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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Building a quantum computing architecture using 3D superconducting cavities

Quantum computers promise advantages over classical machines for solving certain complex problems, but building processors that truly deliver this advantage remains a central challenge, particularly due to limited coherence times. Three-dimensional superconducting radio-frequency (SRF) cavities offer an attractive platform due to their exceptionally long lifetimes. However, since these harmonic systems require nonlinear elements, such as transmons, for control, additional losses are often introduced. In this talk, I will present a multimode quantum system based on an elliptical SRF cavity hosting two cavity modes weakly coupled to an ancillary transmon circuit. This architecture is carefully engineered to preserve coherence while enabling efficient control. By optimizing the design to mitigate transmon-induced decoherence, we realize single-photon lifetimes of 20.6 ms and 15.6 ms in the two modes, with pure dephasing times exceeding 40 ms. Using sideband interactions and error-resilient protocols, such as measurement-based correction and post-selection, we demonstrate high-fidelity state control, including preparation of Fock states up to N=20 with fidelities above 95% (to our knowledge, the highest reported to date), as well as high-fidelity two-mode entanglement. These results highlight 3D SRF cavities as a robust foundation for qudit-based quantum information processing, harnessing the large Hilbert space of cavity modes. I will conclude by outlining strategies to further enhance coherence in both cavities and ancilla qubits, and discuss pathways toward scaling this architecture into a larger quantum computing platform.

Roy, Tanay [Fermilab]↗
DOE OSTI2025

Recent advances in 3D SRF cavity-based quantum computing facility at the Fermilab SQMS Center

This talk will describe the most recent advances and progress in building an SRF cavity-based quantum computing facility at the Fermilab SQMS center. Several technical challenges had been successfully overcome to preserve the highest quality factors of SRF cavities in the presence of the sapphire chip holding the transmon qubit inside the cavity. The record values of the attained multicell cavity (2-cell, 9-cell)-qubit systems will be presented, as well as a variety of quantum operations realized with such systems, including the generation of large Fock states, coherent states, entangled mode-mode states etc. The quantum algorithms and computational problems being implemented on this 3D SQMS QPUs will be discussed as well.

Romanenko, Alexander [Fermilab]↗
DOE OSTI2025

SRF-Based Quantum Transduction for Quantum Computing and Sensing

The next groundbreaking frontier in Quantum Information Science (QIS) is the development of low-noise interconnections over fiber optics between superconducting radio-frequency (SRF) quantum devices. High-efficiency microwave-optical transduction serves as a pivotal enabler for distributed quantum computing and sensor networks. This presentation will provide a comprehensive overview of quantum transduction achieved by coupling SRF cavities to electro-optic optical resonators, enabling efficient conversion between microwave and optical photons. This research, supported by the DOE Early Career Research Program, advances technologies for quantum computing and sensing, and complements the mission of the Superconducting Quantum Materials and Systems (SQMS) Center at Fermilab.

Zorzetti, Silvia [Fermilab] (ORCID:000000023208338↗
DOE OSTI2026

Image processing workflow yielding high contrast synchrotron nanoscale computed tomography data from Ni-YSZ electrodes

The operating lifetime of Ni-YSZ fuel electrodes used in solid oxide electrolysis cells and fuel cells (SOECs and SOFCs) is limited by Ni redistribution, one of the primary degradation mechanisms that must be overcome to extend the longevity and maximize the performance of SOECs and SOFCs. To achieve this, 3D microstructural data is needed to relate both initial performance and performance loss over time to microstructural properties and their evolution throughout operation under various conditions. However, 3D microstructure data remains relatively scarce within the literature due to multiple challenges in acquiring and analyzing such data reliably. This work presents a workflow for acquiring and processing synchrotron X-ray nanoscale computed tomography (nano-CT) data from Ni-YSZ electrodes. Parameters for each step in the nano-CT workflow are described up to the final result (a 3D reconstruction), with particular emphasis on image alignment using freely available software. Following the results of a parametric sweep of the image alignment step, high contrast, low signal-to-noise 3D nano-CT data is obtained with relatively short compute times. While the exact methods best suited to samples with different microstructural qualities, or similar Ni-YSZ nano-CT data obtained from other sources may deviate from the solution found herein, this work also generalizes the decision points and evaluation of each step to provide a starting point to adapt this workflow to other datasets.

08 HYDROGEN↗
DOE OSTI2025

A Pentavalent HIV-1 Subtype C Vaccine Containing Computationally Selected gp120 Strains Improves the Breadth of V1V2 Region Responses

Background: HIV-1 envelope (Env) variable loops 1 and 2 (V1V2) directed non-neutralizing antibodies were a correlate of decreased transmission risk in the RV144 vaccine trial. Thus, the elicitation and breadth of antibody responses against the V1V2 of HIV-1 Env are important considerations for HIV-1 vaccine candidates. The V1V2 region’s highly variable nature and the extensive diversity of subtype C HIV-1 Envelopes (Envs) make the V1V2 response breadth a high priority for HIV-1 vaccine regimens aiming for V1V2-mediated protection in Southern Africa. Here, we determined whether the breadth of the anti-V1V2 vaccine response can be broadened by including HIV-1 Env strains computationally designed to enhance the coverage of subtype C V1V2 sequence diversity. Methods: Three subtype C Env strains were selected to maximize antibody binding coverage while complementing subtype C vaccine gp120s that were given in human clinical trials in South Africa, as well as to improve epitope accessibility. Humoral immunogenicity of a novel trivalent gp120 vaccine immunogen, a bivalent gp120 boost already in clinical trials (1086C and TV1), and a pentavalent (all five gp120s combined) were evaluated in a preclinical immunization study in guinea pigs. The pentavalent combination was further evaluated with alum versus glucopyranosyl lipid adjuvants formulated in squalene-in-water emulsion (GLA-SE) adjuvants in non-human primates. The breadth of the anti-V1V2 response was assessed using an array of cross-subtype variable loops 1&2 (V1V2) scaffold proteins and linear V2 peptides. Results: The breadth of the IgG response against V1V2 antigens of the trivalent and pentavalent groups was comparable, and both were greater than the breadth of the bivalent group. Linear epitope mapping showed that two linear epitopes in V2 were targeted by the vaccinated animals: the V2 hotspot focused at 169K that potentially correlated with decreased HIV-1 risk in RV144 and the V2.2 site (179LDV/I181) that is part of the integrin α4β7 binding site. The bivalent vaccine elicited a significantly higher magnitude of binding to the V2 hotspot compared to the trivalent vaccine whereas the trivalent vaccine elicited significantly higher binding to the V2.2 epitope compared to the bivalent vaccine, while the pentavalent recognized both regions. Conclusions: These results demonstrate that the three new computationally selected subtype C Envs successfully complemented 1086C and TV1 for broader V1V2 antibody responses, and, in concert with adjuvants that stimulate V1V2 responses, can be considered as part of a rationale immunogen design to improve V1V2 IgG coverage in future vaccine trials in South Africa.

Immunology↗
DOE OSTI2025

Computationally Selected Multivalent HIV-1 Subtype C Vaccine Protects Against Heterologous SHIV Challenge

Background: The RV144 trial in Thailand is the only HIV-1 vaccine efficacy trial to date to demonstrate any efficacy. Genetic signatures suggested that antibodies targeting the variable loop 2 (V2) of the HIV-1 envelope played an important protective role. The ALVAC prime and protein boost follow-up trial in southern Africa (HVTN702) failed to show any efficacy. One hypothesis for this is the greater diversity of subtype C viruses in southern Africa relative to CRF01_AE in Thailand. Methods: Here, we determined whether an ALVAC prime with computationally selected gp120 boost immunogens maximizing coverage of diversity of subtype C viruses in the variable V1 and V2 regions (V1V2) improved the protection of non-human primates (NHPs) from a heterologous subtype C SHIV challenge compared to more traditional regimens. Results: An ALVAC prime with Trivalent subtype C gp120 boosts resulted in statistically significant protection from repeated intrarectal SHIV challenges compared to the control. Evaluation of the immunogenicity of each vaccine regimen at the time of challenge demonstrated that different gp120 combination boosts elicited similar high magnitudes of gp120 and breadth of V1V2-binding antibodies, as well as strong Fc-mediated immune responses. Low-to-no neutralization of the challenge virus was detected. A Cox proportional hazard analysis of five pre-selected immune parameters at the time of challenge identified ADCC against the challenge envelope as a correlate of protection. Systems serology analysis revealed that immune responses elicited by the different vaccine regimens were distinct and identified further correlates of resistance to infection. Conclusions: Computationally designed vaccines with maximized subtype C V1V2 coverage mediated protection of NHPs from a heterologous Tier-2 subtype C SHIV challenge.

Immunology↗
DOE OSTI2025

An Integral-based Technique to Accelerate the Monte Carlo Radiative Transfer Computation for Supernovae

We present an integral-based technique (IBT) algorithm to accelerate supernova (SN) radiative transfer calculations. The algorithm utilizes “integral packets,” which are calculated by the path integral of the Monte Carlo (MC) energy packets, to synthesize the observed spectropolarimetric signal at a given viewing direction in a 3D time-dependent radiative transfer program. Compared to the event-based technique (EBT) proposed by M. Bulla et al., our algorithm significantly reduces the computation time and increases the MC signal-to-noise ratio (S/N). Using a 1D spherical symmetric Type Ia SN ejecta model DDC10 and its derived 3D model, the IBT algorithm has successfully passed the verification of spherical symmetry and cross comparison on a 3D SN model with the direct-counting technique and EBT. Notably, with our algorithm implemented in the 3D MC radiative transfer code SEDONA, the computation time is faster than EBT by a factor of 10−30, and the S/N is better by a factor of 1.5−3, with the same number of MC quanta.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Technical note: A modified formulation of dynamic energy budget theory for faster computation of biological growth

Abstract. The mass conservation equation in the presence of boundary fluxes and chemical reactions from non-equilibrium thermodynamics is used to derive a modified dynamic energy budget (mDEB) model. Compared to the standard dynamic energy budget (sDEB) model (Kooijman, 2009), this modified formulation does not place the dilution effect in the mobilization kinetics of reserve biomass, and it maintains the partition principle for reserve mobilization dynamics for both linear and non-linear kinetics. Overall, the mDEB model shares most features with the sDEB model. However, for biological growth that requires multiple nutrients, the mDEB model is computationally much more efficient by not requiring numerical iterations for obtaining the specific growth rate. In an example of modeling the growth of Thalassiosira weissflogii in a nitrogen-limiting chemostat, the mDEB model was found to have almost the same accuracy as the sDEB model while requiring almost half of the computing time of the sDEB model. Since the sDEB model has been successfully applied in numerous studies, we believe that the mDEB model can help improve the modeling of biological growth and the associated ecosystem processes in various contexts.

Tang, Jinyun↗
DOE OSTI2025

Computationally efficient subglacial drainage modelling using Gaussian process emulators: GlaDS-GP v1.0

Subglacial drainage models represent water flow at the ice–bed interface through coupled distributed and channelized systems to determine water pressure, discharge, and drainage system geometry. While they are used to understand processes such as the relationship between surface melt and ice flow, the number of uncertain model parameters and the computational cost of running models makes it difficult to adequately explore the high-dimensional parameter space and evaluate uncertainty in model predictions. Here, we develop Gaussian process (GP) emulators that make fast predictions with associated uncertainty of subglacial drainage model outputs. Using a truncated principal component (PC) basis representation, we construct a GP emulator for diurnally averaged subglacial water pressure. We also explore emulation of scalar variables describing drainage efficiency and configuration. We train the emulators using ensembles of up to 512 simulations varying eight parameters of the Glacier Drainage System (GlaDS) model on a synthetic domain intended to represent an ice-sheet margin. The emulators make predictions ∼ 1000 times faster than GlaDS simulations, with errors <3 % for the water pressure field and ∼ 5 %–9 % for drainage efficiency and configuration. We apply the emulators to explore the eight-dimensional parameter space by computing variance-based parameter sensitivity indices, finding that three parameters (ice flow coefficient, bed bump aspect ratio, and the subglacial cavity system conductivity) explain 90 % of the variance in modelled water pressure in response to parameter changes. The GP emulator approach described here is well suited to integrating observational data with models to make calibrated, credible predictions of subglacial drainage.

58 GEOSCIENCES↗
DOE OSTI2025

Quantum computation of mass gap in an asymptotically free theory

In relativistic field theories, the mass spectrum is given by the difference between the energy of the vacuum and the excited states. Near the continuum limit, the cancellation between these two values leads to loss of precision. We propose a method to extract the mass gap directly using quantum computers and apply it to a particular version of the nonlinear $σ$-model with the correct continuum limit and perform calculations in quantum hardware (at strong coupling) and simulation in classical computers (at weak coupling).

Bedaque, Paulo F. [Maryland U.] (ORCID:00000001521↗
DOE OSTI2025

Numerical Method Improvements in Griffin for Pebble Bed Reactors with a Focus on the Computation of Burnup

Griffin, a MOOSE (Multiphysics Object-Oriented Simulation Environment) based application targeting transient multiphysics modeling of advanced reactors, has been used recently to model both high-temperature gas-cooled and fluoride-salt-cooled pebble bed reactors (PBRs). Griffin uses deterministic methods for solving neutron transport and an Eulerian approach to model pebble movement. An Eulerian approach is also used to directly compute burnup instead of using a pass approach like other tools such as VSOP or PANGU. This work discusses verification efforts and numerical method improvements related specifically to the Eulerian modeling approach implemented for directly computing pebble burnup.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

A novel A-ϕ formulation for efficient electromagnetic computations

In numerical simulation of electromagnetic prob- lems, potential-based formulations have advantages over field- based formulations because of their immunity to the low- frequency breakdown catastrophe. Recently, an all-frequency stable formulation has been proposed to solve electromagnetic problems in a wide frequency band. This formulation employs magnetic vector and electric scalar potentials, as well as an auxiliary potential to enforce an inhomogeneous Coulomb gauge. However, such a three-potential formulation has encountered convergence issues at low frequencies. To avoid the convergence issue and improve computational efficiency, a novel formulation with only two potentials and an implicit Coulomb gauge is proposed in this paper. A numerical example is presented to show its solution accuracy and computational efficiency.

Mekonnen, Minyechil↗
DOE OSTI2026

Computing the Critical Temperature of the Affine-Transformed $D=3$ Ising Model Using Masked Autoregressive Flow

The simple Ising model provides a rich environment to build and study lattice field theories. As part of an ongoing project to construct a conformal field theory (CFT) on an arbitrarily curved manifold, in this work we develop methods to measure the critical temperature $β_c$ of the affine-transformed Ising model on the face-centered cubic (FCC) lattice. The main challenge in this endeavor is finding a computationally efficient and accurate method of interpolating and extrapolating Monte Carlo observables with respect to coupling coefficients and temperature. Herein, we compare two such methods. A traditional statistical approach uses the multiple histogram (MH) method, while a newer machine learning approach uses a masked autoregressive flow (MAF) to estimate the underlying probability density function of a set of observables. While the MH method is specifically designed to interpolate and extrapolate Monte Carlo observables, we find that MAF is a viable alternative for measuring $β_c$ with a computational cost that scales more favorably. Furthermore, we comment on additional advantages of MAF relevant to our work, such as extrapolating in system volume.

Svenson, Kai [Texas U.]↗
DOE OSTI2025

Alternative mixed integer linear programming optimization for joint job scheduling and data allocation in grid computing

This paper presents a novel approach to the joint optimization of job scheduling and data allocation in grid computing environments. We formulate this joint optimization problem as a mixed integer quadratically constrained program. To tackle the nonlinearity in the constraint, we alternatively fix a subset of decision variables and optimize the remaining ones via Mixed Integer Linear Programming (MILP). We solve the MILP problem at each iteration via an off-the-shelf MILP solver. Our experimental results show that our method significantly outperforms existing heuristic methods, employing either independent optimization or joint optimization strategies. We have also verified the generalization ability of our method over grid environments with various sizes and its high robustness to the algorithm setting.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Reducing the Energy Consumption of Magnetic Resonance Imaging and Computed Tomography Scanners: Integrating Ecodesign and Sustainable Operations

This review aims to provide valuable insights into how energy consumption in magnetic resonance imaging (MRI) and computed tomography (CT) scanners can be effectively monitored, managed, and reduced, thereby contributing to more sustainable medical imaging practices. Demand for advanced imaging technologies such as MRI and CT scanners continues to increase, and understanding the resultant impact on greenhouse gas emissions requires a thorough evaluation of their energy consumption. Here, this review examines the energy monitoring and consumption characteristics of MRI and CT scanners, highlighting potential approaches for energy savings. An overview of MRI and CT principles, hardware components, and their associated energy consumption is provided. After addressing the technical aspects, the hardware and software requirements essential for accurate energy metering are detailed. Baseline measurements of energy consumption data are then provided as a foundation to understand current usage patterns and identify areas for improvement. Ongoing efforts to reduce energy consumption are categorized into 3 main strategies: operations, scanner design enhancements, and active scanning techniques, including accelerated MRI protocols. Ultimately, we emphasize that achieving sustainability in medical imaging requires collaboration across disciplines. By incorporating eco-friendly design in new imaging equipment, we can reduce the environmental impact, promote sustainability, and set a health care industry standard for a healthier planet.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

Exabiome: Advancing Microbial Science through Exascale Computing

The Exabiome project seeks to improve the understanding of microbiomes through the development of methods for accelerating metagenomic science using exascale computing. This article gives an overview of scientific impact of the three components of the project: metagenome assembly, protein family detection, and comparative analysis of metagenomes. Exabiome developed MetaHipMer, the only metagenome assembler capable of scaling to full exascale systems. MetaHipMer has enabled ground-breaking assemblies on the Frontier supercomputer, with many scientific benefits, such as the discovery of rare species and viral genomes. To investigate protein families, Exabiome developed two exascale tools, PASTIS and HipMCL. Together, these can utilize exascale resources to understand the functional diversity of billions of dark matter proteins and novel protein families. For comparative analysis, Exabiome developed kmerprof, a tool that can be used to compare huge metagenomes for many different scientific purposes, for example, grouping human microbiomes according to body location.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

ARQUIN: Architectures for Multinode Superconducting Quantum Computers

Many proposals to scale quantum technology rely on modular or distributed designs wherein individual quantum processors, called nodes, are linked together to form one large multinode quantum computer (MNQC). One scalable method to construct an MNQC is using superconducting quantum systems with optical interconnects. However, internode gates in these systems may be two to three orders of magnitude noisier and slower than local operations. Surmounting the limitations of internode gates will require improvements in entanglement generation, use of entanglement distillation, and optimized software and compilers. Still, it remains unclear what performance is possible with current hardware and what performance algorithms require. In this article, we employ a systems analysis approach to quantify overall MNQC performance in terms of hardware models of internode links, entanglement distillation, and local architecture. We show how to navigate tradeoffs in entanglement generation and distillation in the context of algorithm performance, lay out how compilers and software should balance between local and internode gates, and discuss when noisy quantum internode links have an advantage over purely classical links. Here, we find that a factor of 10–100× better link performance is required and introduce a research roadmap for the co-design of hardware and software towards the realization of early MNQCs. While we focus on superconducting devices with optical interconnects, our approach is general across MNQC implementations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗