K2SC: Flexible systematics correction and detrending of K2 light curves using Gaussian Process regression

We present k2sc (K2 Systematics Correction), a python pipeline to model instrumental systematics and astrophysical variability in light curves from the K2 mission. k2sc uses Gaussian Process regression to model position-dependent systematics and time-dependent variability simultaneously, enabling the user to remove both (e.g. for transit searches) or to remove systematics while preserving variability (for variability studies). For periodic variables, k2sc automatically computes estimates of the period, amplitude and evolution time-scale of the variability. We apply k2sc to publicly available K2 data from Campaigns 3-5 showing that we obtain photometric precision approaching that of the original Kepler mission. We compare our results to other publicly available K2 pipelines, showing that we obtain similar or better results, on average. We use transit injection and recovery tests to evaluate the impact of k2sc on planetary transit searches in K2 Pre-search Data Conditioning data, for planet-to-star radius ratios down to R p /R * = 0.01 and periods up to P = 40 d, and show that k2sc significantly improves the ability to distinguish between true and false detections, particularly for small planets. k2sc can be run automatically on many light curves, or manually tailored for specific objects such as pulsating stars or large amplitude eclipsing binaries. It can be run on ASCII and FITS light-curve files, regardless of their origin. Both the code and the processed light curves are publicly available, and we provide instructions for downloading and using them. The methodology used by k2sc will be applicable to future transit search missions such as TESS and PLATO

K2SC: Flexible systematics correction and detrending of K2 light curves using Gaussian Process regression

We present k2sc (K2 Systematics Correction), a python pipeline to model instrumental systematics and astrophysical variability in light curves from the K2 mission. k2sc uses Gaussian Process regression to model position-dependent systematics and time-dependent variability simultaneously, enabling the user to remove both (e.g. for transit searches) or to remove systematics while preserving variability (for variability studies). For periodic variables, k2sc automatically computes estimates of the period, amplitude and evolution time-scale of the variability. We apply k2sc to publicly available K2 data from Campaigns 3-5 showing that we obtain photometric precision approaching that of the original Kepler mission. We compare our results to other publicly available K2 pipelines, showing that we obtain similar or better results, on average. We use transit injection and recovery tests to evaluate the impact of k2sc on planetary transit searches in K2 Pre-search Data Conditioning data, for planet-to-star radius ratios down to R p /R * = 0.01 and periods up to P = 40 d, and show that k2sc significantly improves the ability to distinguish between true and false detections, particularly for small planets. k2sc can be run automatically on many light curves, or manually tailored for specific objects such as pulsating stars or large amplitude eclipsing binaries. It can be run on ASCII and FITS light-curve files, regardless of their origin. Both the code and the processed light curves are publicly available, and we provide instructions for downloading and using them. The methodology used by k2sc will be applicable to future transit search missions such as TESS and PLATO

Modelling cosmic radiation events in the tree-ring radiocarbon record

Peer reviewed: TrueFunder: Big Questions Institute Annually resolved measurements of the radiocarbon content in tree-rings have revealed rare sharp rises in carbon-14 production. These ‘Miyake events’ are likely produced by rare increases in cosmic radiation from the Sun or other energetic astrophysical sources. The radiocarbon produced is not only circulated through the Earth’s atmosphere and oceans, but also absorbed by the biosphere and locked in the annual growth rings of trees. To interpret high-resolution tree-ring radiocarbon measurements therefore necessitates modelling the entire global carbon cycle. Here, we introduce ‘ ticktack ’ ( https://github.com/SharmaLlama/ticktack/ ), the first open-source Python package that connects box models of the carbon cycle with modern Bayesian inference tools. We use this to analyse all public annual   14 C tree data, and infer posterior parameters for all six known Miyake events. They do not show a consistent relationship to the solar cycle, and several display extended durations that challenge either astrophysical or geophysical models. </jats:p

The Kepler Smear Campaign: Light curves for 102 very bright stars

We present the first data release of the Kepler Smear Campaign, using collateral 'smear' data obtained in the Kepler four-year mission to reconstruct light curves of 102 stars too bright to have been otherwise targeted. We describe the pipeline developed to extract and calibrate these light curves, and show that we attain photometric precision comparable to stars analyzed by the standard pipeline in the nominal Kepler mission. In this paper, aside from publishing the light curves of these stars, we focus on 66 red giants for which we detect solar-like oscillations, characterizing 33 of these in detail with spectroscopic chemical abundances and asteroseismic masses as benchmark stars. We also classify the whole sample, finding nearly all to be variable, with classical pulsations and binary effects. All source code, light curves, TRES spectra, and asteroseismic and stellar parameters are publicly available as a Kepler legacy sample

Beyond the Kepler/K2 bright limit: variability in the seven brightest members of the Pleiades

The most powerful tests of stellar models come from the brightest stars in the sky, for which complementary techniques, such as astrometry, asteroseismology, spectroscopy, and interferometry can be combined. The K2 Mission is providing a unique opportunity to obtain high-precision photometric time series for bright stars along the ecliptic. However, bright targets require a large number of pixels to capture the entirety of the stellar flux, and bandwidth restrictions limit the number and brightness of stars that can be observed. To overcome this, we have developed a new photometric technique, that we call halo photometry, to observe very bright stars using a limited number of pixels. Halo photometry is simple, fast and does not require extensive pixel allocation, and will allow us to use K2 and other photometric missions, such as TESS, to observe very bright stars for asteroseismology and to search for transiting exoplanets. We apply this method to the seven brightest stars in the Pleiades open cluster. Each star exhibits variability; six of the stars show what are most-likely slowly pulsating B-star (SPB) pulsations, with amplitudes ranging from 20 to 2000 ppm. For the star Maia, we demonstrate the utility of combining K2 photometry with spectroscopy and interferometry to show that it is not a 'Maia variable', and to establish that its variability is caused by rotational modulation of a large chemical spot on a 10 d time scale

Beyond the Kepler/K2 bright limit: variability in the seven brightest members of the Pleiades

The most powerful tests of stellar models come from the brightest stars in the sky, for which complementary techniques, such as astrometry, asteroseismology, spectroscopy, and interferometry can be combined. The K2 Mission is providing a unique opportunity to obtain high-precision photometric time series for bright stars along the ecliptic. However, bright targets require a large number of pixels to capture the entirety of the stellar flux, and bandwidth restrictions limit the number and brightness of stars that can be observed. To overcome this, we have developed a new photometric technique, that we call halo photometry, to observe very bright stars using a limited number of pixels. Halo photometry is simple, fast and does not require extensive pixel allocation, and will allow us to use K2 and other photometric missions, such as TESS, to observe very bright stars for asteroseismology and to search for transiting exoplanets. We apply this method to the seven brightest stars in the Pleiades open cluster. Each star exhibits variability; six of the stars show what are most-likely slowly pulsating B-star (SPB) pulsations, with amplitudes ranging from 20 to 2000 ppm. For the star Maia, we demonstrate the utility of combining K2 photometry with spectroscopy and interferometry to show that it is not a 'Maia variable', and to establish that its variability is caused by rotational modulation of a large chemical spot on a 10 d time scale