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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

How Cyanobacterial Distributions Reveal Flow and Irradiance Conditions of Photosynthetic Biofilm Formation

Microbial life on Earth is enormously abundant at sediment-water interfaces. The fossil record in fact contains abundant evidence of the preservation of life on such surfaces. It is therefore critical to our interpretation of early Earth history, and potentially to history of life on other planets, to be able to recognize life forms at these interfaces. On Earth this life often occurs as organized structures of microbes and their extracellular exudates known as biofilms. When such biofilms occur in areas receiving sunlight photosynthetic biofilms are the dominant form in natural ecosystems due to selective advantage inherent in their ability to utilize solar energy. Cyanobacteria are the dominant phototrophic microbes in most modern and ancient photosynthetic biofilms, microbial mats and stromatolites. Due to their long (3.5 billion year) evolutionary history, this group has extensively diversified resulting in an enormous array of morphologies and physiological abilities. This enormous diversity and specialization results in very specific selection for a particular cyanobacterium in each available photosynthetic niche. Furthermore these organisms can alter their spatial orientation, cell morphology, pigmentation and associations with heterotrophic organisms in order to fine tune their optimization to a given micro-niche. These adaptations can be detected, and if adequate knowledge of the interaction between environmental conditions and organism response is available, the detectable organism response can be used to infer the environmental conditions causing that response. This presentation will detail two specific examples which illustrate this point. Light and water are essential to photosynthesis in cyanobacteria and these organisms have specific detectable behavioral responses to these parameters. We will present cyanobacterial responses to quantified flow and irradiance to demonstrate the interpretative power of distribution and orientation information. This study presents new results, but many such examples are already found in the literature. However this information exists in such a wide variety of journals, spanning decades of research that the utility of the vast storehouse of information is limited, not by the ability of cyanobacteria to respond in recognizable ways to environmental stimuli, but by our ability to compile and use this information. Recent advances in information technology will soon allow us to overcome these difficulties and utilize the detailed responses of cyanobacteria to environmental microniches as powerful records of the interaction between the biosphere and lithosphere.

Prufert-Bebout, Lee↗
DOE OSTI2021

Italian prototype building models for urban scale building performance simulation

Urban building energy modeling (UBEM) seeks to evaluate strategies to optimize building energy use at urban scale to support a city's building energy goals. Prototype building models are usually developed to represent typical urban building characteristics of a specific use type, construction year, and climate zone, as detailed characteristics of individual buildings at urban scale are difficult to obtain. This study investigated the Italian building stock, developing 46 building prototypes, based on construction year, for residential and office buildings. The study included 16 single-family buildings, 16 multi-family buildings, and 14 office buildings. Building envelope properties and heating, ventilation, and air conditioning system characteristics were defined according to existing building energy codes and standards for climatic zone E, which covers about half the Italian municipalities. Novel contributions of this study include (1) detailed specifications of prototype building energy models for Italian residential and office buildings that can be adopted by UBEM tools, and (2) a dataset in GeoJSON format of Italian urban buildings compiled from diverse data sources and national standards. Finally, the developed prototype building specifications, the building dataset, and the workflow can be applied to create other building prototypes and to support Italian national building energy efficiency and environmental goals.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Gleipnir: toward practical error analysis for Quantum programs

Practical error analysis is essential for the design, optimization, and evaluation of Noisy Intermediate-Scale Quantum(NISQ) computing. However, bounding errors in quantum programs is a grand challenge, because the effects of quantum errors depend on exponentially large quantum states. In this work, we present Gleipnir, a novel methodology toward practically computing verified error bounds in quantum programs. Gleipnir introduces the (ρ,δ)-diamond norm, an error metric constrained by a quantum predicate consisting of the approximate state ρ and its distance δ to the ideal state ρ. This predicate (ρ,δ) can be computed adaptively using tensor networks based on the Matrix Product States. Gleipnir features a lightweight logic for reasoning about error bounds in noisy quantum programs, based on the (ρ,δ)-diamond norm metric. Furthermore, our experimental results show that Gleipnir is able to efficiently generate tight error bounds for real-world quantum programs with 10 to 100 qubits, and can be used to evaluate the error mitigation performance of quantum compiler transformations.

Tao, Runzhou↗
DOE OSTI2024

Towards reverse mode automatic differentiation of Kokkos-based codes

Derivative computation is a key component of optimization, sensitivity analysis, uncertainty quantification, and the solving of nonlinear problems. Automatic differentiation (AD) is a powerful technique for evaluating such derivatives, and in recent years, has been integrated into programming environments such as Jax, PyTorch, and TensorFlow to support derivative computations needed for training of machine learning models, facilitating wide-spread use of these technologies. The C++ language has become the de facto standard for scientific computing due to numerous factors, yet language complexity has made the wide-spread adoption of AD technologies for C++ difficult, hampering the incorporation of powerful differentiable programming approaches into C++ scientific simulations. This is exacerbated by the increasing emergence of architectures, such as GPUs, with limited memory capabilities and requiring massive thread-level concurrency. C++ AD tools must effectively use these environments to bring novel scientific simulations to next-generation DOE experimental and observational facilities. In this project, we investigated source transformation-based automatic differentiation using LLVM compiler infrastructure to automatically generate portable and efficient gradient computations of Kokkos-based code. We have demonstrated that our proposed strategy is feasible by investigating the usage of a prototype LLVM-based source transformation tool to generate gradients of simple functions made of sequences of simple Kokkos parallel regions. Speedups of up to 500x compared to Sacado were observed on NVIDIA V100 GPU.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Assessing hydrogen supply chains: An integrated review of leakage and energy efficiency studies

This paper examines hydrogen leakage and efficiency across the supply chain for liquid, gaseous, and mixed hydrogen systems. These factors are crucial for assessing hydrogen's role in mitigating emissions and facilitating a clean energy transition. Drawing on a comprehensive review of existing literature and model-based analysis, the study compiles leakage rates and efficiency metrics at each stage of the supply chain: production, storage, transmission, distribution, and end-use. These data inform system scenarios that estimate the impact of leakage on overall performance and climate benefits. The analysis also identifies persistent data gaps, particularly for liquid and mixed system configurations, and outlines priorities for future research. A comparison of hydrogen system types shows that gaseous pathways generally achieve the highest efficiencies (28 %–39 %) and the lowest leakage rates (∼4.5 %) across the supply chain. Liquid hydrogen systems, while favorable for long-distance and high-volume transport due to their higher energy density, exhibit lower efficiency (∼28 %) and a greater leakage potential (∼12 %). Mixed systems, which combine gaseous and liquid elements (e.g., pipeline transmission followed by liquefaction and truck distribution), show compounded energy losses and moderate-to-high leakage rates (6.8 %–9.4 %), highlighting trade-offs associated with added system complexity. The study highlights opportunities for technological advancements, including optimizing liquefaction, enhancing insulation for storage and transportation, and refining refueling equipment. These improvements are crucial for maximizing the climate benefits of hydrogen. The results offer actionable insights for researchers, industry, and policymakers working to develop low-leakage, high-efficiency hydrogen infrastructure.

08 HYDROGEN↗
NASA NTRSDate not supplied

Assessing Crew Medical Officer Preparedness for International Space Station Missions

INTRODUCTION Astronaut crew medical officers (CMO) undergo additional, specialized training to provide medical support onboard the International Space Station (ISS). CMO training focuses on utilizing resources on-station and optimizing communication with ground-based expertise to manage both common minor conditions as well as emergency/trauma situations. As NASA moves towards future Artemis and exploration class missions, we sought CMO perspectives on past, present, and future CMO training and medical resourcing to help inform mission planners regarding medical risk mitigation considerations. We present an interview-based qualitative assessment of CMO preparedness for the International Space Station with the aim to help iterate future training flows for Low Earth Orbit, Artemis, and exploration-class missions. METHODS A semi-structured interview tool was developed to assess CMO experience and their recommendations for future mission training considerations. Participants were recruited from former or current US astronauts who were designated as CMO and subsequently flew to the International Space Station. 10 former CMOs took part in the study. Interview transcripts were deidentified and evaluated for qualitative thematic analysis by two independent coders with NVivo Software suite (Lumivero, Denver, CO), and emergent themes were compiled. RESULTS Former CMO crew expressed appropriate preparedness for current ISS medical capabilities and requirements. They identified the role of the CMO as serving as a healthcare extender to ground-based flight surgeons for ISS and other LEO missions. Individuals with prior medical experience were preferred though not felt to be necessary for LEO missions. For exploration class missions with limitations in ground communication, a physician-as-CMO and more rigorous training curricula for both the CMO and astronaut crew were desired. DISCUSSION Former NASA astronaut crew were interviewed to retrospectively assess their preparedness as ISS crew medical officers and hypothesize future medical knowledge, skill, and ability needs. Along with medical operations subject matter expert opinion and advanced probabilistic risk assessment modeling, past CMO experience can help inform future CMO training considerations and responsibilities for future Artemis and exploration class missions.

M A Labarbera↗
DOE OSTI2021

Quantum Divide and Compute: Exploring the Effect of Different Noise Sources

Abstract Our recent work (Ayral et al. in Proceedings of IEEE computer society annual symposium on VLSI, ISVLSI, pp 138–140, 2020. 10.1109/ISVLSI49217.2020.00034 ) showed the first implementation of the Quantum Divide and Compute (QDC) method, which allows to break quantum circuits into smaller fragments with fewer qubits and shallower depth. This accommodates the limited number of qubits and short coherence times of quantum processors. This article investigates the impact of different noise sources—readout error, gate error and decoherence—on the success probability of the QDC procedure. We perform detailed noise modeling on the Atos Quantum Learning Machine, allowing us to understand tradeoffs and formulate recommendations about which hardware noise sources should be preferentially optimized. We also describe in detail the noise models we used to reproduce experimental runs on IBM’s Johannesburg processor. This article also includes a detailed derivation of the equations used in the QDC procedure to compute the output distribution of the original quantum circuit from the output distribution of its fragments. Finally, we analyze the computational complexity of the QDC method for the circuit under study via tensor-network considerations, and elaborate on the relation the QDC method with tensor-network simulation methods.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2009

Roadmaps and Strategies for Crop Research for Bioregenerative Life Support Systems A Compilation of Findings from NASA’s Advanced Life Support Meetings

Extensive testing with plants for bioregenerative life support systems has been conducted by NASA for nearly 40 years, both through university grants and work at NASA field centers. During this time, numerous meetings were held to develop strategies and roadmaps for implementing bioregenerative life support systems. Findings from several of these meetings are summarized in this report. In nearly all cases, the recommendations included an active ground-based research program and integration tests with other life support subsystems, followed by eventual spaceflight testing. The most recent roadmap of NASA’s Exploration Life Support Crop Element suggests a sequence of first developing a modular vegetable production unit (VPU) to provide perishable foods to supplement the crew’s diet. A similar system could then be used on the lunar surface, with additional modules added as the lunar outpost expands. Eventually, these modules could be transferred to a dedicated pressurized logistics module (PLM) for crop production. Experience from the lunar tests could then be used to conduct a similar buildup for Mars missions, where in situ food production and bioregeneration would be important for achieving outpost autonomy. To date, most trade studies of bioregenerative life support systems indicate that reducing the costs associated with crop lighting systems are key, and use of light-emitting diodes (LEDs) or direct solar lighting offers promising options. Likewise, sustaining high yields and high harvest index (% edible biomass) will be important for minimizing costs, and this can be achieved by optimizing growth environments and through selecting, breeding, and genetically engineering crops suitable for space environments. Collectively, these strategies and roadmaps suggest that a combined approach of fundamental research, hardware (plant chamber) development, and operational testing is required to achieve reliable bioregenerative life support systems.

Bioregenerative↗
DOE OSTI2024

Plastic additives in the ocean: Use of a comprehensive dataset for meta-analysis and method development

In excess of 13,000 chemicals are added to plastics (‘additives’) to improve performance, durability, and production of plastic products. They are categorized into numerous chemical classes including flame retardants, light stabilizers, antioxidants, and plasticizers. While research on plastic additives in the marine environment has increased over the past decade, there is a lack of methodological standardization. To direct future measurement of plastic additives, we compiled a first-of-its-kind dataset of literature assessing plastic additives in marine environments, delineated by sample type (plastic debris, seawater, sediment, biota). Using this dataset, we performed a meta-analysis to summarize the state of the science. Currently, our dataset includes 217 publications published between 1978 and May 2023. The majority of publications analyzed plastic additives in biota collected from Europe and Asia. Analyses concentrated on plasticizers, brominated flame retardants, and bisphenols. Common sample preparation techniques included Solvent - Agitation extraction for plastic, sediment, and biota samples, and Solid Phase Extraction for seawater samples with dichloromethane and solvent mixtures including dichloromethane as the organic extraction solvent. Finally, most analyses were performed utilizing gas chromatography/mass spectrometry. There are a variety of data gaps illuminated by this meta-analysis, most notably the small number of compounds that have been targeted for detection compared to the large number of additives used in plastic production. The provided dataset facilitates future investigation of trends in plastic additive concentration data in the marine environment (allowing for comparison to toxicity thresholds) and acts as a starting point for optimizing and harmonizing plastic additive analytical methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1996

1996 Coolant Flow Management Workshop

The following compilation of documents includes a list of the 66 attendees, a copy of the viewgraphs presented, and a summary of the discussions held after each session at the 1996 Coolant Flow Management Workshop held at the Ohio Aerospace Institute, adjacent to the NASA Lewis Research Center, Cleveland, Ohio on December 12-13, 1996. The workshop was organized by H. Joseph Gladden and Steven A. Hippensteele of NASA Lewis Research Center. Participants in this workshop included Coolant Flow Management team members from NASA Lewis, their support service contractors, the turbine engine companies, and the universities. The participants were involved with research projects, contracts and grants relating to: (1) details of turbine internal passages, (2) computational film cooling capabilities, and (3) the effects of heat transfer on both sides. The purpose of the workshop was to assemble the team members, along with others who work in gas turbine cooling research, to discuss needed research and recommend approaches that can be incorporated into the Center's Coolant Flow Management program. The workshop was divided into three sessions: (1) Internal Coolant Passage Presentations, (2) Film Cooling Presentations, and (3) Coolant Flow Integration and Optimization. Following each session there was a group discussion period.

Steven A. Hippensteele↗
DOE OSTI2021

Spatial biases of information influence global estimates of soil respiration: how can we improve global predictions?

Soil respiration (Rs), the efflux of CO2 from soils to the atmosphere, is a major component of the terrestrial carbon cycle, but is poorly constrained from regional to global scales. The global soil respiration database (SRDB) is a compilation of in-situ Rs observations from around the globe that has been consistently updated with new measurements over the past decade. It is unclear whether the addition of data to new versions of the SRDB has produced better-constrained global Rs estimates. We compared two versions of the SRDB (v3.0 n=5173 and v5.0 n=10366) to determine how additional data influenced the global sum and uncertainty of Rs as predicted by a quantile regression forest model. A model parameterized using SRDBv3 yielded a global Rs sum of 88.6 Pg C yr-1, and associated uncertainty of 29.9 (mean absolute error) and 57.9 (standard deviation) Pg C yr-1, whereas parameterization using SRDBv5 yielded 96.5 Pg C yr-1 and associated uncertainty of 30.2 (mean average error) and 73.4 (standard deviation) Pg C yr-1. Empirically estimated global heterotrophic respiration (Rh) from v3 and v5 were 49.9-50.2 (mean 50.1) and 53.3-53.5 (mean 53.4) Pg C yr-1, respectively. Interestingly, SRDBv5’s inclusion of new data from underrepresented regions (e.g., Asia, Africa, South America) thus resulted in overall higher model uncertainty. The SRDBv5 is still biased towards northern latitudes and temperate zones, so we tested that an optimized global distribution of Rs measurements resulted in a global sum of 96.4 ± 21.4 Pg C yr-1 and lower model uncertainty. These results support current global estimates of Rs but highlight spatial inconsistencies that influence model parameterization and interpretation that should be addressed to improve regional- to global-scale predictions.

Stell, Emma↗
NASA NTRS2007

ISHM Anomaly Lexicon for Rocket Test

Integrated Systems Health Management (ISHM) is a comprehensive capability. An ISHM system must detect anomalies, identify causes of such anomalies, predict future anomalies, help identify consequences of anomalies for example, suggested mitigation steps. The system should also provide users with appropriate navigation tools to facilitate the flow of information into and out of the ISHM system. Central to the ability of the ISHM to detect anomalies is a clearly defined catalog of anomalies. Further, this lexicon of anomalies must be organized in ways that make it accessible to a suite of tools used to manage the data, information and knowledge (DIaK) associated with a system. In particular, it is critical to ensure that there is optimal mapping between target anomalies and the algorithms associated with their detection. During the early development of our ISHM architecture and approach, it became clear that a lexicon of anomalies would be important to the development of critical anomaly detection algorithms. In our work in the rocket engine test environment at John C. Stennis Space Center, we have access to a repository of discrepancy reports (DRs) that are generated in response to squawks identified during post-test data analysis. The DR is the tool used to document anomalies and the methods used to resolve the issue. These DRs have been generated for many different tests and for all test stands. The result is that they represent a comprehensive summary of the anomalies associated with rocket engine testing. Fig. 1 illustrates some of the data that can be extracted from a DR. Such information includes affected transducer channels, narrative description of the observed anomaly, and the steps used to correct the problem. The primary goal of the anomaly lexicon development efforts we have undertaken is to create a lexicon that could be used in support of an associated health assessment database system (HADS) co-development effort. There are a number of significant byproducts of the anomaly lexicon compilation effort. For example, (1) Allows determination of the frequency distribution of anomalies to help identify those with the potential for high return on investment if included in automated detection as part of an ISHM system, (2) Availability of a regular lexicon could provide the base anomaly name choices to help maintain consistency in the DR collection process, and (3) Although developed for the rocket engine test environment, most of the anomalies are not specific to rocket testing, and thus can be reused in other applications.

Schmalzel, John L.↗
NASA NTRS1998

Integrated Task And Data Parallel Programming: Language Design

his research investigates the combination of task and data parallel language constructs within a single programming language. There are an number of applications that exhibit properties which would be well served by such an integrated language. Examples include global climate models, aircraft design problems, and multidisciplinary design optimization problems. Our approach incorporates data parallel language constructs into an existing, object oriented, task parallel language. The language will support creation and manipulation of parallel classes and objects of both types (task parallel and data parallel). Ultimately, the language will allow data parallel and task parallel classes to be used either as building blocks or managers of parallel objects of either type, thus allowing the development of single and multi-paradigm parallel applications. 1995 Research Accomplishments In February I presented a paper at Frontiers '95 describing the design of the data parallel language subset. During the spring I wrote and defended my dissertation proposal. Since that time I have developed a runtime model for the language subset. I have begun implementing the model and hand-coding simple examples which demonstrate the language subset. I have identified an astrophysical fluid flow application which will validate the data parallel language subset. 1996 Research Agenda Milestones for the coming year include implementing a significant portion of the data parallel language subset over the Legion system. Using simple hand-coded methods, I plan to demonstrate (1) concurrent task and data parallel objects and (2) task parallel objects managing both task and data parallel objects. My next steps will focus on constructing a compiler and implementing the fluid flow application with the language. Concurrently, I will conduct a search for a real-world application exhibiting both task and data parallelism within the same program m. Additional 1995 Activities During the fall I collaborated with Andrew Grimshaw and Adam Ferrari to write a book chapter which will be included in Parallel Processing in C++ edited by Gregory Wilson. I also finished two courses, Compilers and Advanced Compilers, in 1995. These courses complete my class requirements at the University of Virginia. I have only my dissertation research and defense to complete.

Grimshaw, Andrew S.↗
NASA NTRS1998

Integrated Task and Data Parallel Programming

This research investigates the combination of task and data parallel language constructs within a single programming language. There are an number of applications that exhibit properties which would be well served by such an integrated language. Examples include global climate models, aircraft design problems, and multidisciplinary design optimization problems. Our approach incorporates data parallel language constructs into an existing, object oriented, task parallel language. The language will support creation and manipulation of parallel classes and objects of both types (task parallel and data parallel). Ultimately, the language will allow data parallel and task parallel classes to be used either as building blocks or managers of parallel objects of either type, thus allowing the development of single and multi-paradigm parallel applications. 1995 Research Accomplishments In February I presented a paper at Frontiers 1995 describing the design of the data parallel language subset. During the spring I wrote and defended my dissertation proposal. Since that time I have developed a runtime model for the language subset. I have begun implementing the model and hand-coding simple examples which demonstrate the language subset. I have identified an astrophysical fluid flow application which will validate the data parallel language subset. 1996 Research Agenda Milestones for the coming year include implementing a significant portion of the data parallel language subset over the Legion system. Using simple hand-coded methods, I plan to demonstrate (1) concurrent task and data parallel objects and (2) task parallel objects managing both task and data parallel objects. My next steps will focus on constructing a compiler and implementing the fluid flow application with the language. Concurrently, I will conduct a search for a real-world application exhibiting both task and data parallelism within the same program. Additional 1995 Activities During the fall I collaborated with Andrew Grimshaw and Adam Ferrari to write a book chapter which will be included in Parallel Processing in C++ edited by Gregory Wilson. I also finished two courses, Compilers and Advanced Compilers, in 1995. These courses complete my class requirements at the University of Virginia. I have only my dissertation research and defense to complete.

Grimshaw, A. S.↗
NASA NTRSDate not supplied

DLES Unreal Simulation Tool (DUST)

NASA’s future Artemis missions to the Moon seek to explore areas around the Lunar South Pole. Though humans have previously set foot on the lunar surface, the proposed region provides unique and challenging environments that require insight and investigation prior to arrival. Several teams throughout the agency are performing this site and mission planning, design, and analysis to support areas like the Human Landing System (HLS), surface mobility, habitation elements, and scientific exploration. The NASA Exploration Systems Simulation (NExSyS) team at Johnson Space Center is developing a graphical environment of the Lunar South Pole region. Lunar terrain information collected from the Lunar Reconnaissance Orbiter (LRO) is compiled and made available through Johnson Space Center’s Digital Lunar Exploration Sites (DLES) data sets. The DLES data is used to build this graphic environment. The process of ingesting and accurately modeling this information in a meaningful way for analysis creates its own challenges such as generating a performant model from the source data and the application of curvature. Additionally, the area around the Lunar South Pole experiences different lighting conditions than those observed from the Apollo missions. The need to use the lunar environmental data products provided by DLES combined with the capability to calculate date specific ephemerides in real-time has given rise to the development of the DLES Unreal Simulation Tool (DUST). DUST incorporates augmented terrain from the DLES product into a desktop application that allows exploration of the Lunar South Pole region and its complex lighting conditions. DUST leverages advanced capabilities in the recently released Unreal Engine 5 renderer by Epic Games such as double precision for positioning of planetary bodies and surface elements, multiple infinite light sources to represent the Sun and eventually Earthshine, high resolution shadow maps for dynamic shadow accuracy, real-time software ray-tracing for multi-surface bounce lighting to render sunlight reflected off surface elements and terrain features, and performance optimized level of detail shifting as the eyepoint changes in a scene. This paper details the DUST application, the technologies of the engine platform that enable scientific and engineering analysis, the unique techniques and processes developed to consume the DLES data sets, and how the tool is being used to support the Artemis program.

Lunar Visualization↗
NASA NTRS2010

Trajectory Optimization: OTIS 4

The latest release of the Optimal Trajectories by Implicit Simulation (OTIS4) allows users to simulate and optimize aerospace vehicle trajectories. With OTIS4, one can seamlessly generate optimal trajectories and parametric vehicle designs simultaneously. New features also allow OTIS4 to solve non-aerospace continuous time optimal control problems. The inputs and outputs of OTIS4 have been updated extensively from previous versions. Inputs now make use of objectoriented constructs, including one called a metastring. Metastrings use a greatly improved calculator and common nomenclature to reduce the user s workload. They allow for more flexibility in specifying vehicle physical models, boundary conditions, and path constraints. The OTIS4 calculator supports common mathematical functions, Boolean operations, and conditional statements. This allows users to define their own variables for use as outputs, constraints, or objective functions. The user-defined outputs can directly interface with other programs, such as spreadsheets, plotting packages, and visualization programs. Internally, OTIS4 has more explicit and implicit integration procedures, including high-order collocation methods, the pseudo-spectral method, and several variations of multiple shooting. Users may switch easily between the various methods. Several unique numerical techniques such as automated variable scaling and implicit integration grid refinement, support the integration methods. OTIS4 is also significantly more user friendly than previous versions. The installation process is nearly identical on various platforms, including Microsoft Windows, Apple OS X, and Linux operating systems. Cross-platform scripts also help make the execution of OTIS and post-processing of data easier. OTIS4 is supplied free by NASA and is subject to ITAR (International Traffic in Arms Regulations) restrictions. Users must have a Fortran compiler, and a Python interpreter is highly recommended.

Riehl, John P.↗
DOE OSTI2023

Short-Depth QAOA circuits and Quantum Annealing on Higher-Order Ising Models (Rev.2)

The Quantum Alternating Operator Ansatz (QAOA) and Quantum Annealing (QA) are quantum algorithms that are both based on the adiabatic theorem and both have the goal of sampling the optimal solution(s) of combinatorial optimization problems. Quantum annealing has been physically instantiated on D-Wave devices using superconducting flux qubits, and QAOA can be programmed on digital gate-model quantum computers such as the programmable superconducting transmon qubits devices of the IBMQ series, for instance ibm washington. QAOA and QA address the same types of problems, but it is unclear how they will scale to large problem sizes and to larger and higher-fidelity quantum computers. In this article, we present a direct comparison between QAOA, one and two rounds, run on all 127 qubits of ibm washington and QA run on D-Wave Advantage system4.1 and Advantage system6.1. The problems which allow for this comparison are random Ising model problems whose connectivity matches the heavy hexagonal lattice topology of ibm washington and the Pegasus graph connectivity of the two D-Wave devices. We create two classes of problem instances for this comparison: one with higher order terms (ZZZ variable interactions), linear terms, and quadratic terms, and a separate problem type with only linear and quadratic terms. Our QAOA circuits are novel and extremely short depth, with a CNOT depth of 6 per round, which allows whole chip usage of ibm washington’s heavy hexagonal lattice and can be applied to future heavy-hex chips. We also test the effectiveness of the error suppression technique digital dynamical decoupling on the QAOA circuits. The QAOA circuits compiled to ibm washington are composed of several thousand circuit instructions, approximately 3, 000 depending on the details of the circuit, making these some the largest quantum circuits ever executed on a digital quantum processor. QAOA and QA are compared against the classical heuristic algorithm of simulated annealing and all problem instances are exactly solved using CPLEX in order to evaluate which samplers, if any, correctly found the ground state solution(s) of the problem instances. We find that (i) QA outperforms QAOA on all problem instances, (ii) QAOA samples the problems better than random sampling, and (iii) QAOA angle computation exhibits clear parameter concentration across the ensemble of Ising models.

127 Qubits↗
DOE OSTI2022

Data for Determining Spatially Varying Profit-Maximizing Management Practices for Miscanthus and Switchgrass Production in the Rainfed United States

The compiled datasets include county-level variables used for simulating miscanthus and switchgrass production in 2287 counties across the rainfed US including 5-year (2012-2016) averaged growing season degree days (GDD), 5-year (2012-2016) averaged growing season cumulative precipitation, National Commodity Crop Productivity Index (NCCPI) values, regional dummies (only for miscanthus), the regional-level random effect of the yield response function, N price, land cash rent, the first year fixed cost (only for switchgrass), and separate datasets for simulating an alternative model assuming a constant N rate. The GAMS codes are used to run the simulation to obtain the main results including the age-varying profit-maximizing N rate, biomass yields, and annual profits for miscanthus and switchgrass production across counties in the rainfed US. The STATA codes are used to merge and analyze simulation results and create summary statistics tables and key figures.

Age↗