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Register a new userWavelet-based filter methods to detect small transiting planets in stellar light curves
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Strong variations of any kind and causes within a stellar light curve may prohibit the detection of transits, particularly of faint or shallow transits caused by small planets passing in front of the stellar disk. The success of future space telescopes with the goal for finding small planets will be based on proper filtering, analysis and detection of transits in perturbed stellar light curves. The wavelet-based filter methods VARLET and PHALET, developed by RIU-PF, in combination with the transit detection software package EXOTRANS allow the extraction of (i) strong stellar variations, (ii) instrument caused spikes and singularities within a stellar light curve, (iii) already detected planetary or stellar binary transits in order to be able to search for further planets or planets about binary stars. Once the light curve is filtered, EXOTRANS is able to search efficiently, effectively and precisely for transits, in particular for faint transits.
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We report the discovery of two super-Earth-sized planets transiting the bright (V = 8.94, K = 7.07) nearby late G-dwarf HD 3167, using data collected by the K2 mission. The inner planet, HD 3167 b, has a radius of 1.6 R_e and an ultra-short orbital period of only 0.96 days. The outer planet, HD 3167 c, has a radius of 2.9 R_e and orbits its host star every 29.85 days. At a distance of just 45.8 +/- 2.2 pc, HD 3167 is one of the closest and brightest stars hosting multiple transiting planets, making HD 3167 b and c well suited for follow-up observations. The star is chromospherically inactive with low rotational line-broadening, ideal for radial velocity observations to measure the planets masses. The outer planet is large enough that it likely has a thick gaseous envelope which could be studied via transmission spectroscopy. Planets transiting bright, nearby stars like HD 3167 are valuable objects to study leading up to the launch of the James Webb Space Telescope.
We present an analytic model to estimate the capabilities of space missions dedicated to the search for biosignatures in the atmosphere of rocky planets located in the habitable zone of nearby stars. Relations between performance and mission parameters such as mirror diameter, distance to targets, and radius of planets, are obtained. Two types of instruments are considered: coronagraphs observing in the visible, and nulling interferometers in the thermal infrared. Missions considered are: single-pupil coronagraphs with a 2.4 m primary mirror, and formation flying interferometers with 4 x 0.75 m collecting mirrors. The numbers of accessible planets are calculated as a function of {eta}earth. When Kepler gives its final estimation for {eta}earth, the model will permit a precise assessment of the potential of each instrument. Based on current estimations, {eta}earth = 10% around FGK stars and 50% around M stars, the coronagraph could study in spectroscopy only ~1.5 relevant planets, and the interferometer ~14.0. These numbers are obtained under the major hypothesis that the exozodiacal light around the target stars is low enough for each instrument. In both cases, a prior detection of planets is assumed and a target list established. For the long-term future, building both types of spectroscopic instruments, and using them on the same targets, will be the optimal solution because they provide complementary information. But as a first affordable space mission, the interferometer looks the more promising in term of biosignature harvest.
In this note we present the starry_process code, which implements an interpretable Gaussian process (GP) for modeling variability in stellar light curves. As dark starspots rotate in and out of view, the total flux received from a distant star will change over time. Unresolved flux time series therefore encode information about the spatial structure of features on the stellar surface. The starry_process software package allows one to easily model the flux variability due to starspots, whether one is interested in understanding the properties of these spots or marginalizing over the stellar variability when it is treated as a nuisance signal. The main difference between the GP implemented here and typical GPs used to model stellar variability is the explicit dependence of our GP on physical properties of the star, such as its period, inclination, and limb darkening coefficients, and on properties of the spots, such as their radius and latitude distributions. This code is the Python implementation of the interpretable GP algorithm developed in Luger, Foreman-Mackey, and Hedges (2021).
Instrumental data are affected by systematic effects that dominate the errors and can be relevant when searching for small signals. This is the case of the K2 mission, a follow up of the Kepler mission, that, after a failure on two reaction wheels, has lost its stability properties rising strongly the systematics in the light curves and reducing its photometric precision. In this work, we have developed a general method to remove time related systematics from a set of light curves, that has been applied to K2 data. The method uses the Principal Component Analysis to retrieve the correlation between the light curves due to the systematics and to remove its effect without knowing any information other than the data itself. We have applied the method to all the K2 campaigns available at the Mikulski Archive for Space Telescopes, and we have tested the effectiveness of the procedure and its capability in preserving the astrophysical signal on a few transits and on eclipsing binaries. One product of this work is the identification of stable sources along the ecliptic plane that can be used as photometric calibrators for the upcoming Atmospheric Remote-sensing Exoplanet Large-survey mission.
Theoretical predictions suggest that the distribution of planets in very young stars could be very different to that typically observed in Gyr old systems that are the current focus of radial velocity surveys. However, the detection of planets around young stars is hampered by the increased stellar activity associated with young stars, the signatures of which can bias the detection of planets. In this paper we place realistic limitations on the possibilities for detecting planets around young active G and K dwarfs. The models of stellar activity based on tomographic imaging of the G dwarf HD 141943 and the K1 dwarf AB Dor and also include contributions from plage and many small random starspots. Our results show that the increased stellar activity levels present on young Solar-type stars strongly impacts the detection of Earth-mass and Jupiter mass planets and that the degree of activity jitter is directly correlated with stellar vsinis. We also show that for G and K dwarfs, the distribution of activity in individual stars is more important than the differences in induced radial velocities as a function of spectral type. We conclude that Jupiter mass planets can be detected close-in around fast-rotating young active stars, Neptune-mass planets around moderate rotators and that Super-Earths are only detectable around very slowly rotating stars. The effects of an increase in stellar activity jitter by observing younger stars can be compensated for by extending the observational base-line to at least 100 epochs.
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