Spitzer/IRAC precision photometry: a machine learning approach

The largest source of noise in exoplanet and brown dwarf photometric time series made with Spitzer/IRAC is the coupling between intra-pixel gain variations and spacecraft pointing fluctuations. Observers typically correct for this systematic in science data by deriving an instrumental noise model simultaneously with the astrophysical light curve and removing the noise model. Such techniques for self-calibrating Spitzer photometric datasets have been extremely successful, and in many cases enabled near-photon-limited precision on exoplanet transit and eclipse depths. Self-calibration, however, can suffer from certain limitations: (1) temporal astrophysical signals can become aliased as part of the instrument model; (2) for some techniques adequate model estimation often requires a high degree of intra-pixel positional redundancy (multiple samples with nearby centroids) over long time spans; (3) many techniques do not account for sporadic high frequency telescope vibrations that smear out the point spread function. We have begun to build independent general-purpose intra-pixel systematics removal algorithms using three machine learning techniques: K-Nearest Neighbors (with kernel regression), Random Decision Forests, and Artificial Neural Networks. These methods remove many of the limitations of self-calibration: (1) they operate on a dedicated calibration database of approximately one million measurements per IRAC waveband (3.6 and 4.5 microns) of non-variable stars, and thus are independent of the time series science data to be corrected; (2) the database covers a large area of the "Sweet Spot, so the methods do not require positional redundancy in the science data; (3) machine learning techniques in general allow for flexibility in training with multiple, sometimes unorthodox, variables, including those that trace PSF smear. We focus in this report on the K-Nearest Neighbors with Kernel Regression technique. (Additional communications are in preparation describing Decision Forests and Neural Networks.

A comparative study of WASP-67b and HAT-P-38b from WFC3 data

Atmospheric temperature and planetary gravity are thought to be the main parameters affecting cloud formation in giant exoplanet atmospheres. Recent attempts to understand cloud formation have explored wide regions of the equilibrium temperature-gravity parameter space. In this study, we instead compare the case of two giant planets with nearly identical equilibrium temperature ($T_\mathrm{eq}$ $\sim 1050 \, \mathrm{K}$) and gravity ($g \sim 10 \, \mathrm{m \, s}^{-1})$. During $HST$ Cycle 23, we collected WFC3/G141 observations of the two planets, WASP-67 b and HAT-P-38 b. HAT-P-38 b, with mass 0.42 M$_\mathrm{J}$ and radius 1.4 $R_\mathrm{J}$, exhibits a relatively clear atmosphere with a clear detection of water. We refine the orbital period of this planet with new observations, obtaining $P = 4.6403294 \pm 0.0000055 \, \mathrm{d}$. WASP-67 b, with mass 0.27 M$_\mathrm{J}$ and radius 0.83 $R_\mathrm{J}$, shows a more muted water absorption feature than that of HAT-P-38 b, indicating either a higher cloud deck in the atmosphere or a more metal-rich composition. The difference in the spectra supports the hypothesis that giant exoplanet atmospheres carry traces of their formation history. Future observations in the visible and mid-infrared are needed to probe the aerosol properties and constrain the evolutionary scenario of these planets.Comment: 16 pages, 17 figures, 8 tables, accepted for publication in The Astronomical Journa

Starspot occultations in infrared transit spectroscopy: the case of WASP-52b

Stellar activity is one of the main obstacles to high-precision exoplanet observations and has motivated extensive studies in detection and characterization problems. Most efforts focused on unocculted starspots in optical transit spectrophotometry, while the impact of starspot crossings is assumed to be negligible in the near-infrared. Here, we present \textit{HST}/WFC3 transit observations of the active star WASP-52, hosting an inflated hot Jupiter, which present a possible starspot occultation signal. By using this data set as a benchmark, we investigated whether the masking of the transit profile distortion or modeling it with both a starspot model and a Gaussian process affects the shape of the transmission spectrum. Different methods produced spectra with the same shape and a robust detection of water vapor, and with $\lesssim 1 \sigma$ different reference radii for the planet. The solutions of all methods are in agreement and reached a similar level of precision. Our WFC3 light curve of WASP-52b hints that starspot crossings might become more problematic with \textit{JWST}'s higher sensitivity and complete coverage of the transit profile.Comment: 15 pages, 15 figures, 5 tables, data available onlin

Infrared Eclipses of the Strongly Irradiated Planet WASP-33b, and Oscillations of its Host Star

We observe two secondary eclipses of the strongly irradiated transiting planet WASP-33b in the Ks band, and one secondary eclipse each at 3.6- and 4.5 microns using Warm Spitzer. This planet orbits an A5V delta-Scuti star that is known to exhibit low amplitude non-radial p-mode oscillations at about 0.1-percent semi-amplitude. We detect stellar oscillations in all of our infrared eclipse data, and also in one night of observations at J-band out of eclipse. The oscillation amplitude, in all infrared bands except Ks, is about the same as in the optical. However, the stellar oscillations in Ks band have about twice the amplitude as seen in the optical, possibly because the Brackett-gamma line falls in this bandpass. We use our best-fit values for the eclipse depth, as well as the 0.9 micron eclipse observed by Smith et al., to explore possible states of the exoplanetary atmosphere, based on the method of Madhusudhan and Seager. On this basis we find two possible states for the atmospheric structure of WASP-33b. One possibility is a non-inverted temperature structure in spite of the strong irradiance, but this model requires an enhanced carbon abundance (C/O>1). The alternative model has solar composition, but an inverted temperature structure. Spectroscopy of the planet at secondary eclipse, using a spectral resolution that can resolve the water vapor band structure, should be able to break the degeneracy between these very different possible states of the exoplanetary atmosphere. However, both of those model atmospheres absorb nearly all of the stellar irradiance with minimal longitudinal re-distribution of energy, strengthening the hypothesis of Cowan et al. that the most strongly irradiated planets circulate energy poorly. Our measurement of the central phase of the eclipse yields e*cos(omega)=0.0003 +/-0.00013, which we regard as being consistent with a circular orbit.Comment: 23 pages, 9 figures, 3 tables, accepted for the Astrophysical Journa

Spitzer/IRAC precision photometry: a machine learning approach

The largest source of noise in exoplanet and brown dwarf photometric time series made with Spitzer/IRAC is the coupling between intra-pixel gain variations and spacecraft pointing fluctuations. Observers typically correct for this systematic in science data by deriving an instrumental noise model simultaneously with the astrophysical light curve and removing the noise model. Such techniques for self-calibrating Spitzer photometric datasets have been extremely successful, and in many cases enabled near-photon-limited precision on exoplanet transit and eclipse depths. Self-calibration, however, can suffer from certain limitations: (1) temporal astrophysical signals can become aliased as part of the instrument model; (2) for some techniques adequate model estimation often requires a high degree of intra-pixel positional redundancy (multiple samples with nearby centroids) over long time spans; (3) many techniques do not account for sporadic high frequency telescope vibrations that smear out the point spread function. We have begun to build independent general-purpose intra-pixel systematics removal algorithms using three machine learning techniques: K-Nearest Neighbors (with kernel regression), Random Decision Forests, and Artificial Neural Networks. These methods remove many of the limitations of self-calibration: (1) they operate on a dedicated calibration database of approximately one million measurements per IRAC waveband (3.6 and 4.5 microns) of non-variable stars, and thus are independent of the time series science data to be corrected; (2) the database covers a large area of the "Sweet Spot, so the methods do not require positional redundancy in the science data; (3) machine learning techniques in general allow for flexibility in training with multiple, sometimes unorthodox, variables, including those that trace PSF smear. We focus in this report on the K-Nearest Neighbors with Kernel Regression technique. (Additional communications are in preparation describing Decision Forests and Neural Networks.

Spitzer Transits of the Super-Earth GJ1214b and Implications for its Atmosphere

We observed the transiting super-Earth exoplanet GJ1214b using warm Spitzer at 4.5 μm wavelength during a 20 day quasi-continuous sequence in 2011 May. The goals of our long observation were to accurately define the infrared transit radius of this nearby super-Earth, to search for the secondary eclipse, and to search for other transiting planets in the habitable zone of GJ1214. We here report results from the transit monitoring of GJ1214b, including a reanalysis of previous transit observations by Désert et al. In total, we analyze 14 transits of GJ1214b at 4.5 μm, 3 transits at 3.6 μm, and 7 new ground-based transits in the I+z band. Our new Spitzer data by themselves eliminate cloudless solar composition atmospheres for GJ1214b, and methane-rich models from Howe & Burrows. Using our new Spitzer measurements to anchor the observed transit radii of GJ1214b at long wavelengths, and adding new measurements in I+z, we evaluate models from Benneke & Seager and Howe & Burrows using a χ^2 analysis. We find that the best-fit model exhibits an increase in transit radius at short wavelengths due to Rayleigh scattering. Pure water atmospheres are also possible. However, a flat line (no atmosphere detected) remains among the best of the statistically acceptable models, and better than pure water atmospheres. We explore the effect of systematic differences among results from different observational groups, and we find that the Howe & Burrows tholin-haze model remains the best fit, even when systematic differences among observers are considered

Transiting Exoplanet Studies and Community Targets for JWST's Early Release Science Program

The James Webb Space Telescope will revolutionize transiting exoplanet atmospheric science due to its capability for continuous, long-duration observations and its larger collecting area, spectral coverage, and spectral resolution compared to existing space-based facilities. However, it is unclear precisely how well JWST will perform and which of its myriad instruments and observing modes will be best suited for transiting exoplanet studies. In this article, we describe a prefatory JWST Early Release Science (ERS) program that focuses on testing specific observing modes to quickly give the community the data and experience it needs to plan more efficient and successful future transiting exoplanet characterization programs. We propose a multi-pronged approach wherein one aspect of the program focuses on observing transits of a single target with all of the recommended observing modes to identify and understand potential systematics, compare transmission spectra at overlapping and neighboring wavelength regions, confirm throughputs, and determine overall performances. In our search for transiting exoplanets that are well suited to achieving these goals, we identify 12 objects (dubbed "community targets") that meet our defined criteria. Currently, the most favorable target is WASP-62b because of its large predicted signal size, relatively bright host star, and location in JWST's continuous viewing zone. Since most of the community targets do not have well-characterized atmospheres, we recommend initiating preparatory observing programs to determine the presence of obscuring clouds/hazes within their atmospheres. Measurable spectroscopic features are needed to establish the optimal resolution and wavelength regions for exoplanet characterization. Other initiatives from our proposed ERS program include testing the instrument brightness limits and performing phase-curve observations.(Abridged)Comment: This is a white paper that originated from an open discussion at the Enabling Transiting Exoplanet Science with JWST workshop held November 16 - 18, 2015 at STScI (http://www.stsci.edu/jwst/science/exoplanets). Accepted for publication in PAS

A chemical survey of exoplanets with ARIEL

Thousands of exoplanets have now been discovered with a huge range of masses, sizes and orbits: from rocky Earth-like planets to large gas giants grazing the surface of their host star. However, the essential nature of these exoplanets remains largely mysterious: there is no known, discernible pattern linking the presence, size, or orbital parameters of a planet to the nature of its parent star. We have little idea whether the chemistry of a planet is linked to its formation environment, or whether the type of host star drives the physics and chemistry of the planet’s birth, and evolution. ARIEL was conceived to observe a large number (~1000) of transiting planets for statistical understanding, including gas giants, Neptunes, super-Earths and Earth-size planets around a range of host star types using transit spectroscopy in the 1.25–7.8 μm spectral range and multiple narrow-band photometry in the optical. ARIEL will focus on warm and hot planets to take advantage of their well-mixed atmospheres which should show minimal condensation and sequestration of high-Z materials compared to their colder Solar System siblings. Said warm and hot atmospheres are expected to be more representative of the planetary bulk composition. Observations of these warm/hot exoplanets, and in particular of their elemental composition (especially C, O, N, S, Si), will allow the understanding of the early stages of planetary and atmospheric formation during the nebular phase and the following few million years. ARIEL will thus provide a representative picture of the chemical nature of the exoplanets and relate this directly to the type and chemical environment of the host star. ARIEL is designed as a dedicated survey mission for combined-light spectroscopy, capable of observing a large and well-defined planet sample within its 4-year mission lifetime. Transit, eclipse and phase-curve spectroscopy methods, whereby the signal from the star and planet are differentiated using knowledge of the planetary ephemerides, allow us to measure atmospheric signals from the planet at levels of 10–100 part per million (ppm) relative to the star and, given the bright nature of targets, also allows more sophisticated techniques, such as eclipse mapping, to give a deeper insight into the nature of the atmosphere. These types of observations require a stable payload and satellite platform with broad, instantaneous wavelength coverage to detect many molecular species, probe the thermal structure, identify clouds and monitor the stellar activity. The wavelength range proposed covers all the expected major atmospheric gases from e.g. H2O, CO2, CH4 NH3, HCN, H2S through to the more exotic metallic compounds, such as TiO, VO, and condensed species. Simulations of ARIEL performance in conducting exoplanet surveys have been performed – using conservative estimates of mission performance and a full model of all significant noise sources in the measurement – using a list of potential ARIEL targets that incorporates the latest available exoplanet statistics. The conclusion at the end of the Phase A study, is that ARIEL – in line with the stated mission objectives – will be able to observe about 1000 exoplanets depending on the details of the adopted survey strategy, thus confirming the feasibility of the main science objectives.Peer reviewedFinal Published versio