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At least 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Captan+X Data Converter Integration

Fermi National Accelerator Laboratory's CAPTAN (Compact And Programmable daTa Acquisition Node) series provides a flexible hardware platform for data acquisition across a range of experiments and facilities. The latest iteration, CAPTAN+X, is built around a Kintex-7 FPGA supporting four FPGA Mezzanine Card (FMC) connections. As part of a broader laboratory effort to bring facility systems under a Model-Based Systems Engineering (MBSE) framework, CAPTAN+X is one of several systems slated to be incorporated into this modeling environment in the near term. A necessary step toward that goal is incorporating the platform's core functionality, which centers on integration with the LXD31K4 FMC, a data converter module combining dual AD9652 analog-to-digital converters and dual AD9142A digital-to-analog converters. Achieving compatibility required resolving pin-mapping conflicts between the LXD31K4's High Pin Count connector and the CAPTAN+X's available pin types, adapting a Board Support Project originally written for an UltraScale-class evaluation board to the Kintex-7 architecture, replacing incompatible primitives, restructuring clock distribution, and manually configuring chip initialization in place of an unsupported soft-processor-based approach. Functional verification of the ADC and DAC channels, followed by closed-loop testing combining both converters with real-time filtering, confirmed correct operation of the integrated system. These results establish a working hardware and firmware baseline for the CAPTAN+X platform, positioning it for future inclusion in the laboratory's growing MBSE modeling effort.

Espinoza, David [Illinois U., Urbana (main)]↗
DOE OSTI2026

A Cryogenic Muon Tagging System Integrated with a Superconducting Qubit Device for Radiation-Induced Error Mitigation

Superconducting qubits are highly sensitive to ionizing radiation, which can induce correlated errors and limit scalable fault-tolerant quantum computing. In particular, cosmic-ray muons can deposit energy in the substrate, generating phonon bursts that break Cooper pairs and produce quasiparticles, leading to correlated decoherence events across multiple qubits. We present the development of a cryogenic muon tagging system based on Kinetic Inductance Detectors (KIDs) and its integration with superconducting quantum hardware. Originally developed within the ACE-SuperQ project and validated as a standalone detector, the system demonstrated a muon tagging efficiency of approximately 90% and excellent agreement with Monte Carlo simulations. Building on this validation, the tagging system has been integrated with a multi-qubit superconducting chip operated in a dilution refrigerator. The detector configuration consists of a multi-layer KID stack arranged above and below the quantum device, enabling time-coincident identification of muon-induced events within the same cryogenic environment. The integrated setup has been successfully commissioned, enabling simultaneous operation of the qubit chip and the muon tagging system. A first measurement campaign has been carried out, and preliminary data show time-correlated events between the muon tagging detectors and the qubit readout. A quantitative analysis of radiation-induced effects on qubit performance is currently ongoing. This work represents a step toward the implementation of event-level radiation tagging as a tool for characterizing and potentially mitigating correlated errors in superconducting quantum processors, while establishing a modular platform for future studies at the interface between particle physics and quantum information science.

Roy, Tanay [Fermilab] (ORCID:000000019442862X)↗
DOE OSTI2024

Qudit-based quantum computing with SRF cavities at Fermilab

Superconducting radio frequency (SRF) cavities provide an excellent platform for storing quantum information as quantum $d$-level systems (qudits) due to their exceptionally long lifetimes and large accessible Hilbert spaces. A common strategy to manipulate the states is to use a nonlinear element like a transmon. There are, however, several challenges to building a 3D SRF architecture while maintaining a long cavity lifetime. We demonstrate our successful integration of transmons with single-cell Nb SRF cavities and the ability to prepare several non-classical states. Finally, we discuss our strategies to improve the coherence times, gate schemes, and extend the system for building a multi-qudit quantum processor.

Roy, Tanay↗
DOE OSTI2020

Operational, gauge-free quantum tomography

As increasingly impressive quantum information processors are realized in laboratories around the world, robust and reliable characterization of these devices is now more urgent than ever. These diagnostics can take many forms, but one of the most popular categories is tomography, where an underlying parameterized model is proposed for a device and inferred by experiments. Here, we introduce and implement efficient operational tomography, which uses experimental observables as these model parameters. This addresses a problem of ambiguity in representation that arises in current tomographic approaches (the gauge problem). Solving the gauge problem enables us to efficiently implement operational tomography in a Bayesian framework computationally, and hence gives us a natural way to include prior information and discuss uncertainty in fit parameters. We demonstrate this new tomography in a variety of different experimentally-relevant scenarios, including standard process tomography, Ramsey interferometry, randomized benchmarking, and gate set tomography.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Gate Set Tomography

Gate set tomography (GST) is a protocol for detailed, predictive characterization of logic operations (gates) on quantum computing processors. Early versions of GST emerged around 2012-13, and since then it has been refined, demonstrated, and used in a large number of experiments. This paper presents the foundations of GST in comprehensive detail. The most important feature of GST, compared to older state and process tomography protocols, is that it is calibration-free . GST does not rely on pre-calibrated state preparations and measurements. Instead, it characterizes all the operations in a gate set simultaneously and self-consistently, relative to each other. Long sequence GST can estimate gates with very high precision and efficiency, achieving Heisenberg scaling in regimes of practical interest. In this paper, we cover GST's intellectual history, the techniques and experiments used to achieve its intended purpose, data analysis, gauge freedom and fixing, error bars, and the interpretation of gauge-fixed estimates of gate sets. Our focus is fundamental mathematical aspects of GST, rather than implementation details, but we touch on some of the foundational algorithmic tricks used in the pyGSTi implementation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Mitiq: A software package for error mitigation on noisy quantum computers

We introduce Mitiq, a Python package for error mitigation on noisy quantum computers. Error mitigation techniques can reduce the impact of noise on near-term quantum computers with minimal overhead in quantum resources by relying on a mixture of quantum sampling and classical post-processing techniques. Mitiq is an extensible toolkit of different error mitigation methods, including zero-noise extrapolation, probabilistic error cancellation, and Clifford data regression. The library is designed to be compatible with generic backends and interfaces with different quantum software frameworks. We describe Mitiq using code snippets to demonstrate usage and discuss features and contribution guidelines. We present several examples demonstrating error mitigation on IBM and Rigetti superconducting quantum processors as well as on noisy simulators.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Ancilla-free continuous-variable SWAP test

We propose a continuous-variable (CV) SWAP test that requires no ancilla register, thereby generalizing the ancilla-free SWAP test for qubits. In this ancilla-free CV SWAP test, the computational basis measurement is replaced by photon number-resolving measurement, and we calculate an upper bound on the error of the overlap estimate obtained from a finite Fock cutoff in the detector. As an example, we show that estimation of the overlap of pure, centered, single-mode Gaussian states of energy E and squeezed in opposite quadratures can be obtained to error ϵ using photon statistics below a Fock basis cutoff O(Elnϵ –1 ). This cutoff is greatly reduced to E + O(√ Elnϵ –1 ) when the states have rapidly decaying Fock tails, such as coherent states. We show how the ancilla-free CV SWAP test can be extended to many modes and applied to quantum algorithms such as variational compiling and entanglement spectroscopy in the CV setting. For the latter we also provide a new algorithm which does not have an analog in qubit systems. The ancilla-free CV SWAP test is implemented on Xanadu's 8-mode photonic processor in order to estimate the vacuum probability of a two-mode squeezed state.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Model predictive control for robust quantum state preparation

A critical engineering challenge in quantum technology is the accurate control of quantum dynamics. Model-based methods for optimal control have been shown to be highly effective when theory and experiment closely match. Consequently, realizing high-fidelity quantum processes with model-based control requires careful device characterization. In quantum processors based on cold atoms, the Hamiltonian can be well-characterized. For superconducting qubits operating at milli-Kelvin temperatures, the Hamiltonian is not as well-characterized. Unaccounted for physics (i.e., mode discrepancy), coherent disturbances, and increased noise compromise traditional model-based control. This work introduces model predictive control (MPC) for quantum control applications. MPC is a closed-loop optimization framework that (i) inherits a natural degree of disturbance rejection by incorporating measurement feedback, (ii) utilizes finite-horizon model-based optimizations to control complex multi-input, multi-output dynamical systems under state and input constraints, and (iii) is flexible enough to develop synergistically alongside other modern control strategies. We show how MPC can be used to generate practical optimized control sequences in representative examples of quantum state preparation. Specifically, we demonstrate for a qubit, a weakly-anharmonic qubit, and a system undergoing crosstalk, that MPC can realize successful model-based control even when the model is inadequate. These examples showcase why MPC is an important addition to the quantum engineering control suite.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Completely Positive Map for Noisy Driven Quantum Systems Derived by Keldysh Expansion

Accurate modeling of decoherence errors in quantum processors is crucial for analyzing and improving gate fidelities. To increase the accuracy beyond that of the Lindblad dynamical map, several generalizations have been proposed, and the exploration of simpler and more systematic frameworks is still ongoing. In this paper, we introduce a decoherence model based on the Keldysh formalism. This formalism allows us to include non-periodic drives and correlated quantum noise in our model. In addition to its wide range of applications, our method is also numerically simple, and yields a CPTP map. These features allow us to integrate the Keldysh map with quantum-optimal-control techniques. We demonstrate that this strategy generates pulses that mitigate correlated quantum noise in qubit state-transfer and gate operations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Efficiently improving the performance of noisy quantum computers

Using near-term quantum computers to achieve a quantum advantage requires efficient strategies to improve the performance of the noisy quantum devices presently available. We develop and experimentally validate two efficient error mitigation protocols named "Noiseless Output Extrapolation" and "Pauli Error Cancellation" that can drastically enhance the performance of quantum circuits composed of noisy cycles of gates. By combining popular mitigation strategies such as probabilistic error cancellation and noise amplification with efficient noise reconstruction methods, our protocols can mitigate a wide range of noise processes that do not satisfy the assumptions underlying existing mitigation protocols, including non-local and gate-dependent processes. We test our protocols on a four-qubit superconducting processor at the Advanced Quantum Testbed. We observe significant improvements in the performance of both structured and random circuits, with up to 86 % improvement in variation distance over the unmitigated outputs. Our experiments demonstrate the effectiveness of our protocols, as well as their practicality for current hardware platforms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Temporal Coarse Graining for Classical Stochastic Noise in Quantum Systems

Simulations of quantum systems with Hamiltonian classical stochastic noise can be challenging when the noise exhibits temporal correlations over a multitude of time scales, such as for 1/f noise in solid-state quantum information processors. Here we present an approach for simulating Hamiltonian classical stochastic noise that performs temporal coarse-graining by effectively integrating out the high-frequency components of the noise. We focus on the case where the stochastic noise can be expressed as a sum of Ornstein-Uhlenbeck processes. Temporal coarse-graining is then achieved by conditioning the stochastic process on a coarse realization of the noise, expressing the conditioned stochastic process in terms of a sum of smooth, deterministic functions and bridge processes with boundaries fixed at zero, and performing the ensemble average over the bridge processes. For Ornstein-Uhlenbeck processes, the deterministic components capture all dependence on the coarse realization, and the stochastic bridge processes are not only independent but taken from the same distribution with correlators that can be expressed analytically, allowing the associated noise propagators to be precomputed once for all simulations. This combination of noise trajectories on a coarse time grid and ensemble averaging over bridge processes has practical advantages, such as a simple concatenation rule, that we highlight with numerical examples.

Albash, Tameem [Sandia National Lab. (SNL-NM), Alb↗
DOE OSTI2026

Viskores: Integrating Parallel Scientific Visualization Research into Applications

Viskores is a scientific visualization library that is the primary deployment of such algorithms to the parallel accelerated processors of modern DOE supercomputers. In this paper, we review the capabilities provided by Viskores and how these capabilities are leveraged by other software in the high-performance computing ecosystem. We discuss the Viskores data representation and pay particular attention to array management. Through this array management we describe how data is adapted between Viskores and other software along with strategies for converting dynamic, polymorphic objects to static representations better suited to GPU processing. We conclude with several examples of Viskores integrating with high-performance software that is used in production today.

Moreland, Ken [ORNL] (ORCID:0000000270513288)↗
DOE OSTI2025

Defining quantum-ready primitives for hybrid HPC-QC supercomputing: a case study in Hamiltonian simulation

As computational demands in scientific applications continue to rise, hybrid high-performance computing (HPC) systems integrating classical and quantum computers (HPC-QC) are emerging as a promising approach to tackling complex computational challenges. One critical area of application is Hamiltonian simulation, a fundamental task in quantum physics and other large-scale scientific domains. This paper investigates strategies for quantum-classical integration to enhance Hamiltonian simulation within hybrid supercomputing environments. By analyzing computational primitives in HPC allocations dedicated to these tasks, we identify key components in Hamiltonian simulation workflows that stand to benefit from quantum acceleration. To this end, we systematically break down the Hamiltonian simulation process into discrete computational phases, highlighting specific primitives that could be effectively offloaded to quantum processors for improved efficiency. Our empirical findings provide insights into system integration, potential offloading techniques, and the challenges of achieving seamless quantum-classical interoperability. We assess the feasibility of quantum-ready primitives within HPC workflows and discuss key barriers such as synchronization, data transfer latency, and algorithmic adaptability. These results contribute to the ongoing development of optimized hybrid solutions, advancing the role of quantum-enhanced computing in scientific research.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Validation of time-dependent shift using the pulsed sphere benchmarks

The detailed behavior of neutrons in a rapidly changing time-dependent physical system is a challenging computational physics problem, particularly when using Monte Carlo methods on heterogeneous high-performance computing architectures. A small number of algorithms and code implementations have been shown to be performant for time-independent (fixed source and k-eigenvalue) Monte Carlo, and there are existing simulation tools that successfully solve the time-dependent Monte Carlo problem on smaller computing platforms. To bridge this gap, a time-dependent version of ORNL’s Shift code has been recently developed. Shift’s history-based algorithm on CPUs, and its event-based algorithm on GPUs, have both been observed to scale well to very large numbers of processors, which motivated the extension of this code to solve time-dependent problems. The validation of this new capability requires a comparison with time-dependent neutron experiments. Lawrence Livermore National Laboratory’s (LLNL) pulsed sphere benchmark experiments were simulated in Shift to validate both the time-independent as well as new time-dependent features recently incorporated into Shift. A suite of pulsed-sphere models was simulated using Shift and compared to the available experimental data and simulations with MCNP. Overall results indicate that Shift accurately simulates the pulsed sphere benchmarks, and that the new time-dependent modifications of Shift are working as intended. Validated exascale neutron transport codes are essential for a wide variety of future multiphysics applications.

Palmer, Camille J.↗
DOE OSTI2024

Neural network methods for radiation detectors and imaging

Recent advances in image data proccesing through deep learning allow for new optimization and performance-enhancement schemes for radiation detectors and imaging hardware. This enables radiation experiments, which includes photon sciences in synchrotron and X-ray free electron lasers as a subclass, through data-endowed artificial intelligence. We give an overview of data generation at photon sources, deep learning-based methods for image processing tasks, and hardware solutions for deep learning acceleration. Most existing deep learning approaches are trained offline, typically using large amounts of computational resources. However, once trained, DNNs can achieve fast inference speeds and can be deployed to edge devices. A new trend is edge computing with less energy consumption (hundreds of watts or less) and real-time analysis potential. While popularly used for edge computing, electronic-based hardware accelerators ranging from general purpose processors such as central processing units (CPUs) to application-specific integrated circuits (ASICs) are constantly reaching performance limits in latency, energy consumption, and other physical constraints. These limits give rise to next-generation analog neuromorhpic hardware platforms, such as optical neural networks (ONNs), for high parallel, low latency, and low energy computing to boost deep learning acceleration (LA-UR-23-32395).

edge computing↗
DOE OSTI2024

Precise micromotion compensation of a tilted ion chain

Excess micromotion can be a substantial source of errors in trapped-ion based quantum processors and clocks due to the sensitivity of the internal states of the ion to external fields and motion. This problem can be fixed by compensating background electric fields in order to position ions at the RF node and minimize their driven micromotion. Here we describe techniques for compensating ion chains in scalable surface ion traps. These traps are capable of cancelling stray electric fields with fine spatial resolution in order to compensate multiple closely spaced ions due to their large number of relatively small control electrodes. We demonstrate a technique that compensates an ion chain to better than 5 V/m and within 0.1 degrees of chain rotation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Physical Properties of Moist, Fermented Corn Grain after Processing by Grinding or Milling

A novel biomass production system, integrating the co-harvesting and co-storage of moist corn grain and stover, promises a reduction in delivered feedstock costs. In this innovative method, the dry grain traditionally utilized for feed or biofuel production will now be processed at a considerably greater moisture content. The adoption of this approach may necessitate a substantial redesign of existing material handling infrastructure to effectively accommodate the handling and storage of moist grain after processing by milling or grinding. A comprehensive study was conducted to quantify the physical properties of this grain after processing with a knife processor or a hammermill. The geometric mean particle size, bulk and tapped density, sliding angle, material coefficient of friction, and discharged angle of repose were quantified. Five grain treatments, either fermented or unfermented, and having different moisture contents, were used. After processing, the moist, fermented ground grain exhibited a significantly smaller particle size compared to the dry grain. Additionally, both moist processed grains resulted in a decreased bulk density and increased material sliding angle, friction coefficient, and angle of repose. The examined metrics collectively suggest that handling, mixing, and storing moist ground grain will pose significant challenges compared to conventional dry ground grain. This increased difficulty may lead to substantially higher costs, a crucial factor that must be carefully considered when evaluating the overall economics of implementing this new biomass production system using combined harvesting and storage of corn grain and stover.

Blazer, Keagan J.↗
DOE OSTI2021

Influence of Cs Loading on Pt/m-ZrO 2 Water–Gas Shift Catalysts

Certain alkali metals (Na, K) at targeted loadings have been shown in recent decades to significantly promote the LT-WGS reaction. This occurs at alkali doping levels where a redshift in the C-H band of formate occurs, indicating electronic weakening of the bond. The C-H bond breaking of formate is the proposed rate-limiting step of the formate associative mechanism, lending support to the occurrence of this mechanism in H2-rich environments of the LT-WGS stage of fuel processors. Continuing in this vein of research, 2%Pt/m-ZrO 2 was promoted with various levels of Cs in order to explore its influence on the rate of formate intermediate decomposition, as well as that of LT-WGS in a fixed bed reactor. In situ DRIFTS experiments revealed that Cs promoter loadings of 3.87% to 7.22% resulted in significant acceleration of the forward formate decomposition in steam at 130 °C. Of all of the alkali metals tested to date, the redshift in the formate ν(CH) band with the incorporation of Cs was the greatest. XANES difference experiments at the Pt L 2 and L 3 edges indicated that the electronic effect was not likely due to an enrichment of electronic density on Pt. CO 2 TPD experiments revealed that, unlike Na and K promoters, Cs behaves more like Rb in that the decomposition of the second intermediate in LT-WGS, carbonate species, is hindered due to (1) increased basicity of Cs, (2) the tendency of Cs to cover Pt sites that facilitate CO 2 decomposition, and (3) the tendency of Cs to increase Pt particle size as shown by EXAFS results, resulting in fewer Pt sites that facilitate CO2 decomposition. As such, the LT-WGS rate was hindered overall and the rate-limiting step shifted to carbonate decomposition (CO 2 removal). Like its Rb counterpart, low levels of added Cs (e.g., 0.72%Cs) were found to improve the stability of the catalyst relative to the unpromoted catalyst; the stability comparison was made at similar CO conversion level as well as similar space velocity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗