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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Austin Sustainable and Holistic Integration of Energy Storage and Solar PV [Austin SHINES]. Final Report, Version 2

The Austin SHINES project and solution is a software management platform, for an electric grid with a high penetration of dispersed photovoltaic (PV) solar generation sites, which maintains the traditional power quality and reliability associated with grid service. This project developed and deployed the platform as a Distributed Energy Resource Management System (DERMS), engaging multiple advanced controls, to evaluate operation and optimization of a fleet of diverse DER assets, installed at several locations among Austin Energy’s customers and distribution system. The project also produced a methodology to create a replicable DERMS template, adaptable to other regions and market structures. Last, Austin SHINES aimed to demonstrate the solution’s methodology would enable the DER grid ecosystem to serve load at a technical cost (System Levelized Cost of Electricity, or System LCOE) of less than the U.S. Department of Energy SHINES program metric of $0.14/kWh, in a defined boundary, while enabling a high penetration of distributed PV. Research was categorized in 6 reports (Final Deliverables = FD) listed below, with titles and descriptions indicating which area of understanding was investigated: FD-1: System Levelized Cost of Electricity (System LCOE) Methodology The creation and use of the System LCOE to Serve Load metric that encompasses the holistic, system-level costs and benefits of all resources, and enables them to be evaluated based on their ability to support an efficient and low-cost integrated grid ecosystem. FD-2: Software Platform Product Description The creation of new DER control methodologies deployable within a utility-grade software platform that enable DER's to maximize their benefit within a grid, that is capable of serving load enabling a high penetration of distributed PV generation. FD-3: Optimal Design Methodology Optimal design methodologies for individual DER installations that enable utilities to determine the optimal combinations and sizing for individual DER sites. FD-4: Austin SHINES Ownership and Operation Models for DER System Performance A comparison of multiple DER aggregation and ownership methodologies including direct utility control, third-party aggregator, and autonomous. FD-5: Economic Modeling & Optimization A comparison of multiple DER technology mixes and configurations within the distribution system, providing insight into an optimal blend of technologies that best enable the distribution system to serve load at the lowest cost at high penetrations of solar. FD-6: Fielded Assets Deployed DER assets within the Austin Energy SHINES circuits. Austin SHINES provided an opening for state-of-the-art technology products to be deployed, providing a rich opportunity for improving how each of the products perform as stand-alone products, and in concert with other complementary products. The Austin SHINES project comprised of two key metrics for System LCOE: SystemLCOE_SHINES<$0.14/kWh Modeled ΔSystemLCOE_SHINES/ΔSystemLCOE_Base≥20% at same solar penetration The System LCOE calculation uses the costs of the utility-owned infrastructure as it exists today, the cost of the DERs that exist in the system today, and the cost of the purchase of energy from ERCOT wholesale markets over the course of the calendar year. All costs are on an annualized basis. The capital and operating costs are derived from the rate case, which produces a yearly cost. The net cost of energy and services imported to the system is integrated over the test year, as is the load served and solar penetration. The first metric was easily achieved by every scenario considered. The goal was set when the Department of Energy’s SHINES Funding Opportunity Announcement was written in 2015 and was a more difficult target at the time. Due mostly to rapidly declining costs for DERs and the significant decrease in the Electric Reliability Council of Texas (ERCOT) energy market prices, which results in lower net cost of energy purchases, the System LCOE is well below this target for all scenarios considered. A fleet of DERs can assume different mixtures, each of which serves the load at a different LCOE. The optimal mixture of DERs serves load at the smallest System LCOE. The second metric (hereinafter %delta metric) asks that the holistic DERMS controls reduce the incremental cost above the baseline of going to a high solar penetration future by at least 20% as compared to the case of a DER deployment with no sophisticated controls (autonomous). Many comparison sets were created throughout this project. Physical technology was installed for informing utility engineering and testing several types of operational control schemes, through the DERMS. The types of operational control which were compared for valuation of the System LCOE Metric were: Holistic control = using the full suite of the DERMS platform to decide and optimize how/why the systems operate depending on weather, market, and reliability signal input. Autonomous control = a local mode at the asset site, wherein a schedule operates the asset, with visibility into performance only No control = the baseline for comparing value against the other two types of control The types of ownership control included: Direct Utility control = the utility dispatches a signal to each asset Third-Party Aggregator = a third party aggregates a fleet of assets and the utility dispatches one signal for all Autonomous = a local mode is set for operation at the asset site, wherein a schedule operates the asset, with visibility into performance only The types of control methodologies deployable within a utility-grade software platform included: Utility Peak Load Reduction = Lower transmission cost obligation Day-Ahead Energy Arbitrage = Realize economic value through price differential Real-Time Price Dispatch = Realize economic value from real-time price spikes Voltage support = Reduce losses and increase solar generation Distribution Congestion Management = Increase local grid reliability Demand Charge Reduction = Lower customer bills and realize system benefit The fielded assets deployed for the project were: Utility Scale Kingsbery Energy Storage System: 1.5 MW / 3 MWh Li-Ion battery storage Mueller Energy Storage System: 1.75 MW / 3.2 MWh Li-Ion battery storage, 7 Energy Storage Units (250 kW each) La Loma Community Solar: 2.6 MW Commercial Scale Aggregated storage installations at 3 sites, with existing solar (300+ kW): One 18 kW / 36 kWh Li-Ion battery storage Two 72 kW / 144 kWh Li-Ion battery storage Residential Scale Aggregated storage installations: -Six stationary battery storage systems (10 kWh each) at homes with existing solar -One Electric Vehicle installed as Vehicle-to-Grid (V2G) Utility-Controlled Solar via Smart Inverters at 12 homes Autonomously-Controlled Smart Inverters at 6 homes Over the course of the project, Austin SHINES undertook installing more than 3 MW of distributed battery energy storage, smart PV inverters, a DER control platform, and other enabling technologies utilizing customer and utility locations and aggregation models. All of these resources were to be integrated and optimized at the utility level. DER assets and control methodologies were designed to achieve a credible pathway to a System LCOE for energy delivered to load of $0.14//kWh or less by 2020, while maximizing distributed solar generation and maintaining acceptable standards of power quality. The project also established a template for other regions to follow, to maximize the adoption of distributed solar PV in support of an economic and efficient grid. In total, the Austin SHINES project added value to the DER subject area in each layer of integration. From utility, to commercial to residential scales, the sheer hierarchy of communication and coordination was a significant accomplishment in addition to learnings from what these communications revealed was unique to each. Economically, the most effective method demonstrated was the criticality of planning phases. Contingencies and multiple projection scenarios helped guide the project to deploy optimal design as close as feasible, in real world conditions. The project and reports will serve public benefit by outlining specific areas of DER strategy and installation where many stakeholders and needs can be addressed with improved efficiency. Overall, communities and utilities should use the results to guide the increasing options available for powering the grid with DER, renewables, and carbon considerate energy.

14 SOLAR ENERGY↗
DOE OSTI2021

Pulsar Based Timing for Grid Synchronization

Existing synchronization systems in the power grid, such as the global positioning system, are susceptible to temporary or permanent failures due to various unpredictable and uncontrollable factors such as cyber-attack and electromagnetic interferences, thus affecting the accuracy and reliability of generated timing signal. In this article, a pulsar astronomy-based timing system is proposed to provide an alternative synchronization signal. Further, this clock will offer significant security improvements to power grid applications, such as a wide-area monitoring system, which depends on a precise timing signal. The hardware and software frameworks are described in detail. First, a high-speed sampling hardware platform is designed to collect signals from radio telescopes. Then a periodic pulse extraction method with three steps is proposed to process the pulsar signal, including polyphase filterbanks, incoherent de-dispersion, and sliding window folding. Lastly, three experiments are conducted to verify the effectiveness of the frameworks. The generated pulsar timing pulse is presented, and the factors affecting its accuracy are also discussed. The analysis results demonstrate that the pulsar signals can provide high-accurate timing pulses for grid synchronization.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Uncertainty-Guided Prediction Horizon of Phase-Resolved Ocean Wave Forecasting Under Data Sparsity: Experimental and Numerical Evaluation

Accurate short-term wave forecasting is critical for the safe and efficient operation of marine structures that rely on real-time, phase-resolved ocean wave information for control and monitoring purposes (e.g., digital twins). These systems often depend on environmental sensors (e.g., waverider buoys, wave-sensing LIDAR). Challenges arise when upstream sensor data are missing, sparse, or phase-shifted due to drift. This study investigates the performance of two machine learning models, time-series dense encoder (TiDE) and long short-term memory (LSTM), for forecasting phase-resolved ocean surface elevations under varying degrees of data degradation. We introduce the τ-trimming algorithm, which adapts the prediction horizon based on uncertainty thresholds derived from historical forecasts. Numerical wave tank (NWT) and wave basin experiments are used to benchmark model performance under short- and long-term data masking, spatially coarse sensor grids, and upstream phase shifts. Results show under a 50% probability of upstream data loss, the τ-trimmed TiDE model achieves a 46% reduction in error at the most upstream target, compared to 22% for LSTM. Furthermore, phase misalignment in upstream data introduces a near-linear increase in forecast error. Under moderate model settings, a ±3 s misalignment increases the mean absolute error by approximately 0.5 m, while the same error is accumulated at ±4 s using the more conservative approach. These findings inform the design of resilient, uncertainty-aware wave forecasting systems suited for realistic offshore sensing environments.

42 ENGINEERING↗
DOE OSTI2022

The Role of Groundwater Withdrawals on River Regulation: Example From the Columbia River Basin

The Columbia River Basin (CRB) is heavily regulated by more than 250 dams on its river system while depending significantly on groundwater withdrawals in certain sub-basins. Neglecting groundwater withdrawals in hydrologic models of the basin could result in inaccurate predictions of its water budget and thus mislead water management decisions in the basin. This work aims to understand the impacts of groundwater pumping on the spatiotemporal patterns of modeling regulated streamflow in the CRB using a modified version of the Variable Infiltration Capacity (VIC) model integrated with a water management component that accounts for groundwater withdrawals, irrigation demands, and reservoir operation (VIC-GIRR). The VIC-GIRR simulations showed that considering additional groundwater withdrawals would alleviate the stress of irrigation water deficit in the Snake River Basin with an average reduction of 10 km 3 /year. Such a reduction in water deficit resulted in slight streamflow increase over the CRB with maximum increase up to 40% during dry period in certain locations. We also note that the implementation of groundwater withdrawal does not, however, improve the overall model performance in long-term averaged streamflow and storage predictions. Our results highlight the efforts needed to examine additional important processes in representing the interactions between water withdrawals and reservoir operations. Such efforts will aid in better simulation of multi-reservoir system and improve effectiveness for agricultural productivity, power generation, flood control, and navigation purposes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Disjunctive optimization model and algorithm for long-term capacity expansion planning of reliable power generation systems

This paper proposes a new optimization model and algorithm for long-term capacity expansion planning of reliable power generation systems. The model optimizes both investment decisions (e.g., size, location, and time to install, retire and decommission facilities) and operation decisions (e.g., on/off status, operating capacity, and expected power output). It is also able to optimize reserve systems (or backup systems), as well as the main systems, to improve power systems reliability. An impact of operational strategies of generators (i.e., participating in electricity production vs. remaining as idle units during operation) on power systems reliability is considered. Probability of equipment failures and capacity failure states are used to rigorously estimate the power systems reliability depending on design and operation strategies. The optimization model is formulated with Generalized Disjunctive Programming (GDP), which is reformulated as a mixed-integer linear programming (MILP) model using the Hull relaxation. Two reliability-related penalties, such as downtime penalty and unmet demand penalty, are included in the objective function to maximize reliability while minimizing the total net present cost. Furthermore, a bilevel decomposition with tailored cuts is developed to reduce computational times of the multi-scale optimization model. The effectiveness of the proposed model is shown by comparing the results with the results obtained from the expansion planning models that do not explicitly consider reliability. In conclusion, we also show that the proposed bilevel decomposition is computationally efficient for solving large scale problems through 5-years and 10-years planning case studies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Silica nanocluster binding rate coefficients from molecular dynamics trajectory calculations

Oxide nanoparticle growth from vapor phase precursors occurs in high temperature aerosol reactors first via the formation of nanoclusters, which are nanometer-scale condensed-phase species composed of 10 1 -10 2 atoms. The binding rate for nanoclusters, defined as the rate at which two nanoclusters collide with and stick to one another, is hence of interest in predicting nanoparticle size distribution functions in an aerosol. We have utilized molecular dynamics (MD) trajectory calculations to determine the homogeneous (equal-sized) and heterogeneous (disparate-sized) binding rate coefficients of SiO2 (silica) nanoclusters composed of 18, 144, and 333 atoms. MD trajectory calculations incorporated all-atom models of nanoclusters using a combined Born–Huggins–Mayer-Lennard-Jones potential model, which accounts for both short range interactions and electrostatic interactions. MD calculations were utilized to determine the binding probability as a function of both initial relative velocity and impact parameter; integration of the binding probability across impact parameter and relative velocity space yields the binding rate coefficient. MD trajectory calculations reveal that the most common type of encounters between nanoclusters leading to binding are grazing collisions, i.e. instances where collision would not occur without induced dipole potential influences. The resulting binding rate coefficients are found to be extremely weakly dependent on system temperature, which is in contrast to the use of rate coefficient models which are the product of a hard-sphere collision rate coefficient and a constant enhancement factor (leading to a rate coefficient proportional to the square root of temperature). Enhancement factors defined from MD trajectory calculations fall in the range of 3–9 as system temperature decreases from 1500 K to 300 K. Furthermore, such large values suggest that potential interactions need to be considered when modeling oxide nanocluster growth in the gas phase.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Electro-osmo-dialysis through nanoporous layers physically conjugated to micro-perforated ion-exchange membranes: Highly selective accumulation of trace coions

This study explores theoretically and numerically the phenomenon of counter-flow accumulation of trace coions during electro-osmo-dialysis through composite membranes containing nanoporous and perforated ion-exchange layers. The combination of charged nanopores and perforations allows electroosmosis, and ion concentration polarization appears near the ion-exchange layer. Accumulation of trace coions occurs because their advective and electromigration flow velocity components have opposite signs and are locally compensating in depletion regions where electric fields are high. This local compensation of flow components can give rise to high accumulation factors (>1000 in some cases) for trace coions at some distance from the interface between the nanoporous and ion-exchange layers. Moreover, the extent of this accumulation depends on the trace-coion diffusion coefficient. The resulting selectivity between different coions might serve as a basis for environmentally friendly separation of ionic species such as synthetic peptides or rare-earth elements. For example, a periodic process might include accumulation followed by species release into smaller volumes of solution. For both rare-earth ions and peptide-like species, the accumulation selectivity between ions with small differences in mobilities depends on system parameters such as nanoporous-layer thickness, distance between the perforations, and the zeta potential of the nanopore surface. Here, the use of optimal values of these membrane parameters may enable tuning of the electro-osmo-dialysis system for separation of specific ions. Modelling reveals that despite inhomogeneous patterns of fluid and ion flows close to the nanoporous/perforated ion-exchange interface, at relatively short distances from this interface (less than half the distance between the perforations) all the flows become practically one-dimensional (1D). Similarly, the concentration profiles of trace coions also become 1D. The flow one-dimensionality at short distances from the current-polarized interface enables a simple 1D approximation that is useful for an approximate analysis of trends in this multi-parameter system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Disturbance legacies regulate coastal forest soil stability to changing salinity and inundation: A soil transplant experiment

Coastal forests worldwide are vulnerable to a dramatic transition from upland to wetland as sea-level rise accelerates and regimes of precipitation and storms change. However, the biogeochemical impacts of shifting salinity and inundation disturbance that foreshadow forest to wetland state transitions are largely unknown. This experiment used a natural salinity gradient in a tidal creek in eastern Maryland, U.S.A., to examine how soil respiration and chemistry may change under novel salinity and inundation disturbance regimes. Soil monoliths were transplanted in a reciprocal design among plots varying in seawater exposure and elevation above the creek. We monitored the monoliths’ carbon dioxide (CO 2 ) flux for two years and performed soil chemical analyses at the end of the experiment. Soil CO 2 flux was affected by changing disturbance regimes and responses were dependent upon the salinity and inundation legacies associated with each study location. Lowland soil CO 2 flux was resistant to changing salinity and inundation disturbance, with transplanted soil monolith chemistry composition in between that of its origin and destination. Conversely, upland soil CO 2 flux was sensitive to changing salinity and inundation disturbance and remained suppressed throughout the 2-year study when exposed to wetter, saline conditions. Additionally, transplanted upland soil chemistry composition was like that of its destination, rather than origin, with upland soils displaying higher pH, base saturation, and nutrient availability relative to lowland soils. Here, we hypothesize that reductions in soil respiration rates were driven by loss of soil nutrients and osmotic and redox stress on microbial communities following exposure to seawater. Together, our results suggest that disturbance legacies shape coastal forest soil responses to changing salinity and inundation disturbance regimes. However, fully understanding the dependence of system responses on disturbance legacies requires future study across a variety of systems and spatial and temporal scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Electrocatalytic Reduction of CO 2 to CO over Ag(110) and Cu(211) Modeled by Grand-Canonical Density Functional Theory

We report the results of modeling CO 2 reduction (CO 2 R) to CO over Ag(110) and Cu(211) surfaces at different applied potentials using grand-canonical density functional theory (GC-DFT), a method specifically designed to accurately model electrochemical systems. In addition to demonstrating GC-DFT’s ability to accurately model electrochemical processes, we also compare it with the computational hydrogen electrode (CHE) approach. GC-DFT predicts that the geometries of these reacting systems strongly depend on the applied potential and the Helmholtz free energies vary nonlinearly with the applied potential, which contradicts a central assumption of the CHE approach. The CHE approach neglects the change in the number of electrons on the electrode surface at different applied potentials, which reduces its accuracy as the potential changes from the potential of zero charge. Our results further demonstrate that the grand free energies of the reaction intermediates not only depend on the value of the applied potential but also on the metal surface type, adsorption site, and adsorbate. GC-DFT’s ability to predict the effect of the applied potential on adsorbate geometry enables it to evaluate different possible reaction mechanisms at different applied potentials. For instance, GC-DFT predicts that the first step of CO2R likely switches from proton-coupled electron transfer to sequential electron transfer and then proton transfer at more reducing potentials, a result that cannot be determined by the CHE because it assumes that all electron transfers are coupled to proton transfers and neglects the effect of the applied potential on the adsorbate geometry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Dynamic Carrier Modulation via Nonlinear Acoustoelectric Transport in van der Waals Heterostructures

Dynamically manipulating carriers in van der Waals heterostructures could enable solid-state quantum simulators with tunable lattice parameters. A key requirement is the formation of deep potential wells to reliably trap excitations. Here, we report the observation of nonlinear acoustoelectric transport and dynamic carrier modulation in boron nitride-encapsulated graphene devices coupled to intense surface acoustic waves (SAWs) on LiNbO 3 substrates. SAWs generate strong acoustoelectric current densities ( J AE ), transitioning from linear to nonlinear regimes with increasing SAW intensity. In the nonlinear regime, periodic carrier (electrons, holes, or their mixtures) stripes emerge. Using counter-propagating SAWs, we create standing SAWs (SSAWs) to dynamically manipulate charge distributions without static gates. The saturation of J AE , attenuation transitions, and tunable resistance peaks confirms strong carrier localization. Finally, these results establish SAWs as a powerful tool for controlling carrier dynamics in two-dimensional (2D) materials, paving the way for the development of time-dependent quantum systems and acoustic lattices for quantum simulation.

2D materials↗
DOE OSTI2024

Cooperative control of a DNA origami force sensor

Abstract Biomolecular systems are dependent on a complex interplay of forces. Modern force spectroscopy techniques provide means of interrogating these forces, but they are not optimized for studies in constrained environments as they require attachment to micron-scale probes such as beads or cantilevers. Nanomechanical devices are a promising alternative, but this requires versatile designs that can be tuned to respond to a wide range of forces. We investigate the properties of a nanoscale force sensitive DNA origami device which is highly customizable in geometry, functionalization, and mechanical properties. The device, referred to as the NanoDyn, has a binary (open or closed) response to an applied force by undergoing a reversible structural transition. The transition force is tuned with minor alterations of 1 to 3 DNA oligonucleotides and spans tens of picoNewtons (pN). The DNA oligonucleotide design parameters also strongly influence the efficiency of resetting the initial state, with higher stability devices (≳10 pN) resetting more reliably during repeated force-loading cycles. Finally, we show the opening force is tunable in real time by adding a single DNA oligonucleotide. These results establish the potential of the NanoDyn as a versatile force sensor and provide fundamental insights into how design parameters modulate mechanical and dynamic properties.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Efficient Langevin dynamics for “noisy” forces

Efficient Boltzmann-sampling using first-principles methods is challenging for extended systems due to the steep scaling of electronic structure methods with the system size. Additionally, stochastic approaches provide a gentler system-size dependency at the cost of introducing “noisy” forces, which could limit the efficiency of the sampling. When the forces are deterministic, the first-order Langevin dynamics (FOLD) offers efficient sampling by combining a well-chosen preconditioning matrix S with a time-step-bias-mitigating propagator [G. Mazzola and S. Sorella, Phys. Rev. Lett. 118, 015703 (2017)]. However, when forces are noisy, S is set equal to the force-covariance matrix, a procedure that severely limits the efficiency and the stability of the sampling. Here, we develop a new, general, optimal, and stable sampling approach for FOLD under noisy forces. We apply it for silicon nanocrystals treated with stochastic density functional theory and show efficiency improvements by an order-of-magnitude.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Birefringence in thermally anisotropic relativistic plasmas and its impact on laser–plasma interactions

One of the paradigm-shifting phenomena triggered in laser–plasma interactions at relativistic intensities is the so-called relativistic transparency. As the electrons become heated by the laser to relativistic energies, the plasma becomes transparent to the laser light even though the plasma density is sufficiently high to reflect the laser pulse in the non-relativistic case. This paper highlights the impact that relativistic transparency can have on laser-matter interactions by focusing on a collective phenomenon that is associated with the onset of relativistic transparency: plasma birefringence in thermally anisotropic relativistic plasmas. Here, the optical properties of such a system become dependent on the polarization of light, and this can serve as the basis for plasma-based optical devices or novel diagnostic capabilities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Nonthermal electron and ion acceleration by magnetic reconnection in large laser-driven plasmas

Magnetic reconnection is a fundamental plasma process that is thought to play a key role in the production of nonthermal particles associated with explosive phenomena in space physics and astrophysics. Experiments at high-energy-density facilities are starting to probe the microphysics of reconnection at high Lundquist numbers and large system sizes. We have performed particle-in-cell (PIC) simulations to explore particle acceleration for parameters relevant to laser-driven reconnection experiments. We study particle acceleration in large system sizes that may be produced soon with the most energetic laser drivers available, such as at the National Ignition Facility. In these conditions, we show the possibility of reaching the multi-plasmoid regime, where plasmoid acceleration becomes dominant. Our results show the transition from X point to plasmoid-dominated acceleration associated with the merging and contraction of plasmoids that further extend the maximum energy of the power-law tail of the particle distribution for electrons. We also find for the first time a system-size-dependent emergence of nonthermal ion acceleration in driven reconnection, where the magnetization of ions at sufficiently large sizes allows them to be contained by the magnetic field and energized by direct X point acceleration. For feasible experimental conditions, electrons and ions can attain energies of ϵ max , e / k B T e > 100 and ϵ max , i / k B T i > 1000 . Using PIC simulations with binary Monte Carlo Coulomb collisions, we study the impact of collisionality on plasmoid formation and particle acceleration. The implications of these results for understanding the role reconnection plays in accelerating particles in space physics and astrophysics are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Domain-specific compilers for dynamic simulations of quantum materials on quantum computers

Abstract Simulation of the dynamics of quantum materials is emerging as a promising scientific application for noisy intermediate-scale quantum (NISQ) computers. Due to their high gate-error rates and short decoherence times, however, NISQ computers can only produce high-fidelity results for those quantum circuits smaller than some given circuit size. Dynamic simulations, therefore, pose a challenge as current algorithms produce circuits that grow in size with each subsequent time-step of the simulation. This underscores the crucial role of quantum circuit compilers to produce executable quantum circuits of minimal size, thereby maximizing the range of physical phenomena that can be studied within the NISQ fidelity budget. Here, we present two domain-specific (DS) quantum circuit compilers for the Rigetti and IBM quantum computers, specifically designed to compile circuits simulating dynamics under a special class of time-dependent Hamiltonians. The compilers outperform state-of-the-art general-purpose compilers in terms of circuit size reduction by around 25%–30% as well as wall-clock compilation time by around 40% (dependent on system size and simulation time-step). Drawing on heuristic techniques commonly used in artificial intelligence, both compilers scale well with simulation time-step and system size. Code for both compilers is open-source and packaged into a full-stack quantum simulation software with tutorials included for ease of use for future researchers wishing to perform dynamic simulations of quantum materials on quantum computers. As our DS compilers provide significant improvements in both compilation time and simulation fidelity, they provide a building block for accelerating progress toward physical quantum supremacy.

Physics↗
DOE OSTI2026

Data-driven method to estimate contamination from light ion beam transmutation at colliders

Collisions of relativistic light ions, such as oxygen, neon, and magnesium, have been proposed as a way to examine the system-size dependence of dynamics typically associated with the quark-gluon plasma produced in collisions of heavier ions such as xenon, gold, or lead. Recent efforts at both the Relativistic Heavy Ion Collider (RHIC) and Large Hadron Collider (LHC) have produced large datasets of proton-oxygen, oxygen-oxygen, and neon-neon collisions, catalyzing intense interest in experimental backgrounds associated with light-ion collisions. In particular, electromagnetic dissociation of light ions while they are circulating in a collider can result in beam contamination that is difficult to simulate precisely. Here we propose a data-driven method for evaluating the potential impact of beam contaminants on physics analyses. The method exploits the time dependence and smaller size of contaminant ion species to define control regions that can be used to quantify potential contamination effects. A simple model is used to illustrate the method and to study its robustness. Furthermore, this method can inform studies of recent LHC and RHIC data and could also be useful for future light-ion programs at the LHC and beyond.

Beam loss↗
DOE OSTI2022

Λ spin polarization in event-by-event relativistic heavy-ion collisions

We present a systematic study of $\Lambda$ hyperon's polarization observables using event-by-event (3+1)D relativistic hydrodynamics. The effects of initial hot spot size and QGP's specific shear viscosity on the polarization observables are quantified. We examine the effects of the two formulations of the thermal shear tensor on the polarization observables using the same hydrodynamic background. With event-by-event simulations, we make predictions for the Fourier coefficients of $\Lambda$'s longitudinal polarization $P^z$ with respect to the event planes of different orders of anisotropic flow. We propose new correlations among the Fourier coefficients of $P^z$ and charged hadron anisotropic flow coefficients to further test the mapping from fluid velocity gradients to hyperon's polarization. Finally, we present a system size scan with Au+Au, Ru+Ru, and O+O collisions at $\sqrt{s_\mathrm{NN}} = 200$ GeV to study the system size dependence of polarization observables at the Relativistic Heavy-ion Collider.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗