43 research outputs found

    The Gravity Probe B Experiment

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    This presentation briefly describes the Gravity Probe B (GP-B) Experiment which is designed to measure parts of Einstein's general theory of relativity by monitoring gyroscope orientation relative to a distant guide star. To measure the miniscule angles predicted by Einstein's theory, it was necessary to build near-perfect gyroscopes that were approximately 50 million times more precise than the best navigational gyroscopes. A telescope mounted along the central axis of the dewar and spacecraft provided the experiment's pointing reference to a guide star. The telescope's image divide precisely split the star's beam into x-axis and y-axis components whose brightness could be compared. GP-B's 650-gallon dewar, kept the science instrument inside the probe at a cryogenic temperature for 17.3 months and also provided the thruster propellant for precision attitude and translation control. Built around the dewar, the GP-B spacecraft was a total-integrated system, comprising both the space vehicle and payload, dedicated as a single entity to experimentally testing predictions of Einstein's theory

    Kepler Presearch Data Conditioning II - A Bayesian Approach to Systematic Error Correction

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    With the unprecedented photometric precision of the Kepler Spacecraft, significant systematic and stochastic errors on transit signal levels are observable in the Kepler photometric data. These errors, which include discontinuities, outliers, systematic trends and other instrumental signatures, obscure astrophysical signals. The Presearch Data Conditioning (PDC) module of the Kepler data analysis pipeline tries to remove these errors while preserving planet transits and other astrophysically interesting signals. The completely new noise and stellar variability regime observed in Kepler data poses a significant problem to standard cotrending methods such as SYSREM and TFA. Variable stars are often of particular astrophysical interest so the preservation of their signals is of significant importance to the astrophysical community. We present a Bayesian Maximum A Posteriori (MAP) approach where a subset of highly correlated and quiet stars is used to generate a cotrending basis vector set which is in turn used to establish a range of "reasonable" robust fit parameters. These robust fit parameters are then used to generate a Bayesian Prior and a Bayesian Posterior Probability Distribution Function (PDF) which when maximized finds the best fit that simultaneously removes systematic effects while reducing the signal distortion and noise injection which commonly afflicts simple least-squares (LS) fitting. A numerical and empirical approach is taken where the Bayesian Prior PDFs are generated from fits to the light curve distributions themselves.Comment: 43 pages, 21 figures, Submitted for publication in PASP. Also see companion paper "Kepler Presearch Data Conditioning I - Architecture and Algorithms for Error Correction in Kepler Light Curves" by Martin C. Stumpe, et a

    Kepler Mission Stellar and Instrument Noise Properties

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    Kepler Mission results are rapidly contributing to fundamentally new discoveries in both the exoplanet and asteroseismology fields. The data returned from Kepler are unique in terms of the number of stars observed, precision of photometry for time series observations, and the temporal extent of high duty cycle observations. As the first mission to provide extensive time series measurements on thousands of stars over months to years at a level hitherto possible only for the Sun, the results from Kepler will vastly increase our knowledge of stellar variability for quiet solar-type stars. Here we report on the stellar noise inferred on the timescale of a few hours of most interest for detection of exoplanets via transits. By design the data from moderately bright Kepler stars are expected to have roughly comparable levels of noise intrinsic to the stars and arising from a combination of fundamental limitations such as Poisson statistics and any instrument noise. The noise levels attained by Kepler on-orbit exceed by some 50% the target levels for solar-type, quiet stars. We provide a decomposition of observed noise for an ensemble of 12th magnitude stars arising from fundamental terms (Poisson and readout noise), added noise due to the instrument and that intrinsic to the stars. The largest factor in the modestly higher than anticipated noise follows from intrinsic stellar noise. We show that using stellar parameters from galactic stellar synthesis models, and projections to stellar rotation, activity and hence noise levels reproduces the primary intrinsic stellar noise features.Comment: Accepted by ApJ; 26 pages, 20 figure

    Flagging and Correction of Pattern Noise in the Kepler Focal Plane Array

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    In order for Kepler to achieve its required less than 20 PPM photometric precision for magnitude 12 and brighter stars, instrument-induced variations in the CCD readout bias pattern (our "2D black image"), which are either fixed or slowly varying in time, must be identified and the corresponding pixels either corrected or removed from further data processing. The two principle sources of these readout bias variations are crosstalk between the 84 science CCDs and the 4 fine guidance sensor (FGS) CCDs and a high frequency amplifier oscillation on less than 40% of the CCD readout channels. The crosstalk produces a synchronous pattern in the 2D black image with time-variation observed in less than 10% of individual pixel bias histories. We will describe a method of removing the crosstalk signal using continuously-collected data from masked and over-clocked image regions (our "collateral data"), and occasionally-collected full-frame images and reverse-clocked readout signals. We use this same set to detect regions affected by the oscillating amplifiers. The oscillations manifest as time-varying moir pattern and rolling bands in the affected channels. Because this effect reduces the performance in only a small fraction of the array at any given time, we have developed an approach for flagging suspect data. The flags will provide the necessary means to resolve any potential ambiguity between instrument-induced variations and real photometric variations in a target time series. We will also evaluate the effectiveness of these techniques using flight data from background and selected target pixels

    IXPE Mirror Module Assemblies

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    Expected to launch in 2021 Spring, the Imaging X-ray Polarimetry Explorer (IXPE) is a NASA Astrophysics Small Explorer Mission with significant contributions from the Italian space agency (ASI). The IXPE observatory features three identical x-ray telescopes, each comprised of a 4-m-focal-length mirror module assembly (MMA, provided by NASA Marshall Space Flight Center) that focuses x rays onto a polarization-sensitive, imaging detector (contributed by ASI-funded institutions). This paper summarizes the MMAs design, fabrication, alignment and assembly, expected performance, and calibration plans

    Kepler Presearch Data Conditioning I - Architecture and Algorithms for Error Correction in Kepler Light Curves

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    Kepler provides light curves of 156,000 stars with unprecedented precision. However, the raw data as they come from the spacecraft contain significant systematic and stochastic errors. These errors, which include discontinuities, systematic trends, and outliers, obscure the astrophysical signals in the light curves. To correct these errors is the task of the Presearch Data Conditioning (PDC) module of the Kepler data analysis pipeline. The original version of PDC in Kepler did not meet the extremely high performance requirements for the detection of miniscule planet transits or highly accurate analysis of stellar activity and rotation. One particular deficiency was that astrophysical features were often removed as a side-effect to removal of errors. In this paper we introduce the completely new and significantly improved version of PDC which was implemented in Kepler SOC 8.0. This new PDC version, which utilizes a Bayesian approach for removal of systematics, reliably corrects errors in the light curves while at the same time preserving planet transits and other astrophysically interesting signals. We describe the architecture and the algorithms of this new PDC module, show typical errors encountered in Kepler data, and illustrate the corrections using real light curve examples.Comment: Submitted to PASP. Also see companion paper "Kepler Presearch Data Conditioning II - A Bayesian Approach to Systematic Error Correction" by Jeff C. Smith et a

    Direct Polishing of Full-Shell, High-Resolution X-Ray Optics

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    Future x-ray telescopes will likely require lightweight mirrors to attain the large collecting areas needed to accomplish the science objectives. Understanding and demonstrating processes now is critical to achieving sub-arcsecond performance in the future. Consequently, designs not only of the mirrors but of fixtures for supporting them during fabrication, metrology, handling, assembly, and testing must be adequately modeled and verified. To this end, MSFC is using finite-element modeling to study the effects of mounting on thin, full-shell grazing-incidence mirrors, during all processes leading to a flight

    The Imaging X-ray Polarimetry Explorer (IXPE)

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    The Imaging X-ray Polarimetry Explorer (IXPE) expands observation space by simultaneously adding polarization measurements to the array of source properties currently measured (energy, time, and location). IXPE will thus open new dimensions for understanding how X-ray emission is produced in astrophysical objects, especially systems under extreme physical conditions - such as neutron stars and black holes. Polarization singularly probes physical anisotropies - ordered magnetic fields, aspheric matter distributions, or general relativistic coupling to black-hole spin - that are not otherwise measurable. Hence, IXPE complements all other investigations in high-energy astrophysics by adding important and relatively unexplored information to the parameter space for studying cosmic X-ray sources and processes, as well as for using extreme astrophysical environments as laboratories for fundamental physics. Keywords: X-ray astronomy, X-ray polarimetry, X-ray imagin

    Contamination in the Kepler Field. Identification of 685 KOIs as False Positives Via Ephemeris Matching Based On Q1-Q12 Data

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    The Kepler mission has to date found almost 6000 planetary transit-like signals, utilizing three years of data for over 170,000 stars at extremely high photometric precision. Due to its design, contamination from eclipsing binaries, variable stars, and other transiting planets results in a significant number of these signals being false positives (FPs). This directly affects the determination of the occurrence rate of Earth-like planets in our Galaxy, as well as other planet population statistics. In order to detect as many of these FPs as possible, we perform ephemeris matching among all transiting planet, eclipsing binary, and variable star sources. We find that 685 Kepler Objects of Interest (KOIs)—12% of all those analyzed—are FPs as a result of contamination, due to 409 unique parent sources. Of these, 118 have not previously been identified by other methods. We estimate that ~35% of KOIs are FPs due to contamination, when performing a first-order correction for observational bias. Comparing single-planet candidate KOIs to multi-planet candidate KOIs, we find an observed FP fraction due to contamination of 16% and 2.4% respectively, bolstering the existing evidence that multi-planet KOIs are significantly less likely to be FPs. We also analyze the parameter distributions of the ephemeris matches and derive a simple model for the most common type of contamination in the Kepler field. We find that the ephemeris matching technique is able to identify low signal-to-noise FPs that are difficult to identify with other vetting techniques. We expect FP KOIs to become more frequent when analyzing more quarters of Kepler data, and note that many of them will not be able to be identified based on Kepler data alone
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