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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Exploring the Potential of ASHRAE Guideline 36 in District Cooling Systems: Preprint

ASHRAE Guideline 36-2021 (G36) provides high-performance control sequences for all-air and hydronic HVAC systems, and it has proven effective at reducing energy use for single building all-air equipment. The most recent version of G36 included control sequences for water-cooled chiller plants, which can be used in district cooling systems (DCSs). Despite not being a traditional application of G36 controls, DCSs could benefit from energy savings that G36 control sequences have demonstrated in single building systems. We therefore investigate the possibility to extend G36 chiller plant control from a single building to district cooling using a real-world district cooling system in Boulder, Colorado as a case study. Four timeframes representing low to peak loads are simulated and analyzed to compare energy use of the district cooling system for three control sequences. Results show that although G36 chiller plant sequences can be applied to DCSs, further analysis and potentially control optimization is needed to ensure energy savings compared to default controls.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

High-throughput single-cell transcriptomics of bacteria using combinatorial barcoding

Microbial split-pool ligation transcriptomics (microSPLiT) is a high-throughput single-cell RNA sequencing method for bacteria. With four combinatorial barcoding rounds, microSPLiT can profile transcriptional states in hundreds of thousands of Gram-negative and Gram-positive bacteria in a single experiment without specialized equipment. As bacterial samples are fixed and permeabilized before barcoding, they can be collected and stored ahead of time. During the first barcoding round, the fixed and permeabilized bacteria are distributed into a 96-well plate, where their transcripts are reverse transcribed into cDNA and labeled with the first well-specific barcode inside the cells. The cells are mixed and redistributed two more times into new 96-well plates, where the second and third barcodes are appended to the cDNA via in-cell ligation reactions. Finally, the cells are mixed and divided into aliquot sub-libraries, which can be stored until future use or prepared for sequencing with the addition of a fourth barcode. It takes 4 days to generate sequencing-ready libraries, including 1 day for collection and overnight fixation of samples. Here, the standard plate setup enables single-cell transcriptional profiling of up to 1 million bacterial cells and up to 96 samples in a single barcoding experiment, with the possibility of expansion by adding barcoding rounds. The protocol requires experience in basic molecular biology techniques, handling of bacterial samples and preparation of DNA libraries for next-generation sequencing. It can be performed by experienced undergraduate or graduate students. Data analysis requires access to computing resources, familiarity with Unix command line and basic experience with Python or R.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Old Woman Creek Wetland Sediment and Electrochemical Sensor Microbial Community, 2023

We are developing a technique to monitor microbiological activities referred to as zero resistance ammetry, which entails the deployment of graphite electrodes in sediments. Measurement of current between electrodes of contrasting redox regimes and/or predominant terminal electron accepting processes can be used as an indicator of the extents of microbiological activity. We deployed an electrode array at depths of 2 mm, 4 mm, 76 mm, 78 mm, 152 mm, 154 mm, 227 mm, and 229 mm below the wetland sediment water interface in the Old Woman Creek National Estuarine Research Center, Huron, OH, USA (Lat. = 41.380833, Long. = -82.508889). A core was collected from adjacent sediment and subsamples were collected from depth intervals of 0 – 25 mm, 25 – 127 mm, 127 – 128 mm, and below 178 mm. To determine if the microbial communities attached to the electrodes were reflective of the adjacent sediment-associated microbial community, we conducted a 16S rRNA gene-based (V4 region) survey of these respective materials. This data package contains the results of these surveys, including metadata on the depths from which samples were collected (samples.csv), DNA extraction and sequencing information (OWC_DEPTH_AMPLICON_SEQUENCING_METADATA), sequence processing information (OWC_DEPTH_BIOINFORMATIC_METADATA.csv), an operational taxonomic unit (OTU) table (OWC_DEPTH_97OTUS_TABLE.csv), and nucleotide sequences of OTUs (OWC_DEPTH_97OTUS_SEQS.fasta). All files can be opened using a text-editing application. The fasta file is compatible with bioinformatics applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Study of the Protection Improvements for a Weak Grid Area With High Inverter-Based Resources (IBRs)

This project designs enhanced protection scheme for the real-world weak grid area with a high penetration of IBRs. As the existing protection schemes are originally designed for traditional synchronous machines, we first evaluate if the protection scheme will continue to operate reliably in systems with high levels of IBRs. Hardware relays are tested using a controller-hardware-in-the-loop setup. PSCAD electromagnetic transient simulation with IBR original equipment manufacturer black-box models is used to perform fault studies and generate COMTRADE data, which are replayed by a real-time digital simulator (RTDS) to feed input to the hardware relays. Three scenarios are analyzed: normal operation, an N-1 contingency, and an IBR-only scenario. The evaluation results reveal the following: 1) the protection scheme remains reliable under normal conditions and N-1 contingencies and 2) in IBR-only scenarios, differential protection (87L) continues to operate reliably, whereas local protection elements, such as distance and directional elements, fail because of the lack of regulated negative sequence current contributed by IBRs. Enhanced protection is designed to address the challenge of lack of negative sequence current from IBRs, including increased restraining factors a2 and k2 to block 32Q or using V instead QV ORDER for ground faults, enhanced mho distance element with voltage and phase angle supervision for L-L faults. The efficacy of enhanced protection logic is validated and proven to work reliably. Additionally, IEEE Std. 2800-2022 negative sequence current compliant GFL and GFM IBRs from another vendor are tested and proven to work reliably without need for enhanced logic. Therefore, this work provides valuable decision-making for utilities facing protection system challenges due to IBRs, either designing enhanced protection scheme or requesting their IBRs being IEEE Std. 2800-2022 compliant to produce regulated negative sequence current for protection relay to make correct decision.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Developing Asparagaceae1726: An Asparagaceae‐specific probe set targeting 1726 loci for Hyb‐Seq and phylogenomics in the family

Abstract Premise Target sequence capture (Hyb‐Seq) is a cost‐effective sequencing strategy that employs RNA probes to enrich for specific genomic sequences. By targeting conserved low‐copy orthologs, Hyb‐Seq enables efficient phylogenomic investigations. Here, we present Asparagaceae1726—a Hyb‐Seq probe set targeting 1726 low‐copy nuclear genes for phylogenomics in the angiosperm family Asparagaceae—which will aid the often‐challenging delineation and resolution of evolutionary relationships within Asparagaceae. Methods Here we describe and validate the Asparagaceae1726 probe set (https://github.com/bentzpc/Asparagaceae1726) in six of the seven subfamilies of Asparagaceae. We perform phylogenomic analyses with these 1726 loci and evaluate how inclusion of paralogs and bycatch plastome sequences can enhance phylogenomic inference with target‐enriched data sets. Results We recovered at least 82% of target orthologs from all sampled taxa, and phylogenomic analyses resulted in strong support for all subfamilial relationships. Additionally, topology and branch support were congruent between analyses with and without inclusion of target paralogs, suggesting that paralogs had limited effect on phylogenomic inference. Discussion Asparagaceae1726 is effective across the family and enables the generation of robust data sets for phylogenomics of any Asparagaceae taxon. Asparagaceae1726 establishes a standardized set of loci for phylogenomic analysis in Asparagaceae, which we hope will be widely used for extensible and reproducible investigations of diversification in the family.

Plant Sciences↗
DOE OSTI2024

High phenotypic and genotypic plasticity among strains of the mushroom-forming fungus Schizophyllum commune

Schizophyllum commune is a mushroom-forming fungus notable for its distinctive fruiting bodies with split gills. It is used as a model organism to study mushroom development, lignocellulose degradation and mating type loci. It is a hypervariable species with considerable genetic and phenotypic diversity between the strains. In this study, we systematically phenotyped 16 dikaryotic strains for aspects of mushroom development and 18 monokaryotic strains for lignocellulose degradation. There was considerable heterogeneity among the strains regarding these phenotypes. The majority of the strains developed mushrooms with varying morphologies, although some strains only grew vegetatively under the tested conditions. Growth on various carbon sources showed strain-specific profiles. The genomes of seven monokaryotic strains were sequenced and analyzed together with six previously published genome sequences. Moreover, the related species Schizophyllum fasciatum was sequenced. Although there was considerable genetic variation between the genome assemblies, the genes related to mushroom formation and lignocellulose degradation were well conserved. These sequenced genomes, in combination with the high phenotypic diversity, will provide a solid basis for functional genomics analyses of the strains of S. commune.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

A dynamic solvent chamber propagation estimation framework using RNN for warm solvent injection in heterogeneous reservoirs

Warm solvent injection (WSI), injecting low-temperature solvent into formations to reduce the viscosity of heavy oil, is a clean technology for heavy oil production through reducing greenhouse gas emissions and water usage. The success of WSI operation depends on the uniform development and propagation of solvent chambers in reservoirs. However, reservoir heterogeneity stemming from shale barriers plays a detrimental role in the conformance of solvent chamber development and oil production rate. In this work, we developed a novel recurrent neural network (RNN)-based framework with the capability of efficiently tracking and estimating the solvent chamber positions in heterogeneous reservoirs based on only production time-series data. The developed estimation model utilizes the “sequence-to-sequence" mapping methodology to correlate observed production time-series sequence and solvent chamber edge sequence via a long short-term memory (LSTM) algorithm. The trained RNN models exhibit high accuracy, evidenced by the predicted dynamic solvent chamber locations match the corresponding true locations from numerical simulation, with a high coefficient of determination (R 2 ) and a low mean squared error. Specifically, the achieved R 2 values exceed 0.98 on both the training and testing data. The developed RNN-based workflow was tested via several cases from both regularly- and irregularly-shaped shale barriers, and the results were promising. The predicted solvent chambers showed strong agreement with those obtained from numerical simulations. The major benefits of this workflow include reducing computational time and saving overall monitoring and tracking costs for conventional techniques. In conclusion, the present work would provide a good demonstration of the capability of practical integration of machine learning methods in solving engineering problems.

58 GEOSCIENCES↗
DOE OSTI2025

GMFOLD: Subgraph matching for high-throughput DNA-aptamer secondary structure classification and machine learning interpretability

Aptamers are oligonucleotide receptors that bind to their targets with high affinity. Here, we consider aptamers comprised of single-stranded DNA that undergo target-binding-induced conformational changes, giving rise to unique secondary and tertiary structures. Given a specific aptamer primary sequence, there are well-established computational tools (notably mfold) to predict the secondary structure via free energy minimization algorithms. While mfold generates secondary structures for individual sequences, there is a need for a high-throughput process whereby thousands of DNA structures can be predicted in real-time for use in an interactive setting, when combined with aptamer selections that generate candidate pools that are too large to be experimentally interrogated. We developed a new Python code for high-throughput aptamer secondary structure determination (GMfold). GMfold uses subgraph matching methods to group aptamer candidates by secondary structure similarities. We also improve an open-source code, SeqFold, to incorporate subgraph matching concepts. We represent each secondary structure as a lowest-energy bipartite subgraph matching of the DNA graph to itself. These new tools enable thousands of DNA sequences to be compared based on their secondary structures, using machine-learning algorithms. This process is advantageous when analyzing sequences that arise from aptamer selections via systematic evolution of ligands by exponential enrichment (SELEX). This work is a building block for future machine-learning-informed DNA-aptamer selection processes to identify aptamers with improved target affinity and selectivity and advance aptamer biosensors and therapeutics.

Aptamer↗
DOE OSTI2025

Functional Design of Peptide Materials Based on Supramolecular Cohesion

Peptide materials offer a broad platform to design biomimetic soft matter, and filamentous networks that emulate those in extracellular matrices and the cytoskeleton are among the important targets. Given the vast sequence space, a combination of computational approaches and readily accessible experimental techniques is required to design peptide materials efficiently. Here, we report here on a strategy that utilizes this combination to predict supramolecular cohesion within filaments of peptide amphiphiles, a property recently linked to supramolecular dynamics and consequently bioactivity. Using established coarse-grained simulations on 10,000 randomly generated peptide sequences, we identified 3500 likely to self-assemble in water into nanoscale filaments. Atomistic simulations of small clusters were used to further analyze this subset of sequences and identify mathematical descriptors that are predictive of intermolecular cohesion, which was the main purpose of this work. We arbitrarily selected a small cohort of these sequences for chemical synthesis and verified their fiber morphology. With further characterization, we were able to link the latent heat associated with fiber to micelle transitions, an indicator of cohesion and potential supramolecular dynamicity within the filaments, to calculated hydrogen bond densities in the simulation clusters. Based on validation from in situ synchrotron X-ray scattering and differential scanning calorimetry, we conclude that the phase transitions can be easily observed by very simple polarized light microscopy experiments. We are encouraged by the methodology explored here as a relatively low-cost and fast way to design potential functions of peptide materials.

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

Atomic-Scale Imaging Reveals Polar-π Interactions in Two-Dimensional Molecular Superlattices

Controlling coassembly of synthetic oligomers into binary superlattices at the atomic level is challenging. Here, we report a strategy for programming polar-π interactions in oligomeric peptoids, a class of sequence-defined peptidomimetics, facilitating the formation of homogeneous two-dimensional (2D) superlattices. N-2-phenylethyl and N-(2-perfluorophenyl)ethyl side chains, similar in size, but with contrasting electrostatic characteristics, were introduced at defined sequence positions to generate favorable dipolar aromatic interactions. The resulting nanosheets exhibit different crystal motifs depending on the side chain interactions: systems containing only one type of aromatic side chain form a parallel V-shaped motif driven by π-π interactions, whereas a combination of both types of aromatic side chains, either within one backbone or through the coassembly of two distinct peptoids, adopt an antiparallel V-shaped superlattice with higher thermal stability, driven by polar-π interactions. Cryogenic transmission electron microscopy directly resolved the packing arrangement of perfluorophenyl and phenyl rings in individual nanosheet superlattices, confirming that intermolecular polar-π interaction dominates the superlattice motifs and increases lattice stability. Molecular dynamics simulations and density functional theory calculations further substantiate the energetic favorability of polar-π interactions over π-π interactions, rationalizing the formation of homogeneous superlattices with enhanced thermal stability. Our discoveries establish a design principle for binary coassembly using sequence-defined oligomers, which enables control over unit cell geometry, lattice stability, and molecular registration through aromatic side chain polarization and sequence control. This ability to program atomic-scale binary superlattices opens new avenues for designing functional 2D soft materials.

Lee, Yen Jea [Lawrence Berkeley National Laborator↗
DOE OSTI2024

Simultaneous enhancement of multiple functional properties using evolution-informed protein design

Abstract A major challenge in protein design is to augment existing functional proteins with multiple property enhancements. Altering several properties likely necessitates numerous primary sequence changes, and novel methods are needed to accurately predict combinations of mutations that maintain or enhance function. Models of sequence co-variation (e.g., EVcouplings), which leverage extensive information about various protein properties and activities from homologous protein sequences, have proven effective for many applications including structure determination and mutation effect prediction. We apply EVcouplings to computationally design variants of the model protein TEM-1 β -lactamase. Nearly all the 14 experimentally characterized designs were functional, including one with 84 mutations from the nearest natural homolog. The designs also had large increases in thermostability, increased activity on multiple substrates, and nearly identical structure to the wild type enzyme. This study highlights the efficacy of evolutionary models in guiding large sequence alterations to generate functional diversity for protein design applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Predicting synthetic mRNA stability using massively parallel kinetic measurements, biophysical modeling, and machine learning

Abstract mRNA degradation is a central process that affects all gene expression levels, though it remains challenging to predict the stability of a mRNA from its sequence, due to the many coupled interactions that control degradation rate. Here, we carried out massively parallel kinetic decay measurements on over 50,000 bacterial mRNAs, using a learn-by-design approach to develop and validate a predictive sequence-to-function model of mRNA stability. mRNAs were designed to systematically vary translation rates, secondary structures, sequence compositions, G-quadruplexes, i-motifs, and RppH activity, resulting in mRNA half-lives from about 20 seconds to 20 minutes. We combined biophysical models and machine learning to develop steady-state and kinetic decay models of mRNA stability with high accuracy and generalizability, utilizing transcription rate models to identify mRNA isoforms and translation rate models to calculate ribosome protection. Overall, the developed model quantifies the key interactions that collectively control mRNA stability in bacterial operons and predicts how changing mRNA sequence alters mRNA stability, which is important when studying and engineering bacterial genetic systems.

Cetnar, Daniel P.↗
DOE OSTI2024

Genomic and morphological characterization of Knufia obscura isolated from the Mars 2020 spacecraft assembly facility

Members of the family Trichomeriaceae, belonging to the Chaetothyriales order and the Ascomycota phylum, are known for their capability to inhabit hostile environments characterized by extreme temperatures, oligotrophic conditions, drought, or presence of toxic compounds. The genus Knufia encompasses many polyextremophilic species. In this report, the genomic and morphological features of the strain FJI-L2-BK-P2 presented, which was isolated from the Mars 2020 mission spacecraft assembly facility located at the Jet Propulsion Laboratory in Pasadena, California. The identification is based on sequence alignment for marker genes, multi-locus sequence analysis, and whole genome sequence phylogeny. The morphological features were studied using a diverse range of microscopic techniques (bright field, phase contrast, differential interference contrast and scanning electron microscopy). The phylogenetic marker genes of the strain FJI-L2-BK-P2 exhibited highest similarities with type strain of Knufia obscura (CBS 148926 T ) that was isolated from the gas tank of a car in Italy. To validate the species identity, whole genomes of both strains (FJI-L2-BK-P2 and CBS 148926 T ) were sequenced, annotated, and strain FJI-L2-BK-P2 was confirmed as K. obscura. The morphological analysis and description of the genomic characteristics of K. obscura FJI-L2-BK-P2 may contribute to refining the taxonomy of Knufia species. Key morphological features are reported in this K. obscura strain, resembling microsclerotia and chlamydospore-like propagules. These features known to be characteristic features in black fungi which could potentially facilitate their adaptation to harsh environments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Activity, structure, and diversity of Type II proline-rich antimicrobial peptides from insects

Abstract Apidaecin 1b (Api), the first characterized Type II Proline-rich antimicrobial peptide (PrAMP), is encoded in the honey bee genome. It inhibits bacterial growth by binding in the nascent peptide exit tunnel of the ribosome after the release of the completed protein and trapping the release factors. By genome mining, we have identified 71 PrAMPs encoded in insect genomes as pre-pro-polyproteins. Having chemically synthesized and tested the activity of 26 peptides, we demonstrate that despite significant sequence variation in the N-terminal sequence, the majority of the PrAMPs that retain the conserved C-terminal sequence of Api are able to trap the ribosome at the stop codons and induce stop codon readthrough—all hallmarks of Type II PrAMP mode of action. Some of the characterized PrAMPs exhibit superior antibacterial activity in comparison with Api. The newly solved crystallographic structures of the ribosome complexed with Api and with the more active peptide Fva1 from the stingless bee demonstrate the universal placement of the PrAMPs’ C-terminal pharmacophore in the post-release ribosome despite variations in their N-terminal sequence.

Huang, Weiping (ORCID:0000000273063550)↗
DOE OSTI2024

A potential role for RNA aminoacylation prior to its role in peptide synthesis

Coded ribosomal peptide synthesis could not have evolved unless its sequence and amino acid–specific aminoacylated tRNA substrates already existed. We therefore wondered whether aminoacylated RNAs might have served some primordial function prior to their role in protein synthesis. Here, we show that specific RNA sequences can be nonenzymatically aminoacylated and ligated to produce amino acid–bridged stem-loop RNAs. We used deep sequencing to identify RNAs that undergo highly efficient glycine aminoacylation followed by loop-closing ligation. The crystal structure of one such glycine-bridged RNA hairpin reveals a compact internally stabilized structure with the same eponymous T-loop architecture that is found in many noncoding RNAs, including the modern tRNA. We demonstrate that the T-loop-assisted amino acid bridging of RNA oligonucleotides enables the rapid template-free assembly of a chimeric version of an aminoacyl-RNA synthetase ribozyme. We suggest that the primordial assembly of amino acid–bridged chimeric ribozymes provides a direct and facile route for the covalent incorporation of amino acids into RNA. A greater functionality of covalently incorporated amino acids could contribute to enhanced ribozyme catalysis, providing a driving force for the evolution of sequence and amino acid–specific aminoacyl-RNA synthetase ribozymes in the RNA World. The synthesis of specifically aminoacylated RNAs, an unlikely prospect for nonenzymatic reactions but a likely one for ribozymes, could have set the stage for the subsequent evolution of coded protein synthesis.

Science & Technology - Other Topics↗
DOE OSTI2026

nf-core/proteinfamilies: a scalable pipeline for the generation of protein families

The growth of metagenomics-derived amino acid sequence data has transformed our understanding of protein function, microbial diversity, and evolutionary relationships. However, the vast majority of these proteins remain functionally uncharacterized. Grouping the millions of such uncharacterized sequences with the few experimentally characterized ones allows the transfer of annotations, while the inspection of conserved residues with multiple sequence alignments can provide clues to function, even in the absence of existing functional information. To address the challenges associated with this data surge and the need to group sequences, we present a scalable, open-source, parametrizable Nextflow pipeline (nf-core/proteinfamilies) that generates nascent protein families or assigns new proteins to existing families. The computational benchmarks demonstrated that resource usage scales approximately linearly with input size, and the biological benchmarks showed that the generated protein families closely resemble manually curated families in widely used databases.

Nextflow↗
DOE OSTI2025

Vanderwaltozyma urihicola sp. nov., a yeast species isolated from rotting wood and beetles in a Brazilian Amazonian rainforest biome

Five yeast isolates belonging to a candidate for novel species were obtained from rotting wood and the gut of a passalid beetle larva in a site of Amazonian rainforest biome in Brazil. Sequence analysis of the Internal Transcribed Spacer (ITS)-5.8S region and the D1/D2 domains of the large subunit rRNA gene showed that the isolates represent a novel species of the genus Vanderwaltozyma. The closest relative of the novel species is Vanderwaltozyma huisunica. These species differs due to 44 nt substitutions and 21 indels in the sequences of the ITS region, as well as by 15 substitutions and four indels in the sequences of the D1/D2 domains. A phylogenomic analysis of the Vanderwaltozyma species with genomes sequenced showed that this novel species is an outgroup to the other species of this genus. We propose the name Vanderwaltozyma urihicola sp. nov. (CBS 18107T, MycoBank MB 856975) to accommodate these isolates. Furthermore, the species is homothallic, producing one to two ascospores per ascus. The habitat of V. urihicola is rotting wood in the Brazilian Amazonian rainforest biome.

Amazonian Forest↗
DOE OSTI2024

Direct pulse-level compilation of arbitrary quantum logic gates on superconducting qutrits

Advanced simulations and calculations on quantum computers require high-fidelity implementations of quantum operations. The universal gateset approach builds complex unitaries from a small set of primitive gates, often resulting in a long gate sequence, which is typically a leading factor in the total accumulated error. Compiling a complex unitary for processors with higher-dimensional logical elements, such as qutrits, exacerbates the accumulated error per unitary, since an even longer gate sequence is required. Optimal control methods promise time- and resource-efficient compact gate sequences and, therefore, higher fidelity. These methods generate pulses that can directly implement any complex unitary on a quantum device. In this work, we demonstrate that any arbitrary qubit and qutrit gate can be realized with high fidelity, which can significantly reduce the length of a gate sequence. We generate and test pulses for a large set of randomly selected arbitrary unitaries on several quantum processing units (QPUs): the Lawrence Livermore National Laboratory Quantum Device and Integration Testbed’s (QuDIT’s) standard QPU and three of Rigetti’s QPUs: Ankaa-2, Ankaa-9Q-1, and Aspen-M-3. On the QuDIT platform’s standard QPU, the average fidelity of random qutrit gates is 97.9 ± 0.5% measured with conventional QPT and 98.8 ± 0.6% from QPT with gate folding. Rigetti’s Ankaa-2 achieves random qubit gates with an average fidelity of 98.4 ± 0.5% (conventional QPT) and 99.7 ± 0.1% (QPT with gate folding). On Ankaa-9Q-1 and Aspen-M-3, the average fidelities with conventional qubit QPT measurements were higher than 99% (see Appendix). Here we show that optimal control gates are robust to drift for at least 3 h and that the same calibration parameters can be used for all implemented gates. Our work promises that the calibration overheads for optimal control gates can be made small enough to enable efficient quantum circuits based on this technique.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗