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NASA NTRS2017

Kepler Planet Detection Metrics: Robovetter Completeness and Effectiveness for Data Release 25

In general, the Kepler pipeline identifies a list of Threshold Crossing Events (TCEs), which are periodic flux decrements meeting certain criteria (Jenkins, 2017). These TCEs are reviewed and those that appear consistent with astrophysically transiting or eclipsing systems are classified as Kepler Objects of Interest (KOIs). Further review is given to KOIs, which are then dispositioned as Planet Candidates (PCs) or False Positive (FPs). FPs are further denoted by four major flags that indicate if the signal is Not Transit-Like (NTL), due to a Stellar Eclipse (SS; previously referred to as Significant Secondary), and/or due to contamination from a source other than the target as evidenced by a Centroid Offset (CO) oran Ephemeris Match (EM) with another object. This entire TCE review process is known as dispositioning or vetting.In the first five Kepler mission planet candidate catalogs (Borucki et al., 2011a,b; Batalha et al., 2013; Burke et al., 2014; Rowe et al., 2015), TCEs were manually examined on an individual basis and dispositioned using various plots and quantitative diagnostic tests (see e.g., Coughlin, 2017). In the sixth catalog, Mullally et al. (2015a) employed partial automation via simple parameter cuts to automatically disposition a large fraction of TCEs as not transit-like. Mullally et al. (2015a) also used an automated technique known as the centroid Robovetter (Mullally, 2017) to automatically identify some FP KOIs due to centroid offsets - a telltale signature of light contamination from another target. The remaining targets were manually dispositioned. In the seventh catalog, Coughlin et al. (2016) automated theentire dispositioning process using what is collectively known simply as the Robovetter.In the eighth and final mission catalog, Thompson et al. (2017) use a revised Robovetter to automate the dispositioning of all TCEs with an emphasis on creating a catalog suitable for accurately determining planet occurrence rates. In order to calculate accurate occurrence rates, the completeness and effectiveness of the Robovetter must be characterized. We define these terms as applied to the Robovetter, following Thompson et al. (2017), as:1. Completeness: The fraction of transiting planets detected by the pipeline that are classified as planet candidates by the Robovetter.2. Effectiveness: The fraction of false positives detected by the pipeline that are classified as false positives by the Robovetter.The remainder of this document describes products that can be used to quantitatively assess Robovetter completeness and effectiveness for an arbitrary set of Kepler stars.

Robovetter↗
NASA NTRS1989

Application of super smooth optics to extra-solar planet detection

The observational constraints on direct detection of extrasolar planets around nearby stars are defined. The design of an instrument capable of meeting these goals requires the efficient reduction of diffracted and scattered light by about three orders of magnitude below the airy wings of the unapodized aperture. The diffraction reduction is achieved through the high-efficiency coronagraph, which uses Gaussian occulting masks in the first focus to concentrate better diffracted light in the pupil plane. Laboratory experiments confirm this high efficiency to the limits set by the experimental setup. Scattering due to midspatial scale figure error in the mirrors must also be reduced to a comparable level.

Terrile, Richard J.↗
NASA NTRS1989

Fabrication experiments on supersmooth optics for extrasolar planet detection

The direct detection of extrasolar planets by imaging will require reductions in scattered and diffracted light by factors in excess of 1000 within one arcsecond of a bright source. While diffraction can be reduced by a number of approaches, small angle scatter can only be reduced by controlling midspatial frequency figure errors. The surface requirements are reviewed and their meaning when compared to the data base of existing mirrors is considered. Experiments are discribed that were successful in reducing midspatial frequency figure so that the scatter level was 500 times less than diffraction for a 25-cm spherical mirror.

Ftaclas, C.↗
NASA NTRS1993

Indirect Planet Detection with Ground-Based Interferometry

Narrow-angle astrometry with long-baseline infrared interferometers can provide extremely high accuracies as required for indirect planet detection. Narrow-angle asrometric interferometry exploits the properties of atmospheric turbulence over fields smaller than the interferometer baseline divided by the atmospheric scale height.

Interferometry Narrow-angle astrometry↗
NASA NTRS1994

Indirect planet detection with ground-based long-baseline interferometry

Narrow-angle astrometry with long-baseline infrared interferometers can provide extremely high accuracies as required for indirect planet detection. Narrow-angle astrometric interferometry exploits the properties of atmospheric turbulence over fields smaller than the interferometer baseline divided by the atmospheric scale height. For such fields, accuracy is linear with star separation, and nearly inversely proportional to baseline length. To exploit these properties, the interferometer observes a relatively bright (less than 13 mag(sub K)) target in the near infrared at 2.2 micrometers, and uses phase referencing to find a reference star within the 2.2-micrometers isoplanatic patch. With this technique faint references can be found for most targets. With baselines greater than 100 m, which also minimize photon-noise errors, and with careful control of systematic errors by using laser metrology, accuracies of tens of microarcseconds/square root of (hour) should be possible.

Colavita, M. M.↗
NASA NTRS2003

Planet detection and spectroscopy in visible light with a single aperture telescope and a nulling coronagraph

This talk describes a new concept for visible direct detection of Earth like extra solar planets using a nulling coronagraph instrument behind a 4m telescope in space. In the baseline design, a 4 beam nulling interferometer is synthesized from the telescope pupil, producing a very deep theta^4null which is then filtered by a coherent array of single mode fibers to suppress the residual scattered light. With perfect optics, the stellar leakage is less than 1e-11 of the starlight at the location of the planet. With diffraction limited telescope optics (lambda/20), suppression of the starlight to ~1e-10 is possible. The concept is described along with the key advantages over more traditional approaches such as apodized aperture telescopes and Lyot type coronagraphs.

coronagraph↗
NASA NTRS1996

Educational And Public Outreach Software On Planet Detection For The Macintosh (TM)

The possibility of extra-solar planets has been a very popular topic with the general public for years. Considerable media coverage of recent detections has only heightened the interest in the topic. School children are particularly interested in learning about space. Astronomers have the knowledge and responsibility to present this information in both an understandable and interesting format. Since most classrooms and homes are now equipped with computers this media can be utilized to provide more than a traditional "flat" presentation. An interactive "stack" has been developed using Hyperstudio (TM). The major topics include: "1996 - The Break Through Year In Planet Detection"; "What Determines If A Planet Is Habitable?"; "How Can We Find Other Planets (Search Methods)"; "All About the Kepler Mission: How To Find Earth-Sized Planets"; and "A Mission Simulator". Using the simulator, the student records simulated observations and then analyzes and interprets the data within the program stacks to determine the orbit and planet size, the planet's temperature and surface gravity, and finally determines if the planet is habitable. Additional related sections are also included. Many of the figures are animated to assist in comprehension of the material. A set of a dozen lesson plans for the middle school has also been drafted.

Koch, David↗
NASA NTRS2004

White-Light Nulling Interferometers for Detecting Planets

A report proposes the development of a white-light nulling interferometer to be used in conjunction with a singleaperture astronomical telescope that would be operated in outer space. When such a telescope is aimed at a given star, the interferometer would suppress the light of that star while passing enough light from planets (if any) orbiting the star, to enable imaging or spectroscopic examination of the planets. In a nulling interferometer, according to the proposal, scattered light would be suppressed by spatial filtering in an array of single-mode optical fibers rather than by requiring optical surfaces to be accurate within 1/4,000 wavelength as in a coronagraph or an apodized telescope. As a result, angstrom-level precision would be needed in only the small nulling combiner, and not in large, meter-sized optics. The nulling interferometer could work as an independent instrument in space or in conjunction with a coronagraphic system to detect planets outside our solar system.

Mennesson, Bertrand↗
NASA NTRS2017

Kepler Planet Detection Metrics: Window and One-Sigma Depth Functions for Data Release 25

This document describes the window and one-sigma depth functions relevant to the Transiting Planet Search (TPS) algorithm in the Kepler pipeline (Jenkins 2002; Jenkins et al. 2017). The window function specifies the fraction of unique orbital ephemeris epochs over which three transits are observable as a function of orbital period. In this context, the epoch and orbital period, together, comprise the ephemeris of an orbiting companion, and ephemerides with the same period are considered equivalent if their epochs differ by an integer multiple of the period. The one-sigma depth function specifies the depth of a signal (in ppm) for a given light curve that results in a one-sigma detection of a transit signature as a function of orbital period when averaged over all unique orbital ephemerides. These planet detection metrics quantify the ability of TPS to detect a transiting planet signature on a star-by-star basis. They are uniquely applicable to a specific Kepler data release, since they are dependent on the details of the light curves searched and the functionality of the TPS algorithm used to perform the search. This document describes the window and one-sigma depth functions relevant to Kepler Data Release 25 (DR25), where the data were processed (Thompson et al. 2016) and searched (Twicken et al. 2016) with the SOC 9.3 pipeline. In Section 4, we describe significant differences from those reported in Kepler Data Release 24 (Burke Seader 2016) and document our verification method.

Planet Detection Metrics↗
NASA NTRS2004

An Infrared Telescope for Planet Detection and General Astrophysics

NASA plans to launch a Terrestrial Planet Finder (TPF) mission in 2014 to detect and characterize Earth-like planets around nearby stars, perform comparative planetology studies, and obtain general astrophysics observations. During our recently completed a TPF Mission Architecture study for NASA/JPL we developed the conceptual design for a 28-meter telescope with an IR Coronagraph that meets these mission objectives. This telescope and the technology it embodies are directly applicable to future Far-IR and Submillimeter space missions. The detection of a 30th magnitude planet located within 50 milli-arc-seconds of a 5th (Visual) magnitude star is an exceptionally challenging objective. Observations in the thermal infrared (7-17 microns) are somewhat easier since the planet is "only" 15(sup m) fainter than the star at these wavelengths, but many severe challenges must still be overcome. These challenges include: 1. Designing a coronagraph for star:planet separations less than or equal to lambda/D. 2. Developing the deployment scheme for a 28m space telescope that can fit in an existing launch vehicle payload fairing. 3. Generating configuration layouts for the IR telescope, coronagraph, spacecraft bus, sunshade, solar array, and high-gain antenna. 4. Providing: Structural stability to within 10 microns to support the optics. Thermal control to achieve the necessary structural stability, as well as providing a stable (approx. 30K) thermal environment for the optics. Dynamics isolation from potential jitter sources. 5. Minimizing launch mass to provide the maximum payload for the science mission Interfacing to an EELV Heavy launch vehicle, including acoustic and stress loads for the launch environment. 6. Identifying the key technologies (which can be developed by 2009) that will enable TPF mission to be performed. 7. Generating a manufacturing plan that will permit TPF to be developed at a reasonable cost and schedule. Many of these design challenges result in inherently conflicting requirements on the design of TPF. Drawing on our experience with large space telescopes such as the Chandra X-ray Observatory and the Next Generation Space Telescope, we have created a conceptual design for TPF that successfully meets these challenging requirements. This paper describes our solution to these challenges.

Lillie, C. F.↗
NASA NTRS2003

Probability of Detecting Planets with Microlensing

The proposed research to determine the probability of detecting extra solar planets from the ground with microlensing was completely accomplished during the grant period. A summary of the publications and their abstracts follow below. The publications include: 1) On microlensing rates and optical depth toward the Galactic center; 2) Newly discovered brown dwarfs not seen in microlensing timescale frequency distribution? 3) Probability of detecting a planetary companion during a microlensing event; 4) Comparison of a ground-based microlensing search for planets with a search from space; 5) Secular evolution of hierarchical planetary systems.

Peale, S. J.↗
NASA NTRS2017

Kepler Planet Detection Metrics: Per-Target Detection Contours for Data Release 25

A necessary input to planet occurrence calculations is an accurate model for the pipeline completeness (Burke et al., 2015). This document describes the use of the Kepler planet occurrence rate products in order to calculate a per-target detection contour for the measured Data Release 25 (DR25) pipeline performance. A per-target detection contour measures for a given combination of orbital period, Porb, and planet radius, Rp, what fraction of transit signals are recoverable by the Kepler pipeline (Twicken et al., 2016; Jenkins et al., 2017). The steps for calculating a detection contour follow the procedure outlined in Burke et al. (2015), but have been updated to provide improved accuracy enabled by the substantially larger database of transit injection and recovery tests that were performed on the final version (i.e., SOC 9.3) of the Kepler pipeline (Christiansen, 2017; Burke Catanzarite, 2017a). In the following sections, we describe the main inputs to the per-target detection contour and provide a worked example of the python software released with this document (Kepler Planet Occurrence Rate Tools KeplerPORTs)1 that illustrates the generation of a detection contour in practice. As background material for this document and its nomenclature, we recommend the reader be familiar with the previous method of calculating a detection contour (Section 2 of Burke et al.,2015), input parameters relevant for describing the data quantity and quality of Kepler targets (Burke Catanzarite, 2017b), and the extensive new transit injection and recovery tests of the Kepler pipeline (Christiansen et al., 2016; Burke Catanzarite, 2017a; Christiansen, 2017).

Planet Detection Metrics↗
NASA NTRS2017

Kepler Planet Detection Metrics: Automatic Detection of Background Objects Using the Centroid Robovetter

We present an automated method of identifying background eclipsing binaries masquerading as planet candidates in the Kepler planet candidate catalogs. We codify the manual vetting process for Kepler Objects of Interest (KOIs) described in Bryson et al. (2013) with a series of measurements and tests that can be performed algorithmically. We compare our automated results with a sample of manually vetted KOIs from the catalog of Burke et al. (2014) and find excellent agreement. We test the performance on a set of simulated transits and find our algorithm correctly identifies simulated false positives approximately 50 of the time, and correctly identifies 99 of simulated planet candidates.

Centroid↗
NASA NTRS2017

Kepler Planet Detection Metrics: Per-Target Flux-Level Transit Injection Tests of TPS for Data Release 25

Quantifying the ability of a transiting planet survey to recover transit signals has commonly been accomplished through Monte-Carlo injection of transit signals into the observed data and subsequent running of the signal search algorithm (Gilliland et al., 2000; Weldrake et al., 2005; Burke et al., 2006). In order to characterize the performance of the Kepler pipeline (Twicken et al., 2016; Jenkins et al., 2017) on a sample of over 200,000 stars, two complementary injection and recovery tests are utilized:1. Injection of a single transit signal per target into the image or pixel-level data, hereafter referred to as pixel-level transit injection (PLTI), with subsequent processing through the Photometric Analysis (PA), Presearch Data Conditioning (PDC), Transiting Planet Search (TPS), and Data Validation (DV) modules of the Kepler pipeline. The PLTI quantification of the Kepler pipeline's completeness has been described previously by Christiansen et al. (2015, 2016); the completeness of the final SOC 9.3 Kepler pipeline acting on the Data Release 25 (DR25) light curves is described by Christiansen (2017).2. Injection of multiple transit signals per target into the normalized flux time series data with a subsequent transit search using a stream-lined version of the Transiting Planet Search (TPS) module. This test, hereafter referred to as flux-level transit injection (FLTI), is the subject of this document. By running a heavily modified version of TPS, FLTI is able to perform many injections on selected targets and determine in some detail which injected signals are recoverable. Significant numerical efficiency gains are enabled by precomputing the data conditioning steps at the onset of TPS and limiting the search parameter space (i.e., orbital period, transit duration, and ephemeris zero-point) to a small region around each injected transit signal.The PLTI test has the advantage that it follows transit signals through all processing steps of the Kepler pipeline, and the recovered signals can be further classified as planet candidates or false positives in the exact same manner as detections from the nominal (i.e., observed) pipeline run (Twicken et al., 2016, Thompson et al., in preparation). To date, the PLTI test has been the standard means of measuring pipeline completeness averaged over large samples of targets (Christiansen et al., 2015, 2016; Christiansen, 2017). However, since the PLTI test uses only one injection per target, it does not elucidate individual-target variations in pipeline completeness due to differences in stellar properties or astrophysical variability. Thus, we developed the FLTI test to provide a numerically efficient way to fully map individual targets and explore the performance of the pipeline in greater detail. The FLTI tests thereby allow a thorough validation of the pipeline completeness models (such as window function (Burke and Catanzarite, 2017a), detection efficiency (Burke Catanzarite, 2017b), etc.) across the spectrum of Kepler targets (i.e., various astrophysical phenomena and differences in instrumental noise). Tests during development of the FLTI capability revealed that there are significant target-to-target variations in the detection efficiency.

DR25↗