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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Biomimetic Rebuilding of Multifunctional Red Blood Cells: Modular Design Using Functional Components

The design and synthesis of artificial materials that mimic the structures, mechanical properties, and ultimately functionalities of biological cells remains a current holy grail of materials science. Here based on a silica cell bio-replication approach, we report the design and construction of synthetic rebuilt red blood cells (RRBCs) that fully mimic the broad properties of native RBCs: size, biconcave shape, deformability, oxygen carrying capacity, long circulation time. Four successive nano-scale processing steps: RBC bioreplication, layer-by-layer polymer deposition, and precision silica etching, followed by RBC ghost membrane vesicles fusion are employed for RRBC construction. A panel of physicochemical analyses including zeta potential measurement, fluorescence microscopy, and antibody-mediated agglutination assay proved the recapitulation of RBC shape, size, and membrane structure. Flow-based deformation studies carried out in a microfluidic blood capillary model confirrned the ability of RRBCs to deform and pass through small slits and reconstitute themselves in a manner comparable to native RBCs. Circulation studies of RRBCs conducted ex-ovo in a chick embryo and in vivo in a mouse model demonstrated the requirement of both deformability and native cell membrane surface to achieve long-term circulation. To confer additional non-native functionalities to RRBCs, we developed modular procedures in which to load functional cargos such as hemoglobin, drugs, magnetic nanoparticles, and ATP biosensors within the RRBC interior to enable various functions, including oxygen delivery, therapeutic drug delivery, magnetic manipulation, and toxin biosensing and detection. Taken together, RRBCs represent a class of long circulating RBC-inspired artificial hybrid materials with a broad range of potential applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

OC6 project Phase IV: validation of numerical models for novel floating offshore wind support structures

Abstract. This paper provides a summary of the work done within Phase IV of the Offshore Code Comparison Collaboration, Continued with Correlation and unCertainty (OC6) project, under International Energy Agency Wind Technology Collaboration Programme Task 30. This phase focused on validating the loading on and motion of a novel floating offshore wind system. Numerical models of a 3.6 MW horizontal-axis wind turbine atop the TetraSpar floating support structure were compared using measurement data from a 1:43-Froude-scale test performed in the University of Maine's Alfond Wind–Wave (W2) Ocean Engineering Laboratory. Participants in the project ran a series of simulations, including system equilibrium, surge offsets, free-decay tests, wind-only conditions, wave-only conditions, and a combination of wind and wave conditions. Validation of the models was performed by comparing the aerodynamic loading, floating support structure motion, tower base loading, mooring line tensions, and keel line tensions. The results show a relatively good estimation of the aerodynamic loading and a reasonable estimation of the platform motion and tower base fore–aft bending moment. However, there is a significant dispersion in the dynamic loading for the upwind mooring line. Very good agreement was observed between most of the numerical models and the experiment for the keel line tensions.

17 WIND ENERGY↗
DOE OSTI2023

Minimum conditions for accurate modeling of urea production via co-electrolysis

Co-electrolysis of carbon oxides and nitrogen oxides promise to simultaneously help restore the balance of the C and N cycles while producing valuable chemicals such as urea. However, co-electrolysis processes are still largely inefficient and numerous knowledge voids persist. Here, we provide a solid thermodynamic basis for modelling urea production via co-electrolysis. First, we determine the energetics of aqueous urea produced under electrochemical conditions based on experimental data, which enables an accurate assessment of equilibrium potentials and overpotentials. Next, we use density functional theory (DFT) calculations to model various co-electrolysis reactions producing urea. The calculated reaction free energies deviate significantly from experimental values for well-known GGA, meta-GGA and hybrid functionals. These deviations stem from errors in the DFT-calculated energies of molecular reactants and products. In particular, the error for urea is approximately -0.25 ± 0.10 eV. Finally, we show that all these errors introduce large inconsistencies in the calculated free-energy diagrams of urea production via co-electrolysis, such that gas-phase corrections are strongly advised.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Machine learning model inputs, outputs, and scripts associated with “Artificial intelligence-guided iterations between observations and modeling significantly improve environmental predictions”

NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the manuscript “Artificial intelligence-guided iterations between observations and modeling significantly improve environmental predictions” (Malhotra et al., in prep). This effort was designed following ICON (integrated, coordinated, open, and networked) principles to facilitate a model-experiment (ModEx) iteration approach, leveraging crowdsourced sampling across the contiguous United States (CONUS). New machine learning models were created every month to guide sampling locations. Data from the resulting samples were used to test and rebuild the machine learning models for the next round of sampling guidance. Associated sediment and water geochemistry and in situ sensor data can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1923689, https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1729719, and https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1603775. This data package is associated with two GitHub repositories found at https://github.com/parallelworks/dynamic-learning-rivers and https://github.com/WHONDRS-Hub/ICON-ModEx_Open_Manuscript. In addition to this readme, this data package also includes two file-level metadata (FLMD) files that describes each file and two data dictionaries (DD) that describe all column/row headers and variable definitions. This data package consists of two main folders (1) dynamic-learning-rivers and (2) ICON-ModEx_Open_Manuscript which contain snapshots of the associated GitHub repositories. The input data, output data, and machine learning models used to guide sampling locations are within dynamic-learning-rivers. The folder is organized into five top-level directories: (1) “input_data” holds the training data for the ML models; (2) “ml_models” holds machine learning (ML) models trained on the data in “input_data”; (3) “examples” contains files for direct experimentation with the machine learning model, including scripts for setting up “hindcast” run; (4) “scripts” contains data preprocessing and postprocessing scripts and intermediate results specific to this data set that bookend the ML workflow; and (5) “output_data” holds the overall results of the ML model on that branch. Each trained ML model resides on its own branch in the repository; this means that inputs and outputs can be different branch-to-branch. There is also one hidden directory “.github/workflows”. This hidden directory contains information for how to run the ML workflow as an end-to-end automated GitHub Action but it is not needed for reusing the ML models archived here. Please see the top-level README.md in the GitHub repository for more details on the automation. The scripts and data used to create figures in the manuscript are within ICON-ModEx_Open_Manuscript. The folder is organized into four folders which contain the scripts, data, and pdf for each figure. Within the “fig-model-score-evolution” folder, there is a folder called “intermediate_branch_data” which contains some intermediate files pulled from dynamic-learning-rivers and reorganized to easily integrate into the workflows. NOTE: THIS FOLDER INCLUDES THE FILES AT THE POINT OF PAPER SUBMISSION. IT WILL BE UPDATED ONCE THE PAPER IS ACCEPTED WITH ANY REVISIONS AND WILL INCLUDE A DD/FLMD AT THAT POINT. We thank the United States Forest Service, Washington Department of Fish and Wildlife, Washington Department of Natural Resources, Cowiche Canyon Conservatory, Washington State Parks and Recreation Commission (Scientific Research Permit #210901), and the Confederated Tribes and Bands of the Yakama Nation for access to field locations where the samples labeled “SSS” were collected. We also thank the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview. WHONDRS consortium members were asked to provide any acknowledgments for the collection of samples labeled “CM” and the following is a list of acknowledgments that were submitted with their corresponding Site IDs: (MART) Research activities were conducted in part on the Wind River Experimental Forest within the Gifford Pinchot National Forest; (MP- 100379) Philadelphia is part of Lenapehoking, the ancestral homelands of the Lenape peoples; (MP-102398) Land surveyed is the ancestral homelands of the Nookhose'iinenno (Arapaho), Tsis tsis'tas (Cheyenne), and Nuuchu (Ute); (MP-100749 and MP- 100747) Georgia Coastal Ecosystem LTER, OCE-1832178; (SP-70 and SP-72) Eastern Shoshone, Shoshone-Bannock; (MP- 102944) Funded by Oregon Watershed Enhancement Board. On the traditional lands of the Confederated Tribes of the Siletz, Confederated Tribes of the Grand Rhonde, and the Clatsop-Nehalem Confederated Tribe; (MP- 100607) Holiday Creek is located on the traditional territory of the Monacan Indian Nation; (SP-45) Lafayette Blue Springs State Park; (MP-102420) NSF DEB-2016749; (MP-100019) New Hampshire Agriculture Experiment Station; (SP-35) Rayonier (land owner; https://www.rayonier.com/); (MP- 101276) US Department of Energy, Office of Science, Biological and Environmental Research, Subsurface Biogeochemical Research, Watershed Dynamics and Evolution SFA at ORNL; (MP- 103224) Watershed Dynamics and Evolution SFA at ORNL; (MP- 101584) Traditional lands of the Oceti Sakowin (Dakota, Lakota, Nakoda) and Anishinaabe Peoples.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Measurement and modeling of methane diffusion in hydrocarbon mixtures

Methane (CH 4 ) dissolution and diffusive mass transfer in liquid hydrocarbon mixtures is of key interest in the context of enhanced oil recovery from tight shales. In this paper, we have studied CH 4 dissolution and diffusion in normal alkane mixtures at a temperature of 50 ⁰C and at pressures of ~8 MPa. For the measurement of CH 4 dissolution/diffusion in bulk liquid hydrocarbon mixtures, we have utilized a high pressure and temperature, constant-volume diffusion (CV-D) setup. Here, we have studied CH 4 diffusion in mixtures with three long-chain normal alkanes: decane (C 10 ), dodecane (C 12 ) and hexadecane (C 16 ). We have measured CH 4 solubility and diffusion in its binary mixtures with each of these three normal alkanes, as well as in ternary and quaternary mixtures. During the experiments, the swelling of the liquid mixture due to CH 4 dissolution was measured in situ via a cathetometer and was subsequently integrated into the data analysis. A key conclusion from this study is that the solubility and transport properties of the multicomponent mixtures can be predicted accurately from binary mixture measurements using an appropriate Equation of State (EOS) and Wilke’s simplification of the classical Maxwell-Stefan (MS) diffusion theory. This observation can facilitate accurate prediction of diffusive mass transfer in more complex liquid hydrocarbon mixtures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Unsteady aerodynamics of large-scale floating offshore wind turbines in surge motion

Unsteady aerodynamic loads significantly influence the design and wake flow field of floating offshore wind turbines, especially due to wave- or vibration-induced tower top motions triggering various unsteady phenomena. Recent studies show that increasing turbine sizes amplify unsteady aerodynamic effects, as their impact typically grows with rotor diameter. This work combines recent findings from experiments and simulations on model-scale FOWT aerodynamics with new numerical analyses of large-scale rotors, providing a comprehensive understanding of unsteady phenomena occurrence and impact. Numerical analyses of the IEA 15-MW and 22-MW rotors undergoing surge motions characterise the combined influence of motion-induced unsteady phenomena on rotor thrust. Results indicate that unsteady effects can reduce thrust force variations by up to 40% at realistic surge periods. These findings contrast with prior model-scale rotor investigations, attributed to the specialised design of the model rotors. Comparisons between numerical methods - the dynamic blade element momentum method in OpenFAST and free vortex wake modules in panMARE and OpenFAST - reveal persistent differences in thrust predictions under both idealised and realistic conditions. This highlights that classical blade element momentum approaches require enhancement to accurately capture unsteady loads on large-scale floating offshore wind turbines at low wind speeds.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

Material efficiency and climate change mitigation of passenger vehicles

A transition to electric vehicles and renewable energy is currently underway but may not be rapid enough in order to reach ambitious climate change mitigation targets. Therefore, additional, preferably instantaneous, measures are needed for quick emissions reductions, which is where material efficiency (ME) could constitute a promising solution. ME strategies include but are not limited to vehicle lightweighting through material substitution, increased recycling of materials, reuse and remanufacturing of vehicle components, vehicle downsizing (switching to a smaller vehicle) and more intensive use by means of increased vehicle occupancy through sharing practices. While recent analyses have focused on a narrow subset of these, we find striking differences in the overall potential of different strategies to decrease vehicular carbon footprints. Downsizing and more intensive use offer the largest mitigation potential but strongly depend on consumer behavior and are highly sensitive to modeling assumptions. Combined, the analyzed strategies can achieve emission reductions of up to 57% over the life cycle of a single vehicle, which is comparable to up to 83% achieved through a shift to low-carbon energy supply. ME can cut carbon footprints of already efficient vehicles charging renewable electricity by half again. This makes ME both an excellent short-term solution for climate change mitigation targeting the light vehicle sector but also an important complementary strategy to the long-term transition towards electric vehicles and renewable energy supply.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Sterile neutrino dark matter within the ν SMEFT

Sterile neutrinos with masses at the keV scale and mixing to the active neutrinos offer an elegant explanation of the observed dark matter (DM) density. However, the very same mixing inevitably leads to radiative photon emission and the non-observation of such peaked X-ray lines rules out this minimal sterile neutrino DM hypothesis. We show that in the context of the Standard Model effective field theory with sterile neutrinos (νSMEFT), higher dimensional operators can produce sterile neutrino DM in a broad range of parameter space. In particular, νSMEFT interactions can open the large mixing parameter space due to their destructive interference, through operator mixing or matching, in the X-ray emission. We also find that, even in the zero mixing limit, the DM density can always be explained by νSMEFT operators. The testability of the studied νSMEFT operators in searches for electric dipole moments, neutrinoless double beta decay, and pion decay measurements is discussed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

A new approach to color-coherent parton evolution

We present a simple parton-shower model that replaces the explicit angular ordering of the coherent branching formalism with a differentially accurate simulation of soft-gluon radiation by means of a non-trivial dependence of the splitting functions on azimuthal angles. We introduce a global kinematics mapping and provide an analytic proof that it satisfies the criteria for next-to leading logarithmic accuracy. In the new algorithm, initial and final state evolution are treated on the same footing. We provide an implementation for final-state evolution in the numerical code ALARIC and present a first comparison to experimental data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Nanobody screening and machine learning guided identification of cross-variant anti-SARS-CoV-2 neutralizing heavy-chain only antibodies

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) continues to persist, demonstrating the risks posed by emerging infectious diseases to national security, public health, and the economy. Development of new vaccines and antibodies for emerging viral threats requires substantial resources and time, and traditional development platforms for vaccines and antibodies are often too slow to combat continuously evolving immunological escape variants, reducing their efficacy over time. Previously, we designed a next-generation synthetic humanized nanobody (Nb) phage display library and demonstrated that this library could be used to rapidly identify highly specific and potent neutralizing heavy chain-only antibodies (HCAbs) with prophylactic and therapeutic efficacy in vivo against the original SARS-CoV-2. In this study, we used a combination of high throughput screening and machine learning (ML) models to identify HCAbs with potent efficacy against SARS-CoV-2 viral variants of interest (VOIs) and concern (VOCs). To start, we screened our highly diverse Nb phage display library against several pre-Omicron VOI and VOC receptor binding domains (RBDs) to identify panels of cross-reactive HCAbs. Using HCAb affinity for SARS-CoV-2 VOI and VOCs (pre-Omicron variants) and model features from other published data, we were able to develop a ML model that successfully identified HCAbs with efficacy against Omicron variants, independent of our experimental biopanning workflow. This biopanning informed ML approach reduced the experimental screening burden by 78% to 90% for the Omicron BA.5 and Omicron BA.1 variants, respectively. The combined approach can be applied to other emerging viruses with pandemic potential to rapidly identify effective therapeutic antibodies against emerging variants.

Antibodies↗
DOE OSTI2024

Daily water stable isotopes, transpiration, and matrix potential data for an aspen and engelmann stand in the East River Watershed (version 2)

We provide daily stable isotope (2H & 18O) ratios in soil water and xylem (plant stem) water, as well as the sap flow (transpiration) and the soil's matric potential at a forested site near Gothic, Colorado, in the East River catchment. We measured the stable isotopic composition of the transpiration and the daily transpiration flux sum of three aspen and three engelmann spruce. In both forest stands, we installed a soil profile and measured the soil matric potential at 15, 30, and 60 cm depth as well as the stable isotopes of soil pore water at 5, 10, 30, 60, and 90 cm depths. All isotope measurements were done in situ via vapor probes connected to a cavity ring down spectrometer (Picarro L1240i).We further report the daily meteorological data observed at billy barr near our study site. We also provide for each tree the relative share of root water uptake derived from the isotope measurements via a Bayesian mixing model (MixSIAR).The daily data is provided as a time series in "Iso_MP_Sap_DataDaily_ESSDiveUpload.csv" and the units are provided in "dd.csv"; the location of the instrumented trees and soil profiles are given as latitude and longitude coordinates saved as CSV and KMZ files; and a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata.The data was gathered to investigate the short-term changes of the water sources (i.e., variation of root water uptake from different soil depths) of the studied subalpine trees.Update 07/16/2025: The relative and absolute plant water uptake depths were grouped to ensure that the MixSIAR model was applied with endmembers that differed in their d2H value by at least 3 permill and at least 1 permill for d18O. Whenever the difference between observed d2H values for two or more probes at neighboring depths was less than 3 permill, we used the average value for the source water endmember. For days at which probes that were not next to each other measurements did not differ at least 3 permill, the average of all probes between these two depths was used as the water source endmember representing the depth range between these two probes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Highly supercooled riming and unusual triple-frequency radar signatures over McMurdo Station, Antarctica

Abstract. Riming of ice crystals by supercooled water droplets is an efficient ice growth process, but its basic properties are still poorly known. While it has been shown to contribute significantly to surface precipitation at mid-latitudes, little is known about its occurrence at high latitudes. In Antarctica, two competing effects can influence the occurrence of riming: (i) the scarcity of supercooled liquid water clouds due to the extremely low tropospheric temperatures and (ii) the low aerosol concentration, which may lead to the formation of fewer and larger supercooled drops potentially resulting in an enhanced riming efficiency. In this work, by exploiting the deployment of an unprecedented number of multiwavelength remote sensing systems (including triple-frequency radar measurements) in West Antarctica, during the Atmospheric Radiation Measurements West Antarctic Radiation Experiment (AWARE) field campaign, we evaluate the riming incidence at McMurdo Station and find that riming occurs at much lower temperatures when compared to previous results in the mid-latitudes. This suggests the possible occurrence of a common atmospheric state over Antarctica that includes a rather stable atmosphere inhibiting turbulent mixing, and a high riming efficiency driven by large cloud droplets. We then focus on a peculiar case study featuring a persistent layer with a particularly pronounced riming signature in triple-frequency radar data but only a relatively modest amount of supercooled liquid water. In-depth analysis of the radar observations suggests that such signatures can only be explained by the combined effects of moderately rimed aggregates or similarly shaped florid polycrystals and a narrow particle size distribution (PSD). Simulations of this case study performed with a one-dimensional bin model indicate that similar triple-frequency radar observations can be reproduced when narrow PSDs are simulated. Such narrow PSDs can in turn be explained by two key factors: (i) the presence of a shallow homogeneous droplet or humidified aerosol freezing layer aloft seeding an underlying supercooled liquid layer, and (ii) the absence of turbulent mixing throughout a stable polar atmosphere that sustains narrow PSDs, as hydrometeors grow from the nucleation region aloft to ice particles of several millimeters in size, by vapor deposition and then riming.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Role of a 3D Structure in Energy Transfer in Mixed-Ligand Metal–Organic Frameworks

We present a detailed investigation of the photophysical properties of mixed-ligand pyrene- and porphyrin-based metal–organic frameworks (MOFs) as a function of their 3D structure. Solvothermal reactions between metal salts (InCl 3 , Zr(acac) 4 , and ZrCl 4 ) and suitable ratios of 1,3,6,8-tetrakis(p-benzoic acid)pyrene (TBAPy) and meso-tetrakis- (4-carboxyphenyl)porphyrin (TCPP) were performed to prepare a series of mixed-ligand ROD-7, NU-901, and NU-1000 MOFs. Time-resolved and steady-state fluorescence measurements were conducted on the mixed-ligand MOFs to study their photophysics. Based on the results, we concluded that upon excitation of TBAPy linkers in the MOFs, singlet excitation energy migrates across TBAPy linkers until it finds a TCPP unit. TCPP acts as an energy trap and quenches the excitation. The efficiency of TBAPy-to-TBAPy energy transfer was found to be sensitive to the structural parameters of MOFs. Analysis of steady-state and time-resolved fluorescence data revealed that excitation energy transfer (EET) is most efficient in ROD-7, followed by NU-901 and NU-1000. We propose that topology that invokes the shorter interchromophoric distances between TBAPy linkers in ROD-7 is responsible for its higher EET efficiency. The distance dependence of the EET rate constant (kEET) was investigated to gain insight into the mechanistic aspects of energy transfer in MOFs. This study revealed that (a) energy transfer in MOFs deviates from the classical Förster model and (b) the geometrical arrangement of linkers influences the mechanism of EET in MOFs. A theoretical investigation was also performed to determine energy-transfer rate constants along different directions and assess the directionality of energy transfer in these MOFs. The magnitude of rate constants indicated that energy transfer in ROD-7 should be highly anisotropic along the stacking direction. Furthermore, these findings suggest that ROD-7 is a promising candidate to play the role of the light-harvesting and energy-transfer component in solar energy conversion devices, where directional energy transfer is required.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

A data-driven approach to real-time vertical position estimation for NSTX-U vertical stability control

In this paper, a database of 77 996 plasma equilibrium reconstructions from 727 discharges during the initial operation of the NSTX-U spherical tokamak is analyzed to develop a statistically robust model of the plasma vertical position for real-time control. A variety of regression models are developed and tested, ranging in complexity from linear models to deep neural networks, and including input signals ranging from the four pairs of flux loops used historically on NSTX-U up to the full set of 389 real-time signals available to the plasma control system. A linear model based on 140 real-time magnetics signals is found to offer excellent accuracy, with a coefficient of determination R 2 = 0.906. The robustness of this model to limited training data, new operating scenarios, and signal errors is tested, and a procedure is demonstrated to tune the model parameters to optimize its robustness. A time-dependent plasma equilibrium solver, TokaMaker, is used to simulate vertical stability control in NSTX-U, demonstrating that it should be possible to iteratively tune the parameters of a linear vertical position model to stabilize both positive and negative triangularity plasmas in future experiments.

magnetic diagnostics↗
DOE OSTI2022

Derivative-free optimization of a rapid-cycling synchrotron

Here, we develop and solve a constrained optimization model to identify an integrable optics rapid-cycling synchrotron lattice design that performs well in several capacities. Our model encodes the design criteria into 78 linear and nonlinear constraints, as well as a single nonsmooth objective, where the objective and some constraints are defined from the output of Synergia, an accelerator simulator. We detail the difficulties of the 23-dimensional simulation-constrained decision space and establish that the space is nonempty. We use a derivative-free manifold sampling algorithm to account for structured nondifferentiability in the objective function. Our numerical results quantify the dependence of solutions on constraint parameters and the effect of the form of objective function.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

$Ξ$ 𝑐 → $Ξ$ form factors from lattice QCD with domain-wall quarks: A new piece in the puzzle of $Ξ^0_𝑐$ decay rates

We present a lattice quantum chromodynamics (QCD) determination of the vector and axial-vector form factors that describe the charm-baryon semileptonic decays Ξ 𝑐 → Ξ⁢ℓ + ⁢𝜈 ℓ . The calculation uses a domain-wall action for the up, down, and strange quarks, and an anisotropic clover action for the charm quark. We use four ensembles of gauge-field configurations generated by the RBC and UKQCD collaborations, with lattice spacings between 0.111 and 0.073 fm and pion masses ranging from 420 to 230 MeV. We present Standard Model predictions for the decay rates and branching fractions of Ξ$^0_𝑐$ → Ξ$^−_𝑐$⁢ℓ + ⁢𝜈 ℓ and Ξ$^+_𝑐$ → Ξ$^0_𝑐$⁢ℓ + ⁢𝜈 ℓ for ℓ =𝑒, 𝜇. In particular, we obtain Γ⁡(Ξ$^0_𝑐$ → Ξ − ⁢𝑒 + ⁢𝜈 𝑒 )/|𝑉 𝑐⁢𝑠 | 2 = 0.2515⁢(73) ps −1 and ℬ⁡(Ξ$^0_𝑐$ → Ξ − ⁢𝑒 +⁢ 𝜈 𝑒 ) = 3.58⁢(12)%. These values are higher than those predicted by a previous lattice calculation and substantially higher than the experimentally measured values, but consistent with expectations from approximate 𝑆⁢𝑈⁡(3) flavor symmetry.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

A survey of nonlinear robust optimization

Robust optimization (RO) has attracted great attention from the optimization community over the past decade. RO is dedicated to solving optimization problems subject to uncertainty: design constraints must be satisfied for all the values of the uncertain parameters within a given uncertainty set. Uncertainty sets may be modeled as deterministic sets (boxes, polyhedra, ellipsoids), in which case the RO problem may be reformulated via worst-case analysis, or as families of distributions. The challenge of RO is to reformulate or approximate robust constraints so that the uncertain optimization problem is transformed into a tractable deterministic optimization problem. Most reformulation methods assume linearity of the robust constraints or uncertainty sets of favorable shape, which represents only a fraction of real-world applications. This survey addresses nonlinear RO and includes problem formulations and applications, solution approaches, and available software with code samples.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Benchmarking quantum logic operations relative to thresholds for fault tolerance

Contemporary methods for benchmarking noisy quantum processors typically measure average error rates or process infidelities. However, thresholds for fault-tolerant quantum error correction are given in terms of worst-case error rates—defined via the diamond norm—which can differ from average error rates by orders of magnitude. One method for resolving this discrepancy is to randomize the physical implementation of quantum gates, using techniques like randomized compiling (RC). In this work, we use gate set tomography to perform precision characterization of a set of two-qubit logic gates to study RC on a superconducting quantum processor. We find that, under RC, gate errors are accurately described by a stochastic Pauli noise model without coherent errors, and that spatially correlated coherent errors and non-Markovian errors are strongly suppressed. We further show that the average and worst-case error rates are equal for randomly compiled gates, and measure a maximum worst-case error of 0.0197(3) for our gate set. Our results show that randomized benchmarks are a viable route to both verifying that a quantum processor’s error rates are below a fault-tolerance threshold, and to bounding the failure rates of near-term algorithms, if—and only if—gates are implemented via randomization methods which tailor noise.

97 MATHEMATICS AND COMPUTING↗