiple datasets simultaneously from various hierarchical organizations of biological complexity, all while concurrently evaluating how experimental design factors affect endpoints of standard assays. To enable this field, it is essential that principal investigators (PIs) submit data in a structure so it can be maximally re-used. The purpose of the NASA Ames Life Sciences Data Archive (ALSDA) is to collect, curate, and make publicly available all non-human space-relevant biological data. ALSDA must also ensure data are open-access, and maximally findable, accessible, interoperable, and reusable (FAIR). The scope of ALSDA data collected and submitted by PIs include subject and study design metadata, assay metadata parameters, raw and processed assay data, assay imagery/video, and subject-experienced mission data telemetry (radiation, temperature, humidity, acoustics, vibrations, etc.). ALSDA recently integrated into a collaborative group of Open Science projects to facilitate a suite of new tools and workflows that will improve data submission, accessibility, and reusability by implementing digital data submission agreements, and adopting the data management system originally developed by NASA GeneLab. ALSDA intends to bring current biological repository data and all future collected data into this new scientific data reuse reality. This new suite of tools will enable ALSDA to deploy a science curation system using scientific assay configurations for the data submission portal. It will capture essential assay parameters according to established standards in each sub-field within biology. The submission portal expedites data collection by enhancing ease of PI data submission, providing a user interface and specificity for which data is to be submitted. Data submissions can be brought into cutting-edge informatic analysis portals to enable mining of physiological, behavioral, biochemical, and imaging datasets in conjunction with ‘omics-level datasets. As ALSDA datasets are submitted, curated, and published (e.g., micro-computed tomography, histology, pulse oximetry, serum metabolites, magnetic resonance imaging, intraocular pressure, novel object recognition, etc.), the merging together of spaceflight data along this multi-hierarchical complexity of biology will enable informatics and data-intensive approaches resulting in knowledge discoveries across missions, space hazards, and biological disciplines.

Biology↗

NASA NTRS1999

Parallel Grid Manipulations in Earth Science Calculations

The National Aeronautics and Space Administration (NASA) Data Assimilation Office (DAO) at the Goddard Space Flight Center is moving its data assimilation system to massively parallel computing platforms. This parallel implementation of GEOS DAS will be used in the DAO's normal activities, which include reanalysis of data, and operational support for flight missions. Key components of GEOS DAS, including the gridpoint-based general circulation model and a data analysis system, are currently being parallelized. The parallelization of GEOS DAS is also one of the HPCC Grand Challenge Projects. The GEOS-DAS software employs several distinct grids. Some examples are: an observation grid- an unstructured grid of points at which observed or measured physical quantities from instruments or satellites are associated- a highly-structured latitude-longitude grid of points spanning the earth at given latitude-longitude coordinates at which prognostic quantities are determined, and a computational lat-lon grid in which the pole has been moved to a different location to avoid computational instabilities. Each of these grids has a different structure and number of constituent points. In spite of that, there are numerous interactions between the grids, e.g., values on one grid must be interpolated to another, or, in other cases, grids need to be redistributed on the underlying parallel platform. The DAO has designed a parallel integrated library for grid manipulations (PILGRIM) to support the needed grid interactions with maximum efficiency. It offers a flexible interface to generate new grids, define transformations between grids and apply them. Basic communication is currently MPI, however the interfaces defined here could conceivably be implemented with other message-passing libraries, e.g., Cray SHMEM, or with shared-memory constructs. The library is written in Fortran 90. First performance results indicate that even difficult problems, such as above-mentioned pole rotation- a sparse interpolation with little data locality between the physical lat-lon grid and a pole rotated computational grid- can be solved efficiently and at the GFlop/s rates needed to solve tomorrow's high resolution earth science models. In the subsequent presentation we will discuss the design and implementation of PILGRIM as well as a number of the problems it is required to solve. Some conclusions will be drawn about the potential performance of the overall earth science models on the supercomputer platforms foreseen for these problems.

Sawyer, W.↗

NASA NTRS1994

Mobile Computing for Aerospace Applications

The use of commercial computer technology in specific aerospace mission applications can reduce the cost and project cycle time required for the development of special-purpose computer systems. Additionally, the pace of technological innovation in the commercial market has made new computer capabilities available for demonstrations and flight tests. Three areas of research and development being explored by the Portable Computer Technology Project at NASA Ames Research Center are the application of commercial client/server network computing solutions to crew support and payload operations, the analysis of requirements for portable computing devices, and testing of wireless data communication links as extensions to the wired network. This paper will present computer architectural solutions to portable workstation design including the use of standard interfaces, advanced flat-panel displays and network configurations incorporating both wired and wireless transmission media. It will describe the design tradeoffs used in selecting high-performance processors and memories, interfaces for communication and peripheral control, and high resolution displays. The packaging issues for safe and reliable operation aboard spacecraft and aircraft are presented. The current status of wireless data links for portable computers is discussed from a system design perspective. An end-to-end data flow model for payload science operations from the experiment flight rack to the principal investigator is analyzed using capabilities provided by the new generation of computer products. A future flight experiment on-board the Russian MIR space station will be described in detail including system configuration and function, the characteristics of the spacecraft operating environment, the flight qualification measures needed for safety review, and the specifications of the computing devices to be used in the experiment. The software architecture chosen shall be presented. An analysis of the performance characteristics of wireless data links in the spacecraft environment will be discussed. Network performance and operation will be modeled and preliminary test results presented. A crew support application will be demonstrated in conjunction with the network metrics experiment.

Alena, Richard↗

NASA NTRS2021

Achieving Breakthroughs in Global Hydrologic Science by Unlocking the Power of Multisensor, Multidisciplinary Earth Observations

Over the last half century, remote sensing has transformed hydrologic science. Whereas early efforts were devoted to observation of discrete variables, we now consider spaceborne missions dedicated to interlinked global hydrologic processes.Furthermore, cloud computing and computational techniquesare accelerating analyses of these data. How will the hydrologic community use these new resources to better understand the world’s water and relatedchallenges facing society? In this Commentary, we suggest that optimizing the benefits of remote sensing for advancing hydrologic research will happen byintegratingmultidisciplinary and multisensor data, leveraging commercial satellite measurements, and employingdata assimilation, cloud computing, and machine learning.We provide several recommendations to these ends. Plain Language Summary Observations from satellites have transformed hydrologic science. Early efforts, five decades ago, mapped attributes like snow cover, rainfall, topography, and vegetation, but now we consider new missions specifically designed to study global hydrologic processes. We also take advantageof new technologies like cloud computing and artificial intelligence. We describe strategiesfor maximizing the benefits of remote sensing for hydrology, encouraging research across disciplines using multiple sensors, using new commercially available satellites, and combining remote sensing measurements with hydrologic models.

Michael Durand↗

NASA NTRS2005

Astronomer's Proposal Tool

Astronomer's Proposal Tool (APT) is a computer program that assists astronomers in preparing their Phase 1 and Phase 2 Hubble Space Telescope science programs. APT is a successor to the Remote Proposal Submission System 2 (RPS2) program, which has been rendered obsolete by more recent advances in computer software and hardware. APT exploits advances associated with widespread use of the Internet, multiplatform visual development software tools, and overall increases in the power of desktop computer hardware, all in such a way as to make the preparation and submission of proposals more intuitive and make observatory operations less cumbersome. APT provides documentation and help that are friendly, up to date, and easily accessible to users of varying levels of expertise, while defining an extensible framework that is responsive to changes in both technology and observatory operations. APT consists of two major components: (1) a set of software tools that are intuitive, visual, and responsive and (2) an integrated software environment that unifies all the tools and makes them interoperable. The APT tools include the Visual Target Tuner, Proposal Editor, Exposure Planner, Bright Object Checker, and Visit Planner.

Krueger, Tony↗

NASA NTRS2021

Quantum Computing to Accelerate High Fidelity Computational Materials Modeling

In this CIF we worked to develop quantum algorithms for material science simulations based on new ideas recently proposed on plane wave basis sets. Many body simulations are not generally performed in plane wave basis sets on classical hardware, but with newly proposed quantum algorithms, it is possible this will be a highly efficient basis set to run quantum simulations on quantum hardware. Using state of the art classical simulations we ran small test simulations to estimate the resources that will be needed to run such plane wave algorithms on quantum hardware. We demonstrate our approach for a series of atoms and molecular systems.

Norman Tubman↗