Search NASA⌕ Search

SEARCH · Search NASA

Results for “flagship”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

The X-ray Integral Field Unit at the end of the Athena reformulation phase

The Athena mission entered a redefinition phase in July 2022, driven by the imperative to reduce the mission cost at completion for the European Space Agency below an acceptable target, while maintaining the flagship nature of its science return. This notably called for a complete redesign of the X-ray Integral Field Unit (X-IFU) cryogenic architecture towards a simpler active cooling chain. Passive cooling via successive radiative panels at spacecraft level is now used to provide a 50 K thermal environment to an X-IFU owned cryostat. 4.5 K cooling is achieved via a single remote active cryocooler unit, while a multi-stage Adiabatic Demagnetization Refrigerator ensures heat lift down to the 50 mK required by the detectors. Amidst these changes, the core concept of the readout chain remains robust, employing Transition Edge Sensor microcalorimeters and a SQUID-based Time-Division Multiplexing scheme. Noteworthy is the introduction of a slower pixel. This enables an increase in the multiplexing factor (from 34 to 48) without compromising the instrument energy resolution, hence keeping significant system margins to the new 4 eV resolution requirement. This allows reducing the number of channels by more than a factor two, and thus the resource demands on the system, while keeping a 4’ field of view (compared to 5’ before). Here, in this article, we will give an overview of this new architecture, before detailing its anticipated performances. Finally, we will present the new X-IFU schedule, with its short term focus on demonstration activities towards a mission adoption in early 2027.

Peille, Philippe [Centre National d’Etudes Spatial↗
DOE OSTI2022

Pitting Corrosion in 316L Stainless Steel Fabricated by Laser Powder Bed Fusion Additive Manufacturing: A Review and Perspective

Abstract 316L stainless steel (316L SS) is a flagship material for structural applications in corrosive environments, having been extensively studied for decades for its favorable balance between mechanical and corrosion properties. More recently, 316L SS has also proven to have excellent printability when parts are produced with additive manufacturing techniques, notably laser powder bed fusion (LPBF). Because of the harsh thermo-mechanical cycles experienced during rapid solidification and cooling, LPBF processing tends to generate unique microstructures. Strong heterogeneities can be found inside grains, including trapped elements, nano-inclusions, and a high density of dislocations that form the so-called cellular structure. Interestingly, LPBF 316L SS not only exhibits better mechanical properties than its conventionally processed counterpart, but it also usually offers much higher resistance to pitting in chloride solutions. Unfortunately, the complexity of the LPBF microstructures, in addition to process-induced defects, such as porosity and surface roughness, have slowed progress toward linking specific microstructural features to corrosion susceptibility and complicated the development of calibrated simulations of pitting phenomena. The first part of this article is dedicated to an in-depth review of the microstructures found in LPBF 316L SS and their potential effects on the corrosion properties, with an emphasis on pitting resistance. The second part offers a perspective of some relevant modeling techniques available to simulate the corrosion of LPBF 316L SS, including current challenges that should be overcome.

Voisin, T. (ORCID:0000000287462659)↗
DOE OSTI2021

Gate-free state preparation for fast variational quantum eigensolver simulations

Abstract The variational quantum eigensolver is currently the flagship algorithm for solving electronic structure problems on near-term quantum computers. The algorithm involves implementing a sequence of parameterized gates on quantum hardware to generate a target quantum state, and then measuring the molecular energy. Due to finite coherence times and gate errors, the number of gates that can be implemented remains limited. In this work, we propose an alternative algorithm where device-level pulse shapes are variationally optimized for the state preparation rather than using an abstract-level quantum circuit. In doing so, the coherence time required for the state preparation is drastically reduced. We numerically demonstrate this by directly optimizing pulse shapes which accurately model the dissociation of H 2 and HeH + , and we compute the ground state energy for LiH with four transmons where we see reductions in state preparation times of roughly three orders of magnitude compared to gate-based strategies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

On measuring stimulated photon–photon scattering using multiple ultraintense lasers

Stimulated photon–photon scattering is a predicted consequence of quantum electrodynamics that has yet to be measured directly. Measuring the cross section for stimulated photon–photon scattering is the aim of a flagship experiment for NSF OPAL, a proposed laser user facility with two, 25-PW beamlines. We present optimized experimental designs for achieving this challenging and canonical measurement. A family of experimental geometries is identified that satisfies the momentum- and energy-matching conditions for two selected laser frequency options. Numerical models predict a maximum signal exceeding 1000 scattered photons per shot at the experimental conditions envisaged at NSF OPAL. Experimental requirements on collision geometry, polarization, cotiming and copointing, background suppression, and diagnostic technologies are investigated numerically. These results confirm that a beam cotiming shorter than the pulse duration and control of the copointing on a scale smaller than the shortest laser wavelength are needed to robustly scatter photons on a per-shot basis. Finally, we assess the bounds that a successful execution of this experiment may place on the mass scale of Born–Infeld nonlinear electrodynamics beyond the standard model of physics.

Beyond the Standard Model↗
DOE OSTI2021

The High Luminosity LHC interaction region magnets towards series production

The High Luminosity Large Hadron Collider (HL-LHC) is the new flagship project of CERN. First endorsed in 2013 and approved in 2016, HL-LHC is an upgrade of the accelerator aiming to increase by a factor of ten the statistics of the LHC collisions at the horizon of 2035-2040. HL-LHC relies on cutting edge technologies: among them, large aperture superconducting magnets will replace the present hardware to allow a smaller beam size in two interaction points (IPs). The project involves the construction of about 150 magnets of six different types: the quadrupole triplet, two main dipoles and three orbit correctors. The triplet, manufactured at CERN and in the USA, will consist of 30 magnets based on Nb3Sn technology, with an operational peak field of 11.4 T. These will be the first quadrupole Nb3Sn magnets installed in a particle accelerator. The other five types of magnets, all relying on Nb-Ti technology, present non-trivial challenges in the design and construction; they will be manufactured as part of in-kind contribution under the responsibility of institutes in Japan, China, Spain, and Italy. The project is now in the phase of transition between qualification through short models and prototypes and the beginning of the series construction. In this paper we review the magnet requirements, the reasons for selecting the design, the technological challenges with respect to previous projects, and we summarize the steps that have been taken to validate the baseline.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Scaling the training of particle classification on simulated MicroBooNE events to multiple GPUs

Measurements in Liquid Argon Time Projection Chamber (LArTPC) neutrino detectors, such as the MicroBooNE detector at Fermilab, feature large, high fidelity event images. Deep learning techniques have been extremely successful in classification tasks of photographs, but their application to LArTPC event images is challenging, due to the large size of the events. Events in these detectors are typically two orders of magnitude larger than images found in classical challenges, like recognition of handwritten digits contained in the MNIST database or object recognition in the ImageNet database. Ideally, training would occur on many instances of the entire event data, instead of many instances of cropped regions of interest from the event data. However, such efforts lead to extremely long training cycles, which slow down the exploration of new network architectures and hyperparameter scans to improve the classification performance. We present studies of scaling a LArTPC classification problem on multiple architectures, spanning multiple nodes. The studies are carried out on simulated events in the MicroBooNE detector. We emphasize that it is beyond the scope of this study to optimize networks or extract the physics from any results here. Institutional computing at Pacific Northwest National Laboratory and the SummitDev machine at Oak Ridge National Laboratory’s Leadership Computing Facility have been used. To our knowledge, this is the first use of state-of-the-art Convolutional Neural Networks for particle physics and their attendant compute techniques onto the DOE Leadership Class Facilities. We expect benefits to accrue particularly to the Deep Underground Neutrino Experiment (DUNE) LArTPC program, the flagship US High Energy Physics (HEP) program for the coming decades.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

LBNF/DUNE Liquid Argon Roadmap

The Deep Underground Neutrino Experiment (DUNE) is an international flagship venture to unlock the mysteries of neutrinos. Hosted at the Sanford Underground Research Facility (SURF) and supported by the Long-Baseline Neutrino Facility (LBNF), DUNE relies on nearly 75,000 tonnes of ultrapure liquid argon (LAr) housed in state-of-the-art cryostats. Transporting such vast quantities of LAr to its destination a mile underground in Lead, SD, is a logistical and engineering challenge. The process begins with securing large quantities of liquid argon from suppliers located far from the site, with major sources situated near Houston, TX and Chicago, IL. The receiving facility, located atop a mountain with steep, often snow-covered access roads, provides limited maneuverability for trucks and can only handle two deliveries simultaneously. The facility serves as an entry point for argon to the greater LBNF cryogenic system. It is furnished with truck unloading stations, limited buffer storage of some 280 tonnes capacity, and vaporizers. The last are crucial for converting liquid argon into gas for transfer down the Ross Shaft, eliminating the need for cryogens in the vertical pipeline. These constraints, along with other operational factors, cap the delivery rate at 70 tonnes per day. Once underground, the argon is purified and recondensed before filling the cryostats. This roadmap outlines the integrated supply chain and cryogenic systems that enable the delivery of LAr to support DUNE’s groundbreaking physics research.

Maciazka, Matt [Fermilab]↗
DOE OSTI2025

Comparison of stress tolerance mechanisms between Saccharomyces cerevisiae and the multistress-tolerant Pichia kudriavzevii

Yeasts play a vital role in both research and industrial biomanufacturing. Saccharomyces cerevisiae has been extensively utilized as a model system. However, its application is often constrained by limited tolerance to the diverse stress conditions encountered in bioprocesses. These challenges have driven increasing interest in nonconventional, multistress-tolerant yeasts as alternative biomanufacturing hosts. This review highlights Pichia kudriavzevii as a promising nonconventional yeast for industrial applications. Unlike S. cerevisiae, P. kudriavzevii exhibits exceptional tolerance to high temperatures, elevated concentrations of furanic and phenolic inhibitors, osmotic stress, salinity, and extreme pH. These traits make it an attractive candidate for industrial processes without requiring extensive genetic modifications to enhance stress resistance. As a result, P. kudriavzevii has emerged as a flagship species for advancing bioeconomy. Despite its industrial potential, the molecular mechanisms underlying P. kudriavzevii's superior stress tolerance remain poorly understood. This review compiles current knowledge on P. kudriavzevii and compares its stress tolerance mechanisms with those of S. cerevisiae, providing insights into its innate resilience. By expanding our understanding of nonconventional yeasts, this review aims to facilitate their broader adoption as robust microbial platforms for industrial biomanufacturing.

Frousnoon, Thasneem Banu↗
DOE OSTI2020

Interacting galaxies in the IllustrisTNG simulations - I: Triggered star formation in a cosmological context

ABSTRACT We use the IllustrisTNG cosmological hydrodynamical simulations to investigate how the specific star formation rates (sSFRs) of massive galaxies (M* > 1010 M⊙) depend on the distance to their closest companions. We estimate sSFR enhancements by comparing with control samples that are matched in redshift, stellar mass, local density, and isolation, and we restrict our analysis to pairs with stellar mass ratios of 0.1 to 10. At small separations (∼15 kpc), the mean sSFR is enhanced by a factor of 2.0 ± 0.1 in the flagship (110.7 Mpc)3 simulation (TNG100-1). Statistically significant enhancements extend out to 3D separations of 280 kpc in the (302.6 Mpc)3 simulation (TNG300-1). We find similar trends in the EAGLE and Illustris simulations, although their sSFR enhancements are lower than those in TNG100-1 by about a factor of two. Enhancements in IllustrisTNG galaxies are seen throughout the redshift range explored (0 ≤ $z$ < 1), with the strength of the enhancements decreasing with increasing redshift for galaxies with close companions. In order to more closely compare with observational results, we separately consider 2D projected distances between galaxies in IllustrisTNG. We detect significant sSFR enhancements out to projected separations of 260 kpc in TNG300-1, with projection effects diluting the size of the enhancements by about 20 per cent below 50 kpc. We find similar sSFR enhancements in TNG100-1 and Sloan Digital Sky Survey galaxies, with enhancements extending out to projected separations of about 150 kpc for star-forming galaxies at $z$ < 0.2. Finally, by summing over all separations, we estimate that the presence of closest companions boosts the average sSFR of massive galaxies in TNG100-1 by 14.5 per cent.

Patton, David R.↗
DOE OSTI2021

ABACUSSUMMIT : a massive set of high-accuracy, high-resolution N -body simulations

We present the public data release of the AbacusSummit cosmological N-body simulation suite, produced with the Abacus N-body code on the Summit supercomputer of the Oak Ridge Leadership Computing Facility. Abacus achieves $\mathcal {O}(10^{-5})$ median fractional force error at superlative speeds, calculating 70M particle updates per second per node at early times, and 45M particle updates per second per node at late times. The simulation suite totals roughly 60 trillion particles, the core of which is a set of 139 simulations with particle mass $2\times 10^{9}\, h^{-1}\, \mathrm{M}_\odot$ in box size $2\, h^{-1}\, \mathrm{Gpc}$. The suite spans 97 cosmological models, including Planck 2018, previous flagship simulation cosmologies, and a linear derivative and cosmic emulator grid. A subsuite of 1883 boxes of size $500\, h^{-1}\, \mathrm{Mpc}$ is available for covariance estimation. AbacusSummit data products span 33 epochs from z = 8 to 0.1 and include light cones, full particle snapshots, halo catalogues, and particle subsets sampled consistently across redshift. AbacusSummit is the largest high-accuracy cosmological N-body data set produced to date.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Accuracy of power spectra in dissipationless cosmological simulations

Abstract We exploit a suite of large N-body simulations (up to N = 40963) performed with abacus, of scale-free models with a range of spectral indices n, to better understand and quantify convergence of the matter power spectrum. Using self-similarity to identify converged regions, we show that the maximal wavenumber resolved at a given level of accuracy increases monotonically as a function of time. At 1 per cent level it starts at early times from a fraction of $k_\Lambda$, the Nyquist wavenumber of the initial grid, and reaches at most, if the force softening is sufficiently small, ${\sim}2{-}3 k_\Lambda$ at the very latest times we evolve to. At the $5{{\ \rm per\ cent}}$ level, accuracy extends up to wavenumbers of order $5k_\Lambda$ at late times. Expressed as a suitable function of the scale-factor, accuracy shows a very simple n-dependence, allowing a extrapolation to place conservative bounds on the accuracy of N-body simulations of non-scale-free models like LCDM. We note that deviations due to discretization in the converged range are not well modelled by shot noise, and subtracting it in fact degrades accuracy. Quantitatively our findings are broadly in line with the conservative assumptions about resolution adopted by recent studies using large cosmological simulations (e.g. Euclid Flagship) aiming to constrain the mildly non-linear regime. On the other hand, we remark that conclusions about small-scale clustering (e.g. concerning the validity of stable clustering) obtained using PS data at wavenumbers larger than a few $k_\Lambda$ may need revision in light of our convergence analysis.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

FORECASTOR – II. Simulating galaxy surveys with the Cosmological Advanced Survey Telescope for Optical and UV Research

The Cosmological Advanced Survey Telescope for Optical and UV Research (CASTOR) is a planned flagship space telescope, covering the blue-optical and UV part of the spectrum. Here, we introduce the CASTOR image simulator, a python GalSim package-based script capable of generating mock CASTOR images from an input catalogue. We generate example images from the CASTOR Wide, Deep, and Ultra-Deep surveys using simulated lightcones from the Santa Cruz semi-analytic model. We make predictions for the performance of these surveys by comparing galaxies that are extracted from each image using Source Extractor to the input catalogue. We find that the Wide, Deep, and Ultra-Deep surveys will be 75 per cent complete for point sources down to $\sim 27$, 29, and 30 mag, respectively, in the UV, u, and g filters, with the UV-split and u-split filters reaching a shallower depth. With a large area of $\sim 2200$ deg$^2$, the Wide survey will detect hundreds of millions of galaxies out to $z\sim 4$, mostly with $M_\ast \gtrsim 10^{9}\,{\rm M}_{\odot }$. The Ultra-Deep survey will probe to $z\sim 5$, detecting galaxies with $M_\ast \gtrsim 10^{7}{\rm M}_{\odot }$. These galaxy samples will enable precision measurements of the distribution of star formation in the cosmic web, connecting the growth of stellar mass to the assembly of dark matter haloes over two thirds of the history of the Universe, and other core goals of CASTOR’s legacy surveys. These image simulations and the tools developed to generate them will be a vital planning tool to estimate CASTOR’s performance and iterate the telescope and survey designs prior to launch.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Twenty-five years of Genomes OnLine Database (GOLD): data updates and new features in v.9

We report the Genomes OnLine Database (GOLD) (https://gold.jgi.doe.gov/) at the Department of Energy Joint Genome Institute (DOE-JGI) continues to maintain its role as one of the flagship genomic metadata repositories of the world. The ever-increasing number of projects and metadata are freely available to the user community world-wide. GOLD’s metadata is consumed by scientists and remains an important source for large-scale comparative genomics analysis initiatives. Encouraged by this active user engagement and growth, GOLD has continued to add new components and capabilities. The new features such as a public Application Programming Interface (API) and Ecosystem landing page as well as the growth of different entities in this current GOLD v.9 edition are described in detail in this manuscript.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Impact of new physics on the JUNO-long-baseline synergy in the neutrino mass ordering determination

The determination of the neutrino mass ordering is one of the flagship goals in particle physics. A well-known and powerful synergy emerges when combining high-precision measurements of the effective atmospheric mass-squared splitting from electron antineutrino disappearance in reactor experiments with that from muon (anti)neutrino disappearance in accelerator-based long-baseline experiments. To fully exploit this synergy, percent-level precision in the atmospheric mass splitting is required—a target that JUNO is expected to achieve within a few months of data taking. This motivated the formulation of a mass ordering sum rule for neutrino disappearance channels, which shows that by combining data from T2K and NOvA with JUNO after one year of operation, the neutrino mass ordering can be determined at the 3⁢𝜎 confidence level. Since JUNO has recently started taking data, it is timely to ask whether this sum rule remains robust in the presence of new physics. We identify the necessary conditions for new physics to affect the sum rule and demonstrate that, in some cases, such effects could lead to an incorrect inference of the mass ordering. As concrete examples, we consider scalar nonstandard interactions (SNSI) and neutrinos coupled to an ultralight scalar field. We find that, for SNSI, current constraints render any modification of the sum rule negligible, whereas in the latter case, the inference of the ordering requires caution. Nevertheless, these effects can be disentangled, illustrating how the sum rule can also be used to search for new physics.

Alves, Gustavo F. S. [Fermi National Accelerator L↗
DOE OSTI2022

Bosonic field digitization for quantum computers

Quantum simulation of quantum field theory is a flagship application of quantum computers that promises to deliver capabilities beyond classical computing. The realization of quantum advantage will require methods that can accurately predict error scaling as a function of the resolution and parameters of the model and that can be implemented efficiently on quantum hardware. In this paper, we address the representation of lattice bosonic fields in a discretized field amplitude basis, develop methods to predict error scaling, and present efficient qubit implementation strategies. A low-energy subspace of the bosonic Hilbert space, defined by a boson occupation number cutoff, can be represented with exponentially good accuracy by a low-energy subspace of a finite-size Hilbert space. The finite representation construction and the associated errors are directly related to the accuracy of the Nyquist-Shannon sampling and the finite Fourier transforms of the boson number states in the field and the conjugate-field bases. We analyze the relation between the boson mass, the discretization parameters used for wave function sampling, and the finite representation size. Numerical simulations of small size Φ 4 problems demonstrate that the boson mass optimizing the sampling of the ground state wave function is a good approximation to the optimal boson mass yielding the minimum low-energy subspace size. However, we find that accurate sampling of general wave functions does not necessarily result in accurate representation. Finally, we develop methods for validating and adjusting the discretization parameters to achieve more accurate simulations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Ultrahigh-precision Compton polarimetry at 2 GeV

Here we report a high precision measurement of electron beam polarization using Compton polarimetry. The measurement was made in experimental Hall A at Jefferson Lab during the CREX experiment in 2020. A precision of dP/P = 0.36% was achieved detecting the back-scattered photons from the Compton scattering process. This is the highest precision in a measurement of electron beam polarization using Compton scattering ever reported, surpassing the ground-breaking measurement from the SLD Compton polarimeter. Such precision reaches the level required for the future flagship measurements to be made by the MOLLER and SoLID Experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Quantum Algorithm for High Energy Physics Simulations

Simulating quantum field theories is a flagship application of quantum computing. However, calculating experimentally relevant high energy scattering amplitudes entirely on a quantum computer is prohibitively difficult. It is well known that such high energy scattering processes can be factored into pieces that can be computed using well established perturbative techniques, and pieces which currently have to be simulated using classical Markov chain algorithms. These classical Markov chain simulation approaches work well to capture many of the salient features, but cannot capture all quantum effects. To exploit quantum resources in the most efficient way, we introduce a new paradigm for quantum algorithms in field theories. This approach uses quantum computers only for those parts of the problem which are not computable using existing techniques. In particular, we develop a polynomial time quantum final state shower that accurately models the effects of intermediate spin states similar to those present in high energy electroweak showers with a global evolution variable. The algorithm is explicitly demonstrated for a simplified quantum field theory on a quantum computer.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

SYCL for Performance Portability: Application Experience with Coupled Cluster Formalism in Quantum Chemistry on Exascale Systems

The exascale computing has brought unprecedented heterogeneity in node architectures, with systems such as Frontier and Aurora featuring diverse GPU accelerators, network connectivity among others. Ensuring performance portability across these platforms is a key challenge. To address this, we employ the SYCL programming model to develop portable, high-performance quantum chemistry workloads. As a representative application, we focus on the non-iterative Triples component of the coupled-cluster CCSD(T) method, a key driver in quantum chemistry. In this work, we report on our experience deploying SYCL-based implementations using both DPC++ and AdaptiveCPP across two flagship exascale platforms: OLCF Frontier with AMD MI250X GPUs and ALCF Aurora with Intel GPUs. Our results demonstrate that SYCL enables efficient, single-source implementations that scale to thousands of nodes, delivering performance on par with vendor-optimized HIP solutions. We highlight key insights into runtime behavior, kernel portability, and scaling characteristics, showing that SYCL offers a viable path for performance-portable computing.

Bagusetty, Abhishek [Argonne National Laboratory (↗