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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Development of data‐driven exponential integrators with application to modeling of delay photocurrents

Abstract Radiation‐induced photocurrent effects represent a threat to microelectronic components operating in space, manmade and terrestrial radiation environments. Analysis of these threats by circuit simulations requires accurate and computationally efficient compact models. Most existing compact models are based on closed form analytic solutions of the governing equations and require empirical assumptions and idealizations that can limit their validity. In this paper we formulate an alternative numerical, data‐driven approach that learns a compact model from data representative of the type of measurements one can obtain in an experimental facility. To develop the model we start from a generic discrete‐time dynamical system and then use physics knowledge to refine its structure. Numerical studies demonstrate the potential of the model and establish some empirical guidelines for its training.

Bochev, Pavel↗
DOE OSTI2024

Parallel hybrid quantum-classical machine learning for kernelized time-series classification

Supervised time-series classification garners widespread interest because of its applicability throughout a broad application domain including finance, astronomy, biosensors, and many others. Here, in this work, we tackle this problem with hybrid quantum-classical machine learning, deducing pairwise temporal relationships between time-series instances using a timeseries Hamiltonian kernel (TSHK). A TSHK is constructed with a sum of inner products generated by quantum states evolved using a parameterized time evolution operator. This sum is then optimally weighted using techniques derived from multiple kernel learning. Because we treat the kernel weighting step as a differentiable convex optimization problem, our method can be regarded as an end-to-end learnable hybrid quantum-classical-convex neural network, or QCC-net, whose output is a data set-generalized kernel function suitable for use in any kernelized machine learning technique such as the support vector machine (SVM). Using our TSHK as input to a SVM, we classify univariate and multivariate time-series using quantum circuit simulators and demonstrate the efficient parallel deployment of the algorithm to 127-qubit superconducting quantum processors using quantum multi-programming.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Direct interpolative construction of the discrete Fourier transform as a matrix product operator

The quantum Fourier transform (QFT), which can be viewed as a reindexing of the discrete Fourier transform (DFT), has been shown to be compressible as a low-rank matrix product operator (MPO) or quantized tensor train (QTT) operator. However, the original proof of this fact does not furnish a construction of the MPO with a guaranteed error bound. Meanwhile, the existing practical construction of this MPO, based on the compression of a quantum circuit, is not as efficient as possible. We present a simple closed-form construction of the QFT MPO using the interpolative decomposition, with guaranteed near-optimal compression error for a given rank. This construction can speed up the application of the QFT and the DFT, respectively, in quantum circuit simulations and QTT applications. We also connect our interpolative construction to the approximate quantum Fourier transform (AQFT) by demonstrating that the AQFT can be viewed as an MPO constructed using a different interpolation scheme.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Flux-pumped impedance-engineered broadband Josephson parametric amplifier

Broadband quantum-limited amplifiers play a critical role in the single-shot readout of superconducting qubits, but a popular implementation, the traveling wave parametric amplifier, involves a complex design and fabrication process. Here, we present a simple design for a Josephson parametric amplifier, using a lumped element resonator comprising a superconducting quantum interference device whose useful bandwidth is enhanced with an on-chip impedance-matching circuit. Additionally, we demonstrate a flux-coupling geometry that maximizes the coupling to the Josepson loop and minimizes spurious excitation of the amplifier resonant circuit. The amplifier, which operates in a flux-pumped mode, is demonstrated with a power gain of more than 20dB over a bandwidth of about 300MHz, where approximate noise measurements indicate quantum-limited pehrformance. A procedure is given for optimizing the bandwidth for this kind of amplifier, using a linearized circuit simulation while minimizing non-linearities.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

QuTree: A tree tensor network package

Here we present QuTree, a C++ library for tree tensor network approaches. QuTree provides class structures for tensors, tensor trees, and related linear algebra functions that facilitate the fast development of tree tensor network approaches such as the multilayer multiconfigurational time-dependent Hartree approach or the density matrix renormalization group approach and its various extensions. We investigate the efficiency of relevant tensor and tensor network operations and show that the overhead for managing the network structure is negligible, even in cases with a million leaves and small tensors. QuTree focuses on providing simple, high-level routines while retaining easy access to the backend to facilitate novel developments. We demonstrate the capabilities of the package by computing the eigenstates of coupled harmonic oscillator Hamiltonians and performing random circuit simulations on a virtual quantum computer.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Linear-depth quantum circuits for loading Fourier approximations of arbitrary functions

Abstract The ability to efficiently load functions on quantum computers with high fidelity is essential for many quantum algorithms, including those for solving partial differential equations and Monte Carlo estimation. In this work, we introduce the Fourier series loader (FSL) method for preparing quantum states that exactly encode multi-dimensional Fourier series using linear-depth quantum circuits. Specifically, the FSL method prepares a (Dn)-qubit state encoding the 2 Dn -point uniform discretization of aD-dimensional function specified by aD-dimensional Fourier series. A free parameter,m, which must be less thann, determines the number of Fourier coefficients, 2 D ( m + 1 ) , used to represent the function. The FSL method uses a quantum circuit of depth at most 2 ( n − 2 ) + ⌈ log 2 ( n − m ) ⌉ + 2 D ( m + 1 ) + 2 − 2 D ( m + 1 ) , which is linear in the number of Fourier coefficients, and linear in the number of qubits (Dn) despite the fact that the loaded function’s discretization is over exponentially many (2 Dn ) points. The FSL circuit consists of at most D n + 2 D ( m + 1 ) + 1 − 1 single-qubit and D n ( n + 1 ) / 2 + 2 D ( m + 1 ) + 1 − 3 D ( m + 1 ) − 2 two-qubit gates; we present a classical compilation algorithm with runtime O ( 2 3 D ( m + 1 ) ) to determine the FSL circuit for a given Fourier series. The FSL method allows for the highly accurate loading of complex-valued functions that are well-approximated by a Fourier series with finitely many terms. We report results from noiseless quantum circuit simulations, illustrating the capability of the FSL method to load various continuous 1D functions, and a discontinuous 1D function, on 20 qubits with infidelities of less than 10 −6 and 10 −3 , respectively. We also demonstrate the practicality of the FSL method for near-term quantum computers by presenting experiments performed on the Quantinuum H1-1 and H1-2 trapped-ion quantum computers: we loaded a complex-valued function on 3 qubits with a fidelity of over 95 % , as well as various 1D real-valued functions on up to 6 qubits with classical fidelities ≈99%, and a 2D function on 10 qubits with a classical fidelity ≈94%.

Physics↗
DOE OSTI2026

A Survey on the Expanding Scope and Interdisciplinary Opportunities for Processing-in-Memory Techniques

Processing-in-Memory (PIM) is emerging as a practical path to overcome the limitations of traditional von Neumann architectures. At its core, PIM systems implement computing primitives such as logic operations and multiply-accumulate acceleration through compute-in-memory, near-memory processing, or hybrid designs. The role of memory cells varies widely across technologies, acting as inputs, outputs, or analog accumulators through bit-lines and sense amplifiers. This diversity creates trade-offs in precision, bandwidth, latency, and programmability, making it difficult to build a unified understanding on the progress of the field. In this survey, we organize recent advances of PIM into three areas. First, we discuss the progress on the architectural optimizations of PIM and its integration with both DRAM and emerging non-volatile memories. Second, we examine how PIM is being used to accelerate key computing domains, including generative AI workloads and high-performance kernels, along with new approaches. Third, we highlight the growing adoption of PIM in computational sciences, where it is being applied to solve interdisciplinary problems such as genome analysis, mRNA quantification, mass spectrometry, quantum circuit simulation, wave modeling, and secure computation. Finally, we synthesize the major challenges that continue to slow PIM adoption, including manufacturing constraints, power delivery, thermal reliability, data consistency, runtime and memory-management coordination, and the difficulty of building portable software abstractions without sacrificing commercial viability. This work provides an updated, structured perspective on PIM’s potential across computing and computational sciences and the barriers that must be solved for it to reach its full impact.

Asifuzzaman, Kazi [Oak Ridge National Laboratory (↗
DOE OSTI2026

A Unified Off-Board Charging System for Integrated Wired and Wireless EV Charging

This work explores a unified off-board charger approach that enables both wired and wireless charging within a single system architecture. Instead of deploying two independent converters, the proposed configuration switches between an LLC-based operation for wired charging and an LCC-S–type operation for wireless charging by rearranging the excitation of commonly used components. With this reconfiguration, the same switch bridge, resonant elements, and magnetic coupling coils can be utilized in both modes without relying on relays or additional hardware paths. To assess the basic operation of the proposed system, PLECS circuit simulations were performed for both wired and wireless charging modes. A 3.3-kW prototype was also built, and representative experimental results for each mode confirm that the unified converter can operate properly while reducing hardware duplication.

Jo, Cheolhui [ORNL] (ORCID:0000000322692434)↗
DOE OSTI2023

Suppression of Parasitic Voltage Oscillation in Power Modules by Turn-Off Current Zero Placement

This paper presents a frequency-domain analysis of the turn-off equivalent switching network of a hard-switched semiconductor switching cell. This paper also proposes a novel method to suppress parasitic voltage ringing by placing the turn-off current zero at the parasitic resonant frequency. The turn-off current was decomposed into ramp functions and a constant-valued function to facilitate obtaining the frequency components of the turn-off current using the Laplace transform of standard signals. The proposed frequency-domain modeling of the parasitic voltage ringing and the suppression were validated by detailed circuit simulation using parameters corresponding to prior literature with experimental validation.

Galigekere, Veda Prakash↗
DOE OSTI2021

The Sensitivity Analysis of Coil Misalignment for a 200-kW Dynamic Wireless Power Transfer System with an LCC-S and LCC-P Compensation

The dynamic wireless power transfer systems may reduce the battery size of electric vehicles while maintaining the travel range. Similar to the stationary wireless power transfer systems, the compensation networks are desired in dynamic wireless charging systems at the primary and secondary sides to reduce the reactive power requirement from the source and improve the efficiency. Consequently, it is essential to understand the behavior of the compensation networks, especially the sensitivity to misalignments. This paper presents a sensitivity analysis of LCC-S and LCC-P compensation networks for a 200-kW power transfer with variations in the coupling coefficient due to the electric vehicle travel and misalignments between the pads. The sensitivity study combines the electromagnetic finite element analysis and circuit analysis to determine the impact of misalignments on the wireless power transfer system characteristics. The theoretical analysis is verified by conducting circuit simulations at discrete points to verify the accuracy of the mathematical model.

Kavimandan, Utkarsh↗
DOE OSTI2026

A Unified Wireless Charger, On-Board Charger, and Auxiliary Power Module for Electric Vehicle Charging Systems

This paper proposes a unified electric vehicle (EV) charging architecture that integrates wireless power transfer (WPT), an on-board charger (OBC), and an auxiliary power module (APM) within a single architecture. By sharing a multi-functional magnetic structure and active switch bridges, the proposed topology eliminates additional transformers and converter stages, reducing hardware complexity and improving power density. A multipurpose magnetic design achieves magnetic decoupling among the WPT, OBC, and APM functions while maintaining the required coupling for each mode. Through electrical reconfiguration, the WPT operates as an LCC-S converter, whereas the OBC and APM operate as dual-active-bridge (DAB) converters. The system supports multiple operating modes, including simultaneous high-voltage and lowvoltage battery charging. Finite-element and circuit simulations verify the magnetic characteristics and system operation, demonstrating the feasibility of the proposed unified architecture for EV charging applications.

Jo, Cheolhui [ORNL] (ORCID:0000000322692434)↗
DOE OSTI2022

A Tri-Port Current-Source Soft-Switching Medium-Voltage String Inverter for Large-Scale Solar-Plus-Storage Farms

This article presents a tri-port current-source soft-switching medium-voltage string inverter (TMVSI) to reduce the Levelized cost of energy (LCOE) of large-scale solar-plus-storage (SPS) farms. Throughout this work, the topology, operating principle, circuit simulation, control, and hardware design of the TMVSI are introduced. In addition, three key challenges compromising the performance of the TMVSI are addressed in this article. First, a new feed-forward compensation for model predictive control of the TMVSI is proposed to compensate for sampling and computational delay and high dc-link ripple with low computational cost and high scalability. Second, the use of laminated permanent magnets is proposed to reduce the losses of the MV medium-frequency transformer (MFT) in the TMVSI while increasing its saturation current. Finally, an improved U-shape winding pattern is proposed to decrease the leakage inductance of the MV MFT and reduce the voltage stress across semiconductor switches without adding cost or complexity. Here, the effectiveness of the TMVSI is validated by experiments at up to 20kW/500V in different test cases with custom-built prototypes. The contributions of this work make the TMVSI a viable solution to SPS farms and unleash its potential for LCOE reduction.

14 SOLAR ENERGY↗
DOE OSTI2022

Development of a 250 Degree C 15kV Supercascode Switch Using SiC JFET Technology

Tetra Corporation is developing a pulsed power drilling system for the geothermal industry. The system requires a high temperature switching technology to replace the existing technology based on Si thyristors with a temperature limit of 150 degrees C. This work focuses on the development of such switch based on a Supercascode configuration using SiC JFET technology. The development presented contains thermal models, packaging design and processes, circuit simulations and prototypes of both the Supercascode switch and the high temperature packaged SiC JFETs.

cascaded switch↗
DOE OSTI2020

Phase Shift Control of a Three-Phase Inverter for Balanced Secondary Currents in Misaligned Three-Phase Inductive Power Transfer Systems

This paper presents a strategy for generating fundamental reference voltage commands for a double-sided LCC tuned three-phase wireless power transfer (WPT) system to achieve balanced output currents when the receiver and transmitter are not perfectly aligned. Formulas for translating the normalized fundamental current commands into phase-shift commands for two of the phase legs in a two-level three-phase inverter are derived. The methodology is validated through circuit simulations performed using coupler models derived from finite-element simulations. Simulation results for a 1.5 k W system design are included, which indicate near perfect correction of imbalance in the secondary currents for a typical misalignment case.

Pries, Jason↗
DOE OSTI2021

NWQ-sim

NWQSim is a quantum circuit simulation environment developed at PNNL. It currently includes two major components: a state-vector simulator (SV-Sim) and a density matrix simulator (DM-Sim) and we may add more components, such as a Clifford simulator, in the future effort. NWQSim has two language interface: C/C++ and Python. It supports Q#/QDK frontend through QIR and QIR-runtime. It supports Qiskit and Cirq frontends through OpenQASM. NWQSim runs on several backends: Intel-CPU, Intel-Xeon-Phi, AMD-CPU, AMD-GPU, NVIDIA-GPU, and IBM-CPU. It supports three modes: (1) single processor, such as a single CPU (with and without AVX2 and AVX512 acceleration), a single NVIDIA GPU or a single AMD GPU; (2) single-node-multi-processors, such as multi-CPUs/Xeon-Phis, multi-NVIDA/AMD GPUs; (3) multi-nodes, such as a CPU cluster, a Xeon-Phi cluster (e.g., ANL Theta, NERSC Cori), an NVIDIA cluster (e.g., ORNL Summit, NERSC Perlmutter).

Li, Ang↗
DOE OSTI2021

Magnetron R&D for high efficiency CW RF sources for industrial accelerators

The scheme of using high-efficiency magnetrons to drive radiofrequency accelerators has been demonstrated at 2450 MHz in CW mode *. Magnetron test stands at JLab and GA have been set up to further test the noise figure and the locking speed of the injection phase-lock method. For higher power applications, power combining experiments using a TM010 cavity-type combiner and a magic tee for the binary combiner while using a single clean injection signal has been carried out at 2450 MHz. The frequency pulling effect between the magnetron and a low-Q cavity has been shown to enhance the frequency locking bandwidth compared to the injection phase-lock alone. The principle has been studied by the equivalent circuit simulation, analytical model, and finally confirmed experimentally on the magnetrons. Due to the pandemic delay in 2020, the equivalent high power tests using a 75kW, 915MHz industrial magnetron will be done in 2021 and will be reported in a future paper.

Wang, H.↗
DOE OSTI2020

Xyce TM XDM Netlist Translator User Guide (V 2.0)

This manual describes the installation and use of the XyCe TM XDM Net list Translator. XDM simplifies the translation of netlists generated by commercial circuit simulator tools into Xyce-compatible netlists. XDM currently supports translation from PSpice and HSPICE netlists into Xyce TM netlists.

97 MATHEMATICS AND COMPUTING↗