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To harness the potential of microbiome science across the broad range of relevant disciplines, new approaches to data infrastructure and transdisciplinary collaboration are necessary. The National Microbiome Data Collaborative (NMDC) is a new initiative to support microbiome data exploration and discovery through a collaborative integrative data science ecosystem.
We report the current development status of the High Brightness X-ray Scattering for Life Sciences (or Life Science X-ray Scattering, LiX) beamline at the NSLS-II facility of Brookhaven National Laboratory. This instrument will operate in the x-ray energy range of 2.1-18 keV, provide variable beam sizes from 1 micron to ∼0.5 mm, and support user experiments in three scientific areas: (1) high-throughput solution scattering, in-line size exclusion chromatography and flow mixers-based time-resolved solution scattering of biological macro-molecules, (2) diffraction from single- and multi-layered lipid membranes, and (3) scattering-based scanning probe imaging of biological tissues. In order to satisfy the beam stability required for these experiments and to switch rapidly between different types of experiments, we have adopted a secondary source with refractive lenses for secondary focusing, a detector system consisting of three Pilatus detectors, and specialized experimental modules that can be quickly exchanged and each dedicated to a defined set of experiments. The construction of this beamline is on schedule for completion in September 2015. User experiments are expected to start in Spring 2016.
In this study, we present results from a study of the photometric redshift performance of the Dark Energy Survey (DES), using the early data from a Science Verification period of observations in late 2012 and early 2013 that provided science-quality images for almost 200 sq. deg. at the nominal depth of the survey. We assess the photometric redshift (photo-z) performance using about 15 000 galaxies with spectroscopic redshifts available from other surveys. These galaxies are used, in different configurations, as a calibration sample, and photo-z's are obtained and studied using most of the existing photo-z codes. A weighting method in a multidimensional colour–magnitude space is applied to the spectroscopic sample in order to evaluate the photo-z performance with sets that mimic the full DES photometric sample, which is on average significantly deeper than the calibration sample due to the limited depth of spectroscopic surveys. In addition, empirical photo-z methods using, for instance, artificial neural networks or random forests, yield the best performance in the tests, achieving core photo-z resolutions σ68 ~ 0.08. Moreover, the results from most of the codes, including template-fitting methods, comfortably meet the DES requirements on photo-z performance, therefore, providing an excellent precedent for future DES data sets.
We present the combination of optical data from the Science Verification phase of the Dark Energy Survey (DES) with near-infrared (NIR) data from the European Southern Observatory VISTA Hemisphere Survey (VHS). The deep optical detections from DES are used to extract fluxes and associated errors from the shallower VHS data. Joint seven-band ( grizYJK ) photometric catalogues are produced in a single 3 sq-deg dedicated camera field centred at 02h26m-04d36m where the availability of ancillary multiwavelength photometry and spectroscopy allows us to test the data quality. Dual photometry increases the number of DES galaxies with measured VHS fluxes by a factor of ~4.5 relative to a simple catalogue level matching and results in a ~1.5 mag increase in the 80 per cent completeness limit of the NIR data. Almost 70 per cent of DES sources have useful NIR flux measurements in this initial catalogue. Photometric redshifts are estimated for a subset of galaxies with spectroscopic redshifts and initial results, although currently limited by small number statistics, indicate that the VHS data can help reduce the photometric redshift scatter at both z < 0.5 and z > 1. We present example DES+VHS colour selection criteria for high-redshift luminous red galaxies (LRGs) at z ~ 0.7 as well as luminous quasars. Using spectroscopic observations in this field we show that the additional VHS fluxes enable a cleaner selection of both populations with <10 per cent contamination from galactic stars in the case of spectroscopically confirmed quasars and <0.5 per cent contamination from galactic stars in the case of spectroscopically confirmed LRGs. The combined DES+VHS data set, which will eventually cover almost 5000 sq-deg, will therefore enable a range of new science and be ideally suited for target selection for future wide-field spectroscopic surveys.
The proposed Fusion Nuclear Science Facility (FNSF) represents the first facility to enter the complex fusion nuclear regime, and its technical mission and attributes are being developed. The FNSF represents one part of the fusion energy development pathway to the first commercial power plant with other major components being the pre-FNSF research and development, research in parallel with the FNSF, pre-DEMO research and development, and the demonstration power plant (DEMO). Finally, the Fusion Energy Systems Studies group is developing the technical basis for the FNSF in order to provide a better understanding of the demands on the fusion plasma and fusion nuclear science programs.
Fundamental transformations in the basic logic of computing are few and far between. Since the invention of digital computers in the early 1940s, the logic underlying computation has remained the same, even as computing hardware evolved from vacuum tubes to silicon transistors. With the advent of quantum computation, a fundamental transformation is near. Quantum computation is based on a different type of logic: rather than being in one of the two states of a classical bit, a quantum bit or qubit can be in a superposition of two states simultaneously. Operations and measurements on these qubits obey the constraints of quantum mechanics. It is now understood that quantum computers have great power in principle to go beyond classical computers, but that not every application is well suited to implementation on quantum computers. For reasons explained in more detail in the Introduction, scientific problems in chemical and materials sciences are uniquely suited to take advantage of quantum computing in the relatively near future. Indeed, quantum computing offers the best hope to solve many of the most important and difficult problems in this field. For example, quantum materials, such as superconductors and complex magnetic materials, show novel kinds of ordered phases that are natural from the point of view of quantum mechanics but difficult to access via computation on classical computers. Quantum sensors based on solid materials are already widely used but could be greatly improved with insight from quantum computations, as could materials for information technologies. Quantum chemical dynamics is another example of a problem that is intrinsically well suited to studies on quantum computers. Applications of quantum chemical dynamics include catalysis, artificial photosynthesis, and other industrially important processes. Quantum computers exist in the laboratory and are beginning to exceed 50 qubits, which is roughly the size beyond which their behavior cannot be predicted or emulated on present-day classical supercomputers. While a quantum computer of 50 qubits is almost certainly not powerful enough to tackle the major scientific challenges in chemical and materials sciences, some of these major challenges start to become accessible with a few hundred qubits if error rates can be kept small. This roundtable was convened to ask how emerging quantum computers can be applied to major scientific problems in chemical and materials sciences, in light of Basic Energy Sciences’s leading role in these fields and the Department of Energy’s leading role in high-performance scientific computation more generally. The main outcome of the roundtable was a consensus that there are scientific problems of great importance on which emerging quantum computers have the potential for disruptive impact, and where comparable progress is unlikely to occur by other means.
The FY21 NNSA NA-22 Final Report represents the progress achieved over the past year (FY21) by the research team for Topic Area 3, Waste Management & Subsurface Science (WM3), and Topic Area 7, Radiation and Thermal Effects on Bituminous Rocks (WM7). WM3 and WM7 are part of Science Area V (Subsurface Science and Waste Management) in the NNSA-IAEC Science and Technology Working Group. The project was initiated four years ago (2017) with an MOU agreement between the U.S. National Nuclear Security Administration (NNSA) and the Israel Atomic Energy Commission (IAEC) to evaluate the feasibility of geological subsurface disposal of radioactive waste in Israel. The core WM3 and WM7 teams are comprised of scientists and engineers from Los Alamos National Laboratory, the Geologic Survey of Israel (GSI), and the Nuclear Research Center - Negev (NRCN), with a close collaboration to the teams from Sandia National Laboratory (SNL) and Lawrence Livermore Laboratory (LLNL)
The National Space Biomedical Research Institute (NSBRI) encourages open involvement by scientists and the public at large in the Institute's activities. Through its Education and Public Outreach Program, the Institute is supporting national efforts to improve Kindergarten through grade twelve (K-12) and undergraduate education and to communicate knowledge generated by space life science research to lay audiences. Three academic institution Baylor College of Medicine, Morehouse School of Medicine and Texas A&M University are designing, producing, field-testing, and disseminating a comprehensive array of programs and products to achieve this goal. The objectives of the NSBRI Education and Public Outreach program are to: promote systemic change in elementary and secondary science education; attract undergraduate students--especially those from underrepresented groups--to careers in space life sciences, engineering and technology-based fields; increase scientific literacy; and to develop public and private sector partnerships that enhance and expand NSBRI efforts to reach students and families. c 2001. Elsevier Science Ltd. All rights reserved.
Humanity is standing on the cusp of its next giant leap – an international, sustainable, and commercial return to the moon. Unlike the Apollo missions, the expectation that a permanent human presence will be established is well founded. Initially, crewed missions to the lunar surface are expected to last between 6 and 30 days and occur approximately once per year, however the robust suite of landers and orbiting assets proposed by both commercial and government entities provide an opportunity to conduct science research on the moon and in cis-lunar space, 24x7 for many years. In the 50 years since the conclusion of Apollo, NASA’s crewed space science missions have been evolving. This can be seen clearly from Skylab and the Space Shuttle’s Spacelab to the International Space Station (ISS). Presently aboard the ISS, international crews spend nearly half their time working on experiments while many payloads collect science non-stop with either very limited, or no crew interaction. Additionally, a fleet of orbiting experiments complement and validate those investigations performed on the ISS. As the number, variety, and complexity of these investigation increase, it becomes ever more necessary to integrate across the many entities involved to prevent duplication of effort, ensure complementary results, reduce cost, and create a sustainable environment to conduct groundbreaking scientific research in space. In this paper, we examine how the various elements of the Artemis program including NASA’s Lunar Gateway, Commercial Lunar Payload Services (CLPS) endeavor, the Human Landing Systems (HLS), surface habitats, rovers and many more will be operated to ensure interoperability, maximize science return, and enable success for government, commercial and private partners.
Humanity is standing on the cusp of its next giant leap – an international, sustainable, and commercial return to the moon. Unlike the Apollo missions, the expectation that a permanent human presence will be established is well founded. Initially, crewed missions to the lunar surface are expected to last between 6 and 30 days and occur approximately once per year, however the robust suite of landers and orbiting assets proposed by both commercial and government entities provide an opportunity to conduct science research on the moon and in cis-lunar space, 24x7 for many years. In the 50 years since the conclusion of Apollo, NASA’s crewed space science missions have been evolving. This can be seen clearly from Skylab and the Space Shuttle’s Spacelab to the International Space Station (ISS). Presently aboard the ISS, international crews spend nearly half their time working on experiments while many payloads collect science non-stop with either very limited, or no crew interaction. Additionally, a fleet of orbiting experiments complement and validate those investigations performed on the ISS. As the number, variety, and complexity of these investigation increase, it becomes ever more necessary to integrate across the many entities involved to prevent duplication of effort, ensure complementary results, reduce cost, and create a sustainable environment to conduct groundbreaking scientific research in space. In this paper, we examine how the various elements of the Artemis program including NASA’s Lunar Gateway, Commercial Lunar Payload Services (CLPS) endeavor, the Human Landing Systems (HLS), surface habitats, rovers and many more will be operated to ensure interoperability, maximize science return, and enable success for government, commercial and private partners.
Humans are poised to explore deep space: the realm of space beyond Earth's orbit. NASA will soon send humans back to the Moon with the Artemis program, and is developing programs to support crewed missions to Mars. Human exploration of such new environments demands fundamental research that can provide the knowledge necessary to ensure the safety of explorers and aid in the development of a sustainable presence in space. Accordingly, the Agency's Moon to Mars objectives1 include three goals in the area of Human Biological Sciences (HBS-1, -2, -3), with the aim to "Advance understanding of how biology responds to the environments of the Moon, Mars, and deep space to advance fundamental knowledge, support safe, productive human space missions and reduce risks for future exploration." Advancing this understanding is a task that is both complex-- comprising diverse organisms, processes, and methods-- and difficult-- because the very aspects of deep space that we strive to understand are the aspects that make it hard to conduct research in that environment. This report of the Beyond LEO Instrumentation & Science Series Science Working Group (BLISS-SWG) represents input from a group of scientists from diverse disciplines within the space biology research and engineering community on the nature of the science and technology that can be used to achieve those aims.
Science is increasingly motivated by the need to process larger quantities of data. It is facing severe challenges in data collection, management, and processing, so much so that the computational demands of “data scaling” are competing with, and in many fields surpassing, the traditional objective of decreasing processing time. Example domains with large datasets include astronomy, biology, genomics, climate/weather, and material sciences. This paper presents a real-world use case in which we wish to answer queries pro- vided by domain scientists in order to facilitate discovery of relevant science resources. The problem is that the metadata for these science resources is very large and is growing quickly, rapidly increasing the need for a data scaling solution. We propose a system – SGEM – designed for answering graph-based queries over large datasets on cluster architectures, and we re- port performance results for queries on the current RDESC dataset of nearly 1.4 billion triples, and on the well-known BSBM SPARQL query benchmark.
Abstract This article is composed of three independent commentaries about the state of Integrated, Coordinated, Open, Networked (ICON) principles (Goldman, et al., 2021b, https://doi.org/10.1029/2021EO153180 ) in Earth and Space Science Informatics (ESSI) and includes discussion on the opportunities and challenges of adopting them. Each commentary focuses on a different topic: (Section 2) Global collaboration, cyberinfrastructure, and data sharing; (Section 3) Machine learning for multiscale modeling; (Section 4) Aerial and satellite remote sensing for advancing Earth system model development by integrating field and ancillary data. ESSI addresses data management practices, computation and analysis, and hardware and software infrastructure. Our role in ICON science therefore involves collaborative work to assess, design, implement, and promote practices and tools that enable effective data management, discovery, integration, and reuse for interdisciplinary work in Earth and space science disciplines. Networks of diverse people with expertise across Earth, space, and data science disciplines are essential for efficient and ethical exchanges of findable, accessible, interoperable, and reusable (FAIR) research products and practices. Our challenge is then to coordinate the development of standards, curation practices, and tools that enable integrating and reusing multiple data types, software, multi‐scale models, and machine learning approaches across disciplines in a way that is as open and/or FAIR as ethically possible. This is a major endeavor that could greatly increase the pace and potential of interdisciplinary scientific discovery.
The Fusion Nuclear Science Facility (FNSF) is a nuclear confinement facility that provides a fusion environment with components of the reactor integrated together to bridge the technical gaps of burning plasma and nuclear science between the International Thermonuclear Experimental Reactor (ITER) and the demonstration power plant (DEMO). Compared with ITER, the FNSF is smaller in size but generates much higher magnetic field, i.e., 30 times higher neutron fluence with three orders of magnitude longer plasma operation at higher operating temperatures for structures surrounding the plasma. Input parameters to the magnet design from system code analysis include magnetic field of 7.5 T at the plasma center with a plasma major radius of 4.8 m and a minor radius of 1.2 m and a peak field of 15.5 T on the toroidal field (TF) coils for the FNSF. Both low-temperature superconductors (LTS) and high-temperature superconductors (HTS) are considered for the FNSF magnet design based on the state-of-the-art fusion magnet technology. The higher magnetic field can be achieved by using the high-performance ternary restacked-rod process Nb3Sn strands for TF magnets. The circular cable-in-conduit conductor (CICC) design similar to ITER magnets and a high-aspect-ratio rectangular CICC design are evaluated for FNSF magnets, but low-activation-jacket materials may need to be selected. The conductor design concept and TF coil winding pack composition and dimension based on the horizontal maintenance schemes are discussed. Neutron radiation limits for the LTS and HTS superconductors and electrical insulation materials are also reviewed based on the available materials previously tested. The material radiation limits for FNSF magnets are defined as part of the conceptual design studies for FNSF magnets.
Cameras built for space exploration are required to meet stringent environmental conditions, such as thermal and dynamic loads for both the optics (camera lens) and imaging electronics. On a multitude of spaceborne imaging instruments, optical elements are supported in their mounts via an elastomeric bonding approach using a room temperature vulcanizing silicone as the bonding agent. Employing this integration method, we achieved element-to-element alignment, measured as the total indicated runout, using a high-precision contact probe to be on the order of half a wavelength of He-Ne laser light, or 0.3 {mu}m, on the Malin Space Science Systems lenses for the Mars Science Laboratory (MSL) cameras. This is a higher precision than the current industry state-of-the-art, and it was achieved for the very challenging small diameter lens elements. This paper describes the design philosophy, implementation, and integration method that resulted in achieving this level of precision for interelement alignment. The results are based on actual measurements that were made during the process of building the MSL rover's science camera lenses, namely Mastcams, the Mars Hand Lens Imager, and the Mars Descent Imager. The optical designs of these cameras lenses are described in detail in [Opt. Eng.48, 103002 (2009)10.1117/1.3251343], while further information on the four science cameras can be found at http://www.msss.com.
Under this SciDAC-2 grant the project’s goal w a s t o stimulate new discoveries by providing scientists with effective and dependable access to an unprecedented national distributed computational facility: the Open Science Grid (OSG). We proposed to achieve this through the work of the Open Science Grid Consortium: a unique hands-on multi-disciplinary collaboration of scientists, software developers and providers of computing resources. Together the stakeholders in this consortium sustain and use a shared distributed computing environment that transforms simulation and experimental science in the US. The OSG consortium is an open collaboration that actively engages new research communities. We operate an open facility that brings together a broad spectrum of compute, storage, and networking resources and interfaces to other cyberinfrastructures, including the US XSEDE (previously TeraGrid), the European Grids for ESciencE (EGEE), as well as campus and regional grids. We leverage middleware provided by computer science groups, facility IT support organizations, and computing programs of application communities for the benefit of consortium members and the US national CI.
The 2018 Basic Research Needs Workshop on Extreme Heterogeneity identified five Priority Research Directions for realizing the capabilities needed to address the challenges posed in this era of rapid technological change. This report captures the outcomes of that workshop. In the context of extreme heterogeneity, it defines basic research needs and opportunities in computer science research to develop smart and trainable operating and runtime systems, programming environments, and predictive tools that will make future systems easier to adapt to scientists’ computing needs and easier for facilities to deploy securely.