Integrating light-curve and atmospheric modelling of transiting exoplanets. (arXiv:1811.04686v2 [astro-ph.EP] UPDATED)
<a href="http://arxiv.org/find/astro-ph/1/au:+Yip_K/0/1/0/all/0/1">Kai Hou Yip</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Waldmann_I/0/1/0/all/0/1">Ingo P. Waldmann</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Tsiaras_A/0/1/0/all/0/1">Angelos Tsiaras</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Tinetti_G/0/1/0/all/0/1">Giovanna Tinetti</a>

Spectral retrieval techniques are currently our best tool to interpret the
observed exoplanet atmospheric data. Said techniques retrieve the optimal
atmospheric components and parameters by identifying the best fit to an
observed transmission/emission spectrum. Over the past decade, our
understanding of remote worlds in our galaxy has flourished thanks to the use
of increasingly sophisticated spectral retrieval techniques and the collective
effort of the community working on exoplanet atmospheric models. A new
generation of instruments in space and from the ground is expected to deliver
higher quality data in the next decade, it is therefore paramount to upgrade
current models and improve their reliability, completeness and numerical speed
with which they can be run. In this paper, we address the issue of reliability
of the results provided by retrieval models in the presence of systematics of
unknown origin. More specifically, we demonstrate that if we fit directly
individual light-curves at different wavelengths (L-retrieval), instead of
fitting transit or eclipse depths, as it is currently done (S-retrieval), the
results obtained are more robust against astrophysical and instrumental noise.
This new approach is tested, in particular, when discrepant simulated
observations from HST/WFC3 and Spitzer/IRAC are combined. We find that while
S-retrievals converge to an incorrect solution without any warning,
L-retrievals are able to identify potential discrepancies between the
data-sets.

Spectral retrieval techniques are currently our best tool to interpret the
observed exoplanet atmospheric data. Said techniques retrieve the optimal
atmospheric components and parameters by identifying the best fit to an
observed transmission/emission spectrum. Over the past decade, our
understanding of remote worlds in our galaxy has flourished thanks to the use
of increasingly sophisticated spectral retrieval techniques and the collective
effort of the community working on exoplanet atmospheric models. A new
generation of instruments in space and from the ground is expected to deliver
higher quality data in the next decade, it is therefore paramount to upgrade
current models and improve their reliability, completeness and numerical speed
with which they can be run. In this paper, we address the issue of reliability
of the results provided by retrieval models in the presence of systematics of
unknown origin. More specifically, we demonstrate that if we fit directly
individual light-curves at different wavelengths (L-retrieval), instead of
fitting transit or eclipse depths, as it is currently done (S-retrieval), the
results obtained are more robust against astrophysical and instrumental noise.
This new approach is tested, in particular, when discrepant simulated
observations from HST/WFC3 and Spitzer/IRAC are combined. We find that while
S-retrievals converge to an incorrect solution without any warning,
L-retrievals are able to identify potential discrepancies between the
data-sets.

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