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Register a new userRandom Forests applied to High Precision Photometry Analysis with Spitzer IRAC
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We present a new method employing machine learning techniques for measuring astrophysical features by correcting systematics in IRAC high precision photometry using Random Forests. The main systematic in IRAC light curve data is position changes due to unavoidable telescope motions coupled with an intrapixel response function. We aim to use the large amount of publicly available calibration data for the single pixel used for this type of work (the sweet spot pixel) to make a fast, easy to use, accurate correction to science data. This correction on calibration data has the advantage of using an independent dataset instead of using the science data on itself, which has the disadvantage of including astrophysical variations. After focusing on feature engineering and hyperparameter optimization, we show that a boosted random forest model can reduce the data such that we measure the median of ten archival eclipse observations of XO-3b to be 1459 +- 200 parts per million. This is a comparable depth to the average of those in the literature done by seven different methods, however the spread in measurements is 30-100% larger than those literature values, depending on the reduction method. We also caution others attempting similar methods to check their results with the fiducial dataset of XO-3b as we were also able to find models providing initially great scores on their internal test datasets but whose results significantly underestimated the eclipse depth of that planet.
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ASTERIA (Arcsecond Space Telescope Enabling Research In Astrophysics) is a 6U CubeSat space telescope (10 cm x 20 cm x 30 cm, 10 kg). ASTERIAs primary mission objective was demonstrating two key technologies for reducing systematic noise in photometric observations: high-precision pointing control and high-stabilty thermal control. ASTERIA demonstrated 0.5 arcsecond RMS pointing stability and $pm$10 milliKelvin thermal control of its camera payload during its primary mission, a significant improvement in pointing and thermal performance compared to other spacecraft in ASTERIAs size and mass class. ASTERIA launched in August 2017 and deployed from the International Space Station (ISS) November 2017. During the prime mission (November 2017 -- February 2018) and the first extended mission that followed (March 2018 - May 2018), ASTERIA conducted opportunistic science observations which included collection of photometric data on 55 Cancri, a nearby exoplanetary system with a super-Earth transiting planet. The 55 Cancri data were reduced using a custom pipeline to correct CMOS detector column-dependent gain variations. A Markov Chain Monte Carlo (MCMC) approach was used to simultaneously detrend the photometry using a simple baseline model and fit a transit model. ASTERIA made a marginal detection of the known transiting exoplanet 55 Cancri e ($sim2$~Rearth), measuring a transit depth of $374pm170$ ppm. This is the first detection of an exoplanet transit by a CubeSat. The successful detection of super-Earth 55 Cancri e demonstrates that small, inexpensive spacecraft can deliver high-precision photometric measurements.
Ground-based exoplanet surveys such as SuperWASP, HATNet and KELT have discovered close to two hundred transiting extrasolar planets in the past several years. The strategy of these surveys is to look at a large field of view and measure the brightnesses of its bright stars to around half a percent per point precision, which is adequate for detecting hot Jupiters. Typically, these surveys use CCD detectors to achieve high precision photometry. These CCDs, however, are expensive relative to other consumer-grade optical imaging devices, such as digital single-lens reflex cameras (DSLRs). We look at the possibility of using a digital single-lens reflex camera for precision photometry. Specifically, we used a Canon EOS 60D camera that records light in 3 colors simultaneously. The DSLR was integrated into the HATNet survey and collected observations for a month, after which photometry was extracted for 6600 stars in a selected stellar field. We found that the DSLR achieves a best-case median absolute deviation (MAD) of 4.6 mmag per 180 s exposure when the DSLR color channels are combined, and 1000 stars are measured to better than 10 mmag (1%). Also, we achieve 10,mmag or better photometry in the individual colors. This is good enough to detect transiting hot Jupiters. We performed a candidate search on all stars and found four candidates, one of which is KELT-3b, the only known transiting hot Jupiter in our selected field. We conclude that the Canon 60D is a cheap, lightweight device capable of useful photometry in multiple colors.
Photometric and astrometric monitoring of directly imaged exoplanets will deliver unique insights into their rotational periods, the distribution of cloud structures, weather, and orbital parameters. As the host star is occulted by the coronagraph, a speckle grid (SG) is introduced to serve as astrometric and photometric reference. Speckle grids are implemented as diffractive pupil-plane optics that generate artificial speckles at known location and brightness. Their performance is limited by the underlying speckle halo caused by evolving uncorrected wavefront errors. The speckle halo will interfere with the coherent SGs, affecting their photometric and astrometric precision. Our aim is to show that by imposing opposite amplitude or phase modulation on the opposite polarization states, a SG can be instantaneously incoherent with the underlying halo, greatly increasing the precision. We refer to these as vector speckle grids (VSGs). We derive analytically the mechanism by which the incoherency arises and explore the performance gain in idealised simulations under various atmospheric conditions. We show that the VSG is completely incoherent for unpolarized light and that the fundamental limiting factor is the cross-talk between the speckles in the grid. In simulation, we find that for short-exposure images the VSG reaches a $sim$0.3-0.8% photometric error and $sim$$3-10cdot10^{-3}$ $lambda/D$ astrometric error, which is a performance increase of a factor $sim$20 and $sim$5, respectively. Furthermore, we outline how VSGs could be implemented using liquid-crystal technology to impose the geometric phase on the circular polarization states. The VSG is a promising new method for generating a photometric and astrometric reference SG that has a greatly increased astrometric and photometric precision.
We develop a new photometry algorithm that is optimized for $Spitzer$ time series in crowded fields and that is particularly adapted to faint and/or heavily blended targets. We apply this to the 170 targets from the 2015 $Spitzer$ microlensing campaign and present the results of three variants of this algorithm in an online catalog. We present detailed accounts of the application of this algorithm to two difficult cases, one very faint and the other very crowded. Several of $Spitzer$s instrumental characteristics that drive the specific features of this algorithm are shared by $Kepler$ and $WFIRST$, implying that these features may prove to be a useful starting point for algorithms designed for microlensing campaigns by these other missions.
The dominant non-instrumental background source for space-based infrared observatories is the zo- diacal light. We present Spitzer Infrared Array Camera (IRAC) measurements of the zodiacal light at 3.6, 4.5, 5.8, and 8.0 {mu}m, taken as part of the instrument calibrations. We measure the changing surface brightness levels in approximately weekly IRAC observations near the north ecliptic pole (NEP) over the period of roughly 8.5 years. This long time baseline is crucial for measuring the annual sinusoidal variation in the signal levels due to the tilt of the dust disk with respect to the ecliptic, which is the true signal of the zodiacal light. This is compared to both Cosmic Background Explorer Diffuse Infrared Background Experiment (COBE DIRBE) data and a zodiacal light model based thereon. Our data show a few percent discrepancy from the Kelsall et al. (1998) model including a potential warping of the interplanetary dust disk and a previously detected overdensity in the dust cloud directly behind the Earth in its orbit. Accurate knowledge of the zodiacal light is important for both extragalactic and Galactic astronomy including measurements of the cosmic infrared background, absolute measures of extended sources, and comparison to extrasolar interplanetary dust models. IRAC data can be used to further inform and test future zodiacal light models.
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