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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Optimizing qubit control pulses for state preparation

In the burgeoning field of quantum computing, the precise design and optimization of quantum pulses are essential for enhancing qubit operation fidelity. This study focuses on refining the pulse engineering techniques for superconducting qubits, employing a detailed analysis of square and Gaussian pulse envelopes under various approximation schemes. We evaluated the effects of coherent errors induced by naive pulse designs. Furthermore, we identified the sources of these errors in the Hamiltonian model’s approximation level. We mitigated these errors through adjustments to the external driving frequency and pulse durations, thus implementing a pulse scheme with stroboscopic error reduction. Our results demonstrate that these refined pulse strategies improve performance and reduce coherent errors. Moreover, the techniques developed herein are applicable across different quantum architectures, such as ion-trap, atomic, and photonic systems.

Chirp modulation↗
DOE OSTI2026

A cryogenic muon tagging system based on kinetic inductance detectors for superconducting quantum processors

Ionizing radiation has emerged as a potential limiting factor for superconducting quantum processors, inducing quasiparticle bursts and correlated errors that challenge fault-tolerant operation. Atmospheric muons are particularly problematic due to their high energy and penetration power, making passive shielding ineffective. Therefore, monitoring the real-time muon flux is crucial to guide the development of alternative error-correction or mitigation strategies. We present the design, simulation, and first operation of a cryogenic muon-tagging system based on kinetic inductance detectors (KIDs), developed as a stand-alone cryogenic particle-tagging module for superconducting quantum processors. The system consists of two KIDs arranged in a vertical stack and operated at ∼20 mK. Monte Carlo simulations based on Geant4 guided the prototype design and provided reference expectations for muon-tagging efficiency and accidental coincidences due to ambient γ-rays. We observed a muon-induced coincidence rate among the top and bottom detectors of (192 ± 9) $\times\,10^{-3}$ events s$^{−1}$, in excellent agreement with the Monte Carlo prediction. The prototype achieves a muon-tagging efficiency of about 90% with negligible dead time. These results demonstrate the feasibility of operating a muon-tagging system at millikelvin temperatures and represent a key step toward the integration of cryogenic veto systems with multi-qubit chips to mitigate muon-induced errors.

Mariani, Ambra [INFN, Rome] (ORCID:000000028184857↗
DOE OSTI2025

Quantifying the impact of precision errors on quantum approximate optimization algorithms

The quantum approximate optimization algorithm (QAOA) is a hybrid quantum-classical algorithm that seeks to achieve approximate solutions to optimization problems by iteratively alternating between intervals of controlled quantum evolution. Here, we examine the effect of analog precision errors on QAOA performance from the perspective of both algorithmic training and performance guarantees. Leveraging cumulant expansions, we recast the faulty QAOA as a control problem in which precision errors are expressed as multiplicative control noise and derive bounds on the performance of QAOA. We show using both analytical techniques and numerical simulations that fixed precision implementations of QAOA circuits are subject to an exponential degradation in performance dependent upon the number of optimal QAOA layers and magnitude of the precision error. Despite this significant reduction, we show that it is possible to mitigate precision errors in QAOA via digitization of the variational parameters at the cost of increasing circuit depth.

quantum algorithms↗
DOE OSTI2024

Quantum Information for Fusion Energy Sciences (Final Technical Report)

The simulation of plasma dynamics is a critical area of Fusion Energy Sciences (FES) due to it’s usefulness in predicting, controlling, and confining plasmas in the context of potential fusion reactors. The simulation of plasmas is a computationally difficult problem in both classical and quantum physics, motivating investigation into the potential of quantum computers to simulate these systems. This project took several concrete steps towards this goal by developing tools for improving the control, characterization, and calibration of quantum gates on a superconducting quantum computer, developing error suppression and mitigation tools to reduce errors on the quantum computer, and utilizing these advancements to simulate reduced models of plasma dynamics on the quantum computer.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Using Density-Corrected DFT to Understand Density-Driven and Functional-Dependent Errors in Ab Initio Simulations of the Hydrated Electron

The hydrated electron, an excess electron in liquid water, plays a crucial role in a plethora of chemical processes, motivating extensive research efforts to characterize its structure, dynamics, and reactivity in solution. Recent theoretical approaches to understanding this intriguing object have involved ab initio simulations based on density functional theory (DFT). Although DFT allows for the study of hydrated electron reactivity and quantum mechanical behavior, it is well-known that anionic systems can suffer from significant density-driven errors (DDEs). Density-corrected DFT (DC-DFT) provides a framework to mitigate such errors; the method reduces DDEs by replacing the self-consistent (SC) density associated with a given density functional with the Hartree–Fock (HF) density. Since HF densities tend to be more localized than DFT SC densities, the DC-DFT scheme significantly improves errors in calculations where the SC density is spuriously delocalized. Here, we investigate how the use of density correction affects the calculated properties of the DFT-simulated (PBEh) hydrated electron, a particularly challenging diffuse anionic system to simulate. First, we analyze charge delocalization in a system consisting of a model octahedral hydrated electron water cluster (the so-called Kevan structure) along with a spatially separated sulfur atom. We show that the use of density correction indeed reduces DDEs in comparison to a standard DFT global hybrid functional. We then propagate molecular dynamics trajectories of the hydrated electron using DC-DFT, where we find that DC further localizes electron density in the cavity region, a signature of reduced charge delocalization. Unfortunately, the decreased radius of gyration of the spin density and corresponding tightening of the local solvation structure from density correction causes predicted observables to deviate further from experimental measurements than when density correction is not employed. Here, we argue that DC’s worse agreement with experiment results from the removal of a fortuitous cancellation of errors that is intrinsic to the PBEh functional. This indicates that the difficulties with DFT to simulate hydrated electrons are primarily due to the inherent approximations in DFT rather than to density-driven errors.

Density functional theory↗
DOE OSTI2025

How Representative Are Uncrewed Aircraft System Measurements of the Convective Boundary Layer?

Abstract Uncrewed aircraft systems (UAS) demonstrate significant potential for filling data gaps in the atmospheric boundary layer. However, the extent to which UAS observations—typically vertical profiles taken over 15 min—are representative of the boundary layer as a whole remains poorly characterized. Using large eddy simulations (LES) of the daytime convective boundary layer (CBL), we quantify random errors in UAS measurements that occur due to insufficient statistical convergence of the time average to the true ensemble mean. Random errors in first‐order moments increase as the CBL becomes increasingly unstable, and are largest near the surface for most quantities. Errors are on the order of 2–6 m for wind speed, 15–60 for wind direction, 0.2–3 K for potential temperature, and 0.1–1 g for specific humidity, with errors in turbulent fluxes on the order of 50%–100%. Sampling strategies that mitigate random errors are discussed in light of our results.

Greene, Brian R. [Now at Verisk Extreme Event Solu↗
DOE OSTI2015

Multi-qubit gates protected by adiabaticity and dynamical decoupling applicable to donor qubits in silicon

In this paper, we present a strategy for producing multiqubit gates that promise high fidelity with minimal tuning requirements. Our strategy combines gap protection from the adiabatic theorem with dynamical decoupling in a complementary manner. Energy-level transition errors are protected by adiabaticity and remaining phase errors are mitigated via dynamical decoupling. This is a powerful way to divide and conquer the various error channels. In order to accomplish this without violating a no-go theorem regarding black-box dynamically corrected gates [Phys. Rev. A 80, 032314 (2009)], we require a robust operating point (sweet spot) in control space where the qubits interact with little sensitivity to noise. There are also energy gap requirements for effective adiabaticity. We apply our strategy to an architecture in Si with P donors where we assume we can shuttle electrons between different donors. Electron spins act as mobile ancillary qubits and P nuclear spins act as long-lived data qubits. Furthermore, this system can have a very robust operating point where the electron spin is bound to a donor in the quadratic Stark shift regime. High fidelity single qubit gates may be performed using well-established global magnetic resonance pulse sequences. Single electron-spin preparation and measurement has also been demonstrated. Thus, putting this all together, we present a robust universal gate set for quantum computation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Ferroelectric capacitors and field-effect transistors as in-memory computing elements for machine learning workloads

Abstract This study discusses the feasibility of Ferroelectric Capacitors (FeCaps) and Ferroelectric Field-Effect Transistors (FeFETs) as In-Memory Computing (IMC) elements to accelerate machine learning (ML) workloads. We conducted an exploration of device fabrication and proposed system-algorithm co-design to boost performance. A novel FeCap device, incorporating an interfacial layer (IL) and$$\text {Hf}_{0.5}\text {Zr}_{0.5}\text {O}_2$$ Hf 0.5 Zr 0.5 O 2 (HZO), ensures a reduction in operating voltage and enhances HZO scaling while being compatible with CMOS circuits. The IL also enriches ferroelectricity and retention properties. When integrated into crossbar arrays, FeCaps and FeFETs demonstrate their effectiveness as IMC components, eliminating sneak paths and enabling selector-less operation, leading to notable improvements in energy efficiency and area utilization. However, it is worth noting that limited capacitance ratios in FeCaps introduced errors in multiply-and-accumulate (MAC) computations. The proposed co-design approach helps in mitigating these errors and achieves high accuracy in classifying the CIFAR-10 dataset, elevating it from a baseline of 10% to 81.7%. FeFETs in crossbars, with a higher on-off ratio, outperform FeCaps, and our proposed charge-based sensing scheme achieved at least an order of magnitude reduction in power consumption, compared to prevalent current-based methods.

Science & Technology - Other Topics↗
DOE OSTI2022

Digital Quantum Simulation of the Schwinger Model and Symmetry Protection with Trapped Ions

Tracking the dynamics of physical systems in real time is a prime application of quantum computers. Using a trapped-ion system with up to six qubits, we simulate the real-time dynamics of a lattice gauge theory in 1+1 dimensions, i.e., the lattice Schwinger model, and demonstrate nonperturbative effects such as pair creation for times much longer than previously accessible. We study the gate requirement of two formulations of the model using the Suzuki-Trotter product formula, as well as the trade-off between errors from the ordering of the Hamiltonian terms, the Trotter step size, and experimental imperfections. To mitigate experimental errors, a recent symmetry-protection protocol for suppressing coherent errors and a symmetry-inspired postselection scheme are applied. This work demonstrates the integrated theoretical, algorithmic, and experimental approach that is essential for efficient simulation of lattice gauge theories and other complex physical systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

An exploration of online-simulation-driven portfolio scheduling in Workflow Management Systems

Workflow Management Systems used to automate the execution of scientific workflow applications on parallel and distributed computing platforms must make scheduling decisions at runtime. A large number of workflow scheduling algorithms have been proposed in the literature, but often these algorithms are evaluated based on simplifying assumptions that may not hold in practice. Furthermore, published algorithm evaluation and/or comparison results are necessarily only for a subset of all possible scenarios, and thus may not include scenarios relevant to particular use-cases. Consequently, it is difficult for Workflow Management Systems (WMSs) developers to decide which scheduling algorithm should be implemented. To obviate this difficulty, one possible approach is to implement a portfolio of scheduling algorithms and select the most effective algorithm at runtime. One method for performing this selection is to run an online simulation for each algorithm in the portfolio. The algorithm that leads to the best performance, in simulation, is selected for future use. The above simulation-driven portfolio scheduling (SDPS) approach has been proposed in a few parallel and distributed computing contexts. The main objective of this work is to evaluate the feasibility and potential merit of SDPS if implemented in WMSs. Here we perform this evaluation using simulated WMS executions, where the simulations are instantiated from real-world platform and workflow configurations. Our main finding is that SDPS is on par with or outperforms an approach in which a single algorithm is used, where this algorithm is the one that performs best on average across all our experimental scenarios. Furthermore, we find that SDPS remains an attractive proposition even in the presence of high levels of simulation error and for simulators with relatively low levels of sophistication. In many of our experimental scenarios we find that mitigating simulation error at runtime can further improve performance. Finally, we show that simulation overhead can be made sufficiently low for SDPS to be feasible in practice.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Reducing the Spatial Discretization Error of Thermal Emission in Implicit Monte Carlo Simulations

Implicit Monte Carlo simulations of thermal radiative transport can exhibit what is known as teleportation error in problems with strong coupling between radiation and matter. Teleportation error occurs when energy deposited in a localized region of a spatial zone is emitted throughout the zone in the next time step. Teleportation error is commonly reduced by biasing the positions of photon thermal emission using a fit to the spatial distribution of temperature to the fourth power. The current work samples and stores locations along photon paths based on absorption probabilities. These locations are used as sites for emission in the subsequent time step. This method of teleportation correction is demonstrated in several sample problems, and is validated against an Implicit Monte Carlo Diffusion Method, which does not exhibit teleportation error. We report the new method reduces teleportation error relative to the source tilting method, and enables the use of lower spatial resolutions than would be required to mitigate teleportation error using the source tilting method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Temperature dependent index of refraction compensation and radiation resistance in monolithic optical systems

Monolithic catadioptric optical systems are susceptible to defocus errors caused by inhomogeneous temperature within the glass material due to temperature dependent index of refraction. This invention discloses methods to mitigate these errors using tuned materials in its optical design coupled with active optical radiative heating to provide optimal performance and includes methods to enhance radiation resistance.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Error rate reduction of single-qubit gates via noise-aware decomposition into native gates

In the current era of Noisy Intermediate-Scale Quantum (NISQ) technology, the practical use of quantum computers remains inhibited by our inability to aptly decouple qubits from their environment to mitigate computational errors. In this paper, we introduce an approach by which knowledge of a qubit’s initial quantum state and the standard parameters describing its decoherence can be leveraged to mitigate the noise present during the execution of a single-qubit gate. We benchmark our protocol using cloud-based access to IBM quantum processors. On ibmq_rome, we demonstrate a reduction of the single-qubit error rate by 38%, from $1.6 \times 10 ^{-3}$ to $1.0 \times 10 ^{-3}$ , provided the initial state of the input qubit is known. On ibmq_bogota, we prove that our protocol will never decrease gate fidelity, provided the system’s T 1 and T 2 times have not drifted above 100 times their assumed values. The protocol can be used to reduce quantum state preparation errors, as well as to improve the fidelity of quantum circuits for which some knowledge of the qubits’ intermediate states can be inferred. This paper presents a pathway to using information about noise levels and quantum state distributions to significantly reduce error rates associated with quantum gates via optimized decomposition into native hardware gates.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Characterization of Soft Error Rate Against Memory Elements Spacing and Clock Skew in a Logic with Triple Modular Redundancy in a 65nm Process

Single Event Effects introduce soft errors in ASICs. Design methodologies like Triple ModularRedundancy (TMR) with clock skew insertion, a system level redundancy technique is a commonpractice by designers to mitigate soft errors. However, the optimal spacing between memoryelements in a TMR in 65nm process hasn't been addressed so far. RD53SEU is a mini ASICdevelopment under the framework of the CERN RD53 collaboration to characterize the soft errorrates against the separation spacing and clock skew between memory elements in a TMR. Thisarticle describes the architecture and design aspects of the various test structures on the RD53SEUtest chip.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Variational quantum simulation of the critical Ising model with symmetry averaging

Here we investigate the use of deep multiscale entanglement renormalization ansatz (DMERA) circuits as a variational ansatz. We use the exactly solvable one-dimensional critical transverse-field Ising model as a test bed. Numerically exact simulation of the quantum circuit ansatz can in this case be carried out to hundreds of qubits by exploiting efficient classical algorithms for simulating matchgate circuits. We find that, for this system, the DMERA strongly outperforms a standard quantum approximate optimization algorithm (QAOA)–style ansatz, and that a major source of systematic error in correlation functions approximated using the DMERA is the breaking of the translational and Kramers-Wannier symmetries of the transverse-field Ising model. We are able to reduce this error by up to four orders of magnitude by symmetry averaging, without incurring additional cost in qubits or circuit depth. Here, we propose that this technique for mitigating systematic error could be applied to noisy intermediate-scale quantum (NISQ) simulations of physical systems with other symmetries.

1-dimensional spin chains↗
DOE OSTI2014

Effects of Spectral Error in Efficiency Measurements of GaInAs-Based Concentrator Solar Cells

This technical report documents a particular error in efficiency measurements of triple-absorber concentrator solar cells caused by incorrect spectral irradiance -- specifically, one that occurs when the irradiance from unfiltered, pulsed xenon solar simulators into the GaInAs bottom subcell is too high. For cells designed so that the light-generated photocurrents in the three subcells are nearly equal, this condition can cause a large increase in the measured fill factor, which, in turn, causes a significant artificial increase in the efficiency. The error is readily apparent when the data under concentration are compared to measurements with correctly balanced photocurrents, and manifests itself as discontinuities in plots of fill factor and efficiency versus concentration ratio. In this work, we simulate the magnitudes and effects of this error with a device-level model of two concentrator cell designs, and demonstrate how a new Spectrolab, Inc., Model 460 Tunable-High Intensity Pulsed Solar Simulator (T-HIPSS) can mitigate the error.

14 SOLAR ENERGY↗
DOE OSTI2014

Radiation-induced refraction artifacts in the optical CT readout of polymer gel dosimeters

Purpose: The objective of this work is to demonstrate imaging artifacts that can occur during the optical computed tomography (CT) scanning of polymer gel dosimeters due to radiation-induced refractive index (RI) changes in polyacrylamide gels. Methods: A 1 L cylindrical polyacrylamide gel dosimeter was irradiated with 3 × 3 cm{sup 2} square beams of 6 MV photons. A prototype fan-beam optical CT scanner was used to image the dosimeter. Investigative optical CT scans were performed to examine two types of rayline bending: (i) bending within the plane of the fan-beam and (ii) bending out the plane of the fan-beam. To address structured errors, an iterative Savitzky–Golay (ISG) filtering routine was designed to filter 2D projections in sinogram space. For comparison, 2D projections were alternatively filtered using an adaptive-mean (AM) filter. Results: In-plane rayline bending was most notably observed in optical CT projections where rays of the fan-beam confronted a sustained dose gradient that was perpendicular to their trajectory but within the fan-beam plane. These errors caused distinct streaking artifacts in image reconstructions due to the refraction of higher intensity rays toward more opaque regions of the dosimeter. Out-of-plane rayline bending was observed in slices of the dosimeter that featured dose gradients perpendicular to the plane of the fan-beam. These errors caused widespread, severe overestimations of dose in image reconstructions due to the higher-than-actual opacity that is perceived by the scanner when light is bent off of the detector array. The ISG filtering routine outperformed AM filtering for both in-plane and out-of-plane rayline errors caused by radiation-induced RI changes. For in-plane rayline errors, streaks in an irradiated region (>7 Gy) were as high as 49% for unfiltered data, 14% for AM, and 6% for ISG. For out-of-plane rayline errors, overestimations of dose in a low-dose region (∼50 cGy) were as high as 13 Gy for unfiltered data, 10 Gy for AM, and 3.1 Gy for ISG. The ISG routine also addressed unrelated artifacts that previously needed to be manually removed in sinogram space. However, the ISG routine blurred reconstructions, causing losses in spatial resolution of ∼5 mm in the plane of the fan-beam and ∼8 mm perpendicular to the fan-beam. Conclusions: This paper reveals a new category of imaging artifacts that can affect the optical CT readout of polyacrylamide gel dosimeters. Investigative scans show that radiation-induced RI changes can cause significant rayline errors when rays confront a prolonged dose gradient that runs perpendicular to their trajectory. In fan-beam optical CT, these errors manifested in two ways: (1) distinct streaking artifacts caused by in-plane rayline bending and (2) severe overestimations of opacity caused by rays bending out of the fan-beam plane and missing the detector array. Although the ISG filtering routine mitigated these errors better than an adaptive-mean filtering routine, it caused unacceptable losses in spatial resolution.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Combining compositional data sets introduces error in covariance network reconstruction

Microbial communities are diverse biological systems that include taxa from across multiple kingdoms of life. Notably, interactions between bacteria and fungi play a significant role in determining community structure. However, these statistical associations across kingdoms are more difficult to infer than intra-kingdom associations due to the nature of the data involved using standard network inference techniques. We quantify the challenges of cross-kingdom network inference from both theoretical and practical points of view using synthetic and real-world microbiome data. We detail the theoretical issue presented by combining compositional data sets drawn from the same environment, e.g. 16S and ITS sequencing of a single set of samples, and we survey common network inference techniques for their ability to handle this error. We then test these techniques for the accuracy and usefulness of their intra- and interkingdom associations by inferring networks from a set of simulated samples for which a ground-truth set of associations is known. We show that while the two methods mitigate the error of cross-kingdom inference, there is little difference between techniques for key practical applications including identification of strong correlations and identification of possible keystone taxa (i.e. hub nodes in the network). Furthermore, we identify a signature of the error caused by transkingdom network inference and demonstrate that it appears in networks constructed using real-world environmental microbiome data.

59 BASIC BIOLOGICAL SCIENCES↗