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Modern Statistical and Computational for Analysis of Kepler Data

[This is a program of SAMSI, the NSF-supported Statistical and Applied Mathematical Sciences Institute. SAMSI runs high-quality cross-disciplinary research workshops for many fields, including astrophysics. Travel funding for U.S. participants is often available.] The discovery of planets orbiting other stars (exoplanets) in the past two decades has demonstrated that nature often produces planetary systems quite different from our own. NASA's Kepler mission has been observing over 190,000 stars nearly continuously since 2009. Kepler's high-precision photometery is revolutionizing multiple subfields (exoplanets, astroseismology, variable stars, etc.), but also raising several new statistical challenges. This three week SAMSI mini-research program will provide a venue for astronomers and astrostatisticians to share experience with statistical techniques and to help existing best practices spread amongst the community. Simultaneously, this SAMSI min-research program will provide an opportunity for statisticians, mathematicians and computer scientists to interact much more closely with astronomers than is otherwise practical. We hope that the statisticians will be able to help the astronomers in improving their current statistical tools, and also in developing new techniques geared towards analysis of exoplanet data.
When 10 June 2013 08:20 AM to
18 June 2013 08:20 AM
Where Research Triangle NC USA
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Motivation

For centuries, theories of planet formation were guided exclusively by our solar system. The discovery of planets orbiting other stars (exoplanets) in the past two decades has demonstrated that nature often produces planetary systems quite different from our own. NASA's Kepler mission has been observing over 190,000 stars nearly continuously since 2009 (once every 1 or 30 minutes with ~95% duty cycle). The primary science goal of NASA's Kepler mission is to determine the frequency of Earth-size planets in the habitable zone of other stars. Kepler's high-precision photometery is revolutionizing multiple subfields (exoplanets, astroseismology, variable stars, etc.), but also raising several new statistical challenges.

This three week SAMSI mini-research program will provide a venue for astronomers and astrostatisticians to share experience with statistical techniques and to help existing best practices spread amongst the community. Simultaneously, this SAMSI min-research program will provide an opportunity for statisticians, mathematicians and computer scientists to interact much more closely with astronomers than is otherwise practical. We hope that the statisticians will be able to help the astronomers in improving their current statistical tools, and also in developing new techniques geared towards analysis of exoplanet data.

Program Details

The first day (Monday, June 10, 2013) will consist of invited talks, designed to help participants understand the nature of Kepler data, and to provide an introduction to relevant statistical methods.

On the second day (Tuesday, June 11, 2013), participants will organize themselves into three working groups, for intensive research collaboration among astronomers and statisticians. During subsequent days, most of the participant's time will be devoted to collaborative research.

On the final day (Friday, June 28, 2013), program participants will present their results, as well as plans for continued collaboration beyond the SAMSI mini-research program.

Proposed (tentative) Working Groups

  1. Object detection and validation (e.g., searching the Kepler data for planets, moons, binary stars and/or other interesting astrophysical objects in the presence of measurement noise, instrumental systematics and other astrophysical signals; model comparison to establish that signals are due to planets rather than an astrophysical false positive),
  2. Characterizing exoplanets and/or binary stars (e.g., efficient posterior sampling for measuring masses, orbits and their uncertainties using transit timing variations; Bayesian model comparison to quantify evidence for non-transiting planets),
  3. Population statistics (e.g., making inferences about the distribution of extrasolar planets along with their physical and orbital properties; likelihood-free methods and approximate Bayesian computing for population analyses with many model parameters).

 

Organizing committee