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To maximize the return on future planetary missions, it will be critical that rovers have the capability to analyze information onboard and select and return data that is most likely to yield valuable scientific discoveries. Additional information is contained in the original extended abstract.
The Large Area Telescope (LAT) on GLAST will make pioneering observations of gamma-ray bursts in the energy range above about 20 MeV. The primary function of the GLAST Burst Monitor (GBM) is to extend the energy range for GRB observations down to about 10 keV, allowing time-resolved spectroscopy over an energy range of six decades or more for strong bursts. The GBM will also generate alerts for strong bursts outside the LAT field-of-view, permitting re-orientation of the spacecraft so that the LAT can observe prompt or delayed high-energy emission. Burst locations will be disseminated rapidly to ground observers. The GBM will also provide data suitable for a variety of other studies, including discovery of gamma-ray transient sources, monitoring of Soft Gamma Repeaters, and observations of solar flares.
We report the discovery in archival Rossi X-Ray Timing Explorer data of a approx. 40 Hz quasi-periodic oscillation QPO) in the hard X-ray flux from the Galactic microquasar GRS 1915+105. The QPO is detected only in the hard X-ray band above approx. 13 keV and was discovered in observations in which the previously known 67 Hz QPO is present. The 40 Hz QPO has a typical rms amplitude of approx. 2% in the 13-27 keV band and a width of approx. 5.5 Hz (FWHM). We show that the 67 and 40 Hz QPOs are detected in the same observations in 1997 July and November. However, the QPO is not detected in observations from 1996 April, May, and June in which the 67 Hz QPO was first discovered. The frequency of the 67 Hz QPO is significantly higher in the 1997 observations by about 5% compared with the 1996 data. The identification of the 40 Hz QPO makes GRS 1915 + 105 the second black hole binary to show a pair of simultaneous high-frequency QPOs (the other being GRO J1655-40). The similarities between the properties of the 67 Hz QPO in GRS 1915+105 and the recently discovered 450 Hz QPO in GRO J1655-40 suggest that the pairs of frequencies in these systems may be produced by the same physical mechanism, with the frequency differences between the two being likely due to different black hole masses in the two systems. We discuss the implications of our result for the mass and spin of GRS 1915+105 as well as for models of X-ray variability in black holes and neutron stars.
These are intriguing times in the exploration of other solar-system bodies. Continuing discoveries about life on Earth and the return of data suggesting the presence of liquid water environments on or under the surfaces of other planets and moons have combined to suggest the significant possibility that extraterrestrial life may exist in this solar system. Similarly, not since the Viking missions of the mid-1970s has there been as great an appreciation for the potential for Earth life to contaminate other worlds. Current plans for the exploration of the solar system include constraints intended to prevent biological contamination from being spread by solar-system exploration missions.
Paul Hill, STS-114 Lead Shuttle Flight Director and Wayne Hale, Space Shuttle Deputy Program Director is shown during this mission status briefing. Hill talks about the first 24 hours of the Space Shuttle Discovery in orbit. He expresses that he has acquired data from the launch through imagery and hand held photographs of the external tank. Hale answers questions from the news media about how the engineers may be managing this data and if there is an overwhelming amount of data. Live downlink television pictures from the end-effectors camera on the Robotic Arm as it has completed its reberthing of the Orbiter Boom Sensor System (OBSS) are shown.
From launch on February 17 through the repositioning to final orbits that began in September 2007, the five-spacecraft of the THEMIS mission operated nominally in nearly identical 14.6 RE apogee near-equatorial orbits. On March 23, while aligned from east to west in the duskside magnetotail, the spacecraft observed two substorm sequences in fast survey mode. Timing the motion of these signatures served as an early proof of concept for the main phase of the mission: particle injection and dipolarization signatures propagated duskward from one probe to another, as did auroral intensifications seen by the dedicated array of ground-based observatories. During the summer of 2007, the spacecraft were on the dayside, where the three inner spacecraft (C, D, E) were separated by 100-500 km and the two outer probes (B, -4) by 5,000 - 10,000 km. Here the THEMIS probes repeatedly encountered the magnetopause and bow shock, dissecting flux transfer events (FTEs), determining the instantaneous width of the low-latitude boundary layer, and simultaneously observing hot flow anomalies upstream and downstream from the bow shock at the moment of their inception. From January to March 2008, the spacecraft were in the Earths magnetotail with apogees of 31.0, 19.5, 11.8 (2) and 10.0 RE corresponding to periods of 4, 2, and 1 days. Radial alignments once each four days offered an opportunity to pinpoint when and where substorms begin. This talk reviews THEMIS discoveries to date, with an emphasis on model-data comparisons of FTE characteristics
We present new ways to identify single and multiple moons around extrasolar planets using planetary transit timing variations (TTVs) and transit duration variations (TDVs). For planets with one moon, measurements from successive transits exhibit a hitherto undescribed pattern in the TTV-TDV diagram, originating from the stroboscopic sampling of the planet's orbit around the planet-moon barycenter. This pattern is fully determined and analytically predictable after three consecutive transits. The more measurements become available, the more the TTV-TDV diagram approaches an ellipse. For planets with multiple moons in orbital mean motion resonance (MMR), like the Galilean moon system, the pattern is much more complex and addressed numerically in this report. Exomoons in MMR can also form closed, predictable TTV-TDV figures, as long as the drift of the moons' pericenters is suciently slow.We find that MMR exomoons produce loops in the TTV-TDV diagram and that the number of these loops is equal to the order of the MMR, or the largest integer in the MMR ratio.We use a Bayesian model and Monte Carlo simulations to test the discoverability of exomoons using TTV-TDV diagrams with current and near-future technology. In a blind test, two of us (BP, DA) successfully retrieved a large moon from simulated TTV-TDV by co-authors MH and RH, which resembled data from a known Kepler planet candidate. Single exomoons with a 10 percent moon-to-planet mass ratio, like to Pluto-Charon binary, can be detectable in the archival data of the Kepler primary mission. Multi-exomoon systems, however, require either larger telescopes or brighter target stars. Complementary detection methods invoking a moon's own photometric transit or its orbital sampling effect can be used for validation or falsification. A combination of TESS, CHEOPS, and PLATO data would offer a compelling opportunity for an exomoon discovery around a bright star.
Metadata Quality is one of the chief drivers of discovery and use of NASA EOSDIS (Earth Observing System Data and Information System) data. Issues with metadata such as lack of completeness, inconsistency, and use of legacy terms directly hinder data use. As the central metadata repository for NASA Earth Science data, the Common Metadata Repository (CMR) has a responsibility to its users to ensure the quality of CMR search results. This poster covers how we use humanizers, a technique for dealing with the symptoms of metadata issues, as well as our plans for future metadata validation enhancements. The CMR currently indexes 35K collections and 300M granules.
Chemical evolution in molecular clouds in the interstellar medium is well established, with the identification of over 200 molecules and molecular ions. Among the classes of interstellar organic compounds found are the aldehydes. However, laboratory work on the aldehydes has scarcely kept pace with astronomical discoveries as little quantitative solid-phase infrared (IR) data has been published on any of the aldehydes, and the same is true for important properties such as density, refractive indices, and vapor pressures. In this paper we examine the IR spectra of solid propanal (HC(O)CH2CH3, propionaldehyde), along with several physical properties, for both the amorphous and crystalline forms of the compound. The quantitative measurements we report, such as infrared intensities and optical constants, will be useful in laboratory investigations of the formation and evolution of propanal-containing ices, will serve as benchmark data for theoretical investigations, and will inform observational studies.
We report on the serendipitous discovery of three transient millimeter-wave sources using data from the Atacama Cosmology Telescope. The first, detected at R.A. = 273.8138, decl. = −49.4628 at ∼50σ total, brightened from less than 5 mJy to at least 1100 mJy at 150 GHz with an unknown rise time shorter than 13 days, during which the increase from 250 mJy to 1100 mJy took only 8 minutes. Maximum flux was observed on 2019 November 8. The source's spectral index in flux between 90–150 GHz was positive, α = 1.5 ± 0.2. The second, detected at R.A. = 105.1584, decl. = −11.2434 at ∼20σ total, brightened from less than 20 mJy to at least 300 mJy at 150 GHz with an unknown rise time shorter than 8 days. Maximum flux was observed on 2019 December 15. Its spectral index was also positive, α = 1.8 ± 0.2. The third, detected at R.A. = 301.9952, decl. = 16.1652 at ∼40σ total, brightened from less than 8 mJy to at least 300 mJy at 150 GHz over a day or less but decayed over a few days. Maximum flux was observed on 2018 September 11. Its spectrum was approximately flat, with a spectral index of α = −0.2 ± 0.1. None of the sources were polarized to the limits of these measurements. The two rising-spectrum sources are coincident in position with M and K stars, while the third is coincident with a G star.
One of the most intriguing discoveries of Juno is the quasi-systematic detection of upgoing electrons above the auroral regions. Here we discuss a by-product of the most energetic component of this population: a contamination resembling bar codes in the Juno-UVS images. This pattern is likely caused by bursts of ∼10 MeV electrons penetrating the instrument. These events are mostly detected when Juno’s magnetic footprint is located poleward of the main emission relative to the magnetic pole. The signal is not periodic, but the bursts are typically 0.1–1 s apart. They are essentially detected when Juno-UVS is oriented toward Jupiter, indicating that the signal is due to upgoing electrons. The event detections occur between 1 and 7 Jovian radii above the 1-bar level, suggesting that the electron acceleration takes place close to Jupiter and is thus both strong and brief.
The Lidar In-space Technology Experiment (LITE) was a payload onboard the Space Shuttle Discovery as part of the September 1994 STS-64 mission. LITE successfully made both atmospheric and surface measurements at the 355 nm, 532 nm, and 1064 nm wavelengths [Winker et al., 1996]. At mission completion, nearly 45 Gbytes of data had been obtained. As the data were collected they were organized into three data sets. The largest of these data sets contained the single-shot full resolution digitized lidar signals for all three wavelengths. The other two data sets contained the instrument status data block (ISDB) and the quick look science data (QLSD). ISDB information was generated once per second and contained timing parameters and engineering data related to the health, status, and configuration of the instrument. The QLSD are 100shot averages of the 355 nm and 532 nm lidar signals and were generated at ten second intervals. As the LITE data were generated, they were output to low-rate and high-rate telemetry streams. The low-rate data contained the ISDB and QLSD. The lowrate data were transmitted to the ground by the Shuttle S-band system through the Tracking and Data Relay Satellite System (TDRSS). The high-rate data contained the full resolution digitized lidar signals for all three wavelengths, the ISDB, and QLSD. The high-rate data were transmitted in real time by the Ku-band system through TDRSS downlink to the LITE operations center at the Johnson Space Center (JSC). High-rate data were only obtained when the orbiter and TDRSS telemetry link coincided with the real-time operations of LITE. The low-rate data were backed up by a Shuttle recorder during periods when the telemetry link was unavailable, and the entire lowrate data stream was transferred to the ground over the course of the mission. A total of 53 hours of lowrate data and 45.5 hours of high-rate data were acquired. All of the LITE raw telemetry data have been archived at the NASA Langley Research Center (LaRC), and the LITE high-rate data have been processed to the level 1 data product. This paper describes the data processing steps required to convert the LITE raw, high-rate telemetry data to the LITE level 1 data product.
Multi-messenger astrophysics is a fast-growing, interdisciplinary field that combines data, which vary in volume and speed of data processing, from many different instruments that probe the Universe using different cosmic messengers: electromagnetic waves, cosmic rays, gravitational waves and neutrinos. In this Expert Recommendation, we review the key challenges of real-time observations of gravitational wave sources and their electromagnetic and astroparticle counterparts, and make a number of recommendations to maximize their potential for scientific discovery. These recommendations refer to the design of scalable and computationally efficient machine learning algorithms; the cyber-infrastructure to numerically simulate astrophysical sources, and to process and interpret multi-messenger astrophysics data; the management of gravitational wave detections to trigger real-time alerts for electromagnetic and astroparticle follow-ups; a vision to harness future developments of machine learning and cyber-infrastructure resources to cope with the big-data requirements; and the need to build a community of experts to realize the goals of multi-messenger astrophysics.
With the Kepler Mission, exoplanet science has entered the era of Big Data and has benefited tremendously from the availability of the NAS (NASA Advanced Supercomputing Division) Pleiades supercomputer. This presentation provides an overview of the history of exoplanet discoveries and highlights the key enabling technologies for Kepler. I provide an overview of the Kepler science pipeline and the algorithms used to analyze the data and detect transiting planets, all of which run routinely on the NAS Pleiades system. The presentation also provides a description of the Blender analysis program used to validate Kepler planet discoveries statistically, and the effort to discover exomoons lurking in Kepler data, both of which also run on Pleiades. Finally, I describe NASA's TESS (Transiting Exoplanet Survey Satellite) Mission, which leverages Kepler heritage to provide a science pipeline similar to that for Kepler and that will also run routinely on the NAS Pleiades supercomputer.
The Infrared Astronomical Satellite (IRAS) was successfully launched on January 25, 1983. This paper presents results based on analysis of early scientific data returned from IRAS. Among the early results of IRAS are the discovery of comet IRAS-Araki-Alcock, evidence for a shell of large particles around the nearby bright star Vega, detection of stars in the process of formation, and detection of many infrared bright galaxies. These early results demonstrate that the IRAS data will be a treasure chest for astronomers for years to come.
The design evolution of Space Shuttle payloads to be launched requires structural analyses and testing, based on Shuttle load environments, to ensure flight safety and mission success. The adequacy of predicted load environments is continually assessed against flight and ground measured data. The Space Shuttle program has utilized extensive flight measurements to assess payload bay environments. As part of the orbital flight test program on STS-1 through STS-5, the orbiter Columbia was equipped with a broad range of instrumentation, including accelerometers and microphone in the payload bay. The orbiter Challenger was equipped with payload bay measurement systems on six of its flights, and the orbiter Discovery was similarly instrumented beginning with STS-26. The payload bay data, along with other measurements recorded on these flights, are compared to design load requirements for payloads, and updates are made as necessary.
Artificial Intelligence (AI) is an integral part of today’s process of conducting science and technology development. At NASA, AI has become an integral and important tool for researchers, engineers, data scientists, and technologists in pursuing the ground-breaking discoveries that we are known for, including the command and controlling of our spacecraft and other supporting infrastructures. Consequently, research and engineering efforts incorporating AI have permeated almost every area of our work. It is contributing to NASA’s drive toward the future, not just of space science, but for society here at home. We are dedicated to continuing the use of AI in a safe and fully transparent approach so that the public can have high confidence in the outcomes and benefits. We believe that the plan outlined here will be responsive and contribute to the call for openness across the federal government. NASA is committed to responsible use of AI in all of its activities and in all phases of development and deployment of its space and terrestrial programs missions. NASA does not deliberately focus on “AI Research” as a separate field (we have no single “AI office” or “AI program”), rather NASA uses AI to build tools for its programs. This plan, being put forward, adheres to the Responsible AI (RAI) principles set and laid down by the White House in its Presidential Executive Order 13960. Our research, engineering and technical communities have been made aware of these guidelines and we are committed to an on-going process of educating and monitoring its implementation to ensure adherence to those principles. The vast majority of NASA’s use cases, which number almost 75 today, are geared toward analyzing the petabytes of data that NASA collects from its fleet of spacecraft across all disciplines, in human space exploration, and in aeronautics, etc.
Geospatial Catalogue Web Service is a vital service for sharing and interoperating volumes of distributed heterogeneous geospatial resources, such as data, services, applications, and their replicas over the web. Based on the Grid technology and the Open Geospatial Consortium (0GC) s Catalogue Service - Web Information Model, this paper proposes a new information model for Geospatial Catalogue Web Service, named as GCWS which can securely provides Grid-based publishing, managing and querying geospatial data and services, and the transparent access to the replica data and related services under the Grid environment. This information model integrates the information model of the Grid Replica Location Service (RLS)/Monitoring & Discovery Service (MDS) with the information model of OGC Catalogue Service (CSW), and refers to the geospatial data metadata standards from IS0 19115, FGDC and NASA EOS Core System and service metadata standards from IS0 191 19 to extend itself for expressing geospatial resources. Using GCWS, any valid geospatial user, who belongs to an authorized Virtual Organization (VO), can securely publish and manage geospatial resources, especially query on-demand data in the virtual community and get back it through the data-related services which provide functions such as subsetting, reformatting, reprojection etc. This work facilitates the geospatial resources sharing and interoperating under the Grid environment, and implements geospatial resources Grid enabled and Grid technologies geospatial enabled. It 2!so makes researcher to focus on science, 2nd not cn issues with computing ability, data locztic~, processir,g and management. GCWS also is a key component for workflow-based virtual geospatial data producing.