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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Preliminary Results on Bayesian Inverse UQ for OECD/NEA WPNCS Subgroup 14 Benchmark Exercise for Error Recovery and Experimental Coverage

The Organization for Economic Cooperation and Development (OECD) Working Party on Nucelar Criticality Safety (WPNCS) has proposed a benchmark exercise representative of neutronic behavior in criticality experiments. Here, the goal is to develop confidence in data assimilation techniques used to adjust nuclear data. Participants are given synthetic experimental models with associated measured data and asked to estimate the model parameters given the model and measurements as well as provide predictions for separate application models. In this work, we performed data assimilation using Bayesian inverse Uncertainty Quantification (UQ) with machine learning surrogate models to produce posterior parameter distributions for the requested parameters and posterior predictive distributions for the requested responses. Several experimental models are shown to insufficiently inform the posterior parameter distributions for the applications involved. However, given sufficient experimental data, posterior parameter estimates yielded reduced uncertainty in the response predictions of interest while covering the experimental data.

Bayesian Inference↗
DOE OSTI2024

SQMS Quantum R&D in Machine Learning, Optimization and Sensing beyond Fundamental Physics Applications

This newly formed team at SQMS under the Ecosystem Thrust is looking to develop capabilities impacting societal advances outside the core domain of HEP and condensed matter physics. We explicitly leverage the experimental and algorithmic innovations developed across all groups as well as connect to broad-scope external projects of the diverse team of PIs. As the inaugural set of projects, we are studying numerically quantum machine learning models inspired by efficiently trainable echo-state and orthogonal neural networks and developing designs for related experiments to be performed on quantum processors based on SQMS SRF cQED technology and Rigetti s transmon arrays. Investigated models exploit ideas and lessons learned from multiple prior work by SQMS team members in a variety of internal and external activities [R1]. Target initial applications include noisy signal processing, potentially captured by quantum sensors or noisy QPUs, as well as simulation and classification of healthcare data. For instance, image reconstruction of the brain s electrical properties by solving the inverse Maxwell equation problem with uncertainty [R2] through a hybrid quantum-classical physics-informed architecture for time-dependent processes [R3]. The group is also investigating the application and development of novel quantum sensors based on magnetic levitation of a superconducting sphere coupled to a superconducting qubit. This coupling enables high-precision measurements of the position of the sphere, which can be used for sensitive detection of forces, enabling practical applications such as gravimetry for geophysics analysis, or accelerometry for GPS-denied navigation [R4] [R1] Rieffel, Eleanor G., Ata Akbari Asanjan, M. Sohaib Alam, Namit Anand, David E. Bernal Neira, Sophie Block, Lucas T. Brady et al. "Assessing and advancing the potential of quantum computing: A NASA case study." Future Generation Computer Systems (2024). [R2] Yu, X., Serrall s, J.E., Giannakopoulos, I.I., Liu, Z., Daniel, L., Lattanzi, R. and Zhang, Z., 2023. Pifon-ept: Mr-based electrical property tomography using physics-informed fourier networks. IEEE Journal on Multiscale and Multiphysics Computational Techniques. [R3] Wudarski, Filip, Daniel OConnor, Shaun Geaney, Ata Akbari Asanjan, Max Wilson, Elena Strbac, P. Aaron Lott, and Davide Venturelli. "Hybrid quantum-classical reservoir computing for simulating chaotic systems." arXiv preprint arXiv:2311.14105 (2023). [R4] Higgins, Gerard, Saarik Kalia, and Zhen Liu. "Maglev for dark matter: Dark-photon and axion dark matter sensing with levitated superconductors." Physical Review D 109.5 (2024): 055024.

Venturelli, Davide↗
DOE OSTI2023

Mycosynthesis of Zinc Oxide Nanoparticles Exhibits Fungal Species Dependent Morphological Preference

Filamentous fungi can synthesize a variety of nanoparticles (NPs), a process referred to as mycosynthesis that requires little energy input, do not require the use of harsh chemicals, occurs at near neutral pH, and do not produce toxic byproducts. While NP synthesis involves reactions between metal ions and exudates produced by the fungi, the chemical and biochemical parameters underlying this process remain poorly understood. Here, the role of fungal species and precursor salt on the mycosynthesis of zinc oxide (ZnO) NPs is investigated. This data demonstrates that all five fungal species tested are able to produce ZnO structures that can be morphologically classified into i) well-defined NPs, ii) coalesced/dissolving NPs, and iii) micron-sized square plates. Further, species-dependent preferences for these morphologies are observed, suggesting potential differences in the profile or concentration of the biochemical constituents in their individual exudates. This data also demonstrates that mycosynthesis of ZnO NPs is independent of the anion species, with nitrate, sulfate, and chloride showing no effect on NP production. Finally, these results enhance the understanding of factors controlling the mycosynthesis of ceramic NPs, supporting future studies that can enable control over the physical and chemical properties of NPs formed through this “green” synthesis method.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Uncertainty Quantification of Machine Learning Predicted Creep Property of Alumina-Forming Austenitic Alloys

The development of machine learning (ML) approaches in materials science offers the opportunity to exploit existing engineering and developmental alloy datasets, such as Oak Ridge National Laboratory (ORNL)’s consistently measured creep-rupture dataset for alumina-forming austenitic (AFA) alloys, to accelerate their further development. As a first step toward achieving ML insights for improved alloy design, the potential sources of uncertainty and their impacts on ML output are examined. It is observed that the selection of algorithms and features as well as data sampling significantly affects the performance of ML models, either positively or negatively. Further, the performance of various ML models in predicting the creep properties of AFA alloys is compared, with further evaluation by assessment of a small set of new developmental AFA alloys that were not part of the training dataset. The present study demonstrates that uncertainty quantification (UQ) is essential in materials science for evaluating the performance of ML algorithms with specifically selected feature sets and obtaining a comprehensive understanding of their limitations and the resultant capability of effective prediction in complex materials systems.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Appendices for Geothermal Exploration Artificial Intelligence Report

The Geothermal Exploration Artificial Intelligence looks to use machine learning to spot geothermal identifiers from land maps. This is done to remotely detect geothermal sites for the purpose of energy uses. Such uses include enhanced geothermal system (EGS) applications, especially regarding finding locations for viable EGS sites. This submission includes the appendices and reports formerly attached to the Geothermal Exploration Artificial Intelligence Quarterly and Final Reports. The appendices below include methodologies, results, and some data regarding what was used to train the Geothermal Exploration AI. The methodology reports explain how specific anomaly detection modes were selected for use with the Geo Exploration AI. This also includes how the detection mode is useful for finding geothermal sites. Some methodology reports also include small amounts of code. Results from these reports explain the accuracy of methods used for the selected sites (Brady Desert Peak and Salton Sea). Data from these detection modes can be found in some of the reports, such as the Mineral Markers Maps, but most of the raw data is included the DOE Database which includes Brady, Desert Peak, and Salton Sea Geothermal Sites.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Harold Agnew’s son gives Lab never-before-seen photos, documents

When I arrived at Los Alamos in 2003, the Laboratory’s long-retired third director was still a very popular figure. He was so popular, in fact, that he enjoyed an honor typically reserved for only the most adored and outrageous pop stars and Brazilian footballers: He was known by one name. Back then, most Lab staff knew exactly who you were talking about when you referred to “Harold.” Harold Agnew was at the helm from 1970 – 1979, though his career here began when he was still just in his 20s. He was recruited to work on the U.S. government’s top-secret project to build the first atomic bombs and help bring a swift end to World War II. Harold died in 2013 at 92, but March 28 would have been his 100th birthday. Although he’s no longer here to celebrate with us, we can gain inspiration by remembering his remarkable life of service – and mischief. Both are now well-documented in the collections of the National Security Research Center (NSRC), the Lab’s classified library, which also includes unclassified pieces of our history. The NSRC’s newest addition to its collections comes from Harold’s son John Agnew, who just recently gave me a box of about 250 images and about 15 documents that belonged to his dad. The contents are nothing short of remarkable, one-of-a-kind, and in some cases, hilarious. As the NSRC staff are accessioning these pieces into the Lab’s collections, looking through these materials is a chance for me to remember our former director and my friend.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2021

Crowdsourcing biocuration: The Community Assessment of Community Annotation with Ontologies (CACAO)

Experimental data about gene functions curated from the primary literature have enormous value for research scientists in understanding biology. Using the Gene Ontology (GO), manual curation by experts has provided an important resource for studying gene function, especially within model organisms. Unprecedented expansion of the scientific literature and validation of the predicted proteins have increased both data value and the challenges of keeping pace. Capturing literature-based functional annotations is limited by the ability of biocurators to handle the massive and rapidly growing scientific literature. Within the community-oriented wiki framework for GO annotation called the Gene Ontology Normal Usage Tracking System (GONUTS), we describe an approach to expand biocuration through crowdsourcing with undergraduates. This multiplies the number of high-quality annotations in international databases, enriches our coverage of the literature on normal gene function, and pushes the field in new directions. From an intercollegiate competition judged by experienced biocurators, Community Assessment of Community Annotation with Ontologies (CACAO), we have contributed nearly 5,000 literature-based annotations. Many of those annotations are to organisms not currently well-represented within GO. Over a 10-year history, our community contributors have spurred changes to the ontology not traditionally covered by professional biocurators. The CACAO principle of relying on community members to participate in and shape the future of biocuration in GO is a powerful and scalable model used to promote the scientific enterprise. It also provides undergraduate students with a unique and enriching introduction to critical reading of primary literature and acquisition of marketable skills.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Managing Solar Photovoltaic Integration in the Western United States Appendix: Reference and High Solar Photovoltaic Scenarios for Three Regions [Slides]

This slide deck is an appendix to a paper series that examines potential challenges related to planning future power systems with higher solar photovoltaic (PV) penetrations. The series uses the western U.S. power system for these investigations because it is a region the authors and their colleagues have already extensively studied. We are therefore well-suited to analyze even higher PV penetrations and then examine the results in multiple models to determine whether our current approaches are missing key details that only emerge at higher PV penetrations. This deck details the systems underlying those analyses and how they were modeled using the Resource Planning Model (RPM), a capacity expansion modeling tool. We examine both Western Interconnection-wide and regional results for three regions in the Western U.S. with significantly different existing power systems and connections to neighboring regions; this provides a more balanced picture as to how power systems with high PV penetration might emerge in different contexts and what the resulting grid challenges, if any, might be.

14 SOLAR ENERGY↗
DOE OSTI2020

Managing Solar Photovoltaic Integration in the Western United States: Power System Flexibility Requirements and Supply

As penetrations of variable renewable energy generation technologies such as wind and solar photovoltaics (PV) continue to increase across the United States, greater uncertainty and variability in the net load often lead to a concern about how power systems may adapt. Managing the system net load (i.e., load minus contribution from variable generation technologies) may become more challenging with increasing variable generation, as the magnitude and frequency of net ramps increase. However, there is inherent flexibility in power systems through the conventional generator fleet (under least-cost unit commitment and economic dispatch), less-conventional generation sources (e.g., storage, demand response, concentrating solar power with thermal energy storage), and imports and exports with neighbors. In this analysis, we create an open-source tool to analyze the flexibility of the results of a specific commercial unit commitment and economic dispatch tool (PLEXOS), but the code can be applied generically as well. The tool assesses the flexibility requirements (or demand) of a system through a net load analysis. The constraints and limitations of each generator are then considered to determine the availability (or supply) of flexibility. Then, the supply and demand of flexibility are compared to gain a more complete picture of potential flexibility concerns. We apply this open-source tool to high-penetration PV scenarios constructed for three focus regions in the western United States defined using the Resource Planning Model (RPM) capacity expansion modeling tool: RPM-OR, RPM-CO, and RPM-AZ. Generally, we find few flexibility concerns, as the western United States represents a large and interconnected power system with significant inherent flexibility. In addition, the PV scenarios we analyzed are overbuilt on capacity, leaving plenty of ramping ability on the system. We do find that for each focus region, the impact of imports on meeting ramping needs is essential. This means the PV integration in each focus region impacts the entire rest of the system. Each system has different dominant sources of flexibility. The conventional generator fleet (especially coal and gas combined-cycle technologies) as well as less-conventional sources such as storage are all shown to be important sources of flexibility. The scenarios evaluated here were designed to study the planning and operations impact of high solar penetration in each of three focus regions. However, none of the three focus regions likely will deploy PV in isolation, meaning the ability of imports and exports to provide flexibility may be considerably different in scenarios with strong PV deployment in every region. Overall, we intend that the framework we present here will be useful in future analysis of other system evolutions to identify whether and how flexibility may constrain the successful deployment of variable generation technologies.

14 SOLAR ENERGY↗
DOE OSTI2023

Control coordination in inverter‐based microgrids using AoI‐based 5G schedulers

Abstract A coordinated set point automatic adjustment with correction enabled (C‐SPAACE) framework that uses 5G communication for real‐time control coordination between inverter‐based resources (IBR) in microgrids is proposed. Utilising slicing capability, 5G offers low‐latency communication to C‐SPAACE under normal conditions. However, given the multitude of power grid use cases, a certain 5G slice for C‐SPAACE may have access only to limited radio spectrum resources, which if not managed well, greatly undermines the communication needs of C‐SPAACE framework. Thus, optimally scheduling the available spectrum resources among IBRs in a sliced 5G network‐based C‐SPAACE framework becomes a critical problem. To address this issue, the authors utilise a novel age of information (AoI) metric and designs an AoI‐based 5G scheduler to provide low‐latency communication to C‐SPAACE. Following this, a co‐simulation environment is designed using PSCAD/EMTDC and Python to simulate a microgrid supported by 5G communication. Time‐domain simulation case studies are performed using the proposed co‐simulation environment to evaluate the performance of C‐SPAACE using 5G with both AoI‐based and other baseline (non‐AoI) schedulers.

Choudhury, Biplav↗
DOE OSTI2021

DPC Cement Filler Development (Progress Report)

The fillers research and development (R&D) program, mostly experimental, is part of a broader R&D program that includes new process modeling and performance assessment of criticality effects and the overall importance of criticality to repository performance (consequence screening). A literature research and consultation effort with experts by Hardin and Brady (2018) identified several potentially effective and workable filler materials including cements (primarily phosphate based), moltenmetal alloys, and low-temperature glasses. Filler attributes were defined, and the preliminary lists were compared qualitatively. Further comparative analysis will be done (e.g., cost estimates) after experimental screening has narrowed the list of alternatives. The following cement filler compositions were selected for experimental development work and accelerated testing in FY20: Aluminum phosphate cements (APCs); more specifically aluminum oxide / aluminum phosphate (Al 2 O 3 / AlPO 4 ) cements in which Al 2 O 3 serves as the filler material bound by an AlPO 4 binder formed by the reaction of Al 2 O 3 with H 3 PO 4 ; Calcium phosphate cements (CPCs); more specifically composed of pure or nearly pure hydroxyapatite or HAP (Ca 5 (PO 4 ) 3 (OH)); Wollastonite phosphate cements (WPC), specifically wollastonite and aluminum or calcium aluminum phosphates in which CaSiO 3 serves as the filler material and the phosphate serves as the binder. The FY20 effort focused on the optimization of compositions and subsequent processing of these three materials to achieve dense and well-consolidated monolithic samples with 30 to 40% porosity and permeabilities of 1 millidarcy. At the close of this progress report the aluminum phosphate cements (APCs) and the wollastonite phosphate cements (WPCs) appear to show the most promise for continued development. Less progress has been made with the calcium phosphate cements (CPCs); their slurry viscosities are high (and difficult to measure) and they exhibit relatively short cure times of 2 to 3 hours with concomitant and excessive volatile (e.g. CO 2 ) generation.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Assessing the Interactive Impacts of Energy Efficiency and Demand Response on Power System Costs and Emissions

Utilities are increasingly interested in integrating energy efficiency (EE) and demand response (DR) measures and technologies (as well as other distributed energy resources) as a strategic approach to improve their cost-effectiveness and performance. However, the specific EE and DR features that may be best integrated, the interplay between changing EE and DR resource potential, and resulting utility system impacts are not well understood. We quantify the impacts of EE and DR in isolation and in combination on bulk power system costs and emissions based on changes in generation expansion, transmission expansion, and dispatch patterns. The study methodology mimics utility resource planning and uses more novel techniques to select least-cost generation and transmission capacity from supply-and demand-side resources, as compared to more commonly used utility approaches that only consider supply-side resources. The results identify key EE and DR characteristics affecting each other’s power system value and the most valuable technologies and strategies that can be jointly deployed. We discuss implications for EE and DR cost-effectiveness frameworks, program design, and integrated resource planning.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Of Clouds and Craters: The History of U.S. Nuclear Weapons Testing

“Now!” With that word, the Atomic Age – and the era of nuclear weapons testing – dawned. The advent of World War II’s first irresistible weapon, which had been secretly tested in the New Mexico desert in July 1945, would help hasten the inevitable: complete victory for the Allies. Codenamed Trinity, the test was the first of over a thousand conducted by the United States between 1945 and 1992. Nuclear weapons would change future clashes as well. The looming Cold War, with roots stretching all the way back to 1917, was history’s first conflict between two, major nations armed with nuclear weapons. It is clear the existence of those weapons played an important role in maintaining a tenuous peace between the United States and the Soviet Union; it is also clear nuclear weapons testing played a prominent role in fueling both the arms race and the success of deterrence. Yet, the history of nuclear weapons testing is rarely remembered, even though nuclear tests have been performed in the very recent past. Of the estimated 2,000-plus nuclear tests ever performed, the U.S. is responsible for approximately half. This is the story of U.S. full-scale nuclear weapons testing.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2022

Simulation of high-frequency dissolved oxygen dynamics in a shallow estuary, the Corsica River, Chesapeake Bay

Understanding shallow water biogeochemical dynamics is a challenge in coastal regions, due to the presence of highly variable land-water interface fluxes, tight coupling with sediment processes, tidal dynamics, and diurnal variability in biogeochemical processes. While the deployment of continuous monitoring devices has improved our understanding of high-frequency (12 - 24 hours) variability and spatial heterogeneity in shallow regions, mechanistic modeling of these dynamics has lagged behind conceptual and empirical models. The inherent complexity of shallow water systems is represented in the Corsica River estuary, a small basin within the Chesapeake Bay ecosystem, where abundant monitoring data have been collected from long-term monitoring stations, continuous monitoring sensors, synoptic sensor surveys, and measurements of sediment-water fluxes. A state-of-the-art modeling system, the Semi-implicit Cross-scale Hydroscience Integrated System Model (SCHISM), was applied to the Corsica domain with a high-resolution grid and nutrient loads from the most recent version of the Chesapeake Bay watershed model. The Corsica SCHISM model reproduced observed high-frequency variability in dissolved oxygen, as well as seasonal variability in chlorophyll-a and sediment-water fluxes. Time-series signal analyses using Empirical Model Decomposition and spectral analysis revealed that the diurnal and M2 tide frequencies are the dominant high-frequency modes and physical transport contributes a larger share to dissolved oxygen budgets than biogeochemical processes on an hourly time scale. Heterogeneity and patchiness in dissolved oxygen resulting from phytoplankton distributions and geometry-driven eddies amplify the physical transport effect, and on longer time scales oxygen is controlled more by photosynthesis and respiration. Our simulation demonstrates that interactions among physical and biological dynamics generate complex high-frequency variability in water quality and non-linear reposes to nutrient loading and environmental forcing in shallow water systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Seismic response to paleo-sand dunes in the Nugget Sandstone Formation, southwestern Wyoming

We have analyzed a 3D seismic survey acquired for a carbon sequestration project on top of the Moxa Arch in southwestern Wyoming. We observed a zone of discontinuous reflectors on vertical slices of seismic amplitude volume, whereas, the northwest–southeast lineations were observed on the time slices. We performed a seismic to well tie that suggested that the lineations occur within the Nugget Sandstone. The Nugget Sandstone is an eolian sandstone deposit of Early Jurassic age, deposited as a subtropical dune field, and equivalent to the Navajo Sandstone of southwestern Utah. Petrophysical analysis indicates that the Nugget Sandstone is dominated by clean sandstone (70%–80%), whereas evaporites, including halite and anhydrite, are present in certain zones. Previous outcrop studies on the Navajo Sandstone indicate the wind direction to be predominantly northeast–southwest. Seismic attributes, including coherence and curvature, displayed on stratal slices within the Nugget Sandstone interval indicate the presence of lineations in the northwest–southeast direction with irregular spacing. These lineations are approximately perpendicular to the inferred dominant wind direction. We computed the dominant wind direction from the average azimuth of the lineations as seen on the curvature attribute in the Nugget Sandstone interval. Geological feature: Eolian sand dunes with interdunal evaporites Seismic appearance: Parallel lineations with irregular spacing on seismic attribute horizon slices Alternative interpretations: Canyons at continental slopes; slope failures Features with a similar appearance: Marine bars; contourites Formation: The Nugget Sandstone — equivalent to the Navajo Sandstone Age: Early Jurassic Location: Moxa Arch, Wyoming Seismic data: Obtained by the University of Wyoming with U.S. DOE funding Contributors: Dhruv Agrawal, Brady Lujan, Sumit Verma, Shuvajit Bhattacharya, and Subhashis Mallick Analysis tools: Coherence and curvature attributes; seismic inversion; petrophysical inversion

Geochemistry & Geophysics↗
DOE OSTI2021

Normalizing Flows for Microscopic Many-Body Calculations: An Application to the Nuclear Equation of State

We report that normalizing flows are a class of machine learning models used to construct a complex distribution through a bijective mapping of a simple base distribution. We demonstrate that normalizing flows are particularly well suited as a Monte Carlo integration framework for quantum many-body calculations that require the repeated evaluation of high-dimensional integrals across smoothly varying integrands and integration regions. As an example, we consider the finite-temperature nuclear equation of state. An important advantage of normalizing flows is the ability to build highly expressive models of the target integrand, which we demonstrate enables precise evaluations of the nuclear free energy and its derivatives. Furthermore, we show that a normalizing flow model trained on one target integrand can be used to efficiently calculate related integrals when the temperature, density, or nuclear force is varied. This work will support future efforts to build microscopic equations of state for numerical simulations of supernovae and neutron star mergers that employ state-of-the-art nuclear forces and many-body methods.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Performance of Structural Alloys in Bio-oil Production, Upgrading, and Storage Systems

Selection of corrosion-resistant, cost-effective structural materials for the process and containment vessels required for the production, upgrading, and storage of biomass-derived oils has been the subject of study in our laboratory for many years. The wide variety of biomass resources and the many liquefaction techniques and processing conditions result in products with a broad range of properties and compositions. Here, this paper will address the materials issues in three distinct areas. In production, materials are exposed to temperatures that range from 350 to 550 °C depending upon the process. Generally, austenitic stainless steels have performed reasonably well, although thicker oxide scales and intergranular attack have sometimes been observed. For storage and transport of the bio-oil products, temperatures experienced by the containment materials are not expected to exceed 50 °C. Our studies have shown that most raw bio-oils contain significant concentrations of organic acids, and low-molecular-weight organic acids were quite corrosive to carbon and low alloy steels. For some applications, subsequent processing is required, which includes hydrotreating or co-processing with a petroleum-derived liquid. These processes utilize a catalyst that requires periodic retreatment with a sulfidizing gas, and the exposure to this gas at elevated temperatures can cause appreciable corrosion to the more common austenitic stainless steels. The materials considered most cost-effective and sufficiently corrosion-resistant for each of these environments were identified.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Simultaneous stoquasticity

Stoquastic Hamiltonians play a role in the computational complexity of the local Hamiltonian problem as well as the study of classical simulability. In particular, stoquastic Hamiltonians can be straightforwardly simulated using Monte Carlo techniques. We address the question of whether two or more Hamiltonians may be made simultaneously stoquastic via a unitary transformation. This question has important implications for the complexity of simulating quantum annealing where quantum advantage is related to the stoquasticity of the Hamiltonians involved in the anneal. We find that for almost all problems no such unitary exists and show that the problem of determining the existence of such a unitary is equivalent to identifying if there is a solution to a system of polynomial (in)equalities in the matrix elements of the initial and transformed Hamiltonians. Furthermore, solving such a system of equations is NP-hard. We highlight a geometric understanding of this problem in terms of a collection of generalized Bloch vectors.

97 MATHEMATICS AND COMPUTING↗