279 research outputs found

    Lessons learned from the introduction of autonomous monitoring to the EUVE science operations center

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    The University of California at Berkeley's (UCB) Center for Extreme Ultraviolet Astrophysics (CEA), in conjunction with NASA's Ames Research Center (ARC), has implemented an autonomous monitoring system in the Extreme Ultraviolet Explorer (EUVE) science operations center (ESOC). The implementation was driven by a need to reduce operations costs and has allowed the ESOC to move from continuous, three-shift, human-tended monitoring of the science payload to a one-shift operation in which the off shifts are monitored by an autonomous anomaly detection system. This system includes Eworks, an artificial intelligence (AI) payload telemetry monitoring package based on RTworks, and Epage, an automatic paging system to notify ESOC personnel of detected anomalies. In this age of shrinking NASA budgets, the lessons learned on the EUVE project are useful to other NASA missions looking for ways to reduce their operations budgets. The process of knowledge capture, from the payload controllers for implementation in an expert system, is directly applicable to any mission considering a transition to autonomous monitoring in their control center. The collaboration with ARC demonstrates how a project with limited programming resources can expand the breadth of its goals without incurring the high cost of hiring additional, dedicated programmers. This dispersal of expertise across NASA centers allows future missions to easily access experts for collaborative efforts of their own. Even the criterion used to choose an expert system has widespread impacts on the implementation, including the completion time and the final cost. In this paper we discuss, from inception to completion, the areas where our experiences in moving from three shifts to one shift may offer insights for other NASA missions

    Software Assists in Responding to Anomalous Conditions

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    Fault Induced Document Retrieval Officer (FIDO) is a computer program that reduces the need for a large and costly team of engineers and/or technicians to monitor the state of a spacecraft and associated ground systems and respond to anomalies. FIDO includes artificial-intelligence components that imitate the reasoning of human experts with reference to a knowledge base of rules that represent failure modes and to a database of engineering documentation. These components act together to give an unskilled operator instantaneous expert assistance and access to information that can enable resolution of most anomalies, without the need for highly paid experts. FIDO provides a system state summary (a configurable engineering summary) and documentation for diagnosis of a potentially failing component that might have caused a given error message or anomaly. FIDO also enables high-level browsing of documentation by use of an interface indexed to the particular error message. The collection of available documents includes information on operations and associated procedures, engineering problem reports, documentation of components, and engineering drawings. FIDO also affords a capability for combining information on the state of ground systems with detailed, hierarchically-organized, hypertext- enabled documentation

    Verification of the Kepler Input Catalog from Asteroseismology of Solar-type Stars

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    We calculate precise stellar radii and surface gravities from the asteroseismic analysis of over 500 solar-type pulsating stars observed by the Kepler space telescope. These physical stellar properties are compared with those given in the Kepler Input Catalog (KIC), determined from ground-based multi-color photometry. For the stars in our sample, we find general agreement but we detect an average overestimation bias of 0.23 dex in the KIC determination of log (g) for stars with log (g)_KIC > 4.0 dex, and a resultant underestimation bias of up to 50% in the KIC radii estimates for stars with R_KIC < 2 R sun. Part of the difference may arise from selection bias in the asteroseismic sample; nevertheless, this result implies there may be fewer stars characterized in the KIC with R ~ 1 R sun than is suggested by the physical properties in the KIC. Furthermore, if the radius estimates are taken from the KIC for these affected stars and then used to calculate the size of transiting planets, a similar underestimation bias may be applied to the planetary radii.Comment: Published in The Astrophysical Journal Letter

    Detection of Potential Transit Signals in Sixteen Quarters of Kepler Mission Data

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    We present the results of a search for potential transit signals in four years of photometry data acquired by the Kepler Mission. The targets of the search include 111,800 stars which were observed for the entire interval and 85,522 stars which were observed for a subset of the interval. We found that 9,743 targets contained at least one signal consistent with the signature of a transiting or eclipsing object, where the criteria for detection are periodicity of the detected transits, adequate signal-to-noise ratio, and acceptance by a number of tests which reject false positive detections. When targets that had produced a signal were searched repeatedly, an additional 6,542 signals were detected on 3,223 target stars, for a total of 16,285 potential detections. Comparison of the set of detected signals with a set of known and vetted transit events in the Kepler field of view shows that the recovery rate for these signals is 96.9%. The ensemble properties of the detected signals are reviewed.Comment: Accepted by ApJ Supplemen

    Detection of Potential Transit Signals in the First Three Quarters of Kepler Mission Data

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    We present the results of a search for potential transit signals in the first three quarters of photometry data acquired by the Kepler Mission. The targets of the search include 151,722 stars which were observed over the full interval and an additional 19,132 stars which were observed for only 1 or 2 quarters. From this set of targets we find a total of 5,392 detections which meet the Kepler detection criteria: those criteria are periodicity of the signal, an acceptable signal-to-noise ratio, and a composition test which rejects spurious detections which contain non-physical combinations of events. The detected signals are dominated by events with relatively low signal-to-noise ratio and by events with relatively short periods. The distribution of estimated transit depths appears to peak in the range between 40 and 100 parts per million, with a few detections down to fewer than 10 parts per million. The detected signals are compared to a set of known transit events in the Kepler field of view which were derived by a different method using a longer data interval; the comparison shows that the current search correctly identified 88.1% of the known events. A tabulation of the detected transit signals, examples which illustrate the analysis and detection process, a discussion of future plans and open, potentially fruitful, areas of further research are included

    Planetary Candidates Observed by Kepler. VII. The First Fully Uniform Catalog Based on The Entire 48 Month Dataset (Q1-Q17 DR24)

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    We present the seventh Kepler planet candidate catalog, which is the first to be based on the entire, uniformly processed, 48 month Kepler dataset. This is the first fully automated catalog, employing robotic vetting procedures to uniformly evaluate every periodic signal detected by the Q1-Q17 Data Release 24 (DR24) Kepler pipeline. While we prioritize uniform vetting over the absolute correctness of individual objects, we find that our robotic vetting is overall comparable to, and in most cases is superior to, the human vetting procedures employed by past catalogs. This catalog is the first to utilize artificial transit injection to evaluate the performance of our vetting procedures and quantify potential biases, which are essential for accurate computation of planetary occurrence rates. With respect to the cumulative Kepler Object of Interest (KOI) catalog, we designate 1,478 new KOIs, of which 402 are dispositioned as planet candidates (PCs). Also, 237 KOIs dispositioned as false positives (FPs) in previous Kepler catalogs have their disposition changed to PC and 118 PCs have their disposition changed to FP. This brings the total number of known KOIs to 8,826 and PCs to 4,696. We compare the Q1-Q17 DR24 KOI catalog to previous KOI catalogs, as well as ancillary Kepler catalogs, finding good agreement between them. We highlight new PCs that are both potentially rocky and potentially in the habitable zone of their host stars, many of which orbit solar-type stars. This work represents significant progress in accurately determining the fraction of Earth-size planets in the habitable zone of Sun-like stars. The full catalog is publicly available at the NASA Exoplanet Archive.Comment: Accepted to the Astrophysical Journal Supplement Series. 30 pages, 9 figures, 7 tables. We make the DR24 robovetter decision code publicly available at http://github.com/JeffLCoughlin/robovetter, with input and output examples provided using the same data as contained in the full paper's table

    Planetary Candidates Observed by Kepler IV: Planet Sample From Q1-Q8 (22 Months)

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    We provide updates to the Kepler planet candidate sample based upon nearly two years of high-precision photometry (i.e., Q1-Q8). From an initial list of nearly 13,400 Threshold Crossing Events (TCEs), 480 new host stars are identified from their flux time series as consistent with hosting transiting planets. Potential transit signals are subjected to further analysis using the pixel-level data, which allows background eclipsing binaries to be identified through small image position shifts during transit. We also re-evaluate Kepler Objects of Interest (KOI) 1-1609, which were identified early in the mission, using substantially more data to test for background false positives and to find additional multiple systems. Combining the new and previous KOI samples, we provide updated parameters for 2,738 Kepler planet candidates distributed across 2,017 host stars. From the combined Kepler planet candidates, 472 are new from the Q1-Q8 data examined in this study. The new Kepler planet candidates represent ~40% of the sample with Rp~1 Rearth and represent ~40% of the low equilibrium temperature (Teq<300 K) sample. We review the known biases in the current sample of Kepler planet candidates relevant to evaluating planet population statistics with the current Kepler planet candidate sample.Comment: 12 pages, 8 figures, Accepted ApJ Supplemen

    Planetary Candidates Observed by Kepler V: Planet Sample from Q1-Q12 (36 Months)

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    The Kepler mission discovered 2842 exoplanet candidates with 2 years of data. We provide updates to the Kepler planet candidate sample based upon 3 years (Q1-Q12) of data. Through a series of tests to exclude false-positives, primarily caused by eclipsing binary stars and instrumental systematics, 855 additional planetary candidates have been discovered, bringing the total number known to 3697. We provide revised transit parameters and accompanying posterior distributions based on a Markov Chain Monte Carlo algorithm for the cumulative catalogue of Kepler Objects of Interest. There are now 130 candidates in the cumulative catalogue that receive less than twice the flux the Earth receives and more than 1100 have a radius less than 1.5 Rearth. There are now a dozen candidates meeting both criteria, roughly doubling the number of candidate Earth analogs. A majority of planetary candidates have a high probability of being bonafide planets, however, there are populations of likely false-positives. We discuss and suggest additional cuts that can be easily applied to the catalogue to produce a set of planetary candidates with good fidelity. The full catalogue is publicly available at the NASA Exoplanet Archive.Comment: Accepted for publication, ApJ

    Planetary Candidates Observed by Kepler. VIII. A Fully Automated Catalog With Measured Completeness and Reliability Based on Data Release 25

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    We present the Kepler Object of Interest (KOI) catalog of transiting exoplanets based on searching four years of Kepler time series photometry (Data Release 25, Q1-Q17). The catalog contains 8054 KOIs of which 4034 are planet candidates with periods between 0.25 and 632 days. Of these candidates, 219 are new and include two in multi-planet systems (KOI-82.06 and KOI-2926.05), and ten high-reliability, terrestrial-size, habitable zone candidates. This catalog was created using a tool called the Robovetter which automatically vets the DR25 Threshold Crossing Events (TCEs, Twicken et al. 2016). The Robovetter also vetted simulated data sets and measured how well it was able to separate TCEs caused by noise from those caused by low signal-to-noise transits. We discusses the Robovetter and the metrics it uses to sort TCEs. For orbital periods less than 100 days the Robovetter completeness (the fraction of simulated transits that are determined to be planet candidates) across all observed stars is greater than 85%. For the same period range, the catalog reliability (the fraction of candidates that are not due to instrumental or stellar noise) is greater than 98%. However, for low signal-to-noise candidates between 200 and 500 days around FGK dwarf stars, the Robovetter is 76.7% complete and the catalog is 50.5% reliable. The KOI catalog, the transit fits and all of the simulated data used to characterize this catalog are available at the NASA Exoplanet Archive.Comment: 61 pages, 23 Figures, 9 Tables, Accepted to The Astrophysical Journal Supplement Serie
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