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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Five-second coherence of a single spin with single-shot readout in silicon carbide

An outstanding hurdle for defect spin qubits in silicon carbide (SiC) is single-shot readout, a deterministic measurement of the quantum state. Here, we demonstrate single-shot readout of single defects in SiC via spin-to-charge conversion, whereby the defect’s spin state is mapped onto a long-lived charge state. With this technique, we achieve over 80% readout fidelity without pre- or postselection, resulting in a high signal-to-noise ratio that enables us to measure long spin coherence times. Combined with pulsed dynamical decoupling sequences in an isotopically purified host material, we report single-spin T 2 > 5 seconds, over two orders of magnitude greater than previously reported in this system. The mapping of these coherent spin states onto single charges unlocks both single-shot readout for scalable quantum nodes and opportunities for electrical readout via integration with semiconductor devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Toward machine-learning-assisted PW-class high-repetition-rate experiments with solid targets

We present progress in utilizing a machine learning (ML) assisted optimization framework to study the trends in a parameter space defined by spectrally shaped, high-intensity, petawatt-class (8 J, 45 fs) laser pulses interacting with solid targets and give the first simulation-based overview of predicted trends. A neural network (NN) incorporating uncertainty quantification is trained to predict the number of hot electrons generated by the laser–target interaction as a function of pulse shaping parameters. The predictions of this NN serve as the basis function for a Bayesian optimization framework to navigate this space. For post-experimental evaluation, we compare two separate neural network (NN) models. One is based solely on data from experiments, and the other is trained only on ensemble particle-in-cell simulations. Reviewing the predicted and observed trends across the experiment-capable laser parameter search space, we find that both ML models predict a maximal increase in hot electron generation at a level of approximately 12%–18%; however, no statistically significant enhancement was observed in experiments. On direct comparison of the NN models, the average discrepancy is 8.5%, with a maximum of 30%. Since shot-to-shot fluctuations in experiments affect the observations, we evaluate the behavior of our optimization framework by performing virtual experiments that vary the number of repeated observations and the noise levels. Here, we discuss the implications of such a framework for future autonomous exploration platforms in high-repetition-rate experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

High-energy, low-jitter, narrowband ps probe laser for kHz-rate fs/ps coherent anti-Stokes Raman scattering

Hybrid fs/ps coherent anti-Stokes Raman scattering (CARS) thermometry often utilizes ps probe pulses derived from pulse shaping or spectrally filtering the primary laser source or by synchronization with a low repetition rate external laser. This results in limited energy, spectral resolution, and/or repetition rate of the ps probe. In this work, a master-oscillator power-amplifier (MOPA) laser was synchronized to the oscillator of a Ti:sapphire regenerative amplifier to achieve high-energy (600 µJ), narrowband (58 ps) probe pulses at kHz repetition rates. Furthermore, temporal filtering allows the pulse characteristics to be adjusted for each application. At 25 Torr, relevant to high-speed flows, the kHz-rate MOPA system generated signal-to-noise ratios 3× higher in nitrogen and had improved precision relative to a 10 ps probe derived from spectral filtering and the power-amplifier. The MOPA system also enabled single-shot ro-vibrational hybrid fs/ps CARS thermometry in 650 K heated air.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

An Adaptive Optimizer for Measurement-Frugal Variational Algorithms

Variational hybrid quantum-classical algorithms (VHQCAs) have the potential to be useful in the era of near-term quantum computing. However, recently there has been concern regarding the number of measurements needed for convergence of VHQCAs. Here, we address this concern by investigating the classical optimizer in VHQCAs. We introduce a novel optimizer called individual Coupled Adaptive Number of Shots (iCANS). This adaptive optimizer frugally selects the number of measurements (i.e., number of shots) both for a given iteration and for a given partial derivative in a stochastic gradient descent. We numerically simulate the performance of iCANS for the variational quantum eigensolver and for variational quantum compiling, with and without noise. In all cases, and especially in the noisy case, iCANS tends to out-perform state-of-the-art optimizers for VHQCAs. We therefore believe this adaptive optimizer will be useful for realistic VHQCA implementations, where the number of measurements is limited.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Inference-Based Quantum Sensing

In a standard quantum sensing (QS) task one aims at estimating an unknown parameter θ, encoded into an n-qubit probe state, via measurements of the system. The success of this task hinges on the ability to correlate changes in the parameter to changes in the system response $\mathscr{R}$⁡(θ) (i.e., changes in the measurement outcomes). For simple cases the form of $\mathscr{R}$⁡(θ) is known, but the same cannot be said for realistic scenarios, as no general closed-form expression exists. Here, in this Letter, we present an inference-based scheme for QS. We show that, for a general class of unitary families of encoding, $\mathscr{R}$⁡(θ) can be fully characterized by only measuring the system response at 2⁢n+1 parameters. This allows us to infer the value of an unknown parameter given the measured response, as well as to determine the sensitivity of the scheme, which characterizes its overall performance. We show that inference error is, with high probability, smaller than δ, if one measures the system response with a number of shots that scales only as Ω⁢(log 3 ⁡(n)/δ 2 ). Furthermore, the framework presented can be broadly applied as it remains valid for arbitrary probe states and measurement schemes, and, even holds in the presence of quantum noise. We also discuss how to extend our results beyond unitary families. Finally, to showcase our method we implement it for a QS task on real quantum hardware, and in numerical simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Enhancement of detachment control with simplified real-time modelling on the KSTAR tokamak

Abstract Detachment control based on ion saturation current I sat measurements from Langmuir probes (LPs) is implemented in the KSTAR tokamak and shown to be capable of following dynamic and constant target trajectories with good accuracy, in H-mode, by moderating the flow rate of nitrogen or deuterium. I sat controllers normalize I sat in order to form attachment fraction ( A frac ) as their control parameter. The KSTAR implementation of A frac control differs from previous work in that it continuously calculates a model for attached I sat and uses that as the denominator in A frac , whereas prior implementations either record peak I sat at rollover as they pass it or take estimated I s a t , r o l l o v e r as a manual input prior to the shot. The KSTAR controller therefore does not need to keep track of rollover status and keep separate targets for pre- and post-rollover states, and it can automatically adapt to changes in scenario at any time. It is also less vulnerable to noise as it will not lock in an outlier as a rollover point.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Radiation, optical, power flow, and electrical diagnostics at the Z facility: Layout and techniques utilized to operate in the harsh environment

The Z machine is a current driver producing up to 30 MA in 100 ns that utilizes a wide range of diagnostics to assess accelerator performance and target behavior conduct experiments that use the Z target as a source of radiation or high pressures. Here, we review the existing suite of diagnostic systems, including their locations and primary configurations. The diagnostics are grouped in the following categories: pulsed power diagnostics, x-ray power and energy, x-ray spectroscopy, x-ray imaging (including backlighting, power flow, and velocimetry), and nuclear detectors (including neutron activation). We will also briefly summarize the primary imaging detectors we use at Z: image plates, x-ray and visible film, microchannel plates, and the ultrafast x-ray imager. The Z shot produces a harsh environment that interferes with diagnostic operation and data retrieval. We term these detrimental processes “threats” of which only partial quantifications and precise sources are known. Finally, we summarize the threats and describe techniques utilized in many of the systems to reduce noise and backgrounds.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

End-to-end protocol for high-quality quantum approximate optimization algorithm parameters with few shots

The quantum approximate optimization algorithm (QAOA) is a quantum heuristic for combinatorial optimization that has been demonstrated to scale better than state-of-the-art classical solvers for some problems. For a given problem instance, QAOA performance depends crucially on the choice of the parameters. While average-case optimal parameters are available in many cases, meaningful performance gains can be obtained by fine-tuning these parameters for a given instance. This task is especially challenging, however, when the number of circuit executions (shots) is limited. In this work, we develop an end-to-end protocol that combines multiple parameter settings and fine-tuning techniques. We use large-scale numerical experiments to optimize the protocol for the shot-limited setting and observe that optimizers with the simplest internal model (linear) perform best. We implement the optimized pipeline on a trapped-ion processor using up to 32 qubits and 5 QAOA layers, and we demonstrate that the pipeline is robust to small amounts of hardware noise. To the best of our knowledge, these are the largest demonstrations of QAOA parameter fine-tuning on a trapped-ion processor in terms of two-qubit gate count.

quantum algorithms & computation↗
DOE OSTI2025

Single-shot femtosecond laser-induced breakdown spectroscopy in low-density gases

Single-shot fs laser-induced breakdown spectroscopy (LIBS) has been used to interrogate low-density gases of H 2 ⁠, CH 4 ⁠, CO 2 ⁠, and H 2 O ranging from 0.5 × 10 15 to 9.1 × 10 15 cm −3 (15–275 mTorr). Strong spectral signatures were observed above the noise baseline for each test gas at all densities considered. Unique molecular signatures were observed for both CH 4 and CO 2 along with atomic features for each gas. The LIBS intensity response with respect to density was determined for each species using Voigt lineshape fitting or numerical integration. Finally, the collection and analysis of LIBS spectra of composite mixtures of CH 4 –CO 2 and CH 4 –H 2 demonstrates that the extraction of individual densities from gas mixtures is feasible at low densities.

Artificial neural networks↗
DOE OSTI2023

Inferring Quantum Network Topology Using Local Measurements

Statistical correlations that can be generated across the nodes in a quantum network depend crucially on its topology. However, this topological information might not be known a priori, or it may need to be verified. In this paper, we propose an efficient protocol for distinguishing and inferring the topology of a quantum network. We leverage entropic quantities-namely, the von Neumann entropy and the measured mutual information-as well as measurement covariance to uniquely characterize the topology. We show that the entropic quantities are sufficient to distinguish two networks that prepare GHZ states. Moreover, if qubit measurements are available, both entropic quantities and covariance can be used to infer the network topology without state-preparation assumptions. We show that the protocol can be entirely robust to noise and can be implemented via quantum variational optimization. Numerical experiments on both classical simulators and quantum hardware show that covariance is generally more reliable for accurately and efficiently inferring the topology, whereas entropy-based methods are often better at identifying the absence of entanglement in the low-shot regime.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Unifying and benchmarking state-of-the-art quantum error mitigation techniques

Error mitigation is an essential component of achieving a practical quantum advantage in the near term, and a number of different approaches have been proposed. In this work, we recognize that many state-of-the-art error mitigation methods share a common feature: they are data-driven, employing classical data obtained from runs of different quantum circuits. For example, Zero-noise extrapolation (ZNE) uses variable noise data and Clifford-data regression (CDR) uses data from near-Clifford circuits. We show that Virtual Distillation (VD) can be viewed in a similar manner by considering classical data produced from different numbers of state preparations. Observing this fact allows us to unify these three methods under a general data-driven error mitigation framework that we call UNIfied Technique for Error mitigation with Data (UNITED). In certain situations, we find that our UNITED method can outperform the individual methods (i.e., the whole is better than the individual parts). Specifically, we employ a realistic noise model obtained from a trapped ion quantum computer to benchmark UNITED, as well as other state-of-the-art methods, in mitigating observables produced from random quantum circuits and the Quantum Alternating Operator Ansatz (QAOA) applied to Max-Cut problems with various numbers of qubits, circuit depths and total numbers of shots. We find that the performance of different techniques depends strongly on shot budgets, with more powerful methods requiring more shots for optimal performance. For our largest considered shot budget (10 10 ), we find that UNITED gives the most accurate mitigation. Hence, our work represents a benchmarking of current error mitigation methods and provides a guide for the regimes when certain methods are most useful.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Photoinduced correlations in stochastic dynamics of a solid-state ionic conductor

Photoexcitation by ultrashort laser pulses plays a crucial role in controlling reaction pathways, creating nonequilibrium material properties, and probing complex molecular dynamics. The photoresponse following a laser pulse is generally nonidentical between exposures due to spatiotemporal fluctuations or the stochastic nature of dynamical pathways. However, most ultrafast pump-probe experiments struggle to distinguish intrinsic sample fluctuations from extrinsic apparatus noise, often missing deviations from the averaged response. Leveraging the stability and high photon flux of time-resolved X-ray micro-diffraction at a synchrotron, we characterized stochastic photoinduced dynamics in a solid-state ionic conductor. By analyzing temporal evolutions of the lattice parameter of a single grain, we found that shot-to-shot fluctuations are not independent. Instead, correlations exist between nonequilibrium lattice trajectories following adjacent shots, with a characteristic correlation length of approximately 1500 shots, corresponding to an energy barrier of 0.4 ± 0.1 eV, close to the activation energy of lithium-ion diffusion.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Sensitive and single-shot OH and temperature measurements by femtosecond cavity-enhanced absorption spectroscopy

In many low-temperature plasmas (LTPs), the OH radical and temperature represent key properties of plasma reactivity. However, OH and temperature measurements in weakly ionized LTPs are challenging, due to the low concentration and short lifetime of OH and the abrupt temperature rise caused by fast gas heating. To address such issues, this Letter combined cavity-enhanced absorption spectroscopy (CEAS) with femtosecond (fs) pulses to enable sensitive single-shot broadband measurements of OH and temperature with a time resolution of ∼180 ns in LTPs. Such a combination leveraged several benefits. With the appropriately designed cavity, an absorption gain of ∼66 was achieved, enhancing the actual OH detection limit by ∼55× to the 10 11 cm -3 level (sub-ppm in this work) compared with single-pass absorption. Single-shot measurements were enabled while maintaining a time resolution of ∼180 ns, sufficiently short for detecting OH with a lifetime of ∼100 μs. With the broadband fs laser, ∼34,000 cavity modes were matched with ∼95 modes matched on each CCD pixel bandwidth, such that fs-CEAS became immune to the laser-cavity coupling noise and highly robust across the entire spectral range. Also, the broadband fs laser allowed simultaneous sensing of many absorption features to enable simultaneous multi-parameter measurements with enhanced accuracies.

Liu, Ning↗
DOE OSTI2021

Multi-energy reconstructions, central electron temperature measurements, and early detection of the birth and growth of runaway electrons using a versatile soft x-ray pinhole camera at MST

A multi-energy soft x-ray pinhole camera has been designed, built, and deployed at the Madison Symmetric Torus to aid the study of particle and thermal transport, as well as MHD stability physics. This novel imaging diagnostic technique employs a pixelated x-ray detector in which the lower energy threshold for photon detection can be adjusted independently on each pixel. The detector of choice is a PILATUS3 100 K with a 450 μm thick silicon sensor and nearly 100 000 pixels sensitive to photon energies between 1.6 and 30 keV. An ensemble of cubic spline smoothing functions has been applied to the line-integrated data for each time-frame and energy-range, obtaining a reduced standard-deviation when compared to that dominated by photon-noise. The multi-energy local emissivity profiles are obtained from a 1D matrix-based Abel-inversion procedure. Central values of Te can be obtained by modeling the slope of the continuum radiation from ratios of the inverted radial emissivity profiles over multiple energy ranges with no a priori assumptions of plasma profiles, magnetic field reconstruction constraints, high-density limitations, or need of shot-to-shot reproducibility. In tokamak plasmas, a novel application has recently been tested for early detection, 1D imaging, and study of the birth, exponential growth, and saturation of runaway electrons at energies comparable to 100 × Te,0; thus, early results are also presented.

Delgado-Aparicio, L. F. (ORCID:0000000167394380)↗
DOE OSTI2024

Efficient prediction of attosecond two-colour pulses from an X-ray free-electron laser with machine learning

Abstract X-ray free-electron lasers are sources of coherent, high-intensity X-rays with numerous applications in ultra-fast measurements and dynamic structural imaging. Due to the stochastic nature of the self-amplified spontaneous emission process and the difficulty in controlling injection of electrons, output pulses exhibit significant noise and limited temporal coherence. Standard measurement techniques used for characterizing two-coloured X-ray pulses are challenging, as they are either invasive or diagnostically expensive. In this work, we employ machine learning methods such as neural networks and decision trees to predict the central photon energies of pairs of attosecond fundamental and second harmonic pulses using parameters that are easily recorded at the high-repetition rate of a single shot. Using real experimental data, we apply a detailed feature analysis on the input parameters while optimizing the training time of the machine learning methods. Our predictive models are able to make predictions of central photon energy for one of the pulses without measuring the other pulse, thereby leveraging the use of the spectrometer without having to extend its detection window. We anticipate applications in X-ray spectroscopy using XFELs, such as in time-resolved X-ray absorption and photoemission spectroscopy, where improved measurement of input spectra will lead to better experimental outcomes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Two-phase accurate multiplexed structured image capture (2pAc-MUSIC)

Multiplexed Structural Image Capture (MUSIC) technique uses modulation of light from a scene prior to imaging to encode the temporal evolution of target into spatial frequency shifts, with each shift corresponding to a unique time and resulting in individual distinct snapshots. Computational-processing of the multiplexed single-shot image can recover the nanosecond-resolution scene evolution. One of the limitations is the loss of spatial resolution of the recovered image due to limitations of the low-pass spatial frequency filtering depth. Here we demonstrated that two images with complementary spatial phases can be used to enhance the spatial resolutions. For this application, 2 Phase Accurate (2pAc)-MUSIC is implemented that a scene is encoded with two complementary phases. The increased spatial information captured reduces the lower frequency noise in the Fourier domain found in single-phase MUSIC. A recovery algorithm combines the 180-degree spatial frequency shifted images into a single scene and applies a spatial filter in the Fourier domain that has a larger depth than previously possible to achieve a scene with increased spatial resolution. The 2pAc-MUSIC can effectively enhance the spatial resolution by removing the overlapping zero-order spatial frequencies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Validation of 266 nm UV Raman thermometry using the alpha-to-beta quartz transition

Ultraviolet Raman scattering is a promising diagnostic for temperature measurements relevant to dynamic compression experiments, where improved signal strength and reduced background are critical. In this work, we experimentally validate Raman thermometry at 266 nm using crystalline quartz heated through the α to β phase transition in a tube furnace. Quartz provides a useful benchmark because of its well-characterized transition temperature near 846 K at ambient pressure. Temperatures inferred from the Stokes to anti-Stokes intensity ratio are compared with thermocouple measurements and with the observed phase transition. Single-shot Raman temperatures track the thermocouple closely, with an empirical single-shot scatter of approximately ±15 K under the present conditions. Temporal averaging reduces shot-to-shot scatter and improves agreement between the Raman temperatures and thermocouple readings to within approximately 8 K, while the transition is identified within 5 K of the accepted value. Measurements are performed using the fourth harmonic of a nanosecond pulsed Nd:YAG laser at 266 nm. The shorter excitation wavelength provides enhanced Raman scattering efficiency and reduced visible background relative to conventional visible excitation. Comparison with 532 nm Raman measurements acquired in the same experimental geometry demonstrates substantially improved signal-to-noise ratio for the UV configuration. These results establish 266 nm Raman thermometry as a reliable and accurate temperature diagnostic under controlled heating conditions and provide a quantitative benchmark for future application in dynamic compression and shock physics experiments.

Chemistry - Chemical explosives↗
DOE OSTI2020

Aftershocks of a Chemical Explosion in Granite from the Source Physics Experiment Phase I

The Source Physics Experiment (SPE) is a multiphase experiment to better understand explosion source physics and thereby improve explosion monitoring. The rst phase (Phase I) examined the explosion source in a hard-rock medium and took place in a granite outcrop called the Climax Stock section of the Nevada National Security Site (NNSS). This series of chemical explosions are called the Wet Granite Geology (WGG) events, but are usually referred to simply as the SPE events (i.e., SPE-1, SPE-2, etc.). Event information for the chemical explosions is given in Table 1. The study of explosion aftershocks can aid in understanding of in-situ stresses and be used as a discriminant for earthquakes [Ford and Walter, 2010]. Sweeney and Harben reported no observed aftershocks for SPE-1 and -2, respectively. They calculated a minimum magnitude of observation based on the noise oor of the seismic array and predicted at least one or two events in the week after the events using the hard-rock aftershock model from Ford and Labak. Possible explanations for the null observation ranged from instrumental - poor seismometer coupling, to physical - the shallow depth of burial was unable to access the deep tectonic stress that causes some explosion aftershocks. We extend the analysis of Sweeney and Harben to the largest of the SPE Phase I chemical explosions, SPE-5, which was approximately a 5 tonne TNT-equivalent shot at 76.5 m depth. This event registered as an M L 2 on the University of Nevada, Reno seismic network and should produce a measurable aftershock sequence.

58 GEOSCIENCES↗