The Experts below are selected from a list of 115350 Experts worldwide ranked by ideXlab platform
Rodrigo Luger - One of the best experts on this subject based on the ideXlab platform.
-
eleanor an open source tool for extracting Light Curves from the tess full frame images
Publications of the Astronomical Society of the Pacific, 2019Co-Authors: Adina D Feinstein, Benjamin T Montet, Daniel Foremanmackey, Megan Bedell, Nicholas Saunders, Jacob L Bean, Jessie L Christiansen, Christina Hedges, Rodrigo Luger, D ScolnicAbstract:During its two-year prime mission, the Transiting Exoplanet Survey Satellite (TESS) will perform a time-series photometric survey covering over 80% of the sky. This survey comprises observations of 26 24° × 96° sectors that are each monitored continuously for approximately 27 days. The main goal of TESS is to find transiting planets around 200,000 pre-selected stars for which fixed aperture photometry is recorded every two minutes. However, TESS is also recording and delivering full-frame images (FFIs) of each detector at a 30-minutes cadence. We have created an open-source tool, eleanor, to produce Light Curves for objects in the TESS FFIs. Here, we describe the methods used in eleanor to produce Light Curves that are optimized for planet searches. The tool performs background subtraction; aperture and point-spread function photometry; decorrelation of instrument systematics; and cotrending using principal component analysis. We recover known transiting exoplanets in the FFIs to validate the pipeline and perform a limited search for new planet candidates in Sector 1. Our tests indicate that eleanor produces Light Curves with significantly less scatter than other tools that have been used in the literature. Cadence-stacked images, and raw and detrended eleanor Light Curves for each analyzed star will be hosted on Mikulski Archive for Space Telescopes, with planet candidates on ExoFOP-TESS as Community TESS Objects of Interest. This work confirms the promise that the TESS FFIs will enable the detection of thousands of new exoplanets and a broad range of time domain astrophysics.
-
eleanor an open source tool for extracting Light Curves from the tess full frame images
arXiv: Instrumentation and Methods for Astrophysics, 2019Co-Authors: Adina D Feinstein, Benjamin T Montet, Daniel Foremanmackey, Megan Bedell, Nicholas Saunders, Jacob L Bean, Jessie L Christiansen, Christina Hedges, Rodrigo Luger, D ScolnicAbstract:During its two year prime mission the Transiting Exoplanet Survey Satellite (TESS) will perform a time-series photometric survey covering over 80% of the sky. This survey comprises observations of 26 24 x 96 degree sectors that are each monitored continuously for approximately 27 days. The main goal of TESS is to find transiting planets around 200,000 pre-selected stars for which fixed aperture photometry is recorded every two minutes. However, TESS is also recording and delivering Full-Frame Images (FFIs) of each detector at a 30 minute cadence. We have created an open-source tool, eleanor, to produce Light Curves for objects in the TESS FFIs. Here, we describe the methods used in eleanor to produce Light Curves that are optimized for planet searches. The tool performs background subtraction, aperture and PSF photometry, decorrelation of instrument systematics, and cotrending using principal component analysis. We recover known transiting exoplanets in the FFIs to validate the pipeline and perform a limited search for new planet candidates in Sector 1. Our tests indicate that eleanor produces Light Curves with significantly less scatter than other tools that have been used in the literature. Cadence-stacked images, and raw and detrended eleanor Light Curves for each analyzed star will be hosted on MAST, with planet candidates on ExoFOP-TESS as Community TESS Objects of Interest (CTOIs). This work confirms the promise that the TESS FFIs will enable the detection of thousands of new exoplanets and a broad range of time domain astrophysics.
-
everest pixel level decorrelation of k2 Light Curves
The Astronomical Journal, 2016Co-Authors: Daniel Foremanmackey, Rodrigo Luger, Eric Agol, Ethan Kruse, Rory Barnes, Andrew C Becker, Drake DemingAbstract:We present EPIC Variability Extraction and Removal for Exoplanet Science Targets (EVEREST), an open-source pipeline for removing instrumental noise from K2 Light Curves. EVEREST employs a variant of pixel level decorrelation to remove systematics introduced by the spacecraft's pointing error and a Gaussian process to capture astrophysical variability. We apply EVEREST to all K2 targets in campaigns 0–7, yielding Light Curves with precision comparable to that of the original Kepler mission for stars brighter than , and within a factor of two of the Kepler precision for fainter targets. We perform cross-validation and transit injection and recovery tests to validate the pipeline, and compare our Light Curves to the other de-trended Light Curves available for download at the MAST High Level Science Products archive. We find that EVEREST achieves the highest average precision of any of these pipelines for unsaturated K2 stars. The improved precision of these Light Curves will aid in exoplanet detection and characterization, investigations of stellar variability, asteroseismology, and other photometric studies. The EVEREST pipeline can also easily be applied to future surveys, such as the TESS mission, to correct for instrumental systematics and enable the detection of low signal-to-noise transiting exoplanets. The EVEREST Light Curves and the source code used to generate them are freely available online.
-
everest pixel level decorrelation of k2 Light Curves
arXiv: Earth and Planetary Astrophysics, 2016Co-Authors: Daniel Foremanmackey, Rodrigo Luger, Eric Agol, Ethan Kruse, Rory Barnes, Andrew C Becker, Drake DemingAbstract:We present EVEREST, an open-source pipeline for removing instrumental noise from K2 Light Curves. EVEREST employs a variant of pixel level decorrelation (PLD) to remove systematics introduced by the spacecraft's pointing error and a Gaussian process (GP) to capture astrophysical variability. We apply EVEREST to all K2 targets in campaigns 0-7, yielding Light Curves with precision comparable to that of the original Kepler mission for stars brighter than $K_p \approx 13$, and within a factor of two of the Kepler precision for fainter targets. We perform cross-validation and transit injection and recovery tests to validate the pipeline, and compare our Light Curves to the other de-trended Light Curves available for download at the MAST High Level Science Products archive. We find that EVEREST achieves the highest average precision of any of these pipelines for unsaturated K2 stars. The improved precision of these Light Curves will aid in exoplanet detection and characterization, investigations of stellar variability, asteroseismology, and other photometric studies. The EVEREST pipeline can also easily be applied to future surveys, such as the TESS mission, to correct for instrumental systematics and enable the detection of low signal-to-noise transiting exoplanets. The EVEREST Light Curves and the source code used to generate them are freely available online.
Thomas Barclay - One of the best experts on this subject based on the ideXlab platform.
-
kepler presearch data conditioning i architecture and algorithms for error correction in kepler Light Curves
Publications of the Astronomical Society of the Pacific, 2012Co-Authors: Martin C Stumpe, Thomas Barclay, Jeffrey C Smith, Jeffrey Van Cleve, Joseph D Twicken, Michael N Fanelli, Forrest R Girouard, Jon M Jenkins, Jeffery J Kolodziejczak, Sean MccauliffAbstract: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 of the removal of errors. In this article we introduce the completely new and significantly improved version of PDC which was implemented in Kepler SOC version 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.
-
kepler eclipsing binary stars iii classification of kepler eclipsing binary Light Curves with locally linear embedding
The Astronomical Journal, 2012Co-Authors: Gal Matijevic, Andrej Prsa, Jerome A Orosz, William F Welsh, S Bloemen, Thomas BarclayAbstract:We present an automated classification of 2165 Kepler eclipsing binary (EB) Light Curves that accompanied the second Kepler data release. The Light Curves are classified using locally linear embedding, a general nonlinear dimensionality reduction tool, into morphology types (detached, semi-detached, overcontact, ellipsoidal). The method, related to a more widely used principal component analysis, produces a lower-dimensional representation of the input data while preserving local geometry and, consequently, the similarity between neighboring data points. We use this property to reduce the dimensionality in a series of steps to a one-dimensional manifold and classify Light Curves with a single parameter that is a measure of detachedness of the system. This fully automated classification correlates well with the manual determination of morphology from the data release, and also efficiently highLights any misclassified objects. Once a lower-dimensional projection space is defined, the classification of additional Light Curves runs in a negligible time and the method can therefore be used as a fully automated classifier in pipeline structures. The classifier forms a tier of the Kepler EB pipeline that pre-processes Light Curves for the artificial intelligence based parameter estimator.
-
kepler eclipsing binary stars iii classification of kepler eclipsing binary Light Curves with locally linear embedding
arXiv: Solar and Stellar Astrophysics, 2012Co-Authors: Gal Matijevic, Andrej Prsa, Jerome A Orosz, William F Welsh, S Bloemen, Thomas BarclayAbstract:We present an automated classification of 2165 \textit{Kepler} eclipsing binary (EB) Light Curves that accompanied the second \textit{Kepler} data release. The Light Curves are classified using Locally Linear Embedding, a general nonlinear dimensionality reduction tool, into morphology types (detached, semi-detached, overcontact, ellipsoidal). The method, related to a more widely used Principal Component Analysis, produces a lower-dimensional representation of the input data while preserving local geometry and, consequently, the similarity between neighboring data points. We use this property to reduce the dimensionality in a series of steps to a one-dimensional manifold and classify Light Curves with a single parameter that is a measure of "detachedness" of the system. This fully automated classification correlates well with the manual determination of morphology from the data release, and also efficiently highLights any misclassified objects. Once a lower-dimensional projection space is defined, the classification of additional Light Curves runs in a negligible time and the method can therefore be used as a fully automated classifier in pipeline structures. The classifier forms a tier of the \textit{Kepler} EB pipeline that pre-processes Light Curves for the artificial intelligence based parameter estimator.
-
kepler presearch data conditioning i architecture and algorithms for error correction in kepler Light Curves
arXiv: Instrumentation and Methods for Astrophysics, 2012Co-Authors: Martin C Stumpe, Thomas Barclay, Jeffrey C Smith, Jeffrey Van Cleve, Joseph D Twicken, Michael N Fanelli, Forrest R Girouard, Jon M Jenkins, Jeffery J Kolodziejczak, Sean MccauliffAbstract: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.
Eric Agol - One of the best experts on this subject based on the ideXlab platform.
-
everest pixel level decorrelation of k2 Light Curves
The Astronomical Journal, 2016Co-Authors: Daniel Foremanmackey, Rodrigo Luger, Eric Agol, Ethan Kruse, Rory Barnes, Andrew C Becker, Drake DemingAbstract:We present EPIC Variability Extraction and Removal for Exoplanet Science Targets (EVEREST), an open-source pipeline for removing instrumental noise from K2 Light Curves. EVEREST employs a variant of pixel level decorrelation to remove systematics introduced by the spacecraft's pointing error and a Gaussian process to capture astrophysical variability. We apply EVEREST to all K2 targets in campaigns 0–7, yielding Light Curves with precision comparable to that of the original Kepler mission for stars brighter than , and within a factor of two of the Kepler precision for fainter targets. We perform cross-validation and transit injection and recovery tests to validate the pipeline, and compare our Light Curves to the other de-trended Light Curves available for download at the MAST High Level Science Products archive. We find that EVEREST achieves the highest average precision of any of these pipelines for unsaturated K2 stars. The improved precision of these Light Curves will aid in exoplanet detection and characterization, investigations of stellar variability, asteroseismology, and other photometric studies. The EVEREST pipeline can also easily be applied to future surveys, such as the TESS mission, to correct for instrumental systematics and enable the detection of low signal-to-noise transiting exoplanets. The EVEREST Light Curves and the source code used to generate them are freely available online.
-
everest pixel level decorrelation of k2 Light Curves
arXiv: Earth and Planetary Astrophysics, 2016Co-Authors: Daniel Foremanmackey, Rodrigo Luger, Eric Agol, Ethan Kruse, Rory Barnes, Andrew C Becker, Drake DemingAbstract:We present EVEREST, an open-source pipeline for removing instrumental noise from K2 Light Curves. EVEREST employs a variant of pixel level decorrelation (PLD) to remove systematics introduced by the spacecraft's pointing error and a Gaussian process (GP) to capture astrophysical variability. We apply EVEREST to all K2 targets in campaigns 0-7, yielding Light Curves with precision comparable to that of the original Kepler mission for stars brighter than $K_p \approx 13$, and within a factor of two of the Kepler precision for fainter targets. We perform cross-validation and transit injection and recovery tests to validate the pipeline, and compare our Light Curves to the other de-trended Light Curves available for download at the MAST High Level Science Products archive. We find that EVEREST achieves the highest average precision of any of these pipelines for unsaturated K2 stars. The improved precision of these Light Curves will aid in exoplanet detection and characterization, investigations of stellar variability, asteroseismology, and other photometric studies. The EVEREST pipeline can also easily be applied to future surveys, such as the TESS mission, to correct for instrumental systematics and enable the detection of low signal-to-noise transiting exoplanets. The EVEREST Light Curves and the source code used to generate them are freely available online.
-
analytic Light Curves for planetary transit searches
The Astrophysical Journal, 2002Co-Authors: Kaisey S Mandel, Eric AgolAbstract:We present exact analytic formulae for the eclipse of a star described by quadratic or nonlinear limb darkening. In the limit that the planet radius is less than a tenth of the stellar radius, we show that the exact Light curve can be well approximated by assuming the region of the star blocked by the planet has constant surface brightness. We apply these results to the Hubble Space Telescope observations of HD 209458, showing that the ratio of the planetary to stellar radii is 0.1207 ± 0.0003. These formulae give a fast and accurate means of computing Light Curves using limb-darkening coefficients from model atmospheres that should aid in the detection, simulation, and parameter fitting of planetary transits.
V Delia - One of the best experts on this subject based on the ideXlab platform.
-
optical and x ray rest frame Light Curves of the bat6 sample
Astronomy and Astrophysics, 2014Co-Authors: A Melandri, S Covino, D Rogantini, R Salvaterra, B Sbarufatti, Maria Grazia Bernardini, S Campana, P Davanzo, V DeliaAbstract:Aims. We present the rest-frame Light Curves in the optical and X-ray bands of an unbiased and complete sample of the Swift long gamma-ray bursts (GRBs), namely, the BAT6 sample.Methods. The unbiased BAT6 sample (consisting of 58 events) has the highest level of completeness in redshift (~95%), allowing us to compute the rest-frame X-ray and optical Light Curves for 55 and 47 objects, respectively. We compute the X-ray and optical luminosities, which accounte for any possible source of absorption (Galactic and intrinsic) that could affect the observed fluxes in these two bands.Results. We compare the behaviour observed in the X-ray to that in the optical bands to assess the relative contribution of the emission during the prompt and afterglow phases. We unarguably demonstrate that rest-frame optical luminosity distribution of the GRBs is not bimodal and is clustered around the mean value Log(LR) = 29.9 ± 0.8 when estimated at a rest-frame time of 12 h. This is in contrast to what is found in previous works and confirms that the GRB population has an intrinsic unimodal luminosity distribution. For more than 70% of the events, the rest-frame Light Curves in the X-ray and optical bands have a different evolution, indicating distinct emitting regions and/or mechanisms. The X-ray Light Curves, which are normalised to the GRB isotropic energy (Eiso), provide evidence for X-ray emission that is still powered by the prompt emission until late times (~hours after the burst event). On the other hand, the same test performed for the Eiso-normalised optical Light Curves shows that the optical emission is a better proxy of the afterglow emission from early to late times.
-
optical and x ray rest frame Light Curves of the bat6 sample
arXiv: High Energy Astrophysical Phenomena, 2014Co-Authors: A Melandri, S Covino, D Rogantini, R Salvaterra, B Sbarufatti, Maria Grazia Bernardini, S Campana, P Davanzo, V DeliaAbstract:We present the rest-frame Light Curves in the optical and X-ray bands of an unbiased and complete sample of Swift long Gamma-Ray Bursts (GRBs), namely the BAT6 sample. The unbiased BAT6 sample (consisting of 58 events) has the highest level of completeness in redshift ($\sim$ 95%), allowing us to compute the rest-frame X-ray and optical Light Curves for 55 and 47 objects, respectively. We compute the X-ray and optical luminosities accounting for any possible source of absorption (Galactic and intrinsic) that could affect the observed fluxes in these two bands. We compare the behaviour observed in the X-ray and in the optical bands to assess the relative contribution of the emission during the prompt and afterglow phases. We unarguably demonstrate that the GRBs rest-frame optical luminosity distribution is not bimodal, being rather clustered around the mean value Log(L$_{R}$) = 29.9 $\pm$ 0.8 when estimated at a rest frame time of 12 hr. This is in contrast with what found in previous works and confirms that the GRB population has an intrinsic unimodal luminosity distribution. For more than 70% of the events the rest-frame Light Curves in the X-ray and optical bands have a different evolution, indicating distinct emitting regions and/or mechanisms. The X-ray Light Curves normalised to the GRB isotropic energy (E$_{\rm iso}$), provide evidence for X-ray emission still powered by the prompt emission until late times ($\sim$ hours after the burst event). On the other hand, the same test performed for the E$_{\rm iso}$-normalised optical Light Curves shows that the optical emission is a better proxy of the afterglow emission from early to late times.
D Rogantini - One of the best experts on this subject based on the ideXlab platform.
-
optical and x ray rest frame Light Curves of the bat6 sample
Astronomy and Astrophysics, 2014Co-Authors: A Melandri, S Covino, D Rogantini, R Salvaterra, B Sbarufatti, Maria Grazia Bernardini, S Campana, P Davanzo, V DeliaAbstract:Aims. We present the rest-frame Light Curves in the optical and X-ray bands of an unbiased and complete sample of the Swift long gamma-ray bursts (GRBs), namely, the BAT6 sample.Methods. The unbiased BAT6 sample (consisting of 58 events) has the highest level of completeness in redshift (~95%), allowing us to compute the rest-frame X-ray and optical Light Curves for 55 and 47 objects, respectively. We compute the X-ray and optical luminosities, which accounte for any possible source of absorption (Galactic and intrinsic) that could affect the observed fluxes in these two bands.Results. We compare the behaviour observed in the X-ray to that in the optical bands to assess the relative contribution of the emission during the prompt and afterglow phases. We unarguably demonstrate that rest-frame optical luminosity distribution of the GRBs is not bimodal and is clustered around the mean value Log(LR) = 29.9 ± 0.8 when estimated at a rest-frame time of 12 h. This is in contrast to what is found in previous works and confirms that the GRB population has an intrinsic unimodal luminosity distribution. For more than 70% of the events, the rest-frame Light Curves in the X-ray and optical bands have a different evolution, indicating distinct emitting regions and/or mechanisms. The X-ray Light Curves, which are normalised to the GRB isotropic energy (Eiso), provide evidence for X-ray emission that is still powered by the prompt emission until late times (~hours after the burst event). On the other hand, the same test performed for the Eiso-normalised optical Light Curves shows that the optical emission is a better proxy of the afterglow emission from early to late times.
-
optical and x ray rest frame Light Curves of the bat6 sample
arXiv: High Energy Astrophysical Phenomena, 2014Co-Authors: A Melandri, S Covino, D Rogantini, R Salvaterra, B Sbarufatti, Maria Grazia Bernardini, S Campana, P Davanzo, V DeliaAbstract:We present the rest-frame Light Curves in the optical and X-ray bands of an unbiased and complete sample of Swift long Gamma-Ray Bursts (GRBs), namely the BAT6 sample. The unbiased BAT6 sample (consisting of 58 events) has the highest level of completeness in redshift ($\sim$ 95%), allowing us to compute the rest-frame X-ray and optical Light Curves for 55 and 47 objects, respectively. We compute the X-ray and optical luminosities accounting for any possible source of absorption (Galactic and intrinsic) that could affect the observed fluxes in these two bands. We compare the behaviour observed in the X-ray and in the optical bands to assess the relative contribution of the emission during the prompt and afterglow phases. We unarguably demonstrate that the GRBs rest-frame optical luminosity distribution is not bimodal, being rather clustered around the mean value Log(L$_{R}$) = 29.9 $\pm$ 0.8 when estimated at a rest frame time of 12 hr. This is in contrast with what found in previous works and confirms that the GRB population has an intrinsic unimodal luminosity distribution. For more than 70% of the events the rest-frame Light Curves in the X-ray and optical bands have a different evolution, indicating distinct emitting regions and/or mechanisms. The X-ray Light Curves normalised to the GRB isotropic energy (E$_{\rm iso}$), provide evidence for X-ray emission still powered by the prompt emission until late times ($\sim$ hours after the burst event). On the other hand, the same test performed for the E$_{\rm iso}$-normalised optical Light Curves shows that the optical emission is a better proxy of the afterglow emission from early to late times.
