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DOE OSTI2026

A Faster-Than-Real-Time Framework for Reliability-Oriented Simulation of PV Inverters

Physics-of-Failure (PoF) based reliability assessment for photovoltaic (PV) inverters requires long-duration electrical and electrothermal stress histories, yet generating such stress histories with high-fidelity switching models over year long mission profiles is computationally prohibitive. Conventional methods either sacrifice modeling fidelity for speed or require runtimes that are impractical for design iteration and uncertainty studies. To address this bottleneck, this paper presents a High-Performance Computing (HPC) based simulation frame work for faster-than-real-time reliability-oriented simulation. The proposed framework integrates the Average-to-Switching (A2S) method with parallel computing techniques to accelerate switching-level waveform reconstruction. We further introduce optimization strategies, including cluster merging and sensitivity based mission profile screening, to reduce the computational burden. Evaluated using real-world mission profile inputs and a MATLAB/Simulink switching-model reference, the framework reduces the simulation time for a one-year mission from an intractable multi-year duration to approximately 7.3 minutes while maintaining low waveform error. This acceleration provides a practical reliability-oriented simulation engine that can be coupled with component-specific aging models for subsequent PV inverter PoF assessment.

High-performance Computing↗

DOE OSTI2026

Dual particle imaging using time-of-flight neutron classification

Fast-neutron imaging technology is well-suited for passive nuclear material monitoring, secondary inspection of flagged cargo, and wide-area search for lost neutron sources. However, imaging systems that use pulse shape discrimination for event classification require complex pulse waveform analysis. In this work, we evaluate time-of-flight (TOF) based particle classification as an alternative solution for fast-neutron imaging by classifying all events with a TOF above a maximum threshold as neutrons. We measured a Cf-252 source next to Cs-137 using a 12-bar organic-glass scintillator array. By varying the TOF thresholds for neutron identification, we demonstrate a clear trade-off between event yield and backprojection image fidelity, with stricter thresholds improving precision at the cost of statistics, TOF thresholded data generated an image that predicted the neutron source direction with 20% reduced mean central angle prediction error compared to a traditional pulse shape discrimination (PSD) method with comparable event count. Time-of-flight particle classification shows promise as an alternative to pulse shape discrimination systems for fast neutron imaging systems looking to minimize costs and size of electronics with comparable imaging quality. The sources used demonstrate that the method is effective in classifying measured neutrons in a measurement environment with 150 μCi Cs-137 and 1.6 × 10 6 n/s Cf-252 sources positioned at distances of 66 cm and 81 cm from the detector. Additionally, the method classifies low-energy neutron events that pulse shape discrimination removes, so a combination of both methods would result in a higher overall neutron event efficiency.

Heriot, William [Univ. of Michigan, Ann Arbor, MI ↗

DOE OSTI2025

Plasma shape and position control development for NSTX-U using the GSEvolve plasma simulator

NSTX-U discharges have been reproduced using the GSEvolve plasma simulator in order to improve their control and reduce oscillations during the plasma current (Ip) ramp-up phase, and with the ultimate goal of enabling reliable H-mode access with a double-null shape at high elongation, low internal inductance, and high plasma performance. The control objective is to eliminate undesired oscillations in the plasma shape and vertical position that start when the plasma diverts during the Ip ramp-up phase, and that happened recurrently during the first NSTX-U experimental campaign. Model-based control solutions have been developed, including alternative H-mode access recipes and a Multi-Input Multi-Output (MIMO) decoupling controller. These solutions have demonstrated their capability to reduce or eliminate the aforementioned oscillations in GSEvolve simulations, enabling reproducible H-mode access. The results of this work aim to inform NSTX-U experimental operations on potential control developments to maximize its scientific output, and highlight the powerful capabilities of high-fidelity control-simulation frameworks like GSEvolve.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Fiber loop quantum buffer for photonic qubits

Abstract We report a fiber loop quantum buffer based on a low-loss 2 × 2 switch and a unit delay made of a fiber delay line. We characterize the device by using a two-photon polarization entangled state in which one photon of the entangled photon pair is stored and retrieved at a repetition rate up to 78 kHz. The device, which enables integer multiples of a unit delay, can store the qubit state in a unit of fiber delay line up to 5.4 km and the number of loop round-trips up to 3. Furthermore, we configure the device with other active elements to realize integer multiplier and divider of a unit delay of a qubit. The quantum state tomography is performed on the retrieved photon and its entangled photon. We obtain a state fidelity > 94 % with a maximum storage time of 52 s with an insertion loss of 5.56 dB. To further characterize the storing and retrieving processes of the device, we perform entanglement-assisted quantum process tomography on the buffered qubit state. The process fidelity of the device is > 0.98. Our result implies that the device preserves the superposition and entanglement of a qubit state from a two-photon polarization-entangled state. This is a significant step towards facilitating applications in optical asynchronous transfer mode based quantum networks.

Fook Lee, Kim (ORCID:0000000290901640)↗

DOE OSTI2020

Backscatter-Immune Injection-Locked Brillouin Laser in Silicon

As self-sustained oscillators, lasers possess the unusual ability to spontaneously synchronize. These nonlinear dynamics are the basis for a simple yet powerful stabilization technique known as injection locking, in which a laser’s frequency and phase can be controlled by an injected signal. Because of its inherent simplicity and favorable noise characteristics, injection locking has become a workhorse for coherent amplification and high-fidelity signal synthesis in applications ranging from precision atomic spectroscopy to distributed sensing. Within integrated photonics, however, these injection-locking dynamics remain relatively untapped—despite significant potential for technological and scientific impact. In this work, we demonstrate injection locking in a silicon photonic Brillouin laser. Injection locking of this monolithic device is remarkably robust, allowing us to tune the laser emission by a significant fraction of the Brillouin gain bandwidth. Harnessing these dynamics, we demonstrate amplification of small signals by more than 23 dB. Moreover, we demonstrate that the injection-locking dynamics of this system are inherently nonreciprocal, yielding unidirectional control and backscatter immunity in an all-silicon system. This device physics opens the door to strategies for phase-noise reduction, low-noise amplification, and backscatter immunity in silicon photonics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Effectiveness of denoising diffusion probabilistic models for fast and high-fidelity whole-event simulation in high-energy heavy-ion experiments

Artificial intelligence (AI) generative models, such as generative adversarial networks (GANs), variational autoencoders, and normalizing flows, have been widely used and studied as efficient alternatives for traditional scientific simulations. However, they have several drawbacks, including training instability and inability to cover the entire data distribution, especially for regions where data are rare. This is particularly challenging for whole-event, full-detector simulations in high-energy heavy-ion experiments, such as sPHENIX at the Relativistic Heavy Ion Collider and Large Hadron Collider experiments, where thousands of particles are produced per event and interact with the detector. This work investigates the effectiveness of denoising diffusion probabilistic models (DDPMs) as an AI-based generative surrogate model for the sPHENIX experiment that includes the heavy-ion event generation and response of the entire calorimeter stack. DDPM performance in sPHENIX simulation data is compared with a popular rival, GANs. Results show that both DDPMs and GANs can reproduce the data distribution where the examples are abundant (low-to-medium calorimeter energies). Nonetheless, DDPMs significantly outperform GANs, especially in high-energy regions where data are rare. Additionally, DDPMs exhibit superior stability compared to GANs. The results are consistent between both central and peripheral centrality heavy-ion collision events. Moreover, DDPMs offer a substantial speedup of approximately a factor of 100 compared to the traditional Geant4 simulation method.

42 ENGINEERING↗

DOE OSTI2024

In-situ strain behavior and BISON simulations of Zircaloy cladding subjected to temperature cycling separate-effects tests in a steam environment

Understanding fuel system performance during anticipated transients without scram (ATWSs) in boiling water reactors (BWRs) is necessary for refining current and future safety limits. High-fidelity material models and simulations are fundamental to rigorous assessment of zirconium-based cladding performance. However, experimental thermomechanical data during simulated ATWSs to validate these modes are limited. To provide relevant in-situ data, Zircaloy-4 cladding was subjected to cyclic heating in a steam environment to simulate an out-of-pile BWR ATWS. Digital image correlation was used to capture the cladding strain behavior in-situ for comparison against simulations using the BISON finite element code. Conventional high-temperature models were compared using multiple schemes to gain a better understanding of the applicability of three BISON models to BWR ATWS: (1) the default combination of creep models in BISON, (2) the high-temperature Erbacher model alone, and (3) the low-temperature Limback-Andersson model alone. The cases run with the Limback-Andersson model alone produced the lowest root mean square error (RMSE). The lowest RMSE for the Limback-Andersson model alone was 0.659%, and the highest RMSE reported was 4.22%. A data gap within the model in the temperature regime of interest was also identified, and to account for this gap, the current model in BISON is linearly interpolated between two separate datasets. In conclusion, this evaluation highlights the need to either develop a new model or to improve the existing model to capture transient creep effects resulting from a cyclic temperature transient.

Anticipated transient without SCRAM↗

DOE OSTI2020

Low-energy physics of isotropic spin-1 chains in the critical and Haldane phases

Using a matrix product state algorithm with infinite boundary conditions, we compute high-resolution dynamic spin and quadrupolar structure factors in the thermodynamic limit to explore the low-energy excitations of isotropic bilinear-biquadratic spin-1 chains. Haldane mapped the spin-1 Heisenberg antiferromagnet to a continuum field theory, the nonlinear sigma model (NLσM). In this work, we find that the NLσM fails to capture the influence of the biquadratic term and provides only an unsatisfactory description of the Haldane phase physics. But several features in the Haldane phase can be explained by noninteracting multimagnon states. The physics at the Uimin-Lai-Sutherland point is characterized by multisoliton continua. Moving into the extended critical phase, we find that these excitation continua contract, which we explain using a field-theoretic description. New excitations emerge at higher energies and, in the vicinity of the purely biquadratic point, they show simple cosine dispersions. Using block fidelities, we identify them as elementary one-particle excitations and relate them to the integrable Temperley-Lieb chain.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2022

Evaluation of the Effect of Burnup Acceleration on UO 2 Microstructure Evolution

Accelerated fuel qualification (AFQ) is a methodology by which new nuclear fuels are developed in an accelerated time frame compared with historical fuel qualification approaches. AFQ generally relies on high-fidelity physics-based modeling and simulation tools to adequately describe fuel performance as well as on revolutionary methods to accelerate burnup accumulation and collect relevant data more quickly. This report summarizes the use of advanced fuel modeling and simulation tools to evaluate microstructures from commercially irradiated fuel and microstructures from proposed MiniFuel irradiations, in which burnup accumulation is accelerated while prototypic temperature conditions are maintained. In this milestone, we used the mesoscale fuel performance code MARMOT to model the evolution of irradiated UO 2 microstructures and their potential restructuring at high burnup. The simulation conditions were informed by BISON models of both commercially irradiated fuel and MiniFuel. A first set of simulations investigated the recrystallization behavior of fully dense microstructures and showed full recrystallization at burnups as low as 52 MWd/kgU at 950°C. However, these simulations did not account for the presence of fission gas bubbles (predicted by BISON). Therefore, a second set of simulations including fission gas bubbles was performed and indicated that at the lowest temperature considered (650°C), the porous UO 2 microstructures have the highest total Gibbs free energies and are likely to recrystallize earlier than higher temperature cases (800 and 950°C), which agrees with high-burnup fuel characterization data. The results also showed that at lower temperature (650°C), the total free energies of the PWR fuel and MiniFuel microstructures are not significantly different. However, at the highest temperature (950°C), MiniFuel microstructures have a lower free energy than that of the PWR fuel microstructure. The competing effects between the temperature-dependent grain nucleation rate and the reduction of the free energy of the microstructure at higher temperature as a result of diffusion indicated that restructuring may occur at even higher temperatures than those considered in this study. In addition to the microstructure evolution modeling efforts, the burnup gradient across a single fuel specimen was also considered. This evaluation was for the VXF-15 position of the High Flux Isotope Reactor (HFIR) using the code suite HFIRCON, which was developed to automate the workflow for evaluating targets and fuel as they are irradiated in HFIR. The burnup gradient evaluation showed a dependence on both the axial and radial locations within the specimen, with a maximum difference of 1.7 between the inner and outermost radial layers. This relationship was further supported by considering the fission product speciation with respect to location within the specimen, which showed a higher concentration of 239 Pu, 240 Pu, and 241 Pu on the outer radial locations of the specimen than the center. The findings of the burnup and speciation evaluation show that some amount of self-shielding is occurring in the specimen when irradiated in the high-flux environment of HFIR; however, this impact is more pronounced for natural uranium when compared to 6% enrichment due to the higher ratio of 238 U in the specimen. Further analyses are required to understand the sensitivity of this gradient to spatial mesh and enrichment of the specimen.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

Dust Reverberation Mapping in Distant Quasars from Optical and Mid-infrared Imaging Surveys

The size of the dust torus in active galactic nuclei (AGNs) and their high-luminosity counterparts, quasars, can be inferred from the time delay between UV/optical accretion disk continuum variability and the response in the mid-infrared (MIR) torus emission. This dust reverberation mapping (RM) technique has been successfully applied to ~70 z ≲ 0.3 AGNs and quasars. Here we present first results of our dust RM program for distant quasars covered in the Sloan Digital Sky Survey Stripe 82 region combining ~20 yr ground-based optical light curves with 10 yr MIR light curves from the WISE satellite. Here, we measure a high-fidelity lag between W1 band (3.4 μm) and g band for 587 quasars over 0.3 ≲ z ≲ 2 () and two orders of magnitude in quasar luminosity. They tightly follow (intrinsic scatter ~0.17 dex in lag) the IR lag–luminosity relation observed for z < 0.3 AGNs, revealing a remarkable size–luminosity relation for the dust torus over more than four decades in AGN luminosity, with little dependence on additional quasar properties such as Eddington ratio and variability amplitude. This study motivates further investigations in the utility of dust RM for cosmology and strongly endorses a compelling science case for the combined 10 yr Vera C. Rubin Observatory Legacy Survey of Space and Time (optical) and 5 yr Nancy Grace Roman Space Telescope 2 μm light curves in a deep survey for low-redshift AGN dust RM with much lower luminosities and shorter, measurable IR lags. The compiled optical and MIR light curves for 7384 quasars in our parent sample are made public with this work.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Synchrotron micro-computed tomography analysis of neutron-irradiated U-Mo fuel

The three-dimensional (3D) microstructure of neutron-irradiated uranium-10 wt.% molybdenum (U-10Mo) fuel with a burn-up of 9.8 × 10 21 fissions/cm 3 was characterized using a novel, multi-modal synchrotron micro-computed tomography approach combining propagation-based phase-contrast enhanced and absorption contrast techniques. The porosity development, porosity interconnectedness, swelling, composition, local thickness of the zirconium (Zr) diffusion barrier, and the influence of the fuel–cladding interaction on the local composition and pore morphology, were uniquely determined in 3D. Two cuboids were produced using a focused ion beam-scanning electron microscope at the Zr diffusion barrier–fuel interface and in the bulk fuel. The bulk fuel sample swelled by 53.3 [+9.7/−3.1]%, while the fuel near the Zr–fuel interface swelled by 63.3 [+14.7/−7.2]%. The average local thickness of the Zr diffusion barrier decreased by 53 %, compared to the expected pre-irradiated thickness. Four pore morphology regions were identified initiating parallel to the fuel–Zr interaction region: (1) an interaction layer of suppressed porosity, (2) a layer of elongated and interconnected porosity, (3) a transition zone of low porosity, and (4) a layer of unoriented porosity representative of the bulk fuel behavior. The increase in porosity near the diffusion barrier corresponded to a higher U concentration compared to that in the bulk fuel. The interconnected porosity in the fuel near the diffusion barrier was extensive and oriented parallel to the diffusion barrier, while the bulk fuel had more compact and isolated pore networks. The interaction layer, despite having suppressed porosity, was nearly 100 wt.% U. Porosity suppression at the diffusion barrier corresponds to the expected reduction in radiation-driven diffusion of Xe at the interface despite the anticipated increase in fission product nucleation originating from a higher U concentration. In conclusion, the novel 3D insights of the porosity, swelling, and compositional variations characterized herein can improve the fidelity of fuel performance codes for proliferation-resistant fuels for research and test reactors.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

QASMBench: A Low-Level Quantum Benchmark Suite for NISQ Evaluation and Simulation

The rapid development of quantum computing (QC) in the NISQ era urgently demands a low-level benchmark suite and insightful evaluation metrics for characterizing the properties of prototype NISQ devices, the efficiency of QC programming compilers, schedulers and assemblers, and the capability of quantum system simulators in a classical computer. In this work, we fill this gap by proposing a low-level, easy-to-use benchmark suite called QASMBench based on the OpenQASM assembly representation. It consolidates commonly used quantum routines and kernels from a variety of domains including chemistry, simulation, linear algebra, searching, optimization, arithmetic, machine learning, fault tolerance, cryptography, and so on, trading-off between generality and usability. To analyze these kernels in terms of NISQ device execution, in addition to circuit width and depth, we propose four circuit metrics including gate density, retention lifespan, measurement density, and entanglement variance, to extract more insights about the execution efficiency, the susceptibility to NISQ error, and the potential gain from machine-specific optimizations. Applications in QASMBench can be launched and verified on several NISQ platforms, including IBM-Q, Rigetti, IonQ and Quantinuum. For evaluation, we measure the execution fidelity of a subset of QASMBench applications on 12 IBM-Q machines through density matrix state tomography, comprising 25K circuit evaluations. In addition we also compare the fidelity of executions among the IBM-Q machines, the IonQ QPU and the Rigetti Aspen M-1 system.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

C3MechLite: An integrated component library of compact kinetic mechanisms for low-carbon, carbon neutral and zero-carbon fuels

Based on our latest detailed chemical reaction mechanism, C3MechV4.0, we have developed two reduced reaction mechanisms—C3MechLite and C3MechCore—targeting C 0 –C 3 chemical species including NH 3 . C3MechLite (61 species), contains a number of species comparable to GRI-Mech (53 species), that can accurately predict the combustion characteristics of hydrogen, carbon monoxide, ammonia, methane, natural gas, nitrogen oxides, and their mixtures for a wide range of conditions. C3MechCore (118 species) targets a more comprehensive range of C 0 –C 3 fuels, including ammonia, methanol, ethanol, and dimethyl ether. Both mechanisms demonstrate predictive accuracy comparable to C3MechV4.0 for the combustion characteristics of the target fuels. C3MechLite is designed with a component library structure, enabling further reduction in mechanism size depending on the fuel(s) of interest for 2D/3D numerical simulations. Various combinations of component libraries were validated, and the average prediction error remains within 1 % compared to C3MechLite. Furthermore, the mechanism was applied to 3D LES simulations of H 2 lifted flames and was confirmed to reproduce flame characteristics with high accuracy. C3MechLite and its component library structure enable high-fidelity and computationally efficient chemical kinetic mechanisms, paving the way for application in more complex combustion simulations.

Ammonia↗

DOE OSTI2025

LLRF System Analysis for the Fermilab PIP-II LINAC

Developing long-lived quantum processing units (QPUs) capable of supporting high-fidelity quantum operations is a crucial challenge on the path toward fault-tolerant quantum computing. TESLA-shaped superconducting RF (SRF) cavities, known for photon relaxation times on the order of seconds, provide an excellent foundation for 3D QPUs and quantum memory. This talk presents a novel design that leverages TESLA cavity modes coupled to ancillary transmon qubits, optimized to preserve coherence and control. By carefully engineering the package geometry, optimizing Hamiltonian parameters, and minimizing lossy participation ratios, we achieve photon relaxation times of over 16 ms and 20 ms for the two cavity modes, representing a significant improvement over previous multimode quantum memories. Despite the reduced coupling between the qubit and cavity modes, which is necessary to preserve long lifetimes, the platform supports robust and universal control schemes that are not limited by low coupling strength. We will also discuss how this architecture can lead to scalable, modular quantum computing systems.

Varghese, P. [Fermilab]↗

DOE OSTI2024

Probabilistic projections of the Amery Ice Shelf catchment, Antarctica, under conditions of high ice-shelf basal melt

Abstract. Antarctica's Lambert Glacier drains about one-sixth of the ice from the East Antarctic Ice Sheet and is considered stable due to the strong buttressing provided by the Amery Ice Shelf. While previous projections of the sea-level contribution from this sector of the ice sheet have predicted significant mass loss only with near-complete removal of the ice shelf, the ocean warming necessary for this was deemed unlikely. Recent climate projections through 2300 indicate that sufficient ocean warming is a distinct possibility after 2100. This work explores the impact of parametric uncertainty on projections of the response of the Lambert–Amery system (hereafter “the Amery sector”) to abrupt ocean warming through Bayesian calibration of a perturbed-parameter ice-sheet model ensemble. We address the computational cost of uncertainty quantification for ice-sheet model projections via statistical emulation, which employs surrogate models for fast and inexpensive parameter space exploration while retaining critical features of the high-fidelity simulations. To this end, we build Gaussian process (GP) emulators from simulations of the Amery sector at a medium resolution (4–20 km mesh) using the Model for Prediction Across Scales (MPAS)-Albany Land Ice (MALI) model. We consider six input parameters that control basal friction, ice stiffness, calving, and ice-shelf basal melting. From these, we generate 200 perturbed input parameter initializations using space filling Sobol sampling. For our end-to-end probabilistic modeling workflow, we first train emulators on the simulation ensemble and then calibrate the input parameters using observations of the mass balance, grounding line movement, and calving front movement with priors assigned via expert knowledge. Next, we use MALI to project a subset of simulations to 2300 using ocean and atmosphere forcings from a climate model for both low- and high-greenhouse-gas-emission scenarios. From these simulation outputs, we build multivariate emulators by combining GP regression with principal component dimension reduction to emulate multivariate sea-level contribution time series data from the MALI simulations. We then use these emulators to propagate uncertainty from model input parameters to predictions of glacier mass loss through 2300, demonstrating that the calibrated posterior distributions have both greater mass loss and reduced variance compared to the uncalibrated prior distributions. Parametric uncertainty is large enough through about 2130 that the two projections under different emission scenarios are indistinguishable from one another. However, after rapid ocean warming in the first half of the 22nd century, the projections become statistically distinct within decades. Overall, this study demonstrates an efficient Bayesian calibration and uncertainty propagation workflow for ice-sheet model projections and identifies the potential for large sea-level rise contributions from the Amery sector of the Antarctic Ice Sheet after 2100 under high-greenhouse-gas-emission scenarios.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Explicit structure-preserving geometric particle-in-cell algorithm in curvilinear orthogonal coordinate systems and its applications to whole-device 6D kinetic simulations of tokamak physics

Explicit structure-preserving geometric particle-in-cell (PIC) algorithm in curvilinear orthogonal coordinate systems is developed. The work reported represents a further development of the structure-preserving geometric PIC algorithm achieving the goal of practical applications in magnetic fusion research. The algorithm is constructed by discretizing the field theory for the system of charged particles and electromagnetic field using Whitney forms, discrete exterior calculus, and explicit non-canonical symplectic integration. In addition to the truncated infinitely dimensional symplectic structure, the algorithm preserves exactly many important physical symmetries and conservation laws, such as local energy conservation, gauge symmetry and the corresponding local charge conservation. As a result, the algorithm possesses the long-term accuracy and fidelity required for first-principles-based simulations of the multiscale tokamak physics. The algorithm has been implemented in the SymPIC code, which is designed for high-efficiency massively-parallel PIC simulations in modern clusters. The code has been applied to carry out whole-device 6D kinetic simulation studies of tokamak physics. A self-consistent kinetic steady state for fusion plasma in the tokamak geometry is numerically found with a predominately diagonal and anisotropic pressure tensor. The state also admits a steady-state sub-sonic ion flow in the range of 10 km s -1 , agreeing with experimental observations and analytical calculations Kinetic ballooning instability in the self-consistent kinetic steady state is simulated. It is shown that high-n ballooning modes have larger growth rates than low-n global modes, and in the nonlinear phase the modes saturate approximately in 5 ion transit times at the 2% level by the E × B flow generated by the instability. These results are consistent with early and recent electromagnetic gyrokinetic simulations.

43 PARTICLE ACCELERATORS↗

DOE OSTI2022

Quantum Krylov subspace algorithms for ground- and excited-state energy estimation

Quantum Krylov subspace diagonalization (QKSD) algorithms provide a low-cost alternative to the conventional quantum phase estimation algorithm for estimating the ground- and excited-state energies of a quantum many-body system. While QKSD algorithms typically rely on using the Hadamard test for estimating Krylov subspace matrix elements of the form $\langle \phi_i|e^{-\widehat{H}τ}|\phi_j\rangle$, the associated quantum circuits require an ancilla qubit with controlled multiqubit gates that can be quite costly for near-term quantum hardware. In this paper, we show that a wide class of Hamiltonians relevant to condensed-matter physics and quantum chemistry contain symmetries that can be exploited to avoid the use of the Hadamard test. We propose a multifidelity estimation protocol that can be used to compute such quantities, showing that our approach, when combined with efficient single-fidelity estimation protocols, provides a substantial reduction in circuit depth. In addition, here we develop a unified theory of quantum Krylov subspace algorithms and present three quantum-classical algorithms for the ground- and excited-state energy estimation problems, where each algorithm provides various advantages and disadvantages in terms of total number of calls to the quantum computer, gate depth, classical complexity, and stability of the generalized eigenvalue problem within the Krylov subspace.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

The Critical Need for Innovations in Instruments and Techniques to Enable In-Situ Cold Ion and Cold Electron Measurements within the Magnetosphere

Relatively few studies have focused on the cold plasma populations of the magnetosphere due to difficulties associated with obtaining measurements. The cold particle populations are defined here as those with total energy approximately <100 eV which is an energy range for which measurements are difficult (regardless of species), but which often make up the bulk of the plasma density. These populations have known and suspected impacts on the structure and dynamics of the magnetosphere. Unfortunately, the lack of accurate measurements of the cold ion and cold electron populations through the magnetosphere makes closure of these science questions extremely difficult if not impossible. In a complex system of interconnected parts like the Earth’s magnetosphere, a lack of understanding of one part of the system (the cold electron and ion populations) is disabling. Hence, until cold electron and cold ion measurements are obtained robustly with every mission, the magnetospheric plasma environment cannot be completely understood. This will require innovations in plasma spectrometers and associated techniques required to obtain high-fidelity in-situ measurements of the cold ion and cold electron populations in the magnetosphere. This paper seeks to review the instruments and techniques that have been used to date and present possible options for future missions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗