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Register a new userExoplanet Atmospheres and Giant Ground-Based Telescopes
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I.J.M. Crossfield
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The study of extrasolar planets has rapidly expanded to encompass the search for new planets, measurements of sizes and masses, models of planetary interiors, planetary demographics and occurrence frequencies, the characterization of planetary orbits and dynamics, and studies of these worlds complex atmospheres. Our insights into exoplanets dramatically advance whenever improved tools and techniques become available, and surely the largest tools now being planned are the optical/infrared Extremely Large Telescopes (ELTs). Two themes summarize the advantages of atmospheric studies with the ELTs: high angular resolution when operating at the diffraction limit and high spectral resolution enabled by the unprecedented collecting area of these large telescopes. This brief review describes new opportunities afforded by the ELTs to study the composition, structure, dynamics, and evolution of these planets atmospheres, while specifically focusing on some of the most compelling atmospheric science cases for four qualitatively different planet populations: highly irradiated gas giants, young, hot giant planets, old, cold gas giants, and small planets and Earth analogs.
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Imaging rocky planets in reflected light, a key focus of future NASA missions and ELTs, requires advanced wavefront control to maintain a deep, temporally correlated null of stellar halo at just several diffraction beam widths. We discuss development of Linear Dark Field Control (LDFC) to achieve this aim. We describe efforts to test spatial LDFC in a laboratory setting for the first time, using the Ames Coronagraph Experiment (ACE) testbed. Our preliminary results indicate that spatial LDFC is a promising method focal-plane wavefront control method capable of maintaining a static dark hole, at least at contrasts relevant for imaging mature planets with 30m-class telescopes.
Direct imaging and spectral characterization of exoplanets using extreme adaptive optics (ExAO) is a key science goal of future extremely large telescopes and space observatories. However, quasi-static wavefront errors will limit the sensitivity of this endeavor. Additional limitations for ground-based telescopes arise from residual AO-corrected atmospheric wavefront errors, generating millisecond-lifetime speckles that average into a halo over a long exposure. A solution to both of these problems is to use the science camera of an ExAO system as a wavefront sensor to perform a fast measurement and correction method to minimize these aberrations as soon as they are detected. We develop the framework for one such method based on the self-coherent camera (SCC) to be applied to ground-based telescopes, called Fast Atmospheric SCC Technique (FAST). We show that with the use of a specially designed coronagraph and coherent differential imaging algorithm, recording images every few milliseconds allows for a subtraction of atmospheric and static speckles while maintaining a close to unity algorithmic exoplanet throughput. Detailed simulations reach a contrast close to the photon noise limit after 30 seconds for a 1 % bandpass in H band on both 0$^text{th}$ and 5$^text{th}$ magnitude stars. For the 5th magnitude case, this is about 110 times better in raw contrast than what is currently achieved from ExAO instruments if we extrapolate for an hour of observing time, illustrating that sensitivity improvement from this method could play an essential role in the future detection and characterization of lower mass exoplanets.
We outline the important role that ground-based, Doppler monitoring of exoplanetary systems will play in advancing our theories of planet formation and dynamical evolution. A census of planetary systems requires a well designed survey to be executed over the course of a decade or longer. A coordinated survey to monitor several thousand targets each at ~1000 epochs (~3-5 million new observations) will require roughly 40 dedicated spectrographs. We advocate for improvements in data management, data sharing, analysis techniques, and software testing, as well as possible changes to the funding structures for exoplanet science.
The Characterising Exoplanet Satellite (CHEOPS) is a space mission designed to perform photometric observations of bright stars to obtain precise radii measurements of transiting planets. The high-precision photometry of CHEOPS relies on careful on-ground calibration of its payload. For that purpose, intensive pre-launch campaigns of measurements were carried out to calibrate the instrument and characterise its photometric performances. We report on main results of these campaigns, provide a complete analysis of data sets and estimate in-flight photometric performance by mean of end-to-end simulation. The on-ground photometric stability of the instrument is found to be of the order of 15 parts per million over 5 hours. Our end-to-end simulation shows that measurements of planet-to-star radii ratio with CHEOPS can be determined with a precision of 2% for a Neptune-size planet transiting a K-dwarf star and 5% for an Earth-size planet orbiting a Sun-like star. It corresponds to signal-to-noise ratios on the transit depths of 25 and 10 respectively, allowing the characterisation and detection of these planets. The pre-launch CHEOPS performances are shown to be compliant with the mission requirements.
exoplanet is a toolkit for probabilistic modeling of astronomical time series data, with a focus on observations of exoplanets, using PyMC3 (Salvatier et al., 2016). PyMC3 is a flexible and high-performance model-building language and inference engine that scales well to problems with a large number of parameters. exoplanet extends PyMC3s modeling language to support many of the custom functions and probability distributions required when fitting exoplanet datasets or other astronomical time series. While it has been used for other applications, such as the study of stellar variability, the primary purpose of exoplanet is the characterization of exoplanets or multiple star systems using time-series photometry, astrometry, and/or radial velocity. In particular, the typical use case would be to use one or more of these datasets to place constraints on the physical and orbital parameters of the system, such as planet mass or orbital period, while simultaneously taking into account the effects of stellar variability.
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