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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 541 records · Page 30

Reconstructing thermal quantum quench dynamics from pure states

Simulating the nonequilibrium dynamics of thermal states is a fundamental problem across scales from high-energy to condensed-matter physics. Quantum computers may provide a way to solve this problem efficiently. Preparing a thermal state on a quantum computer is challenging, but there exist methods to circumvent this by computing a weighted sum of time-dependent matrix elements in a convenient basis. Further, while the number of basis states can be large, in this paper we show that it can be reduced by simulating only the largest density matrix elements by weight, capturing the density matrix to a specified precision. Leveraging Hamiltonian symmetries enables further reductions. This approach paves the way to more accurate thermal-state dynamics simulations on near-term quantum hardware.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Prepare Ground States of Highly Frustrated Magnetic Clusters on Quantum Computers

Solving challenging problems in physical, chemical, and materials sciences is one of the most promising applications of quantum utility that can be realized on current noisy hardware, considering (i) the direct map (encoding) from the quantum particles and their interactions to the qubits and their entangling gates and (ii) the rapidly improved quantum hardware and advanced error-mitigation techniques. Understanding quantum spin liquid in frustrated magnetic materials is a longstanding challenge in condensed matter physics and the nature of the ground-state phases is highly debated among researchers. Using IBM quantum computers with superconducting qubits, we implemented a variational quantum eigensolver (VQE) algorithm to prepare the ground states of two 12-site cluster approximations of these highly frustrated magnetic materials. The interaction graphs of the two corresponding Hamiltonians are (a) the six-pointed star graph (a unit cell of the kagome lattice) and (b) the cuboctahedral graph (the kagome on a sphere). These are also two instances of Quantum Max Cut problem. With the VQE based on the Hamiltonian variational ansatz acting on a valence bond solid initial trial state, we prepared the ground states and obtained the exact ground energy on simulator and high accuracy on noisy hardware. The deep ansatz necessary to reach the ground state of the cuboctahedral graph indicates that it is a hard instance of Quantum Max Cut.

Wang, Yan↗

Challenges in reducing the computational time of QSTS simulations for distribution system analysis.

The rapid increase in penetration of distributed energy resources on the electric power distribution system has created a need for more comprehensive interconnection modelling and impact analysis. Unlike conventional scenario - based studies , quasi - static time - series (QSTS) simulation s can realistically model time - dependent voltage controllers and the diversity of potential impacts that can occur at different times of year . However, to accurately model a distribution system with all its controllable devices, a yearlong simulation at 1 - second resolution is often required , which could take conventional computers a computational time of 10 to 120 hours when an actual unbalanced distribution feeder is modeled . This computational burden is a clear l imitation to the adoption of QSTS simulation s in interconnection studies and for determining optimal control solutions for utility operations . Our ongoing research to improve the speed of QSTS simulation has revealed many unique aspects of distribution system modelling and sequential power flow analysis that make fast QSTS a very difficult problem to solve. In this report , the most relevant challenges in reducing the computational time of QSTS simulations are presented: number of power flows to solve, circuit complexity, time dependence between time steps, multiple valid power flow solutions, controllable element interactions, and extensive accurate simulation analysis.

24 POWER TRANSMISSION AND DISTRIBUTION↗

The impact of different neutrino transport methods on multidimensional core-collapse supernova simulations

Neutrinos play a crucial role in the core-collapse supernova (CCSN) explosion mechanism. The requirement of accurately calculating the transport of neutrinos makes simulations of the CCSN mechanism extremely challenging and computationally expensive. Historically, this stiff challenge has been met by making approximations to the full transport equation. In this work, we compare CCSN simulations in one- and two-dimensions with three approximate neutrino transport schemes, each implemented in the FLASH simulation framework. We compare a two-moment M1 scheme with an analytic closure (M1), the isotropic diffusion source approximation (IDSA), and the advanced spectral leakage method. We identify and discuss the advantages and disadvantages of each scheme. For each approximate transport scheme, we use identical grid setups, hydrodynamics, and gravity solvers to investigate the transport effects on supernova shock dynamics and neutrino quantities. We find that the transport scheme has a small effect on the evolution of protoneutron star (PNS) radius, PNS mass, and the mass accretion rate. The neutrino luminosities, mean energies, and shock radii have a ~10%–20% quantitative difference but the overall qualitative trends are fairly consistent between all three approximations. We find larger differences in the gain region properties, including the gain region mass and the net heating rate in the gain region, as well as the strength of PNS convection in the core. We investigate the progenitor, nuclear equation of state, and stochastic perturbation dependence of our simulations and find similar magnitudes of impact on key quantities. We also compare the computational expense of the various approximations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Comparison of sparse domain approaches for 4D SPECT dynamic image reconstruction

Purpose: Dynamic imaging (DI) provides additional diagnostic information in emission tomography in comparison to conventional static imaging at the cost of being computationally more challenging. Dynamic single photon emission computed tomography (SPECT) reconstruction is particularly difficult because of the limitations in the sampling geometry present in most existing scanners. We have developed an algorithm Spline Initialized Factor Analysis of Dynamic Structures (SIFADS) that is a matrix factorization method for reconstructing the dynamics of tracers in tissues and blood directly from the projections in dynamic cardiac SPECT, without first resorting to any 3D reconstruction. Methods: SIFADS is different from "pure" factor analysis in dynamic structures (FADS) in that it employs a dedicated spline-based pre-initialization. In this paper, we analyze the convergence properties of SIFADS and FADS using multiple metrics. The performances of the two approaches are evaluated for numerically simulated data and for real dynamic SPECT data from canine and human subjects. Results: For SIFADS, metrics analyzed for reconstruction algorithm convergence show better features of the metric curves vs iterations. In addition, SIAFDS provides better tissue segmentations than that from pure FADS. Measured computational times are also typically better for SIFADS implementations than those with pure FADS. Conclusion: The analysis supports the utility of the pre-initialization of a factorization algorithm for better dynamic SPECT image reconstruction.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Intensity Frontier Computing at Fermilab

The Intensity Frontier (IF) experiments at Fermilab require computing, software, data handling, and infrastructure development for detector and beamline design and to extract maximum scientific output from the data. The emphasis of computing at Fermilab for many years has been on the Tevatron collider Run 2 experiments and CMS. Using the knowledge and experience gained from those experiments as well as new computing developments, preparations for computing for IF experiments are ramping up. There are many challenges in IF computing. These include event generators and detector simulation, beamline simulation, detector design and optimization, data acquisition, data handling, data analysis, and all of the associated services required. In this presentation the computing challenges and requirements will be described and the approaches being taken to address them will be shown.

43 PARTICLE ACCELERATORS↗

Role of High-End Computing in Meeting NASA's Science and Engineering Challenges

High-End Computing (HEC) has always played a major role in meeting the modeling and simulation needs of various NASA missions. With NASA's newest 62 teraflops Columbia supercomputer, HEC is having an even greater impact within the Agency and beyond. Significant cutting-edge science and engineering simulations in the areas of space exploration, Shuttle operations, Earth sciences, and aeronautics research, are already occurring on Columbia, demonstrating its ability to accelerate NASA s exploration vision. The talk will describe how the integrated supercomputing production environment is being used to reduce design cycle time, accelerate scientific discovery, conduct parametric analysis of multiple scenarios, and enhance safety during the life cycle of NASA missions.

Biswas, Rupak↗

ALACRITY: Analytics-Driven Lossless Data Compression for Rapid In-Situ Indexing, Storing, and Querying. In: Transactions on Large-Scale Data- and Knowledge-Centered Systems X. Lecture Notes in Computer Science, vol 8220

High-performance computing architectures face nontrivial data processing challenges, as computational and I/O components further diverge in performance trajectories. For scientific data analysis in particular, methods based on generating heavyweight access acceleration structures, e.g. indexes, are becoming less feasible for ever-increasing dataset sizes. We present ALACRITY, demonstrating the effectiveness of a fused data and index encoding of scientific, floating-point data in generating lightweight data structures amenable to common types of queries used in scientific data analysis. We exploit the representation of floating-point values by extracting significant bytes, using the resulting unique values to bin the remaining data along fixed-precision boundaries. To optimize query processing, we use an inverted index, mapping each generated bin to a list of records contained within, allowing us to optimize query processing with attribute range constraints. Overall, the storage footprint for both index and data is shown to be below numerous configurations of bitmap indexing, while matching or outperforming query performance.

Compression Ratio↗

Post-Fisherian Experimentation: From Physical to Virtual

Fisher's pioneering work in design of experiments has inspired further work with broader applications, especially in industrial experimentation. Three topics in physical experiments are discussed: principles of effect hierarchy, sparsity, and heredity for factorial designs, a new method called CME for de-aliasing aliased effects, and robust parameter design. The recent emergence of virtual experiments on a computer is reviewed. Here, some major challenges in computer experiments, which must go beyond Fisherian principles, are outlined.

97 MATHEMATICS AND COMPUTING↗

Determining Ground-State Phase Diagrams on Quantum Computers via a Generalized Application of Adiabatic State Preparation

Quantum phase transitions materialize as level crossings in the ground-state energy when the parameters of the Hamiltonian are varied. The resulting ground-state phase diagrams are straightforward to determine by exact diagonalization on classical computers, but are challenging on quantum computers because of the accuracy needed and the near degeneracy of the competing states close to the level crossings. On the other hand, classical computers are limited to small system sizes, which quantum computers may help overcome. In this work, we use a local adiabatic ramp for state preparation to allow us to directly compute ground-state phase diagrams on a quantum computer via time evolution. This methodology is illustrated by examining the ground states of the XY model with a magnetic field in the z-direction in one dimension. We are able to calculate an accurate phase diagram on both two- and three-site systems using IBM quantum machines.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

High End Computing Technologies for Earth Science Applications: Trends, Challenges, and Innovations

Earth science applications of the future will stress the capabilities of even the highest performance supercomputers in the areas of raw compute power, mass storage management, and software environments. These NASA mission critical problems demand usable multi-petaflops and exabyte-scale systems to fully realize their science goals. With an exciting vision of the technologies needed, NASA has established a comprehensive program of advanced research in computer architecture, software tools, and device technology to ensure that, in partnership with US industry, it can meet these demanding requirements with reliable, cost effective, and usable ultra-scale systems. NASA will exploit, explore, and influence emerging high end computing architectures and technologies to accelerate the next generation of engineering, operations, and discovery processes for NASA Enterprises. This article captures this vision and describes the concepts, accomplishments, and the potential payoff of the key thrusts that will help meet the computational challenges in Earth science applications.

Parks, John↗

Computational Fluid Dynamics Technology for Hypersonic Applications

Several current challenges in computational fluid dynamics and aerothermodynamics for hypersonic vehicle applications are discussed. Example simulations are presented from code validation and code benchmarking efforts to illustrate capabilities and limitations. Opportunities to advance the state-of-art in algorithms, grid generation and adaptation, and code validation are identified. Highlights of diverse efforts to address these challenges are then discussed. One such effort to re-engineer and synthesize the existing analysis capability in LAURA, VULCAN, and FUN3D will provide context for these discussions. The critical (and evolving) role of agile software engineering practice in the capability enhancement process is also noted.

Gnoffo, Peter A.↗

New Challenges in Visualization of Computational Fluid Dynamics

The development of visualization systems for analyzing computational fluid dynamics data has been driven by increasing size and complexity of the data. New extensions to the system domain into analysis of data from multiple sources, parameter space studies, and multidisciplinary studies in support of integrated aeronautical design systems provide new g challenges for the visualization system developer. Recent work at NASA Ames Research Center in visualization systems, automatic flow feature detection, unsteady flow visualization techniques, and a new area, data exploitation, will be discussed in the context of NASA information technology initiatives.

Gerald-Yamasaki, Michael↗

In Situ Fabrication of PtCo Alloy Embedded in Nitrogen-Doped Graphene Nanopores as Synergistic Catalyst for Oxygen Reduction Reaction

A novel PtCo alloy in situ etched and embedded in graphene nanopores (PtCo/NPG) as a high-performance catalyst for ORR was reported. Graphene nanopores were fabricated in situ while forming PtCo nanoparticles that were uniformly embedded in the graphene nanopores. Given the synergistic effect between PtCo alloy and nanopores, PtCo/NPG exhibited 11.5 times higher mass activity than that of the commercial Pt/C cathode electrocatalyst. DFT calculations indicated that the nanopores in NPG cannot only stabilize PtCo nanoparticles but can also definitely change the electronic structures, thereby change its adsorption abilities. This enhancement can lead to a favorable reaction pathway on PtCo/NPG for ORR. This study showed that PtCo/NPG is a potential candidate for the next generation of Pt-based catalysts in fuel cells. This study also offered a promising alternative strategy and enabled the fabrication of various kinds of metal/graphene nanopore nanohybrids with potential applications in catalysts and potential use for other technological devices. The authors acknowledge the financial support from the National Basic Research Program (973 program, No. 2013CB733501), Zhejiang Provincial Education Department Research Program (Y201326554) and the National Natural Science Foundation of China (No. 21306169, 21101137, 21136001, 21176221 and 91334013). D. Mei acknowledges the support from the US Department of Energy, Office of Science, Office of Basic Energy Sciences, Division of Division of Chemical Sciences, Geosciences & Biosciences. Pacific Northwest National Laboratory (PNNL) is a multiprogram national laboratory operated for DOE by Battelle. Computing time was granted by the grand challenge of computational catalysis of the William R. Wiley Environmental Molecular Sciences Laboratory (EMSL) and by the National Energy Research Scientific Computing Center (NERSC).

electrocatalysis↗

Mechanistic Insights into the Structure-Dependent Selectivity of Catalytic Furfural Conversion on Platinum Catalysts

The effects of structure and size on the selectivity of catalytic furfural conversion over supported Pt catalysts in the presence of hydrogen have been studied using first principles density functional theory (DFT) calculations and microkinetic modeling. Four Pt model systems, i.e., periodic Pt(111), Pt(211) surfaces, as well as small nanoclusters (Pt13 and Pt55) are chosen to represent the terrace, step, and corner sites of Pt nanoparticles. Our DFT results show that the reaction routes for furfural hydrogenation and decarbonylation are strongly dependent on the type of reactive sites, which lead to the different selectivity. On the basis of the size-dependent site distribution rule, we correlate the site distributions as a function of the Pt particle size. Our microkinetic results indicate the critical particle size that controls the furfural selectivity is about 1.0 nm, which is in good agreement with the reported experimental value under reaction conditions. This work was supported by National Basic Research Program of China (973 Program) (2013CB733501) and the National Natural Science Foundation of China (NSFC-21306169, 21176221, 21136001, 21101137 and 91334103). This work was also partially supported by the US Department of Energy (DOE), the Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences & Biosciences. Pacific Northwest National Laboratory (PNNL) is a multiprogram national laboratory operated for DOE by Battelle. Computing time was granted by the grand challenge of computational catalysis of the William R. Wiley Environmental Molecular Sciences Laboratory (EMSL). EMSL is a national scientific user facility located at Pacific Northwest National Laboratory (PNNL) and sponsored by DOE’s Office of Biological and Environmental Research.

biomass conversion↗

Mechanistic insights into aqueous phase propanol dehydration in H-ZSM-5 zeolite

Aqueous phase dehydration of 1-propanol over H-ZSM-5 zeolite was investigated using density functional theory (DFT) calculations. The water molecules in the zeolite pores prefer to aggregate via the hydrogen bonding network and be protonated at the Brønsted acidic sites (BAS). Two typical configurations, i.e., dispersed and clustered, of water molecules were identified by ab initio molecular dynamics simulation of the mimicking aqueous phase H-ZSM-5 zeolite unit cell with 20 water molecules per unit cell. DFT calculated Gibbs free energies suggest that the dimeric propanol-propanol, the propanol-water complex, and the trimeric propanol-propanol-water are formed at high propanol concentrations, which provide a kinetically feasible dehydration reaction channel of 1-propanol to propene. However, calculation results also indicate that the propanol dehydration via the unimolecular mechanism becomes kinetically discouraged due to the enhanced stability of the protonated dimeric propanol and the protonated water cluster acting as the BAS site for alcohol dehydration reaction. This work was supported by the US Department of Energy (DOE), Office of Science, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences & Biosciences. Pacific Northwest National Laboratory (PNNL) is a multiprogram national laboratory operated for DOE by Battelle. Computing time was granted by the grand challenge of computational catalysis of the William R. Wiley Environmental Molecular Sciences Laboratory (EMSL). EMSL is a national scientific user facility located at Pacific Northwest National Laboratory (PNNL) and sponsored by DOE’s Office of Biological and Environmental Research.

Alcohol↗