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Jeffery J. Kolodziejczak

Researcher at Marshall Space Flight Center

Publications -  72
Citations -  7051

Jeffery J. Kolodziejczak is an academic researcher from Marshall Space Flight Center. The author has contributed to research in topics: Telescope & Planet. The author has an hindex of 24, co-authored 72 publications receiving 6236 citations. Previous affiliations of Jeffery J. Kolodziejczak include Universities Space Research Association.

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Characteristics of planetary candidates observed by Kepler. II. Analysis of the first four months of data

William J. Borucki, +69 more
TL;DR: In this article, the Kepler mission released data for 156,453 stars observed from the beginning of the science observations on 2009 May 2 through September 16, and there are 1235 planetary candidates with transit-like signatures detected in this period.
Journal ArticleDOI

Characteristics of planetary candidates observed by Kepler, II: Analysis of the first four months of data

TL;DR: In this paper, the Kepler mission released data for 156,453 stars observed from the beginning of the science observations on 2 May through 16 September 2009, and there are 1235 planetary candidates with transit-like signatures detected in this period.
Journal ArticleDOI

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

TL;DR: In this article, a Bayesian maximum a posteriori (MAP) approach is presented, 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.
Journal ArticleDOI

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

TL;DR: This article introduces the completely new and significantly improved version of Presearch Data Conditioning (PDC) which was implemented in Kepler SOC version 8.0, which reliably corrects errors in the light curves while at the same time preserving planet transits and other astrophysically interesting signals.
Journal ArticleDOI

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

TL;DR: In this article, a Bayesian Maximum A Posteriori (MAP) approach is presented 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.