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NASA NTRS2016

Kepler Archive Manual

A description of Kepler, its design, performance and operational constraints may be found in the Kepler Instrument Handbook (KIH, Van Cleve Caldwell 2016). A description of Kepler calibration and data processing is described in the Kepler Data Processing Handbook (KDPH, Jenkins et al. 2016; Fanelli et al. 2011). Science users should also consult the special ApJ Letters devoted to early Kepler results and mission design (April 2010, ApJL, Vol. 713 L79-L207). Additional technical details regarding the data processing and data qualities can be found in the Kepler Data Characteristics Handbook (KDCH, Christiansen et al. 2013) and the Data Release Notes (DRN). This archive manual specifically documents the file formats, as they exist for the last data release of Kepler, Data Release 25(KSCI-19065-002). The earlier versions of the archive manual and data release notes act as documentation for the earlier versions of the data files.

Kepler↗

NASA NTRS2011

The Little Photometer That Could: Technical Challenges and Science Results from the Kepler Mission

The Kepler spacecraft launched on March 7, 2009, initiating NASA's first search for Earth-size planets orbiting Sun-like stars. Since launch, Kepler has announced the discovery of 17 exoplanets, including a system of six transiting a Sun-like star, Kepler-11, and the first confirmed rocky planet, Kepler-10b, with a radius of 1.4 that of Earth. Kepler is proving to be a cornucopia of discoveries: it has identified over 1200 candidate planets based on the first 120 days of observations, including 54 that are in or near the habitable zone of their stars, and 68 that are 1.2 Earth radii or smaller. An astounding 408 of these planetary candidates are found in 170 multiple systems, demonstrating the compactness and flatness of planetary systems composed of small planets. Never before has there been a photometer capable of reaching a precision near 20 ppm in 6.5 hours and capable of conducting nearly continuous and uninterrupted observations for months to years. In addition to exoplanets, Kepler is providing a wealth of astrophysics, and is revolutionizing the field of asteroseismology. Designing and building the Kepler photometer and the software systems that process and analyze the resulting data to make the discoveries presented a daunting set of challenges, including how to manage the large data volume. The challenges continue into flight operations, as the photometer is sensitive to its thermal environment, complicating the task of detecting 84 ppm drops in brightness corresponding to Earth-size planets transiting Sun-like stars.

Kepler Mission↗

NASA NTRS2003

Kepler Mission to Detect Earth-like Planets

Kepler Mission to detect Earth-like planets in our Milky Way galaxy was approved by NASA in December 2001 for a 4-5 year mission. The launch is planned in about 5 years. The Kepler observatory will be placed in an Earth-trailing orbit. The unique feature of the Kepler Mission is its ability to detect Earth-like planets orbiting around solar-type stars at a distance similar to that of Earth (from our Sun); such an orbit could provide an environment suitable for supporting life as we know it. The Kepler observatory accomplishes this feat by looking for the transits of planetary object in front of their suns; Kepler has a photometric precision of 10E-5 (0.00001) to achieve such detections. Other ongoing planetary detection programs (based mostly on a technique that looks for the shifting of spectral lines of the primary star due to its planetary companions' motions around it) have detected massive planets (with masses in the range of Jupiter); such massive planets are not considered suitable for supporting life. If our current theories for the formation of planetary systems are valid, we expect to detect about 50 Earth-like planets during Kepler's 4-year mission (assuming a random distribution of the planetary orbital inclinations with respect to the line of sight from Kepler). The number of detection will increase about 640 planets if the planets to be detected are Jupiter-sized.

Kondo, Yoji↗

NASA NTRS2002

Kepler Mission to Detect Earth-like Planets

Kondo, Yoji↗

NASA NTRS2016

The Kepler Science Data Processing Pipeline Source Code Road Map

We give an overview of the operational concepts and architecture of the Kepler Science Processing Pipeline. Designed, developed, operated, and maintained by the Kepler Science Operations Center (SOC) at NASA Ames Research Center, the Science Processing Pipeline is a central element of the Kepler Ground Data System. The SOC consists of an office at Ames Research Center, software development and operations departments, and a data center which hosts the computers required to perform data analysis. The SOC's charter is to analyze stellar photometric data from the Kepler spacecraft and report results to the Kepler Science Office for further analysis. We describe how this is accomplished via the Kepler Science Processing Pipeline, including, the software algorithms. We present the high-performance, parallel computing software modules of the pipeline that perform transit photometry, pixel-level calibration, systematic error correction, attitude determination, stellar target management, and instrument characterization.

Kepler pipeline software↗

NASA NTRS2017

Kepler Commissioning Data for Measurement of the Pixel Response Function and Focal Plane Geometry

This document describes the Kepler PRF/FPG data release. This data was taken on April 27-29, 2009, during Kepler's commissioning phase in order to measure the pixel response function (PRF) (Bryson et al., 2010a) and focal plane geometry (FPG) (Tenenbaum and Jenkins, 2010). 33,424 stellar targets were observed for 243 long cadences, each with a duration of 14.7 minutes (half the duration of a normal Kepler long cadence). During these 243 cadences the Kepler photometer was moved, pointing in a dither pattern to facilitate PRF measurement. Motion occurred during the even cadences (second, fourth, etc.), with the telescope in stable fine point at each pointing in the dither pattern during the odd cadences (first, third, etc.). The first and last cadences were at the center of the dither pattern. Motion cadences are included in this release, but they do not contain any data. For details on how this data was used to derive the Kepler PRF and FPG models, see Bryson et al. (2010a) and Tenenbaum and Jenkins (2010). Descriptions of the PRF and FPG models are found in Thompson et al. (2016), x2.3.5.17 and x2.3.5.16 respectively. The data in this release can be used to recompute the Kepler PRF and FPG. Such a reconstruction, however, would not reflect measured seasonal changes in the PRF described in Van Cleve et al. (2016b), x5.2.The dither pattern is shown in Figure 1. The crosses show the commanded pointings and the circles show the measured pointings. Measured pointings are different from the commanded pointings due to the early state of calibration of the fine guidance sensors during commissioning (Van Cleve et al., 2016a). The measured offsets from the center of the pattern are given in RADEC offsets and pixel offsets in Table 1. The order of the offsets was randomized during data collection to avoid time-dependent systematics.

Kepler↗

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↗

NASA NTRS2017

Kepler Planet Detection Metrics: Pixel-Level Transit Injection Tests of Pipeline Detection Efficiency for Data Release 25

This document describes the results of the fourth pixel-level transit injection experiment, which was designed to measure the detection efficiency of both the Kepler pipeline (Jenkins 2002, 2010; Jenkins et al. 2017) and the Robovetter (Coughlin 2017). Previous transit injection experiments are described in Christiansen et al. (2013, 2015a,b, 2016).In order to calculate planet occurrence rates using a given Kepler planet catalogue, produced with a given version of the Kepler pipeline, we need to know the detection efficiency of that pipeline. This can be empirically determined by injecting a suite of simulated transit signals into the Kepler data, processing the data through the pipeline, and examining the distribution of successfully recovered transits. This document describes the results for the pixel-level transit injection experiment performed to accompany the final Q1-Q17 Data Release 25 (DR25) catalogue (Thompson et al. 2017)of the Kepler Objects of Interest. The catalogue was generated using the SOC pipeline version 9.3 and the DR25 Robovetter acting on the uniformly processed Q1-Q17 DR25 light curves (Thompson et al. 2016a) and assuming the Q1-Q17 DR25 Kepler stellar properties (Mathur et al. 2017).

Pixel-Level Transit Injection↗

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 NTRS2016

Processing and Managing the Kepler Mission's Treasure Trove of Stellar and Exoplanet Data

The Kepler telescope launched into orbit in March 2009, initiating NASAs first mission to discover Earth-size planets orbiting Sun-like stars. Kepler simultaneously collected data for 160,000 target stars at a time over its four-year mission, identifying over 4700 planet candidates, 2300 confirmed or validated planets, and over 2100 eclipsing binaries. While Kepler was designed to discover exoplanets, the long term, ultra- high photometric precision measurements it achieved made it a premier observational facility for stellar astrophysics, especially in the field of asteroseismology, and for variable stars, such as RR Lyraes. The Kepler Science Operations Center (SOC) was developed at NASA Ames Research Center to process the data acquired by Kepler from pixel-level calibrations all the way to identifying transiting planet signatures and subjecting them to a suite of diagnostic tests to establish or break confidence in their planetary nature. Detecting small, rocky planets transiting Sun-like stars presents a variety of daunting challenges, from achieving an unprecedented photometric precision of 20 parts per million (ppm) on 6.5-hour timescales, supporting the science operations, management, processing, and repeated reprocessing of the accumulating data stream. This paper describes how the design of the SOC meets these varied challenges, discusses the architecture of the SOC and how the SOC pipeline is operated and is run on the NAS Pleiades supercomputer, and summarizes the most important pipeline features addressing the multiple computational, image and signal processing challenges posed by Kepler.

high performance computing↗

NASA NTRS2018

Kepler Data Validation I: Architecture, Diagnostic Tests, and Data Products for Vetting Transiting Planet Candidates

The Kepler Mission was designed to identify and characterize transiting planets in the Kepler Field of View and to determine their occurrence rates. Emphasis was placed on identification of Earth-size planets orbiting in the Habitable Zone of their host stars. Science data were acquired for a period of four years. Long-cadence data with 29.4 min sampling were obtained for approx. 200,000 individual stellar targets in at least one observing quarter in the primary Kepler Mission. Light curves for target stars are extracted in the Kepler Science Data Processing Pipeline, and are searched for transiting planet signatures. A Threshold Crossing Event is generated in the transit search for targets where the transit detection threshold is exceeded and transit consistency checks are satisfied. These targets are subjected to further scrutiny in the Data Validation (DV) component of the Pipeline. Transiting planet candidates are characterized in DV, and light curves are searched for additional planets after transit signatures are modeled and removed. A suite of diagnostic tests is performed on all candidates to aid in discrimination between genuine transiting planets and instrumental or astrophysical false positives. Data products are generated per target and planet candidate to document and display transiting planet model fit and diagnostic test results. These products are exported to the Exoplanet Archive at the NASA Exoplanet Science Institute, and are available to the community. We describe the DV architecture and diagnostic tests, and provide a brief overview of the data products. Transiting planet modeling and the search for multiple planets on individual targets are described in a companion paper. The final revision of the Kepler Pipeline code base is available to the general public through GitHub. The Kepler Pipeline has also been modified to support the Transiting Exoplanet Survey Satellite (TESS) Mission which is expected to commence in 2018.

data analysis↗

NASA NTRS2012

The Kepler End-to-End Data Pipeline: From Photons to Far Away Worlds

The Kepler mission is described in overview and the Kepler technique for discovering exoplanets is discussed. The design and implementation of the Kepler spacecraft, tracing the data path from photons entering the telescope aperture through raw observation data transmitted to the ground operations team is described. The technical challenges of operating a large aperture photometer with an unprecedented 95 million pixel detector are addressed as well as the onboard technique for processing and reducing the large volume of data produced by the Kepler photometer. The technique and challenge of day-to-day mission operations that result in a very high percentage of time on target is discussed. This includes the day to day process for monitoring and managing the health of the spacecraft, the annual process for maintaining sun on the solar arrays while still keeping the telescope pointed at the fixed science target, the process for safely but rapidly returning to science operations after a spacecraft initiated safing event and the long term anomaly resolution process.The ground data processing pipeline, from the point that science data is received on the ground to the presentation of preliminary planetary candidates and supporting data to the science team for further evaluation is discussed. Ground management, control, exchange and storage of Kepler's large and growing data set is discussed as well as the process and techniques for removing noise sources and applying calibrations to intermediate data products.

data archiving↗

NASA NTRS2018

New Formation Models for the Kepler-36 System

Formation of the planets in the Kepler-36 system is modeled by detailed numerical simulations according to the core-nucleated accretion scenario. The standard model is updated to include the dissolution of accreting rocky planetesimals in the gaseous envelope of the planet, leading to substantial enrichment of the envelope mass in heavy elements and a non-uniform composition with depth. For Kepler-36 c, models involving in situ formation and models involving orbital migration are considered. The results are compared with standard formation models. The calculations include the formation (accretion) phase, as well as the subsequent cooling phase, up to the age of Kepler-36 (7 Gyr). During the latter phase, mass loss induced by stellar XUV radiation is included. In all cases, the results fit the measured mass, 7.84 M, and radius, 3.68 R, of Kepler-36 c. Two parameters are varied to obtain these fits: the disk solid surface density at the formation location, and the "efficiency" factor in the XUV mass loss rate. The updated models are hotter and therefore less dense in the silicate portion of the planet and in the overlying layers of H/He, as compared with standard models. The lower densities mean that only about half as much H/He is needed to be accreted to fit the present-day mass and radius constraints. For Kepler-36 b, an updated in situ calculation shows that the entire H/He envelope is lost, early in the cooling phase, in agreement with observation.

planets and satellites:formation↗

NASA NTRS2016

Kepler Stellar Properties Catalog Update for Q1-Q17 DR25 Transit Search

Huber et al. (2014) presented revised stellar properties for 196,468 Kepler targets, which were used for the Q1-Q16 TPSDV planet search (Tenenbaum et al. 2014). The catalog was based on atmospheric properties (i.e., temperature (Teff), surface gravity (log(g)), and metallicity ([FeH])) published in the literature using a variety of methods (e.g., asteroseismology, spectroscopy, exoplanet transits, photometry), which were then homogeneously fitted to a grid of Dartmouth (DSEP) isochrones (Dotter et al. 2008). The catalog was updated in early 2015 for the Q1-Q17 Data Release (DR) 24 transit search (Seader et al. 2015) based on the latest classifications of Kepler targets in the literature at that time. The methodology followed Huber et al. (2014). Here we provide updated stellar properties of 197,096 Kepler targets. Like the previous catalog, this update is based on atmospheric properties that were either published in the literature or provided by the Kepler community follow-up program (CFOP). The input values again come from different methods: asteroseismology, spectroscopy, flicker, and photometry. This catalog update was developed to support the SOC 9.3 TPSDV planet search (Twicken et al. 2016), which is expected to be the final search and data release by the Kepler project.In this document, we describe the method and the inputs that were used to build the catalog. The methodology follows Huber et al. (2014) with a few improvements as described in Section 2.

DR25↗

NASA NTRS2017

Synergies Between the Kepler, K2 and TESS Missions with the PLATO Mission (Revised)

Two transit survey missions will have been flown by NASA prior to the launch of ESA's PLATO Mission in 2026, laying the groundwork for exoplanet discovery via the transit method. The Kepler Mission, which launched in 2009, collected data on its 100+ square degree field of view for four years before failure of a reaction wheel ended its primary mission. The results from Kepler include 2300+ confirmed or validated exoplanets, 2200+ planetary candidates, 2100+ eclipsing binaries. Kepler also revolutionized the field of asteroseismology by measuring the pressure mode oscillations of over 15000 solar-like stars spanning the lifecycle of such stars from hydrogen-burning dwarfs to helium-burning red giants. The re-purposed Kepler Mission, dubbed K2, continues to observe fields of view in and near the ecliptic plane for 80 days each, significantly broadening the scope of the astrophysical investigations as well as discovering an additional 156 exoplanets to date. The TESS mission will launch in 2017 to conduct an all-sky survey for small exoplanets orbiting stars 10X closer and 100X brighter than Kepler exoplanet host stars, allowing for far greater follow-up and characterization of their masses as well as their sizes for at least 50 small planets. Future assets such as James Webb Space Telescope, and ground-based assets such as ESOs Very Large Telescope (VLT) array, the Exremely Large Telescope (ELT), and the Thirty Meter Telescope (TMT) will be able to characterize the atmospheric composition and properties of these small planets. TESS will observe each 24 X 96 field of view for 30 days and thereby cover first the southern and then the northern hemisphere over 13 pointings during each year of the primary mission. The pole-most camera will observe the James Webb continuous viewing zone for one year in each hemisphere, permitting much longer period planets to be detected in this region. The PLATO mission will seek to detect habitable Earth-like planets with an instrument composed of 26 small telescopes in several 2232 square deg FOVs with a range of observation durations over a mission lifetime of up to eight years. This paper summarizes the findings of the KeplerK2 missions, previews the likely results from the TESS mission, and explores the lessons learned and to be learned from these prior missions that can be incorporated into the observation and data reduction strategy for the PLATO Mission so as to maximize the science return.

exoplanet detection↗

NASA NTRS2010

Kepler Data Release 3 Notes

This describes the collection of data and the processing done on it so when researchers around the world get the Kepler data sets (which are a set of pixels from the telescope of a particular target (star, galaxy or whatever) over a 3 month period) they can adjust their algorithms fro things that were done (like subtracting all of one particular wavelength for example). This is used to calibrate their own algorithms so that they know what it is they are starting with. It is posted so that whoever is accessing the publicly available data (not all of it is made public) can understand it .. (most of the Kepler data is under restriction for 1 - 4 years and is not available, but the handbook is for everyone (public and restricted) The Data Analysis Working Group have released long and short cadence materials, including FFls and Dropped Targets for the Public. The Kepler Science Office considers Data Release 3 to provide "browse quality" data. These notes have been prepared to give Kepler users of the Multimission Archive at STScl (MAST) a summary of how the data were collected and prepared, and how well the data processing pipeline is functioning on flight data. They will be updated for each release of data to the public archive and placed on MAST along with other Kepler documentation, at http:// archive.stsci.edu/kepler/documents.html .Data release 3 is meant to give users the opportunity to examine the data for possibly interesting science and to involve the users in improving the pipeline for future data releases. To perform the latter service, users are encouraged to notice and document artifacts, either in the raw or processed data, and report them to the Science Office.

Cleve, Jeffrey E.↗

NASA NTRS2011

Kepler and Ground-Based Transits of the exo-Neptune HAT-P-11b

We analyze 26 archival Kepler transits of the exo-Neptune HAT-P-11b, supplemented by ground-based transits observed in the blue (B band) and near-IR (J band). Both the planet and host star are smaller than previously believed; our analysis yields Rp = 4.31 R xor 0.06 R xor and Rs = 0.683 R solar mass 0.009 R solar mass, both about 3 sigma smaller than the discovery values. Our ground-based transit data at wavelengths bracketing the Kepler bandpass serve to check the wavelength dependence of stellar limb darkening, and the J-band transit provides a precise and independent constraint on the transit duration. Both the limb darkening and transit duration from our ground-based data are consistent with the new Kepler values for the system parameters. Our smaller radius for the planet implies that its gaseous envelope can be less extensive than previously believed, being very similar to the H-He envelope of GJ 436b and Kepler-4b. HAT-P-11 is an active star, and signatures of star spot crossings are ubiquitous in the Kepler transit data. We develop and apply a methodology to correct the planetary radius for the presence of both crossed and uncrossed star spots. Star spot crossings are concentrated at phases 0.002 and +0.006. This is consistent with inferences from Rossiter-McLaughlin measurements that the planet transits nearly perpendicular to the stellar equator. We identify the dominant phases of star spot crossings with active latitudes on the star, and infer that the stellar rotational pole is inclined at about 12 deg 5 deg to the plane of the sky. We point out that precise transit measurements over long durations could in principle allow us to construct a stellar Butterfly diagram to probe the cyclic evolution of magnetic activity on this active K-dwarf star.

Deming, Drake↗

NASA NTRS2018

Transiting Planets from Kepler, K2 & TESS

NASA's Kepler spacecraft, launched in 2009, has been a resounding success. More than 4000 planet candidates have been identified using data from Kepler primary mission, which ended in 2013, and greater than 2000 of these candidates have been verified as bona fide exoplanets. After the loss of two reaction wheels ended the primary mission, the Kepler spacecraft was repurposed in 2014 to observe many fields on the sky for short periods. This new mission, dubbed K2, has led to the discovery of greater than 600 planet candidates, approximately 200 of which have been verified to date; most of these exoplanets are closer to us than the majority of exoplanets discovered by the primary Kepler mission. TESS, launching in 2018, will survey most of the sky for exoplanets, with emphasis on those orbiting nearby and/or bright host stars, making these planets especially well-suited for follow-up observations with other observatories to characterize atmospheric compositions and other properties. More than one-third of the planet candidates found by NASA's are associated with target stars that have more than one planet candidate, and such 'multis' account for the majority of candidates that have been verified as true planets. The large number of multis tells us that flat multiplanet systems like our Solar System are common. Virtually all of the candidate planetary systems are stable, as tested by numerical integrations that assume a physically motivated mass-radius relationship. Statistical studies performed on these candidate systems reveal a great deal about the architecture of planetary systems, including the typical spacing of orbits and flatness. The characteristics of several of the most interesting confirmed Kepler & K2 multi-planet systems will also be discussed.

Lissauer, Jack↗