Piezochromism in the magnetic chalcogenide MnPS3
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99 GENERAL AND MISCELLANEOUS↗
SEARCH · Engineering Papers
Results for “accelerated discovery”
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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SCExAO/MEC and CHARIS Discovery of a Low-mass, 6 au Separation Companion to HIP 109427 Using Stochastic Speckle Discrimination and High-contrast Spectroscopy
We report the direct imaging discovery of a low-mass companion to the nearby accelerating A star, HIP 109427, with the Subaru Coronagraphic Extreme Adaptive Optics (SCExAO) instrument coupled with the Microwave Kinetic Inductance Detector Exoplanet Camera (MEC) and CHARIS integral field spectrograph. CHARIS data reduced with reference star point spread function (PSF) subtraction yield 1.1–2.4 μm spectra. MEC reveals the companion in Y and J band at a comparable signal-to-noise ratio using stochastic speckle discrimination, with no PSF subtraction techniques. Combined with complementary follow-up L {sub p} photometry from Keck/NIRC2, the SCExAO data favors a spectral type, effective temperature, and luminosity of M4–M5.5, 3000–3200 K, and log{sub 10}(L/L{sub ⊙})=−2.28{sub −0.04}{sup +0.04}, respectively. Relative astrometry of HIP 109427 B from SCExAO/CHARIS and Keck/NIRC2, and complementary Gaia–Hipparcos absolute astrometry of the primary favor a semimajor axis of 6.55{sup +3.0} {sub −0.48} au, an eccentricity of 0.54{sub −0.15}{sup +0.28}, an inclination of 66.7{sub −14}{sup +8.5} degrees, and a dynamical mass of 0.280{sub −0.059}{sup +0.18} M {sub ⊙}. This work shows the potential for extreme AO systems to utilize speckle statistics in addition to widely used postprocessing methods to directly image faint companions to nearby stars near the telescope diffraction limit.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Online Analysis Enhances Use of NASA Earth Science Data
Giovanni, the Goddard Earth Sciences Data and Information Services Center (GES DISC) Interactive Online Visualization and Analysis Infrastructure, has provided researchers with advanced capabilities to perform data exploration and analysis with observational data from NASA Earth observation satellites. In the past 5-10 years, examining geophysical events and processes with remote-sensing data required a multistep process of data discovery, data acquisition, data management, and ultimately data analysis. Giovanni accelerates this process by enabling basic visualization and analysis directly on the World Wide Web. In the last two years, Giovanni has added new data acquisition functions and expanded analysis options to increase its usefulness to the Earth science research community.
Acker, James G.↗
Methods to accelerate high-throughput screening of atomic qubit candidates in van der Waals materials
The discovery of atom-like spin emitters associated with defects in two-dimensional (2D) wide-bandgap (WBG) semiconductors presents new opportunities for highly tunable and versatile qubits. So far, the study of such spin emitters has focused on defects in hexagonal boron nitride (hBN). However, hBN necessarily contains a high density of nuclear spins, which are expected to create a strong incoherent spin-bath that leads to poor coherence properties of spins hosted in the material. Therefore, identification of new qubit candidates in other 2DWBG materials is necessary. Given the time demands of ab initio methods, new approaches for rapid screening and calculations of identifying properties of suitable atom-like qubits are required. In this work, we present two new methods for rapid estimation of the zero-phonon line (ZPL), a key property of atomic qubits in WBG materials. First, the ZPL is calculated by exploiting Janak’s theorem. For finite changes in occupation, we provide the leading-order estimate of the correction to the ZPL obtained using Janak’s theorem, which is more rapid than the standard method (ΔSCF). Next, we demonstrate an approach to converging excited states that is faster for systems with small strain than the standard approach used in the ΔSCF method. We illustrate these methods using the case of the singly negatively charged calcium vacancy in SiS2, which we are the first to propose as a qubit candidate. This work has the potential to assist in accelerating the high-throughput search for quantum defects in materials, with applications in quantum sensing and quantum computing.
Kuate Defo, Rodrick (ORCID:0000000242788196)↗
Neutrino Analysis of the September 2010 Crab Nebula Flare and Time-Integrated Constraints on Neutrino Emission from the Crab Using IceCube
We present the results for a search of high-energy muon neutrinos with the IceCube detector in coincidence with the Crab nebula flare reported on September 2010 by various experiments. Due to the unusual flaring state of the otherwise steady source we performed a prompt analysis of the 79-string configuration data to search for neutrinos that might be emitted along with the observed gamma-rays. We performed two different and complementary data selections of neutrino events in the time window of 10 days around the flare. One event selection is optimized for discovery of E(sub v)(sup -2) neutrino spectrum typical of 1st order Fermi acceleration. A similar event selection has also been applied to the 40-string data to derive the time-integrated limits to the neutrino emission from the Crab [35]. The other event selection was optimized for discovery of neutrino spectra with softer spectral index and TeV energy cut-offs as observed for various galactic sources in gamma-rays. The 90% CL best upper limits on the Crab flux during the 10 day flare are 4.73 x 10(exp -11) per square centimeter per second TeV(sup -1) for an E(sub v)(sup -2) neutrino spectrum and 2.50 x 10(exp -10) per square centimeter per second TeV(sup -1) for a softer neutrino spectra of E(sub v)(sup -2.7), as indicated by Fermi measurements during the flare. IceCube has also set a time-integrated limit on the neutrino emission of the Crab using 375.5 days of livetime of the 40-string configuration data. This limit is compared to existing models of neutrino production from the Crab and its impact on astrophysical parameters is discussed. The most optimistic predictions of some models are already rejected by the IceCube neutrino telescope with more than 90% CL.
Abbasi, R.↗
Neutrino Analysis of the September 2010 Crab Nebula Flare and Time-integrated Constraints on Neutrino Emission From the Crab Using IceCube
We present the results for a search of high-energy muon neutrinos with the IceCube detector in coincidence with the Crab nebula flare reported on September 2010 by various experiments. Due to the unusual flaring state of the otherwise steady source we performed a prompt analysis of the 79-string configuration data to search for neutrinos that might be emitted along with the observed gamma-rays. We performed two different and complementary data selections of neutrino events in the time window of 10 days around the flare. One event selection is optimized for discovery of E(sub nu)(sup -2) neutrino spectrum typical of 1st order Fermi acceleration. A similar event selection has also been applied to the 40-string data to derive the time-integrated limits to the neutrino emission from the Crab [35]. The other event selection was optimized for discovery of neutrino spectra with softer spectral index and TeV energy cut-offs as observed for various galactic sources in gamma-rays. The 90% CL best upper limits on the Crab flux during the 10 day flare are 4.73 x 10(exp -11) per square centimeter per second TeV (sup -1) for an E(sub nu) (sup -2) neutrino spectrum and 2.50 x 10(exp -10) per square centimeter per second TeV(sup -1) for a softer neutrino spectra of E(sub nu)(sup -2.7), as indicated by Fermi measurements during the flare. IceCube has also set a time-integrated limit on the neutrino emission of the Crab using 375.5 days of livetime of the 40-string configuration data. This limit is compared to existing models of neutrino production from the Crab and its impact on astrophysical parameters is discussed. The most optimistic predictions of some models are already rejected by the IceCube neutrino telescope with more than 90% CL.
Stamatikos, M.↗
Advanced Computing Annual Report 2024
In fiscal year (FY) 2024, the National Renewable Energy Laboratory (NREL) took a major leap forward with the completed full buildout of Kestrel, the Office of Energy Efficiency and Renewable Energy's newest high-performance computing (HPC) system. Kestrel is already supporting science across the portfolio, bringing roughly 44 petaflops of computing power, which is more than five times the capacity of our previous supercomputer, Eagle. By delivering greater GPU capacity, Kestrel enables faster progress in artificial intelligence (AI) and opens new avenues in energy research - from defining long-term planning scenarios to accommodate a growing power system to material discovery to improving energy efficiency in photovoltaics (PV). Across the portfolio, research is being accelerated by Kestrel's impressive power. During FY24, 427 projects and more than 700 researchers used NREL's HPC, supporting the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy across 13 funding areas. Through these collaborations, researchers produced more than 450 technical outputs, including 195 articles in peer-reviewed publications, pushing the boundaries of science and engineering. This year's report features new sections spotlighting the expanding roles of Artificial Intelligence and Accelerated Computing. We also introduce an early career section to celebrate the accomplishments of our up-and-coming researchers, whose pioneering work is shaping the future of energy. We hope you enjoy the new insights and discoveries highlighted in these pages.
97 MATHEMATICS AND COMPUTING↗
X-ray free electron laser linear accelerator without a laser heater
Linear accelerator based X-ray free electron laser (FEL) light sources provide an important tool for scientific discoveries. Most of these light source facilities employ a laser heater to increase the electron beam’s uncorrelated energy spread to suppress microbunching instability through the linear accelerators. In this paper, we first studied the microbunching instability in an X-ray FEL linear accelerator with lower initial peak current (~ 10 A) and moderate final peak currents (1-2 kA). In this regime, the microbunching instability can be substantially mitigated with modest initial uncorrelated energy spread. Here, we then suggested a less expensive method to mitigate the microbunching instability using a section of low beta FODO lattice instead of the laser heater. With the use of the high brightness electron beam from a photoinjector, the intrabeam scattering effect inside the beam through the FODO lattice can generate sufficient uncorrelated energy spread to mitigate the microbunching instability. At last, we demonstrated the feasibility of this method with self-consistent solution of the Fokker–Planck equation through the X-ray FEL linear accelerator.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Permutationally Invariant Networks for Enhanced Sampling (PINES): Discovery of Multimolecular and Solvent-Inclusive Collective Variables
The typically rugged nature of molecular free energy landscapes can frustrate efficient sampling of the thermodynamically relevant phase space due to the presence of high free energy barriers. Enhanced sampling techniques can improve phase space exploration by accelerating sampling along particular collective variables (CVs). A number of techniques exist for data-driven discovery of CVs parameterizing the important large scale motions of the system. A challenge to CV discovery is learning CVs invariant to symmetries of the molecular system, frequently rigid translation, rigid rotation, and permutational relabeling of identical particles. Of these, permutational invariance has proved a persistent challenge in frustrating the data-driven discovery of multi-molecular CVs in systems of self-assembling particles and solvent-inclusive CVs for solvated systems. In this work, we integrate Permutation Invariant Vector (PIV) featurizations with autoencoding neural networks to learn nonlinear CVs invariant to translation, rotation, and permutation, and perform interleaved rounds of CV discovery and enhanced sampling to iteratively expand sampling of configurational phase space and obtain converged CVs and free energy landscapes. Here, we demonstrate the Permutationally Invariant Network for Enhanced Sampling (PINES) approach in applications to the self-assembly of a 13-atom Argon cluster, association/dissociation of a NaCl ion pair in water, and hydrophobic collapse of a C 45 H 92 n-pentatetracontane polymer chain. We make the approach freely available as a new module within the PLUMED2 enhanced sampling libraries.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
The Science Discovery Engine: An Open Science Success Story
NASA is committed to building an inclusive open science community over the next decade and is championing the new Open-Source Science Initiative (OSSI) to foster that community. The OSSI is made up of a number of activities including the development of an empowering cyberinfrastructure to accelerate the time to actionable science. One component of the OSSI cyberinfrastructure is the Science Discovery Engine (SDE). The goal of the SDE is to enable the discovery of data, software and documentation across the five SMD divisions including Astrophysics, Biological and Physical Sciences, Earth Science, Heliophysics and Planetary Science. The SDE increases accessibility to the wealth of NASA’s open science data and information. In this presentation, we will present our collaborative work to date to build the SDE and our vision for empowering open source science in the future.
Kaylin Bugbee↗
Accelerating Biological Insight for Understudied Genes
Synopsis The rapid expansion of genome sequence data is increasing the discovery of protein-coding genes across all domains of life. Annotating these genes with reliable functional information is necessary to understand evolution, to define the full biochemical space accessed by nature, and to identify target genes for biotechnology improvements. The majority of proteins are annotated based on sequence conservation with no specific biological, biochemical, genetic, or cellular function identified. Recent technical advances throughout the biological sciences enable experimental research on these understudied protein-coding genes in a broader collection of species. However, scientists have incentives and biases to continue focusing on well documented genes within their preferred model organism. This perspective suggests a research model that seeks to break historic silos of research bias by enabling interdisciplinary teams to accelerate biological functional annotation. We propose an initiative to develop coordinated projects of collaborating evolutionary biologists, cell biologists, geneticists, and biochemists that will focus on subsets of target genes in multiple model organisms. Concurrent analysis in multiple organisms takes advantage of evolutionary divergence and selection, which causes individual species to be better suited as experimental models for specific genes. Most importantly, multisystem approaches would encourage transdisciplinary critical thinking and hypothesis testing that is inherently slow in current biological research.
Zoology↗
Optimizing FPGA-based Accelerator Design for Large-Scale Molecular Similarity Search (Special Session Paper)
Molecular similarity search has been widely used in drug discovery to rapidly identify structurally similar compounds from large molecular databases. With the increasing size of chemical libraries, there is growing interest in the efficient ac- celeration of large-scale similarity search. Existing works mainly focus on CPU and GPU to accelerate the computation of Tatimoto coefficient in measuring the pairwise similarity between different molecular fingerprints. In this paper, we propose and optimize an FPGA-based accelerator design on exhaustive and approximate search algorithms. On exhaustive search using BitBound & fold- ing, we analyze the similarity cutoff and folding level relationship with search speedup and accuracy, and propose a scalable on- the-fly query engine on FPGAs to reduce the resource utilization and pipeline interval. We achieve a 450 million compounds-per- second processing throughput for a single query engine. On approximate search using hierarchical navigable small world (HNSW), a popular algorithm with high recall and query speed, we propose an FPGA-based graph traversal engine to utilize high throughput register array based priority queue and fine- grained distance calculation engine to increase the processing capability. Experimental results show that the proposed FPGA- based HNSW implementation achieves a 35× speedup than existing works on CPU. To the best of our knowledge, our FPGA- based implementation is the first attempt to accelerate molecular similarity search on FPGA and has the highest performance among existing approaches.
Peng, Hongwu↗
Transferring a Molecular Foundation Model for Polymer Property Predictions
Transformer-based large language models have remarkable potential to accelerate design optimization for applications such as drug development and material discovery. Self-supervised pretraining of transformer models requires large-scale data sets, which are often sparsely populated in topical areas such as polymer science. Further, state-of-the-art approaches for polymers conduct data augmentation to generate additional samples but unavoidably incur extra computational costs. In contrast, large-scale open-source data sets are available for small molecules and provide a potential solution to data scarcity through transfer learning. In this work, we show that using transformers pretrained on small molecules and fine-tuned on polymer properties achieves comparable accuracy to those trained on augmented polymer data sets for a series of benchmark prediction tasks.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
How lipidomics can transform our understanding of virus infections
Traditionally, lipids have been thought of as molecules that provide structure and energy, but their functional relevance in disease mechanisms is increasingly clear, and with advancements in mass spectrometry technologies, lipidomics analyses is a tool gaining recognition. Beyond the utility of lipoprotein and fatty acid profiles in clinical diagnosis and chemotaxonomic identifications, respectively, lipidomics analysis that combines knowledge across disciplines and can resolve exact lipid structures has the potential to advance clinical diagnoses and associated treatment, differentiate pathogen types (e.g., virus vs. bacterial vs. fungal), detect natural vs lab-grown viruses, and perhaps distinguish a pathogen from a benign biological agent (i.e., threat potential). As new viruses emerge and localized outbreaks expand, lipidomics will accelerate our understanding of viral infections and aid in maximizing the discovery of novel biomarkers of pathogenicity and host response.
59 BASIC BIOLOGICAL SCIENCES↗
Reviving MeV-GeV indirect detection with inelastic dark matter
Thermal relic dark matter below ∼ 10 GeV is excluded by cosmic microwave background data if its annihilation to visible particles is unsuppressed near the epoch of recombination. Usual model-building measures to avoid this bound involve kinematically suppressing the annihilation rate in the low-velocity limit, thereby yielding dim prospects for indirect detection signatures at late times. In this work, we investigate a class of cosmologically viable sub-GeV thermal relics with late-time annihilation rates that are detectable with existing and proposed telescopes across a wide range of parameter space. We study a representative model of inelastic dark matter featuring a stable state χ 1 and a slightly heavier excited state χ 2 whose abundance is thermally depleted before recombination. Since the kinetic energy of dark matter in the Milky Way is much larger than it is during recombination, χ 1 χ 1 → χ 2 χ 2 upscattering can efficiently regenerate a cosmologically long-lived Galactic population of χ 2 , whose subsequent coannihilations with χ 1 give rise to observable gamma-rays in the ∼ 1 MeV − 100 MeV energy range. We find that proposed MeV gamma-ray telescopes, such as e-ASTROGAM, AMEGO, and MAST, would be sensitive to much of the thermal relic parameter space in this class of models and thereby enable both discovery and model discrimination in the event of a signal at accelerator or direct detection experiments. Published by the American Physical Society 2024
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Modern and Future Colliders
Since the initial development of charged particle colliders in the middle of the 20th century, these advanced scientific instruments have been at the forefront of scientific discoveries in high energy physics over the past 60 years. Collider accelerator technology and beam physics have progressed immensely and modern facilities now operate at energies and luminosities many orders of magnitude greater than the pioneering colliders of the early 1960s. In addition, the field of colliders remains extremely dynamic and continues to develop many innovative approaches. Indeed, several novel concepts are currently being considered for designing and constructing even more powerful future colliders. In this paper, we first review the colliding beam method and the history of colliders, and then present, in detail, the major achievements of operational machines and the key features of near-term collider projects that are currently under development. We conclude with an analysis of numerous proposals and studies for far-future colliders. The evaluation of their respective potentials reveals tantalizing prospects for further significant breakthroughs in the collider field.
43 PARTICLE ACCELERATORS↗
DDCP framework
DDCP protocol software 1.0 This repository contains the C++ implementation of version 1.x of the Distributed Data Communications Protocol (DDCP). DDCP provides request/reply, feature discovery, data transfer, control, interrupt, and transaction support for communicating with accelerator instrumentation over UDP. The standard server port is 65000. The framework is a source dependency for services that communicate directly with DDCP hardware. It is not a deployable service by itself.
Joshi, Shreya [Fermi National Accelerator Laborato↗
AI-enhanced Codesign for Next-Generation Neuromorphic Circuits and Systems
This report details work that was completed to address the Fiscal Year 2022 Advanced Science and Technology (AS&T) Laboratory Directed Research and Development (LDRD) call for “AI-enhanced Co-Design of Next Generation Microelectronics.” This project required concurrent contributions from the fields of 1) materials science, 2) devices and circuits, 3) physics of computing, and 4) algorithms and system architectures. During this project, we developed AI-enhanced circuit design methods that relied on reinforcement learning and evolutionary algorithms. The AI-enhanced design methods were tested on neuromorphic circuit design problems that have real-world applications related to Sandia’s mission needs. The developed methods enable the design of circuits, including circuits that are built from emerging devices, and they were also extended to enable novel device discovery. We expect that these AI-enhanced design methods will accelerate progress towards developing next-generation, high-performance neuromorphic computing systems.
42 ENGINEERING↗