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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 1,513 records · Page 84
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

NISQ+: Boosting quantum computing power by approximating quantum error correction

Quantum computers are growing in size, and design decisions are being made now that attempt to squeeze more computation out of these machines. In this spirit, we design a method to boost the computational power of near-term quantum computers by adapting protocols used in quantum error correction to implement "Approximate Quantum Error Correction (AQEC)." By approximating fully-fledged error correction mechanisms, we can increase the compute volume (qubits × gates, or "Simple Quantum Volume (SQV)") of near-term machines. The crux of our design is a fast hardware decoder that can approximately decode detected error syndromes rapidly. Specifically, we demonstrate a proof-of-concept that approximate error decoding can be accomplished online in near-term quantum systems by designing and implementing a novel algorithm in Single-Flux Quantum (SFQ) superconducting logic technology. This avoids a critical decoding backlog, hidden in all offline decoding schemes, that leads to idle time exponential in the number of T gates in a program. Our design utilizes one SFQ processing module per physical qubit. Employing state-of-the-art SFQ synthesis tools, we show that the circuit area, power, and latency are within the constraints of contemporary quantum system designs. Under pure dephasing error models, the proposed accelerator and AQEC solution is able to expand SQV by factors between 3,402 and 11,163 on expected near-term machines. The decoder achieves a 5% accuracy-threshold and pseudo-thresholds of ~ 5%,4.75%,4.5%, and 3.5% physical error-rates for code distances 3,5,7, and 9. Decoding solutions are achieved in a maximum of ~20 nanoseconds on the largest code distances studied. By avoiding the exponential idle time in offline decoders, we achieve a 10x reduction in required code distances to achieve the same logical performance as alternative designs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

State Dependent Optimization with Quantum Circuit Cutting

Quantum circuits can be reduced through optimization to better fit the constraints of quantum hardware. One such method, initial-state dependent optimization (ISDO), reduces gate count by leveraging knowledge of the input quantum states. Surprisingly, we found that ISDO is broadly applicable to the downstream circuits produced by circuit cutting. Circuit cutting also requires measuring upstream qubits and has some flexibility of selection observables to do reconstruction. Therefore, we propose a state-dependent optimization (SDO) framework that incorporates ISDO, our newly proposed measure-state dependent optimization (MSDO), and a biased observable selection strategy. Building on the strengths of the SDO framework and recognizing the scalability challenges of circuit cutting, we propose nonseparate circuit cutting-a more flexible approach that enables optimizing gates without fully separating them. We validate our methods on noisy simulations of QAOA, QFT, and BV circuits. Results show that our approach consistently mitigates noise and improves overall circuit performance, demonstrating its promise for enhancing quantum algorithm execution on near-term hardware.

Li, Xinpeng↗
DOE OSTI2020

A 150-kW 99% Efficient All-Silicon-Carbide Triple-Active-Bridge Converter for Solar-Plus-Storage Systems

Solar-plus-storage systems could effectively mitigate the uncertainties of the photovoltaic (PV) generation and improve system reliability by adding an integrated battery energy storage system. As a three-port bidirectional isolated dc–dc converter with soft-switching capability, the triple-active-bridge (TAB) converter inherently matches the requirements of the solar-plus-storage system. However, challenges still remain in the TAB converter design to further improve system efficiency. In this article, the detailed design, implementation, and demonstration for a silicon carbide (SiC) 150-kW TAB converter are presented. Starting from a brief review of the TAB converter, the modulation scheme, power characteristics, and soft-switching region are analyzed. Then, the detailed design of the H-bridge converter building block is given. Here, to improve the system efficiency, a comprehensive characterization of the SiC gate driver with various external gate resistances is performed to address tradeoffs between switching loss and voltage overshoot during transients, as well as the thermal performance of the H-bridge building block. In addition, the design and characterization of the 20-kHz three-port transformer are also given. Comprehensive experimental studies are conducted on a full-power prototype to verify the proposed design. With a measured 99.1% peak efficiency, the proposed TAB converter can fulfill the requirements for solar-plus-storage applications.

14 SOLAR ENERGY↗
DOE OSTI2022

Design Methodologies for Integrated Quantum Frequency Processors

We report frequency-encoded quantum information offers intriguing opportunities for quantum communications and networking, with the quantum frequency processor paradigm—based on electro-optic phase modulators and Fourier-transform pulse shapers—providing a path for scalable construction of quantum gates. Yet all experimental demonstrations to date have relied on discrete fiber-optic components that occupy significant physical space and impart appreciable loss. In this article, we introduce a model for the design of quantum frequency processors comprising microring resonator-based pulse shapers and integrated phase modulators. We estimate the performance of single and parallel frequency-bin Hadamard gates, finding high fidelity values that extend to frequency bins with relatively wide bandwidths. By incorporating multi-order filter designs as well, we explore the limits of tight frequency spacings, a regime extremely difficult to obtain in bulk optics. Overall, our model is general, simple to use, and extendable to other material platforms, providing a much-needed design tool for future frequency processors in integrated photonics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Enhancement-Mode GaN Monolithic Bidirectional Switch With Breakdown Voltage Over 3.3 kV

Here, this work demonstrates a GaN enhancement-mode monolithic bidirectional switch (MBDS) with breakdown voltage (BV) higher than 3.3 kV in both polarities. This MBDS is realized on a dual p-GaN gate high electron mobility transistor (HEMT) platform on sapphire substrate. It features a novel dual junction termination extension design for electric field management, which is built on the p-GaN layer in the gate stack and does not require epitaxial regrowth. The GaN MBDS exhibits symmetric on-state characteristics in both directions with a threshold voltage (V th ) of 0.6 V and a low specific on-resistance (R on,sp ) of 5.6 m Ω · cm2. This device presents the highest BV, as well as one of the best BV and R on,sp trade-offs, in all the reported MBDS devices. The R on,sp is lower than the performance limit of conventional BDS realized by two discrete devices. This 3.3 kV GaN MBDS opens the door for developing new circuit topologies and advancing system performance in medium-voltage power electronics.

42 ENGINEERING↗
DOE OSTI2025

GRUMDN: A Multi-Task Model for Predicting Human Patterns-of-Life from Stay Transition Data

Understanding human patterns-of-life (PoL) is essential towards ensuring safe and secure indoor facility environment as well as outdoor urban environment. Prediction of human movement in between places of interest is vital in understanding human PoL. Movement between spaces maybe represented and detected in one of the two forms: 1) trajectories: locations measured at regular time intervals by mobile sensors, bluetooth or GPS sensors; or 2) stay transitions: semantic PoI (points of interest) and stay duration data measurable by eventbased sensors that collect data when a check-in or check-out event is detected. Stay transition data provides a more compressed data format compared to trajectories data, especially in situations with longer stay durations, while preserving the information necessary for PoL analysis. Now as introduced briefly in the paper, our deployed end application (Digital Twin of a facility with non-player characters, besides the interactive user in virtual reality) needed a well-performing and validated AI/ML model for simulating high quality stay transitions behavior. In this study we thus primarily present our findings with developing and validating that model, which is a multi-task neural network for stay transition prediction. The neural network consists of two heads, for corresponding two tasks of stay category prediction and stay duration prediction. We evaluated gated recurrent units and multi-layer perceptrons of varying network sizes for stay category prediction; while mixture density networks, noisy generator-only networks, and generative adversarial networks of varying network sizes for stay duration prediction. We have then evaluated four multi-task models, constructed by combining these specialized models, on their ability to predict stay transition data. We tested our models on datasets from two different cases: 1) a simulation-generated dataset of indoor movement within the HFIR (high flux isotope reactor) nuclear reactor facility at Oak Ridge National Laboratory (ORNL); and 2) the GeoLife human mobility dataset of outdoor urban movement available in literature. Our results indicate that GRUMDN, which combines gated recurrent units (GRU) for stay category prediction task, and mixture density networks (MDN) for stay duration prediction task, did overall outperform other multitask models and the current state-of-the-art.

Gunaratne, Chathika [ORNL] (ORCID:0000000225088745↗
DOE OSTI2020

Extending the Frontier of Quantum Computers with Qutrits

Here, we advocate for a fundamentally different way to perform quantum computation by using three-level qutrits instead of qubits. In particular, we substantially reduce the resource requirements of quantum computations by exploiting a third state for temporary variables (ancilla) in quantum circuits. Past work with qutrits has demonstrated only constant factor improvements, owing to the log 2 (3) binary-to-ternary compression factor. We present a novel technique using qutrits to achieve a logarithmic runtime decomposition of the Generalized Toffoli gate using no ancilla - an exponential improvement over the best qubit-only equivalent. Our approach features a 70× improvement in total two-qudit gate count over the qubit-only decomposition. This results in improvements for important algorithms for arithmetic and QRAM. Simulation results under realistic noise models indicate over 90% mean reliability (fidelity) for our circuit, versus under 30% for the qubit-only baseline. These results suggest that qutrits offer a promising path toward extending the frontier of quantum computers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Digital zero noise extrapolation for quantum error mitigation

Zero-noise extrapolation (ZNE) is an increasingly popular technique for mitigating errors in noisy quantum computations without using additional quantum resources. We review the fundamentals of ZNE and propose several improvements to noise scaling and extrapolation, the two key components in the technique. We introduce unitary folding and parameterized noise scaling. Furthermore, these are digital noise scaling frameworks, i.e. one can apply them using only gate-level access common to most quantum instruction sets. We also study different extrapolation methods, including a new adaptive protocol that uses a statistical inference framework. Benchmarks of our techniques show error reductions of 18X to 24X over non-mitigated circuits and demonstrate ZNE effectiveness at larger qubit numbers than have been tested previously. In addition to presenting new results, this work is a self-contained introduction to the practical use of ZNE by quantum programmers.

quantum computing↗
DOE OSTI2024

A Quantum Approach for Implementing Fixed-Point Arithmetic in Solving Ordinary Differential Equations

Differential equations (DEs) serve as fundamental tools in mathematical modeling across scientific disciplines, yet classical numerical solvers face limitations with large-scale or computationally intensive problems. This study explores a quantum-inspired approach to solving DEs, combining quantum-inspired techniques with classical methods. It focuses on fixed-point arithmetic on quantum circuits, utilizing basic quantum gates to manipulate DE solutions. We expand upon the techniques introduced by Zanger et al. [Quantum, 5, 502 (2021)] by offering a precise computation for a fixed-point signed multiplication scheme, while also presenting a quantum circuit capable of executing the fixed-point division algorithm. We demonstrate the feasibility of our approach through the simulation of a linear Ordinary Differential Equation (ODE), where initial conditions and parameters are encoded into quantum circuits using fixed-point representation. By executing sequences of quantum gates mimicking numerical integration steps, we obtain approximate solutions to the ODE with specified fixed-point precision.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Q-Cluster: Quantum Error Mitigation Through Noise-Aware Unsupervised Learning

Quantum error mitigation (QEM) is critical in reducing the impact of noise in the pre-fault-tolerant era, and is expected to complement error correction in fault-tolerant quantum computing (FTQC). In this work, we propose a novel QEM approach, Q-Cluster, that uses unsupervised learning (clustering) to reshape the measured bit-string distribution. Our approach starts with a simplified bit-flip noise model. It first performs clustering on noisy measurement results, i.e., bit-strings, based on the Hamming distance. The centroid of each cluster is calculated using a qubit-wise majority vote. Next, the noisy distribution is adjusted with the clustering outcomes and the bitflip error rates using Bayesian inference. Our simulation results show that Q-Cluster can mitigate high noise rates (up to 40% per qubit) with the simple bit-flip noise model. However, real quantum computers do not fit such a simple noise model. To address the problem, we (a) apply Pauli twirling to tailor the complex noise channels to Pauli errors, and (b) employ a machine learning model, ExtraTrees regressor, to estimate an effective bit-flip error rate using a feature vector consisting of machine calibration data (gate & measurement error rates), circuit features (number of qubits, numbers of different types of gates, etc.) and the shape of the noisy distribution (entropy). Our experimental results show that our proposed Q-Cluster scheme improves the fidelity by a factor of 1.46x, on average, compared to the unmitigated output distribution, for a set of low-entropy benchmarks on five different IBM quantum machines. Our approach outperforms the state-of-art QEM approaches RZNE [28], M3 [24], Hammer [35], and QBEEP [33] by 1.26x,1.29x,1.47x, and 2.65 x, respectively.

42 ENGINEERING↗
DOE OSTI2021

Al 0.7 Ga 0.3 N MESFET With All-Refractory Metal Process for High Temperature Operation

In this work, ultrawide bandgap Al 0.7 Ga 0.3 N MESFETs with refractory Tungsten Schottky and Ohmic contacts are studied in 300–675 K environments. Variable-temperature dc electrical transport reveals large ON-state drain current densities for an AlGaN device: 209 mA/mm at 300 K and 156 mA/mm at 675 K in the ON-state (25% reduction). Drain and gate currents are only weakly temperature-dependent, suggesting potential for engineering temperature invariant operation. The ON-/ OFF-ratio is limited by OFF-state leakage through the gate, which is attributed to damage from sputter deposition. Future work using refractory metals with larger work functions that are deposited by electron beam deposition is proposed.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Comparison and Discussion on Shortcircuit Protections for Silicon-Carbide MOSFET Modules: Desaturation Versus Rogowski Switch-Current Sensor

Survivability of silicon-carbide (SiC) mosfet modules during short circuit (SC) is essential for modern power electronics systems due to large economic implications. SiC mosfet modules exhibit narrow SC withstand times and generally much lower SC robustness than silicon (Si) insulated-gate bipolar transistors (IGBTs). This puts a critical concern on their utilization, further stressing the importance of reliable protection. This article presents a comprehensive analysis and discussion on the SiC mosfet module SC protection and performance comparison between conventional desaturation detection, previously used for Si IGBT protection, and Rogowski switch-current sensor (RSCS) detection. In addition, this article presents the experimental design for soft turn-off as a reaction to the SC detection to avoid excessive overshoots during the abrupt turn-off of the SC current. To perform different types of SC with various fault inductances on different temperatures, and for the sake of fair comparison under the same conditions, a gate-driver unit for 1.2 kV SiC mosfet half-bridge modules is developed containing both detection methods. The results demonstrate that both methods are successful in protecting the module in all SC types, with superiority of the RSCS detection and concerns for desaturation detection in high-inductance and high dc-bus voltage SC events.

42 ENGINEERING↗
DOE OSTI2021

Instability Issue of Paralleled Dies in an SiC Power Module in Solid-State Circuit Breaker Applications

Paralleled dies in a power module could have instability issues during high current switching transients. Here, the instability is caused by the differential-mode oscillation among paralleled MOSFETs. Conventional analyses of paralleled MOSFETs’ stability are normally limited to a single operating point, which ignores the influences of the switching trajectory and nonlinear device parameters on stability. This article reveals that the switching trajectory can significantly influence parallel stability. The analysis is improved by solving eigenvalues of state-space modeling system matrices of all operating points that the switching trajectory goes through considering nonlinear device parameters. Higher voltage and current stresses result in greater real parts of complex eigenvalues, which explains why the paralleled MOSFETs are more unstable with higher voltage and current stresses. To improve stability in solid-state circuit breaker applications, we propose a method to manipulate the switching trajectory to avoid the unstable region where the conventional hard switching trajectory normally goes through. Experimental results show that the turn- off current capability can be increased from ~five times of rated current with the gate oscillation using the conventional turn- off trajectory to ~ten times of rated current without the gate oscillation using the optimal turn- off trajectory.

42 ENGINEERING↗
DOE OSTI2021

First Experiments and Radiographs on the MegaJOuLe Neutron Imaging Radiography (MJOLNIR) Dense Plasma Focus

We report a dense plasma focus (DPF) is a relatively compact coaxial plasma gun, which completes its discharge as a Z-pinch. These devices are designed to operate at a variety of scales to produce short (<100 ns) pulses of ions, X-rays, and/or neutrons. LLNL recently constructed and brought into operation a new device, the MegaJOuLe Neutron Imaging Radiography (MJOLNIR) DPF, which is designed for radiography and high-yield operations. This device has been commissioned and has achieved neutron yields of up to 3.8E11 neutrons/pulse at 2.5-MA peak current while operating at up to 1 MJ of stored energy in its original pulsed power configuration. MJOLNIR is equipped with a wide range of diagnostics, including nuclear activation detectors, neutron time-of-flight (nToF) detectors, a fast-framing camera, optical light gates, and a time-gated neutron and X-ray imager. LLNL also runs unique particle-in-cell (PIC) simulations of DPF discharges in the Chicago code and has gained significant insight into the various physical factors that influence neutron yield. MJOLNIR is one of the first DPFs whose design and continual upgrades are heavily influenced by model predictions. In this article, we describe insights from modeling, device operation, and recent results. Comparisons between modeling predictions and measurements, as well as X-ray and neutron images are presented.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Au-free low-temperature ohmic contacts for AlGaN/AlN/GaN heterostructures

We report Au-free, Ti/Al/Ta ohmic contact on the AlGaN/AlN/GaN heterostructure using low annealing temperature is studied in this paper. With SiCl 4 plasma treatment at the recess-etched contact region, a low contact resistance of 0.52 Ω mm and a low sheet resistance of 373 Ω/sq are achieved after annealing at 550 °C for 30 s. The low annealing temperature also leads to better surface morphology. Furthermore, AlGaN/AlN/GaN high-electron-mobility transistors (HEMTs) are fabricated with the 550 °C, 30 s annealed Ti/Al/Ta ohmic contacts, and a maximum transconductance of 123 mS/mm and a maximum drain current of 510 mA/mm are obtained for a gate length of 4 μm. Based on Silvaco's Atlas device simulation framework, a scaled-down device with a short gate length of 1 μm would produce a maximum drain current density of 815 mA/mm. It indicates that the direct current performance of the HEMTs with the ohmic metal proposed in this work is considerably better than that with Au-based ohmic contact.

42 ENGINEERING↗
DOE OSTI2025

Initial in-orbit operation of the soft X-ray spectrometer Resolve onboard the X-ray imaging and spectroscopy mission satellite

The X-Ray Imaging and Spectroscopy Mission satellite was launched on September 6, 2023 (UT). Its Resolve instrument is a high-resolution X-ray spectrometer enabled by a microcalorimeter array thermally anchored to a 50-mK heat sink. Many sensitive, critical sub-systems comprise Resolve, including a multistage cryogenic cooling system, thin-film aperture filters, low-noise electronics, on-board signal processing, and several sources of X-rays for calibration. We summarize the initial on-orbit power-on and checkout of Resolve that commenced immediately after launch. Soon after launch, the cryocoolers were activated, and their operation was successfully established. On October 9, 2023, the first cycle of the adiabatic demagnetization refrigerator was carried out, bringing the sensors to their steady-state operational temperatures. Following this, the energy resolution at 5.9 keV was successfully measured. The energy scale of the system is highly sensitive to the thermal environment surrounding both the sensors and their analog electronics. Gain correction was performed using reference X-ray lines from onboard calibration sources. To optimize cooler frequency settings, noise spectra were collected across a range of frequencies, and the most suitable frequency pair was selected based on the in-orbit environment. During the final phase of the checkout, an attempt was made to open the gate valve, which is designed to protect the Dewar’s interior from external pressure during ground operations and launch. Unfortunately, this attempt was unsuccessful. As a result, the checkout process was temporarily paused, and a stable operational strategy was subsequently developed to enable Resolve to function effectively with the gate valve remaining closed.

X-ray micro-calorimeter↗
DOE OSTI2023

Improved noise performance from the next-generation buried-channel p-MOSFET SiSeROs

The Single electron Sensitive Read Out (SiSeRO) is a novel on-chip charge detector output stage for charge-coupled device (CCD) image sensors. Developed at MIT Lincoln Laboratory, this technology uses a p-MOSFET transistor with a depleted internal gate beneath the transistor channel. The transistor source-drain current is modulated by the transfer of charge into the internal gate. At Stanford, we have developed a readout module based on the drain current of the on-chip transistor to characterize the device. In our earlier work, we characterized a number of first prototype SiSeROs with the MOSFET transistor channels at the surface layer. An equivalent noise charge (ENC) of around 15 electrons root mean square (RMS) was obtained. In this work, we examine the first buried-channel SiSeRO. Here we have achieved substantially improved noise performance of around 4.5 electrons root mean square (RMS) and a full width half maximum (FWHM) energy resolution of 132 eV at 5.9 keV, for a readout speed of 625 kpixel/s. We also discuss how digital filtering techniques can be used to further improve the SiSeRO noise performance. Additional measurements and device simulations will be essential to further mature the SiSeRO technology. This new device class presents an exciting new technology for the next-generation astronomical X-ray telescopes requiring fast, low-noise, radiation-hard megapixel imagers with moderate spectroscopic resolution.

79 ASTRONOMY AND ASTROPHYSICS↗