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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Sensitive Resources Assessment and Forest Analysis for the Proposed Versatile Test Reactor, Oak Ridge, Tennessee

The US Department of Energy’s (DOE’s) Oak Ridge National Laboratory (ORNL) is a leading institution in advanced materials, supercomputing, neutrons, and nuclear science. As a research laboratory managed by UT-Battelle, LLC for DOE, ORNL has national priorities in energy, security, and scientific discovery that necessitate facility improvements and expansions. DOE is also committed to environmental stewardship. The laboratory is located on the ~32,000-acre (~13,000-ha) Oak Ridge Reservation (ORR), much of which is categorized as a National Environmental Research Park (NERP) and a state Wildlife Management Area. DOE works with the Tennessee Wildlife Resources Agency (TWRA), Tennessee Department of Environment and Conservation (TDEC), US Fish and Wildlife Service (USFWS), US Department of Agriculture, and other agencies to serve as an effective steward of the ORR. Accordingly, project managers must conform to environmental regulations, agreements, and policies at the federal, state, and institutional levels. Per 40 CFR (Code of Federal Regulations) 1508.14, potential effects on research and science education also represent potential effects of federal actions on the NERP, and impacts on, e.g., deer harvest, must be considered on the Oak Ridge Wildlife Management Area when other aspects of the human environment are affected. The United States currently has no fast neutron testing capability to support advanced nuclear research and development. The proposed Versatile Test Reactor (VTR) will take advantage of current investments by the US government and private industry in nuclear reactors to expedite the design and construction process, using proven technology to create a world-class scientific infrastructure. The VTR will take advantage of fast neutrons provided by this proven technology, along with a capability to rapidly insert, conduct, and remove state-of-the-art experiments. An advantage of the VTR is that it can support future innovations in experimental capabilities without modifying the facility. The VTR will support progress in a variety of science and technology areas, including testing and qualification of advanced reactor fuels; testing and qualification of innovative structural materials; testing of innovative components and instruments; validation of advanced modeling and simulation tools; and versatility for future technical missions. Through proven technology, the VTR can take advantage of existing reactor designs and operating experience to reduce the risk, cost, and time for design and construction. The top available resources of DOE laboratories, industry, and universities will be used to expedite reactor design and construction toward developing the scientific infrastructure that affords a strong testing capability that can be sustained over many years. This report summarizes current knowledge of natural and cultural resources primarily within the VTR construction area. At the time of this report, the proposed VTR site design includes a construction area of ~150.4 acres (~69.9 ha), which contains an ~51.3-acre (~20.8-ha) operations area, located within forested natural areas of the ORR. The primary goal of the work presented here was to evaluate potential effects on sensitive resources that might result from development and construction activities associated with VTR. In addition to on-the-ground surveys during spring and summer 2020 by the ORNL Natural Resources Management Program and Aquatic Ecology Group staff, this report makes use of historical (pre-1995) and contemporary (1995 to present) data from additional confirmed sources (e.g., TDEC). Likewise, forest conditions were compiled from a 2011 forest inventory and supplemented with limited ground observations in 2020. The individuals who obtained and compiled the data presented here are familiar with and routinely assess sensitive resources on the ORR. Anyone who references this report must consider that the timing of surveys did not permit a complete delineation of the resources that will be affected. If the VTR project proceeds, additional surveys will be required to account for the seasonal patterns of various threatened and endangered species. Data deficiencies and potential resources that likely went undetected are indicated where possible. Accordingly, this report should facilitate more environmentally sound decisions during planning and 2 development of the VTR site, provide a foundation for further assessment of sensitive and cultural resources, and help project managers better address regulatory guidance and DOE policies on sustainable development in compliance with, for example, the US Endangered Species Act (ESA), Migratory Bird Treaty Act (MBTA), Tennessee Rare Plant Protection and Conservation Act of 1985, Tennessee Nongame and Endangered or Threatened Wildlife Species Conservation Act of 1974, several federal and state regulations regarding aquatic resource protection, and site-specific policies as outlined in various ORR management plans developed by ORNL and TWRA for DOE.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Comparative Life Cycle Evaluation of the Global Warming Potential (GWP) Impacts of Renewable Natural Gas Production Pathways

Renewable Natural Gas (RNG) sources are being considered in future energy strategy discussions as potential replacements for fossil natural gas (FNG). While today’s supply of RNG resources is insufficient to meet U.S. demands, there is significant interest in its viability to supplement and decarbonize the natural gas supply. However, the resources that compare the life cycle global warming potential (GWP) of various RNG production pathways are lacking and focus mostly on a singular pathway. This effort is an attempt to close this gap and provide a comparison between the life cycle GWP of three major RNG pathways and the FNG pathway. The three RNG pathways evaluated are Anaerobic Digestion (AD), Thermal Gasification (TG), and Power-to-Gas (P2G) using various feedstocks. The functional unit is 1MJ of compressed RNG ready for injection into the natural gas transmission network. The results show that RNG production is not always carbon neutral or negative. Depending on the pathway the GWP impact of RNG production can range from -229 to 27 g CO 2 e/MJ compressed RNG, with AD of animal manure and AD of municipal solid waste being the least and the most impactful pathways, respectively, compared to the 10.1 g CO 2 e/MJ impact for compressed FNG.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Storage Requirements for Grid Integration of Marine Renewable Energy - a Parametric Study

Marine resources such as waves and tides house immense potential to serve as energy-rich sources of renewable power generation. They are known to be highly available,persistent and predictable in nature. Therefore, these can serve as one of the critical components for a primarily renewable energy-driven, resilient and robust future power grid. Although some inherent temporal characteristics of these resources lend themselves favorably to potential grid applications, the inclusion of storage allows the benefits and value streams to become realized more fully. In this paper, we present a framework for assessing impact of marine energy resources inclusion on the overall load generation balance and its impact on the relevant storage requirements to obtain the desired level of renewable energy penetration. From this study, we can critically infer two main points - (a) the relative storage requirements for grid operations with and without marine energy, and (b) the avoided cost of storage by including marine energy into the generation mix. We demonstrate our framework for two different locations across the United States.

Hanif, Sarmad↗
DOE OSTI2023

Eastern Interconnection Wide-Area Oscillation Assessment and Study Report

To meet the government mandates such as Renewable Portfolio Standards (RPS), conventional synchronous generators with rotating mass are being displaced by inverter-based resources (IBRs), leading to high penetration of renewable energy sources (RES). As a result, the inherent properties and characteristics of the transformed generation mix may significantly impact the grid behaviour, and it is of paramount significance that the impact and the consequences of the resource mix change is thoroughly understood to adopt measures to maintain reliable grid operations. Of great concern is the inter-area low-frequency oscillation, which usually propagates through a large region and has a system-wide impact. Such oscillations may lead to unnecessary or inadvertent tripping of generators, that may be simply reacting to the oscillation originating from geographically remote sites. Such tripping of generators can lead to cascading outages, system split and load loss events. Over the years, several system-wide oscillation events have been observed across all three North American interconnections. This project titled Wide-area Oscillation Assessment and Trending Study, sponsored by the Office of Electricity (OE) of the Department of Energy (DOE), aims to conduct the required research to capture and investigate the potential changes in wide-area oscillatory performance of the system as a result of resource mix transition. The Pacific Northwest National Laboratory (PNNL) conducted this research and technical staff of Federal Energy Regulatory Commission (FERC) served as advisors to the project. The primary objective of this study is to assess whether there are significant trends in the power system wide-area oscillatory behaviours, as a result of the generation-mix changes due to the increased penetration of RES in the U.S. Eastern Interconnection (EI). The analysis presented in this report can serve as reference for future grid planning and operation of the EI system. This research conducted in this project evaluates the wide-area oscillatory behaviour of the EI, using a model-based approach for potential future resource mixes, and the measurement-based analysis with 21-month phasor measurement unit (PMU) time series. The oscillation modes in EI system along with the impact of the changes of the generation mix on the frequency and damping ratio (DR) of the oscillations have been studied.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

In-Conduit Hydropower for Public Water Supply Systems: Development Challenges and Costs

Conduit hydropower leverages existing water infrastructure to provide energy solutions, though deployment has been slow. A 2022 US Department of Energy (DOE)–funded report led by Oak Ridge National Laboratory (ORNL) summarizes a reconnaissance-level study of hydropower potential at national conduits (Kao et al., 2022). The report includes power and energy estimates across three major sectors of conduit hydropower potential: municipal, agricultural, and industrial. Water resources include public water supply systems (municipal and industrial), irrigation canal systems (agricultural), thermoelectric cooling systems (industrial), and wastewater systems (municipal and industrial). In total, 1.41 GW of power potential was estimated nationwide. Subsequently, DOE has funded ORNL through the Conduit Hydropower Engineering, Evaluation, and Technology Acceleration project (CHEETA) to improve deployment potential for conduit hydropower. Work thus far has focused on “in-conduit” hydropower (ICH)—or “in-pipe” hydropower—for public water supply systems, though the project is planning to cover conduit hydropower more broadly. The timeline of ORNL’s conduit hydropower related research and development (R&D) is shown in Figure 1. The results of CHEETA should benefit the hydropower industry by providing insights into costs, barriers, and other considerations that impact project development. The hydropower industry and municipal/industrial conduit stakeholders will use the output to inform development decisions and advance low-impact hydropower growth in the US.

13 HYDRO ENERGY↗
DOE OSTI2023

Moisture Absorbing and Water Self‐Releasing from Hybrid Hydrogel Desiccants

Abstract Atmospheric moisture is a valuable resource for fresh water and potentially sustainable energy. However, direct harvesting water from moisture (the vapor form) remains the most challenging. Hybrid desiccants made from hydrogels embedded with salt offer promise in absorbing moisture. However, the desorption process often requires additional energy to heat the samples. Here, poly(acrylic acid) (PAA) hydrogels embedded with lithium chloride are prepared, demonstratng simultaneous moisture absorption and self‐release of liquid water at room temperature with 50–90% relative humidity. The water self‐releasing process can be separated into two distinct stages: 1) surface release, where water droplets grow on the hydrogel surface due to differences in nucleation and diffusion rates, and 2) bulk release, triggered by the collapse of polymer chains, subsequently releasing water from the hydrogel network. Factors such as salt concentration, hydrogel crosslinking density, and film thickness are investigated to better understand the moisture absorption and water‐releasing processes. Moreover, hydrophobic domains are introduced onto the salt‐embedded PAA films, creating an edge effect that enhances the droplet growth rates. When the hydrophobic domains are patterned, the movement of released water can be guided, resulting in a threefold increase in water removal rate attributed to gravitational force.

Chemistry↗
DOE OSTI2023

Deriving spatially explicit direct and indirect interaction networks from animal movement data

Abstract Quantifying spatiotemporally explicit interactions within animal populations facilitates the understanding of social structure and its relationship with ecological processes. Data from animal tracking technologies (Global Positioning Systems [“GPS”]) can circumvent longstanding challenges in the estimation of spatiotemporally explicit interactions, but the discrete nature and coarse temporal resolution of data mean that ephemeral interactions that occur between consecutive GPS locations go undetected. Here, we developed a method to quantify individual and spatial patterns of interaction using continuous‐time movement models (CTMMs) fit to GPS tracking data. We first applied CTMMs to infer the full movement trajectories at an arbitrarily fine temporal scale before estimating interactions, thus allowing inference of interactions occurring between observed GPS locations. Our framework then infers indirect interactions—individuals occurring at the same location, but at different times—while allowing the identification of indirect interactions to vary with ecological context based on CTMM outputs. We assessed the performance of our new method using simulations and illustrated its implementation by deriving disease‐relevant interaction networks for two behaviorally differentiated species, wild pigs ( Sus scrofa ) that can host African Swine Fever and mule deer ( Odocoileus hemionus ) that can host chronic wasting disease. Simulations showed that interactions derived from observed GPS data can be substantially underestimated when temporal resolution of movement data exceeds 30‐min intervals. Empirical application suggested that underestimation occurred in both interaction rates and their spatial distributions. CTMM‐Interaction method, which can introduce uncertainties, recovered majority of true interactions. Our method leverages advances in movement ecology to quantify fine‐scale spatiotemporal interactions between individuals from lower temporal resolution GPS data. It can be leveraged to infer dynamic social networks, transmission potential in disease systems, consumer–resource interactions, information sharing, and beyond. The method also sets the stage for future predictive models linking observed spatiotemporal interaction patterns to environmental drivers.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Indexing habitat opportunity for juvenile anadromous fishes in tidal-fluvial wetland systems

In intertidal wetlands, annual habitat use by migrating juvenile salmon is limited by both physical and biological constraints. Physical limits are set by inundation patterns and water quality parameters, while biological bounds are determined by species specific migration timing and seasonal residency behaviors. We developed a new metric called the fish habitat opportunity index (FHOI) to quantify the total time per calendar year that salmon could access intertidal sites, based on periods of inundation and juvenile salmon seasonal migration. The index was applied using data collected at a recently reconnected tidal freshwater wetland area during 2006-2009. We found the wetland to be accessible to different salmon species for different lengths of time and periods of the year. On average, chum salmon (Oncorhynchus keta) had remarkably consistent opportunities to use marsh habitat over the 4 years sampled, while opportunities were more variable for Chinook (O. tshawytscha), and coho salmon (O. kisutch). Inundation varied nonlinearly with tidal height, and fish had access to the productive marsh edge for approximately 40-50% of the time during periods of access. The FHOI is widely applicable to wetland systems throughout the tidal fluvial continuum, and provides a metric for assessing fish habitat opportunity that is more realistic than simple wetted area calculations. Finally, the FHOI affords a method of a priori comparison among potential restoration sites to help resource managers predict the likely relative benefit to juvenile salmon.

wetland restoration, estuary, habitat opportunity,↗
DOE OSTI2024

Integrated top-down process and voxel-based microstructure modeling for Ti-6Al-4V in laser wire direct energy deposition process

Laser-wire metal additive manufacturing (AM) is one of the ideal direct energy deposition (DED) processes for creating large-scale parts with a medium level of complexity. However, the DED process involves complex thermal signatures and wide length scales making the fabrication of realistic AM components and part qualification often reliant on experimental trial-and-error optimization. While experimental measurements over the full volume of a part are valuable and necessary, measuring the entire area of a part is significantly laborious and practically infeasible, particularly for large parts in terms of cost and rapid qualification. Therefore, in this work, we developed an effective thermal and microstructure modeling framework based on the Johnson–Mehl-Avrami-Kolmogorov (JMAK) and Koistinen & Marburger (KM) models through a top-down approach that considers plate distortion-affected thermal profiles. A voxel-by-voxel simulation method is used to predict individual phase fractions of Ti-6Al-4 V. The predicted results were validated through detailed metallurgical measurements. A combined voxel-by-voxel approach with a sparse data reconstruction technique produced a near-perfect reconstruction of the original data. This approach anticipates a significant reduction in data points and computation time and resources. Lastly, we conclude with potential extensions of this work to other modeling efforts.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Techno-economic analysis of hydroprocessed renewable jet fuel production from pennycress oilseed

Commercial production of jet fuel from biobased feedstocks is still encumbering, mainly due to their high production cost and competition with food resources. Pennycress oilseed is a potential jet fuel feedstock which can be supplied at a lower price compared to similar oilseeds, such as soybean and canola. However, the technoeconomics of pennycress-based jet fuel production needs to be evaluated. The objective of this study was to assess the technical feasibility and costs of hydroprocessed renewable jet fuel (HRJ) production from pennycress. The production capacity was considered to be 18.9 million L/yr (5 million gal/yr). The analysis considered pennycress grain handling and conditioning, oil extraction and conversion to HRJ and byproducts, i.e., LPG, naphtha and green diesel, through hydroprocessing technology, as well as pennycress meal processing as boiler fuel and wastewater treatment. Total investment for establishing the HRJ biorefinery at the selected capacity was estimated to be 90.8 million USD. Minimum selling price (MSP) of HRJ was estimated to be 1.2 USD/L, which was comparable to the MSP of HRJ from similar oilseeds, including soybean and canola. It could also be further reduced by supplying pennycress grain at a lower price, increasing the oil content and increasing the production capacity of the biorefinery. Furthermore, the outcomes of this research would help establish the performance targets needed to reach the economic viability of HRJ production from pennycress at the commercial scale.

09 BIOMASS FUELS↗
DOE OSTI2022

Emergent Chemical Behavior in Mixed Food and Lignocellulosic Green Waste Hydrothermal Liquefaction

Hydrothermal liquefaction (HTL) is a promising strategy for the conversion of energy-dense waste streams to fuels. Mixed-feed HTL aggregates multiple feed streams to achieve greater scales that capitalize on local resources, hence lowering costs. The potential for new pathways and products upon feedstock blending becomes a compounding level of complexity when unlocking emergent chemistries. Here, food and green waste streams were evaluated under HTL conditions (300 °C, 1 h) to understand the effect of feed molecular composition on product distributions and mechanisms. Thousands of emergent chemical compounds were detected via Fourier transform ion cyclotron resonance mass spectrometry, ultimately leading to the emergence of two dominant outcomes. First, the presence of small amounts of food waste into green waste results in substantial decarboxylation and subsequent polymerization to biocrude than chars. Second, in the other limit, small amounts of green waste promote the capping of oxygenates into the biodiesel range, such as with the emergence of fatty acid methyl esters.

09 BIOMASS FUELS↗
DOE OSTI2022

Global Sensitivity Analysis Using the Ultra‐Low Resolution Energy Exascale Earth System Model

Abstract For decades, Arctic temperatures have increased twice as fast as average global temperatures. As a first step toward quantifying parametric uncertainty in Arctic climate, we performed a variance‐based global sensitivity analysis (GSA) using a fully coupled, ultra‐low resolution (ULR) configuration of version 1 of the U.S. Department of Energy's Energy Exascale Earth System Model (E3SMv1). Specifically, we quantified the sensitivity of six quantities of interests (QOIs), which characterize changes in Arctic climate over a 75 year period, to uncertainties in nine model parameters spanning the sea ice, atmosphere, and ocean components of E3SMv1. Sensitivity indices for each QOI were computed with a Gaussian process emulator using 139 random realizations of the random parameters and fixed preindustrial forcing. Uncertainties in the atmospheric parameters in the Cloud Layers Unified by Binormals (CLUBB) scheme were found to have the most impact on sea ice status and the larger Arctic climate. Our results demonstrate the importance of conducting sensitivity analyses with fully coupled climate models. The ULR configuration makes such studies computationally feasible today due to its low computational cost. When advances in computational power and modeling algorithms enable the tractable use of higher‐resolution models, our results will provide a baseline that can quantify the impact of model resolution on the accuracy of sensitivity indices. Moreover, the confidence intervals provided by our study, which we used to quantify the impact of the number of model evaluations on the accuracy of sensitivity estimates, have the potential to inform the computational resources needed for future sensitivity studies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Impact of El Niño‐Southern Oscillation and Madden‐Julian Oscillation on the US Puget Sound Regional Hydroclimate

El Niño-Southern Oscillation (ENSO) and Madden-Julian Oscillation (MJO) are two major modes of climate variability with global hydroclimate impacts. However, their impacts often depend on the local climate and geography, resulting in large regional differences. In this study, we examined the connection of ENSO and MJO to the hydroclimate conditions and extremes in the Puget Sound (PS) basin located in the US Pacific Northwest coast. The results indicate that ENSO significantly modulates the cold season temperature and temperature-mediated hydrologic processes. El Niño cold seasons feature less snow accumulation and intensified surface runoff, even if the precipitation amount is similar to La Niña cold seasons. Therefore, El Niño causes more snow drought (in the form of compound dry and warm snow drought) and shifts the surface runoff seasonality by reducing runoff in the subsequent warm season. MJO phases 6–7 trigger more extreme precipitation, temperature, snowmelt, and runoff in the PS region at 0–9–day lags, and such connections are robust regardless of how the ENSO signals are removed. Meanwhile, MJO modulates large-scale extreme weather systems (e.g., atmospheric rivers) with significant enhancement during phases 6–7. ENSO impacts have intensified in the 2001–2020 period, whereas MJO impacts showed some phase shift in this period. This study reveals ENSO and MJO phases 6–7 as useful predictors of the PS hydroclimate anomalies/extremes at seasonal and daily scales, respectively. Utilizing these findings holds the potential to improve regional water resources prediction and management.

ENSO↗
DOE OSTI2024

High-Q cavity interface for color centers in thin film diamond

Quantum information technology offers the potential to realize unprecedented computational resources via secure channels distributing entanglement between quantum computers. Diamond, as a host to optically-accessible spin qubits, is a leading platform to realize quantum memory nodes needed to extend such quantum links. Photonic crystal (PhC) cavities enhance light-matter interaction and are essential for an efficient interface between spins and photons that are used to store and communicate quantum information respectively. Here, we demonstrate one- and two-dimensional PhC cavities fabricated in thin-film diamonds, featuring quality factors (Q) of 1.8 × 10 5 and 1.6 × 10 5 , respectively, the highest Qs for visible PhC cavities realized in any material. Importantly, our fabrication process is simple and high-yield, based on conventional planar fabrication techniques, in contrast to the previous with complex undercut processes. We also demonstrate fiber-coupled 1D PhC cavities with high photon extraction efficiency, and optical coupling between a single SiV center and such a cavity at 4 K achieving a Purcell factor of 18. The demonstrated photonic platform may fundamentally improve the performance and scalability of quantum nodes and expedite the development of related technologies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Distributed Machine Learning Workflow with PanDA and iDDS in LHC ATLAS

Machine Learning (ML) has become one of the important tools for High Energy Physics analysis. As the size of the dataset increases at the Large Hadron Collider (LHC), and at the same time the search spaces become bigger and bigger in order to exploit the physics potentials, more and more computing resources are required for processing these ML tasks. In addition, complex advanced ML workflows are developed in which one task may depend on the results of previous tasks. How to make use of vast distributed CPUs/GPUs in WLCG for these big complex ML tasks has become a popular research area. In this paper, we present our efforts enabling the execution of distributed ML workflows on the Production and Distributed Analysis (PanDA) system and intelligent Data Delivery Service (iDDS). First, we describe how PanDA and iDDS deal with large-scale ML workflows, including the implementation to process workloads on diverse and geographically distributed computing resources. Next, we report real-world use cases, such as HyperParameter Optimization, Monte Carlo Toy confidence limits calculation, and Active Learning. Finally, we conclude with future plans.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Endophyte mediated Populus trichocarpa water use efficiency is dependent on time of day and plant water status

Endophytes are potential partners for improving the resource use efficiency of bioenergy feedstock systems such as short rotation coppiced Populus. Endophytes isolated from members of the Salicaceae family have broad host compatibility and can improve water use efficiency (WUE) through decreases in stomatal conductance. However, the literature is inconsistent with regards to the environmental conditions and temporal patterns of these benefits. This study investigates how endophyte mediated changes in Populus trichocarpa (Torr. and Gray) ‘Nisqually-1’ stomatal conductance and WUE shift with time and scale in response to water-deficit stress. Leaf gas exchange and above-ground productivity were used to evaluate the carbon and water balances of glasshouse grown plants in response to endophyte inoculation and water-deficit. Differences in stomatal conductance between control and inoculated plants were more pronounced (39.7 % decrease, Welch’s two-sample t(14.34 dfadj) = -2.358, p-value = 0.033) under water-deficit conditions in the late morning during a period of higher light intensity. The decrease in stomatal conductance accompanied a substantial increase in intrinsic WUE (iWUE) for water-deficit inoculated plants. However, increases in iWUE did not result in improvements in aboveground productivity or shoot biomass WUE (WUEsb) for water-deficit inoculated plants. This decoupling between iWUE and aboveground productivity may be an indicator of assimilate allocation to microbial metabolism as an additional carbon sink or a shift in carbon allocation towards belowground biomass. Future work should take a whole-plant approach that accounts for diurnal patterns in incident irradiance to evaluate the impact of endophyte inoculation on host WUE and stress tolerance.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Hybrid Oscillator-Qubit Quantum Processors: Instruction Set Architectures, Abstract Machine Models, and Applications

This tutorial offers a pedagogical guide to hybrid quantum processors that integrate discrete-variable (DV) qubits and continuous-variable (CV) oscillators. Aimed at computer scientists, engineers, and physicists, it provides an overview of the experimental, algorithmic, and architectural aspects of this novel and rapidly developing hardware model. Experimental realizations of this model include superconducting, trapped-ion, and neutral-atom platforms. By combining DV and CV components, hybrid oscillator-qubit processors enable a powerful new paradigm that offers complementary strengths for quantum control, error correction, computation, and simulation. Working toward the goal of a full-stack system connecting applications to CV-DV hardware, we define and formulate abstract machine models and instruction set architectures. These essential abstractions enable codesign of hardware and software, and resource estimation for exploring the potential of current and future hardware for computational and simulation tasks. Using these abstractions, we present both new and existing examples that illustrate the benefits of hybrid CV-DV processors relative to traditional DV-only hardware in computation as well as quantum simulation of physical models. Examples include algorithms for transferring states between DV and CV systems, performing the quantum Fourier transform, and simulation of lattice gauge theories. Relative to qubit-only hardware, the bosonic degrees of freedom natively available in hybrid architectures can substantially reduce the circuit complexity of simulations for physical models containing bosons. A key technique is the extension of quantum signal processing ideas to CV-DV systems. This work is intended to serve as a timely and comprehensive guide to this relatively unexplored yet promising approach to quantum computation and to provide a road map to guide future development.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Robust negativity in the quantum-to-classical transition of Kerr dynamics

Here, we quantify the quantum-to-classical transition of the single-mode Kerr nonlinear dynamics in the presence of loss. We establish three timescales that govern the dynamics, each with distinct characteristics. For times short compared with the Ehrenfest time, the evolution is classical, characterized by Gaussian dynamics. For sufficiently long times, as we increase the initial photon number, unitary Kerr evolution would generate macroscopic superpositions of coherent states (so-called kitten states). However, this is severely restricted in the presence of small photon loss, and the expectation values of observables coincide with their classical values. The intermediate timescale, however, shows resilient quantum behavior in the macroscopic limit. We show that in the mean-field non-Gaussian regime, the Kerr Hamiltonian (with small photon loss) generates a significant amount of Wigner-negativity, and classical flow is recovered only if the loss rate grows with system size. Our results broaden the usual understanding of quantum-to-classical transitions and demonstrate the potential for creating robust nonclassical resources for continuous-variable quantum information processing in the presence of loss.

Raza, Mohsin [University of New Mexico, Albuquerqu↗