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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Optimal Twirling Depth for Classical Shadows in the Presence of Noise

The classical shadows protocol is an efficient strategy for estimating properties of an unknown state p using a small number of state copies and measurements. In its original form, it involves twirling the state with unitaries from some ensemble and measuring the twirled state in a fixed basis. It was recently shown that for computing local properties, optimal sample complexity (copies of the state required) is remarkably achieved for unitaries drawn from shallow depth circuits composed of local entangling gates, as opposed to purely local (zero depth) or global twirling (infinite depth) ensembles. Here, we consider the sample complexity as a function of the depth of the circuit, in the presence of noise. We find that this noise has important implications for determining the optimal twirling ensemble. Under fairly general conditions, we (i) show that any single-site noise can be accounted for using a depolarizing noise channel with an appropriate damping parameter f, (ii) compute thresholds f th at which optimal twirling reduces to local twirling for Pauli operators, (iii) nth order Renyi entropies (n ≥2), and (iv) provide a meaningful upper bound t max on the optimal circuit depth for any finite noise strength f, which applies to observables and entanglement entropy measurements. In conclusion, these thresholds strongly constrain the search for optimal strategies to implement shadow tomography and are easily tailored to the experimental system at hand.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Mu2e Target Thermal Test Project

The Mu2e experiment requires a production target capable of operating under extreme thermal conditions caused by an 8 GeV proton beam. This project’s objective supports the development of the Mu2e Production Target by testing the Stickman model’s thermal behavior. To test this, Angel Flores Luviano has assisted Jonathan Williams in progressing this project by contributing to the development of a Radiative Cooling Test Fixture (RCTF) that will be used to evaluate the thermal behavior of the new production target model. Engineering calculations were performed to analyze thermal performance and pressure drop within the cold well and water cooling circuit, and determine optimal sizing for key components of the water system. An engineering note was made to document the calculations. CAD models of the water circuit piping, thermocouple mount, and radiator chimney were developed, and prototype test rig components were fabricated using 3D printing. Future work will focus on conti nued RCTF development which includes control system integration, heater hardware design, and interfaces that can be scaled up to increase thermal capacity.

Luviano, Angel Flores [Unlisted]↗
DOE OSTI2025

Efficient frequency allocation for superconducting quantum processors using improved optimization techniques

Building on previous research on frequency allocation optimization for superconducting circuit quantum processors, this work incorporates several techniques to improve overall solution quality. Here, we introduce constraints and imposed edgewise differences help to improve the optimization results. We also introduce optimization variables for the orientation of each edge, defined as the direction from the control qubit to the target qubit, to be chosen during optimization. To scale up to larger processors, multimodule designs are employed with various boundary conditions, thereby enhancing the collective yield. These enhancements allow for greater flexibility in processor design by eliminating the need for handpicked orientations. We support the efficient assembly of large processors with dense connectivity by choosing the best boundary conditions. Examples demonstrate that, at low computational cost, this optimization approach finds a frequency configuration for a square chip with over 1000 qubits and over 10% yield at much larger dispersion levels than required by previous approaches.

Zhang, Zewen [Argonne National Laboratory (ANL), A↗
DOE OSTI2021

Resource-Optimized Fermionic Local-Hamiltonian Simulation on a Quantum Computer for Quantum Chemistry

The ability to simulate a fermionic system on a quantum computer is expected to revolutionize chemical engineering, materials design, nuclear physics, to name a few. Thus, optimizing the simulation circuits is of significance in harnessing the power of quantum computers. Here, we address this problem in two aspects. In the fault-tolerant regime, we optimize the R z and T gate counts along with the ancilla qubit counts required, assuming the use of a product-formula algorithm for implementation. We obtain a savings ratio of two in the gate counts and a savings ratio of eleven in the number of ancilla qubits required over the state of the art. In the pre-fault tolerant regime, we optimize the two-qubit gate counts, assuming the use of the variational quantum eigensolver (VQE) approach. Specific to the latter, we present a framework that enables bootstrapping the VQE progression towards the convergence of the ground-state energy of the fermionic system. This framework, based on perturbation theory, is capable of improving the energy estimate at each cycle of the VQE progression, by about a factor of three closer to the known ground-state energy compared to the standard VQE approach in the test-bed, classically-accessible system of the water molecule. The improved energy estimate in turn results in a commensurate level of savings of quantum resources, such as the number of qubits and quantum gates, required to be within a pre-specified tolerance from the known ground-state energy. We also explore a suite of generalized transformations of fermion to qubit operators and show that resource-requirement savings of up to more than 20 % , in small instances, is possible.

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

Efficient quantum circuits based on the quantum natural gradient

Efficient preparation of arbitrary entangled quantum states is crucial for quantum computation. This is particularly important for noisy intermediate-scale quantum simulators relying on variational hybrid quantum-classical algorithms. To that end, we propose symmetry-conserving modified quantum approximate optimization algorithm (SCom-QAOA) circuits. The depths of these circuits depend not only on the desired fidelity to the target state but also on the amount of entanglement the state contains. The parameters of the SCom-QAOA circuits are optimized using the quantum natural gradient method based on the Fubini-Study metric. The SCom-QAOA circuit transforms an unentangled state into a ground state of a gapped one-dimensional Hamiltonian with a circuit depth that depends not on the system size but rather on the finite correlation length. In contrast, the circuit depth grows proportionally to the system size for preparing low-lying states of critical one-dimensional systems. Even in the latter case, SCom-QAOA circuits with depth less than the system size were sufficient to generate states with fidelity in excess of 99%, which is relevant for near-term applications. The proposed scheme enlarges the set of the initial states accessible for variational quantum algorithms and widens the scope of investigation of nonequilibrium phenomena in quantum simulators. Published by the American Physical Society 2024

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Radiation-Hardened GaN HEMT and Cell Design, Modeling, and Fabrication for Nuclear Instrumentation Applications

Recent advances in nuclear power generation technologies show great promise for efficient, safe generation of carbon-free power in the near future. Consequently, many new generation reactor designs are being pursued by government and industry groups, including both fission- and fusion-based technologies. Radiation- and temperature-tolerant sensor technology continues to advance, yet development of the electronics/instrumentation technologies suitable for these environments have fallen behind. Industry has adequately addressed harsh environment electronics needs for low earth orbit satellites, but the much more extreme conditions associated with electronics placed near or in a reactor core remain unaddressed. This project investigates the use of gallium nitride (GaN) circuit technology to address the unique needs for sensor interface electronics and communications in reactor environments. This report provides a summary of the first year’s project activities related to developing and optimizing devices and circuits for this GaN high electronic mobility transistor (HEMT) process. Activities reported include multiple analog and digital circuit designs simulated using custom Verilog-A models generated from measured GaN devices fabricated in the target process. Digital circuit designs included fundamental logic circuits such as an inverter, NAND, NOR, AND and OR gates, as well as a 5-stage ring oscillator. Each design was simulated using an open-source SPICE simulator, and an integrated circuit layout was produced of each design for use in future fabrication. Analog circuit designs focused on the fundamental building blocks to be used to construct sensor interface and communications circuits. These included current mirrors, matched differential pairs, and a Gilbert cell mixer design, each with an associated integrated circuit layout. Layout tools used for these designs included two open-source packages—KLayout and Magic—which were customized for specific use with the OSU GaN process layers. Design rules and preliminary device extraction capabilities were built for the Magic tool to enable device extraction and subsequent netlist generation for SPICE simulation. Finally, future research directions for year two are summarized. When the year-two directions are implemented, the project will be in position to advance the state of the art in electronics for near- or in-reactor sensor interfacing and communications.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2009

Reconfigurable, Bi-Directional Flexfet Level Shifter for Low-Power, Rad-Hard Integration

Two prototype Reconfigurable, Bi-directional Flexfet Level Shifters (ReBiLS) have been developed, where one version is a stand-alone component designed to interface between external low voltage and high voltage, and the other version is an embedded integrated circuit (IC) for interface between internal low-voltage logic and external high-voltage components. Targeting stand-alone and embedded circuits separately allows optimization for these distinct applications. Both ReBiLS designs use the commercially available 180-nm Flex fet Independently Double-Gated (IDG) SOI CMOS (silicon on insulator, complementary metal oxide semiconductor) technology. Embedded ReBiLS circuits were integrated with a Reed-Solomon (RS) encoder using CMOS Ultra-Low-Power Radiation Tolerant (CULPRiT) double-gated digital logic circuits. The scope of the project includes: creation of a new high-voltage process, development of ReBiLS circuit designs, and adjustment of the designs to maximize performance through simulation, layout, and manufacture of prototypes. The primary technical objectives were to develop a high-voltage, thick oxide option for the 180-nm Flexfet process, and to develop a stand-alone ReBiLS IC with two 8-channel I/O busses, 1.8 2.5 I/O on the low-voltage pins, 5.0-V-tolerant input and 3.3-V output I/O on the high-voltage pins, and 100-MHz minimum operation with 10-pF external loads. Another objective was to develop an embedded, rad-hard ReBiLS I/O cell with 0.5-V low-voltage operation for interface with core logic, 5.0-V-tolerant input and 3.3-V output I/O pins, and 100-MHz minimum operation with 10- pF external loads. A third objective was to develop a 0.5- V Reed-Solomon Encoder with embedded ReBilS I/O: Transfer the existing CULPRiT RS encoder from a 0.35-micron bulk-CMOS process to the ASI 180-nm Flexfet, rad-hard SOI Process. 0.5-V low-voltage core logic. 5.0-V-tolerant input and 3.3-V output I/O pins. 100-MHz minimum operation with 10- pF external loads. The stand-alone ReBiLS chip will allow system designers to provide efficient bi-directional communication between components operating at different voltages. Embedding the ReBiLS cells into the proven Reed-Solomon encoder will demonstrate the ability to support new product development in a commercially viable, rad-hard, scalable 180-nm SOI CMOS process.

DeGregorio, Kelly↗
DOE OSTI2022

Equivalence of quantum barren plateaus to cost concentration and narrow gorges

Optimizing parameterized quantum circuits (PQCs) is the leading approach to make use of near-term quantum computers. However, very little is known about the cost function landscape for PQCs, which hinders progress towards quantum-aware optimizers. In this work, we investigate the connection between three different landscape features that have been observed for PQCs: (1) exponentially vanishing gradients (called barren plateaus (BPs)), (2) exponential cost concentration about the mean, and (3) the exponential narrowness of minima (called narrow gorges). Here we analytically prove that these three phenomena occur together, i.e., when one occurs then so do the other two. A key implication of this result is that one can numerically diagnose BPs via cost differences rather than via the computationally more expensive gradients. More broadly, our work shows that quantum mechanics rules out certain cost landscapes (which otherwise would be mathematically possible), and hence our results could be interesting from a quantum foundations perspective.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Feedforward equilibrium trajectory optimization with GSPulse

One of the common tasks required for designing new plasma scenarios or evaluating capabilities of a tokamak is to design the desired equilibria using a Grad-Shafranov (GS) equilibrium solver. However, most standard equilibrium solvers are time-independent and do not include dynamic effects such as plasma current flux consumption, induced vessel currents, or voltage constraints. Another class of tools, plasma equilibrium evolution simulators, do include time-dependent effects. These are generally structured to solve the forward problem of evolving the plasma equilibrium given feedback-controlled voltages. In this work, we introduce GSPulse, a novel algorithm for equilibrium trajectory optimization, that is more akin to a pulse planner than a pulse simulator. GSPulse includes time-dependent effects and solves the inverse problem: given a user-specified set of target equilibrium shapes, as well as limits on the coil currents and voltages, the optimizer returns trajectories of the voltages, currents, and achievable equilibria. This task is useful for scoping performance of a tokamak and exploring the space of achievable pulses. The computed equilibria satisfy both Grad-Shafranov force balance and axisymmetric circuit dynamics. The optimization is performed by restructuring the free-boundary equilibrium evolution equations into a form where it is computationally efficient to optimize the entire dynamic sequence. GSPulse can solve for hundreds of equilibria simultaneously within a few minutes. GSPulse has been validated against NSTX-U and MAST-U experiments and against SPARC feedback control simulations, and is being used to perform scenario design for SPARC. The computed trajectories can be used as feedforward inputs that are connected to the feedback controller to inform and improve feedback performance. The code for GSPulse is available open-source at github.com/jwai-cfs/GSPulse_public.

equilibrium↗
NASA NTRS2009

Passively Shunted Piezoelectric Damping of Centrifugally-Loaded Plates

Researchers at NASA Glenn Research Center have been investigating shunted piezoelectric circuits as potential damping treatments for turbomachinery rotor blades. This effort seeks to determine the effects of centrifugal loading on passively-shunted piezoelectric - damped plates. Passive shunt circuit parameters are optimized for the plate's third bending mode. Tests are performed both non-spinning and in the Dynamic Spin Facility to verify the analysis, and to determine the effectiveness of the damping under centrifugal loading. Results show that a resistive shunt circuit will reduce resonant vibration for this configuration. However, a tuned shunt circuit will be required to achieve the desired damping level. The analysis and testing address several issues with passive shunt circuit implementation in a rotating system, including piezoelectric material integrity under centrifugal loading, shunt circuit implementation, and tip mode damping.

Duffy, Kirsten P.↗
DOE OSTI2026

Tradeoffs in single stage drift step recovery diode generator design

A high-voltage generator of nanosecond pulses utilizing a drift step recovery diode (DSRD) as an opening switch in the compression section is designed to operate at peak voltages of 4 kV and repetition rates of 2 MHz in burst mode at reduced voltages. The generator is used to perform empirical studies on the output metrics of a DSRD generator with a focus on matching the circuit of the reverse current loop parameters and DSRD to the load. The dynamic impedance introduced by nonlinear elements in the DSRD was investigated with respect to the driving circuit by varying the number of DSRDs connected in series. Experimental results indicate that optimization of the driving circuit for the DSRD is key to minimizing losses and achieving optimal pulse compression. Furthermore, the results also indicate trends in DSRD performance as larger storage inductances and longer pumping times are used, limiting the pulse compression capabilities of a single stage DSRD generator.

Electrical properties and parameters↗
DOE OSTI2022

Optimization of a gas–liquid plasma reactor for water treatment applications: Design guidelines and electrical circuit considerations

To provide insights into the design, optimization, and scale up of plasma reactors for water treatment, the influences of discharge energy, grounded electrode size and position, and number of high voltage (HV) discharge points on the production of reactive species and the degradation of 1,4-dioxane and perfluorooctanoic acid in a gas–liquid electrical discharge plasma reactor were assessed. Discharge energy and plasma area largely control the treatment effectiveness. Increasing the number of discharge points lowers the voltage in the reactor and consequently the production rates of reactive species. Finally, bench-scale findings apply directly to large volume systems, resulting in the highest contaminant removal rates using a single HV electrode and a grounded electrode spanning the entirety of the treatment zone.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Hamiltonian variational ansatz without barren plateaus

Variational quantum algorithms, which combine highly expressive parameterized quantum circuits (PQCs) and optimization techniques in machine learning, are one of the most promising applications of a near-term quantum computer. Despite their huge potential, the utility of variational quantum algorithms beyond tens of qubits is still questioned. One of the central problems is the trainability of PQCs. The cost function landscape of a randomly initialized PQC is often too flat, asking for an exponential amount of quantum resources to find a solution. This problem, dubbed barren plateaus , has gained lots of attention recently, but a general solution is still not available. In this paper, we solve this problem for the Hamiltonian variational ansatz (HVA), which is widely studied for solving quantum many-body problems. After showing that a circuit described by a time-evolution operator generated by a local Hamiltonian does not have exponentially small gradients, we derive parameter conditions for which the HVA is well approximated by such an operator. Based on this result, we propose an initialization scheme for the variational quantum algorithms and a parameter-constrained ansatz free from barren plateaus.

Physics↗
DOE OSTI2025

Lie-algebraic classical simulations for quantum computing

The classical simulation of quantum dynamics plays an important role in our understanding of quantum complexity and in the development of quantum technologies. Efficient techniques such as those based on the Gottesman-Knill theorem for Clifford circuits, tensor networks for low entanglement-generating circuits, or Wick's theorem for fermionic Gaussian states have become central tools in quantum computing. In this work, we contribute to this body of knowledge by presenting a framework for classical simulations, dubbed “𝔤-sim”, which is based on the underlying Lie algebraic structure of the dynamical process. When the dimension of the algebra grows at most polynomially in the system size, there exist observables for which the simulation is efficient. Indeed, we show that 𝔤-sim enables new regimes for classical simulations, is able to deal with certain forms of noise in the evolution, as well as can be used to tackle several paradigmatic variational and nonvariational quantum computing tasks. For the former, we perform Lie-algebraic simulations to train and optimize parametrized quantum circuits (thus effectively showing that some variational models can be dequantized), design enhanced parameter initialization strategies, solve tasks of quantum circuit synthesis, and train a quantum-phase classifier. For the latter, we report large-scale noiseless and noisy simulations on benchmark problems. By comparing the limitations of 𝔤-sim and certain Wick's theorem-based simulations, we find that the two methods become inefficient for different types of states or observables, hinting at the existence of distinct, nonequivalent resources for classical simulation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Adaptive Circuit Learning for Quantum Metrology

Quantum sensing is an important application of emerging quantum technologies. We explore whether a hybrid system of quantum sensors and quantum circuits can surpass the classical limit of sensing. In particular, we use optimization techniques to search for encoder and decoder circuits that scalably improve sensitivity under given application and noise characteristics. Furthermore, our approach uses a variational algorithm that can learn a quantum sensing circuit based on platform-specific control capacity, noise, and signal distribution. The quantum circuit is composed of an encoder which prepares the optimal sensing state and a decoder which gives an output distribution containing information of the signal. We optimize the full circuit to maximize the Signal-to-Noise Ratio (SNR). Furthermore, this learning algorithm can be run on real hardware scalably by using the "parameter-shift" rule which enables gradient evaluation on noisy quantum circuits, avoiding the exponential cost of quantum system simulation. We demonstrate up to 13.12x SNR improvement over existing fixed protocol (GHZ), and 3.19x Classical Fisher Information (CFI) improvement over the classical limit on 15 qubits using IBM quantum computer. More notably, our algorithm overcomes the decreasing performance of existing entanglement-based protocols with increased system sizes.

42 ENGINEERING↗
DOE OSTI2022

Solving Large‐Scale Linear Systems of Equations by a Quantum Hybrid Algorithm

Abstract Today's intermediate‐scale quantum computers, although imperfect, already perform computational tasks that are manifestly beyond the capabilities of modern classical supercomputers. However, so far, quantum‐enabled large‐scale solutions have been realized only for limited set of problems. Here a hybrid algorithm based on phase estimation and classical optimization of the circuit width and depth is employed for solving a specific class of large linear systems of equations ubiquitous to many areas of science and engineering. A classification of linear systems based on the entanglement properties of the associated phase‐estimation unitary operation is introduced, enabling a highly efficient search for solutions that is facilitated by a straightforward matrix‐to‐circuit map. A 2 17 ‐dimensional problem is implemented on several IBM quantum computer superconducting quantum processors, a record‐breaking result for a linear system solved by a quantum computer. Demonstrated realisation sets a clear benchmark in the quest for the future quantum speedup in the linear systems of equations solution.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Short-depth QAOA circuits and quantum annealing on higher-order ising models

Abstract We present a direct comparison between QAOA (Quantum Alternating Operator Ansatz), and QA (Quantum Annealing) on 127 qubit problem instances. QAOA with p = 1, 2 rounds is executed on the 127 qubit heavy-hex graph gate-model quantum computer ibm_washington, using on-device grid-searches for angle finding, and QA is executed on two Pegasus-chip D-Wave quantum annealers. The problems are random Ising models whose connectivity matches heavy-hex graphs and the Pegasus graph connectivity, and optionally include hardware-compatible cubic terms ( Z Z Z terms). The QAOA circuits are heavily optimized and of extremely short depth, with a CNOT depth of 6 per round, which allows whole chip usage of the heavy-hex lattice. QAOA and QA are both compared against simulated annealing and the optimal solutions are computed exactly using CPLEX. The noiseless mean QAOA expectation values for p = 1, 2 are computed using classical light-cone based simulations. We find QA outperforms QAOA on the evaluated devices.

127 qubits↗