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At least 721 records · Page 40

Orchestrated trios: compiling for efficient communication in Quantum programs with 3-Qubit gates

Current quantum computers are especially error prone and require high levels of optimization to reduce operation counts and maximize the probability the compiled program will succeed. These computers only support operations decomposed into one- and two-qubit gates and only two-qubit gates between physically connected pairs of qubits. Typical compilers first decompose operations, then route data to connected qubits. We propose a new compiler structure, Orchestrated Trios, that first decomposes to the three-qubit Toffoli, routes the inputs of the higher-level Toffoli operations to groups of nearby qubits, then finishes decomposition to hardware-supported gates. This significantly reduces communication overhead by giving the routing pass access to the higher-level structure of the circuit instead of discarding it. A second benefit is the ability to now select an architecture-tuned Toffoli decomposition such as the 8-CNOT Toffoli for the specific hardware qubits now known after the routing pass. Furthermore, we perform real experiments on IBM Johannesburg showing an average 35% decrease in two-qubit gate count and 23% increase in success rate of a single Toffoli over Qiskit. We additionally compile many near-term benchmark algorithms showing an average 344% increase in (or 4.44x) simulated success rate on the Johannesburg architecture and compare with other architecture types.

compiler↗

Transfer Factors for the FRMAC Assessment Manual and Turbo FRMAC to Improve Radiological Dose Assessment

The Turbo FRMAC analysis tool is used to perform complex calculations to quickly evaluate radiological consequences and aid in decision making during an emergency response by assessing impacts to the public, workers, and the food supply. Turbo FRMAC calculations are based on methods established by the Federal Radiological Monitoring and Assessment Center (FRMAC). To be able to assess impacts, input data called transfer factors that describe radionuclide uptake by local plants and animals are required. During the code application exercises in late 2016, identifying, finding, and validating nonstandard transfer factors proved to be time consuming and diverted the teams’ activity away from other critical tasks. As a result, a task was undertaken to dramatically expand the list of available transfer factors (food and non-food) and incorporate these factors into Turbo FRMAC. This will ultimately result in improved efficiency of the assessment team to perform calculations during times when the FRMAC is activated and provide more defensible, vetted data from which to calculate results. As a result of these and subsequent exercises, transfer factors were needed for the following items: bell peppers, Christmas tree, deer, flowers, fresh cucumbers, tomatoes, grapefruit, lichens, mushrooms, oranges, snap beans, squash, strawberries, sugarcane for sugar and seed, sweet corn, tea, tobacco, tree bark, and watermelon. To expand the applicability of the information tables, generic transfer data were also provided for common categories and recommendations were made for expanding the list of chemicals based on chemical similarity. The data presented in this report were compiled from recent literature with most of the data encompassing the period from 2000 to 2018. The following radionuclides were targeted during the literature search: elements associated with reactor accidents or nuclear detonations (Sr 89/90, Cs 134/137, Ce 141/144, Ru 103/106, I 129/131/133, Pu 238/239, Am 241, Zr 95, and Nb 95) and elements associated with industrial accidents or dirty bombs (Ir 192 and Co 60). Data from other elements were evaluated if they were identified during the literature search. In addition, reports were evaluated that were recommended by the research consultants. For each plant or animal transfer factor, the goal was to determine the geometric mean, the geometric standard deviation, the minimum, the maximum, and the number of measurements used. If only one measurement was available that was presented as the mean. Concentration ratios with large geometric standard deviations (GSDs) were generally the result of a paucity of measurements or a few disparate measurements. Measurement disparity was observed for data from different soil types. The geometric mean (GM) is a good reference value for planning and responses purposes, but the location-specific concentrations are unlikely to be similar to the model results. Recommendations for further work include: segregating the data to reflect the influence of soil type, developing approaches to incorporate animal data based on aggregated transfer measurements, and including data for foliar deposition on plants.

61 RADIATION PROTECTION AND DOSIMETRY↗

Structural Dynamics and Data Analysis

This project consists of two parts, the first will be the post-flight analysis of data from a Delta IV launch vehicle, and the second will be a Finite Element Analysis of a CubeSat. Shock and vibration data was collected on WGS-5 (Wideband Global SATCOM- 5) which was launched on a Delta IV launch vehicle. Using CAM (CAlculation with Matrices) software, the data is to be plotted into Time History, Shock Response Spectrum, and SPL (Sound Pressure Level) curves. In this format the data is to be reviewed and compared to flight instrumentation data from previous flights of the same launch vehicle. This is done to ensure the current mission environments, such as shock, random vibration, and acoustics, are not out of family with existing flight experience. In family means the peaks on the SRS curve for WGS-5 are similar to the peaks from the previous flights and there are no major outliers. The curves from the data will then be compiled into a useful format so that is can be peer reviewed then presented before an engineering review board if required. Also, the reviewed data will be uploaded to the Engineering Review Board Information System (ERBIS) to archive. The second part of this project is conducting Finite Element Analysis of a CubeSat. In 2010, Merritt Island High School partnered with NASA to design, build and launch a CubeSat. The team is now called StangSat in honor of their mascot, the mustang. Over the past few years, the StangSat team has built a satellite and has now been manifested for flight on a SpaceX Falcon 9 launch in 2014. To prepare for the final launch, a test flight was conducted in Mojave, California. StangSat was launched on a Prospector 18D, a high altitude rocket made by Garvey Spacecraft Corporation, along with their sister satellite CP9 built by California Polytechnic University. However, StangSat was damaged during an off nominal landing and this project will give beneficial insights into what loads the CubeSat experienced during the crash. During the year, the MIHS students generated a SolidWorks (CAD software) geometry model of StangSat. This model will be imported into FEMAP (Finite Element Analysis (FEA) Software) and a finite element model wiiJ be created to predict the loads encountered during the crash of this rocket. This analysis will require learning how to import CAD models into the FEM, mesh and add constraints and concentrated masses to represent components inside the CubeSat frame, such as circuit boards, batteries and accelerometers. During the analysis the loads will be varied, in effort to duplicate the damage to the CubeSat. Results will then be peer reviewed and documented.

Luthman, Briana L.↗

Compiler-assisted multiple instruction rollback recovery using a read buffer

Multiple instruction rollback (MIR) is a technique that has been implemented in mainframe computers to provide rapid recovery from transient processor failures. Hardware-based MIR designs eliminate rollback data hazards by providing data redundancy implemented in hardware. Compiler-based MIR designs have also been developed which remove rollback data hazards directly with data-flow transformations. This paper focuses on compiler-assisted techniques to achieve multiple instruction rollback recovery. We observe that some data hazards resulting from instruction rollback can be resolved efficiently by providing an operand read buffer while others are resolved more efficiently with compiler transformations. A compiler-assisted multiple instruction rollback scheme is developed which combines hardware-implemented data redundancy with compiler-driven hazard removal transformations. Experimental performance evaluations indicate improved efficiency over previous hardware-based and compiler-based schemes.

Alewine, N. J.↗

The population of hot subdwarf stars studied with Gaia: IV. Catalogues of hot subluminous stars based on Gaia EDR3

In light of substantial new discoveries of hot subdwarfs by ongoing spectroscopic surveys and the availability of the Gaia mission Early Data Release 3 (EDR3), we compiled new releases of two catalogues of hot subluminous stars: The data release 3 (DR3) catalogue of the known hot subdwarf stars contains 6616 unique sources and provides multi-band photometry, and astrometry from Gaia EDR3 as well as classifications based on spectroscopy and colours. This is an increase of 742 objects over the DR2 catalogue. This new catalogue provides atmospheric parameters for 3087 stars and radial velocities for 2791 stars from the literature. In addition, we have updated the Gaia Data Release 2 (DR2) catalogue of hot subluminous stars using the improved accuracy of the Gaia EDR3 data set together with updated quality and selection criteria to produce the Gaia EDR3 catalogue of 61 585 hot subluminous stars, representing an increase of 21 785 objects. Furthermore, the improvements in Gaia EDR3 astrometry and photometry compared to Gaia DR2 have enabled us to define more sophisticated selection functions. In particular, we improved hot subluminous star detection in the crowded regions of the Galactic plane as well as in the direction of the Magellanic Clouds by including sources with close apparent neighbours but with flux levels that dominate the neighbourhood.

79 ASTRONOMY AND ASTROPHYSICS↗

Pantropical Tree Leaf Hydraulic Properties, 1986 - 2015

This data package contains leaf pressure-volume parameters (osmotic potential at full turgor, turgor loss point, bulk elastic modulus, and others). Data was obtained by combining new data I gleaned from original publications not already in the following compilations (after removing the extratropical data): Bartlett, M. K., Zhang, Y., Kreidler, N., Sun, S., Ardy, R., Cao, K., and Sack, L.: Global analysis of plasticity in turgor loss point, a key drought tolerance trait, Ecol Lett, 17, 1580-1590, 2014. Bartlett, M. K., Scoffoni, C., and Sack, L.: The determinants of leaf turgor loss point and prediction of drought tolerance of species and biomes: a global meta-analysis, Ecology Letters, 15, 393-405, 2012. Maréchaux, I., Bartlett, M. K., Sack, L., Baraloto, C., Engel, J., Joetzjer, E., Chave, J., and Kitajima, K.: Drought tolerance as predicted by leaf water potential at turgor loss point varies strongly across species within an Amazonian forest, Functional Ecology, 29, 1268-1277, 2015. Data are from natural tropical and subtropical forests or savannas and span rainfall gradients from deciduous dry tropical forests to everwet tropical forests, and come from countries all throughout the pantropics. The attached zip file contains data organized into three CSV files.

54 ENVIRONMENTAL SCIENCES↗

Bulk Compositional Trends in Meteorites: A Guide for Analysis and Interpretation of NEAR XGRS Data from Asteroid 433 EROS

The Near Earth Asteroid Rendezvous (NEAR) spacecraft is to orbit the S-class asteroid 433 Eros for about one year beginning on February 14, 2000. The X-ray/gamma-ray O, Mg, Al, Si, Fe, and K; possibly H, Ca, S, Ti, and Th) of Eros with a spatial resolution ranging from a few km for X-rays to approx. 25% of the asteroid's surface for gamma-rays. The major scientific goals for the NEAR XGRS are to relate the composition of Eros to known classes of meteorites, to assess compositional heterogeneity and to identify geological processes that have occurred on the asteroid. Comparing remote-sensing data from asteroids to laboratory data from meteorites requires that the latter be well determined and understood. How well particular classes of meteorites can be identified as analogues of Eros depends not only on the error of the XGRS measurement, but also on the spread in abundances observed among different members of a given meteorite class. To prepare for the return of XGRS data from Eros, we have compiled a large database of bulk elemental compositions of meteorites, using data from a wide variety of published and unpublished sources. Custom software was developed to easily extract statistical information and make plots of data from different meteorite classes. Here, we use the meteorite compositional database to investigate which abundances and abundance ratios, of those measureable by the NEAR XGRS, are most diagnostic for distinguishing meteorite classes and identifying geological processes that have occurred on the samples' parent asteroids.

Nittler, Larry R.↗

Read buffer optimizations to support compiler-assisted multiple instruction retry

Multiple instruction retry is a recovery mechanism for transient processor faults. We previously developed a compiler-assisted approach to multiple instruction ferry in which a read buffer of size 2N (where N represents the maximum instruction rollback distance) was used to resolve some data hazards while the compiler resolved the remaining hazards. The compiler-assisted scheme was shown to reduce the performance overhead and/or hardware complexity normally associated with hardware-only retry schemes. This paper examines the size and design of the read buffer. We establish a practical lower bound and average size requirement for the read buffer by modifying the scheme to save only the data required for rollback. The study measures the effect on the performance of a DECstation 3100 running ten application programs using six read buffer configurations with varying read buffer sizes. Two alternative configurations are shown to be the most efficient and differed depending on whether split-cycle-saves are assumed. Up to a 55 percent read buffer size reduction is achievable with an average reduction of 39 percent given the most efficient read buffer configuration and a variety of applications.

Alewine, N. J.↗

A geologic atlas of TIMS data

In the three years since the first data were taken, it was well demonstrated that the Thermal Infrared Multispectral Scanner (TIMS), properly used, can be a most valuable tool for the geologist. Compilation of the TIMS data into a geological atlas was felt to be useful. Several data sets were extensively studied to establish TIMS as a geologic tool and to explore the optimum enhancement techniques. It was found that a decorrelation stretch of bands 1, 3, and 5 enhance the data to a form that is very useful and this enhancement will be used in the geologic atlas along with an accompanying geologic map and description. Many data sets are well published and familiar to TIMS users, but there are some sets that, for lack of time and funds, were not thoroughly studied or published. A short description of these least studied sets of data is presented. The images presented along with the many previously studied and published TIMS images constitute an enormously useful set of information for the geologist in the 8 to 10 micron range.

Abbott, Elsa↗

A relationship between chemical structure and the critical temperature

The present investigation is concerned with the effect of both molecular weight and chemical structure on the critical temperature. Using data from the comprehensive compilation of critical constants of Kudchadker et al. (1968), a simple relationship could be developed between the critical temperature and chemical structure. This relationship does not require experimental data such as the normal boiling point. It was found that the critical temperature (Tc) is given by an expression containing m and the sum of delta-i, where m is the total number of atoms in the molecule and delta-i is a number whose value is obtained from a table of additive atomic, group, and structural constants.

Fedors, R. F.↗

The ARM Data-oriented Metrics and Diagnostics Package for Climate Models - A New Tool for Evaluating Climate Models with Field Data

The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program User Facility produces ground-based long-term continuous unique measurements for atmospheric state, precipitation, turbulent fluxes, radiation, aerosol, cloud and the land surface, which are collected at multiple sites. These comprehensive datasets have been widely used to calibrate climate models and are proven to be invaluable for climate model development and improvement. This article introduces an evaluation package to facilitate the use of ground-based ARM measurements in climate model evaluation. The ARM data-oriented metrics and diagnostics package (ARM-DIAGS) includes both ARM observational datasets and a Python-based analysis toolkit for computation and visualization. The observational datasets are compiled from multiple ARM data products and specifically tailored for use in climate model evaluation. In addition, ARM-DIAGS also includes simulation data from models participating the Coupled Model Inter-comparison Project (CMIP), which will allow climate-modeling groups to compare a new, candidate version of their model to existing CMIP models. The analysis toolkit is designed to make the metrics and diagnostics quickly available to the model developers.

54 ENVIRONMENTAL SCIENCES↗

An Inventory of AI-ready Benchmark Data for US Fires, Heatwaves, and Droughts

Extreme weather events, including fires, heatwaves, and droughts, have significant impacts on earth, environmental, and energy systems. Mechanistic and predictive understanding, as well as probabilistic risk assessment of these extreme weather events, are crucial for detecting, planning for, and responding to these extremes. Records of extreme weather events provide an important data source for understanding present and future extremes, but the existing data needs preprocessing before it can be used for analysis. Moreover, there are many nonstandard metrics defining the levels of severity or impacts of extremes. In this study, we compile a comprehensive benchmark data inventory of extreme weather events, including fires, heatwaves, and droughts. The dataset covers the period from 2001 to 2020 with a daily temporal resolution and a spatial resolution of 0.5°×0.5° (~55km×55km) over the continental United States (CONUS), and a spatial resolution of 1km × 1km over the Pacific Northwest (PNW) region, together with the co-located and relevant meteorological variables. By exploring and summarizing the spatial and temporal patterns of these extremes in various forms of marginal, conditional, and joint probability distributions, we gain a better understanding of the characteristics of climate extremes. The resulting AI/ML-ready data products can be readily applied to ML-based research, fostering and encouraging AI/ML research in the field of extreme weather. This study can contribute significantly to the advancement of extreme weather research, aiding researchers, policymakers, and practitioners in developing improved preparedness and response strategies to protect communities and ecosystems from the adverse impacts of extreme weather events.

54 ENVIRONMENTAL SCIENCES↗

An Inventory of AI-ready Benchmark Data for US Fires, Heatwaves, and Droughts

Extreme weather events, including fires, heatwaves, and droughts, have significant impacts on earth, environmental, and energy systems. Mechanistic and predictive understanding, as well as probabilistic risk assessment of these extreme weather events, are crucial for detecting, planning for, and responding to these extremes. Records of extreme weather events provide an important data source for understanding present and future extremes, but the existing data needs preprocessing before it can be used for analysis. Moreover, there are many nonstandard metrics defining the levels of severity or impacts of extremes. In this study, we compile a comprehensive benchmark data inventory of extreme weather events, including fires, heatwaves, and droughts. The dataset covers the period from 2001 to 2020 with a daily temporal resolution and a spatial resolution of 0.5°×0.5° (~55km×55km) over the continental United States (CONUS), and a spatial resolution of 1km × 1km over the Pacific Northwest (PNW) region, together with the co-located and relevant meteorological variables. By exploring and summarizing the spatial and temporal patterns of these extremes in various forms of marginal, conditional, and joint probability distributions, we gain a better understanding of the characteristics of climate extremes. The resulting AI/ML-ready data products can be readily applied to ML-based research, fostering and encouraging AI/ML research in the field of extreme weather. This study can contribute significantly to the advancement of extreme weather research, aiding researchers, policymakers, and practitioners in developing improved preparedness and response strategies to protect communities and ecosystems from the adverse impacts of extreme weather events. Usage Notes We presented a long term (2001-2020) and comprehensive data inventory of historical extreme events with daily temporal resolution covering the separate spatial extents of CONUS (0.5°×0.5°) and PNW(1km×1km) for various applications and studies. The dataset with 0.5°×0.5° resolution for CONUS can be used to help build more accurate climate models for the entire CONUS, which can help in understanding long-term climate trends, including changes in the frequency and intensity of extreme events, predicting future extreme events as well as understanding the implications of extreme events on society and the environment. The data can also be applied for risk accessment of the extremes. For example, ML/AI models can be developed to predict wildfire risk or forecast HWs by analyzing historical weather data, and past fires or heateave , allowing for early warnings and risk mitigation strategies. Using this dataset, AI-driven risk assessment models can also be built to identify vulnerable energy and utilities infrastructure, imrpove grid resilience and suggest adaptations to withstand extreme weather events. The high-resolution 1km×1km dataset ove PNW are advantageous for real-time, localized and detailed applications. It can enhance the accuracy of early warning systems for extreme weather events, helping authorities and communities prepare for and respond to disasters more effectively. For example, ML models can be developed to provide localized HW predictions for specific neighborhoods or cities, enabling residents and local emergency services to take targeted actions; the assessment of drought severity in specific communities or watersheds within the PNW can help local authorities manage water resources more effectively.

Lin, Xinming↗

Current data are consistent with flat spatial hypersurfaces in the Λ CDM cosmological model but favor more lensing than the model predicts

Here, we study the performance of three pairs of tilted, and a pair of untilited, ΛCDM cosmological models, with three of these four pairs allowing for non-flat spatial hypersurfaces, against cosmic microwave background (CMB) temperature and polarization power spectrum data (P18), measurements of the Planck 2018 lensing potential power spectrum (lensing), and a large compilation of non-CMB data (non-CMB). For the eight models, we measure cosmological parameters and study whether or not pairs of the data sets (as well as subsets of them) are mutually consistent in these models. Half of these models allow the lensing consistency parameter A L , which re-scales the gravitational potential power spectrum, to be an additional free parameter to be determined from data, while the other three have A L = 1 which is the theoretically expected value. The pair of untilted non-flat ΛCDM models are incompatible with P18 data. The tilted spatially-flat models assume the usual primordial spatial inhomogeneity power spectrum that is a power law in wave number. The tilted non-flat models assume either the primordial power spectrum used in the Planck group anal yses [Planck P(q)], that has recently been numerically shown to be a good approximation to what is quantum-mechanically generated from a particular choice of closed inflation model initial conditions, or a recently computed power spectrum [new P(q)] that quantum-mechanically follows from a different set of non-flat inflation model initial conditions. In the tilted non-flat models with A L = 1 we find differences between P18 data and non-CMB data cosmological parameter constraints, which are large enough to rule out the Planck P(q) model at 3σ but not the new P(q) model. No significant differences are found when cosmological parameter constraints obtained with two different data sets are compared within the standard tilted flat ΛCDM model. While both P18 data and non-CMB data separately favor a closed geometry, with spatial curvature density parameter Ω k < 0, when P18+non-CMB data are jointly analyzed the evidence in favor of non-flat hypersurfaces subsides. Differences between P18 data and non-CMB data cosmological constraints subside when A L is allowed to vary. From the most restrictive P18+lensing+non-CMB data combination we get almost model-independent constraints on the cosmological parameters and find that the A L > 1 option is preferred over the Ω k < 0 one, with the A L parameter, for all models, being larger than unity by ~ 2.5σ. According to the deviance information criterion, in the P18+lensing+non-CMB analysis, the varying A L option is on the verge of being strongly favored over the A L = 1 one, which could indicate a problem for the standard tilted flat ΛCDM model. These data are consistent with flat spatial hypersurfaces but more and better data could improve the constraints on Ω k and might alter this conclusion. Error bars on some cosmological parameters are significantly reduced when non-CMB data are used jointly with P18+lensing data. For example, in the tilted flat ΛCDM model for P18+lensing+non-CMB data the Hubble constant H 0 = 68.09 ± 0.38 km s -1 Mpc -1 , which is consistent with that from a median statistics analysis of a large compilation of H 0 measurements as well as with a number of local measurements of the cosmological expansion rate. This H 0 error bar is 31% smaller than that from P18+lensing data alone.

79 ASTRONOMY AND ASTROPHYSICS↗

Evaluation of Nominal Energy Storage at Existing Hydropower Reservoirs in the US

Long-term planning and operation of hydropower reservoirs require an understanding of both water and energy storage. As energy storage needs of the evolving grid increase, we must account for the water and energy storage potential of these reservoirs. Given the limitations of current data on existing hydropower, we compile statistics related to storage volume and hydraulic head from publicly available data sets and examine differences in descriptions of US hydropower storage. Assembled characteristics are used to calculate nominal energy storage capacity, a simple measure of potential to generate power from a given volume of water, not factoring in detailed constraints. Inventory-based estimates of energy storage are calculated at 2,075 dams, which helps put the potential for US hydropower to support energy storage in context with similar evaluations in other regions and with other energy storage technologies. The national energy storage capacity ranges between 34.5 and 45.1 TWh depending on the information used, with 52% of energy storage located at the 10 largest reservoirs in the US. Energy storage capacities are also calculated at 236 dams with historical volume and elevation data. Finally, reservoir inflows provide context for the storage volumes and sensitivities to hydrologic variability. Larger reservoirs with greater storage volume to inflow ratios are concentrated in the Western US, but the majority of hydropower reservoirs store less than the annual inflow. We address several infrastructure and water resource informatics challenges and highlight remaining issues, including representing seasonal or shorter variability in water volumes and representing connected hydropower facilities.

13 HYDRO ENERGY↗