Disintegrating Exoplanets: Creating Size Constraints by Statistically Peering Through the Debris. (arXiv:2111.12688v1 [astro-ph.EP])
<a href="http://arxiv.org/find/astro-ph/1/au:+Baka_K/0/1/0/all/0/1">Keith Baka</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Schlawin_E/0/1/0/all/0/1">Everett Schlawin</a>
We study two intriguing disintegrating exoplanets, Kepler-1520b and K2-22b,
and attempt to constrain the size of the underlying objects. These two planets
are being disintegrated by their host stars, spewing dust and debris pulled
from their surface into tails that trail and precede the exoplanet in its
orbit, making it difficult to discern the true nature of the object. We
attempted to peer through the dust cloud to put a constraint on the maximum
radii of these exoplanets. While previous studies have done this in the past by
selecting shallow transit events, we attempt a new statistical approach to
model the intrinsic astrophysical and photon noise distributions
simultaneously. We assume that the lightcurve flux distribution is distributed
as a convolution of a Gaussian photon noise component and a Raleigh
astrophysical component. The Raleigh curve has a finite flux maximum, which we
fit with a Hamiltonian Markov Chain. With these methods, a more accurate flux
maximum may be estimated, producing a more accurate and better final value for
the size of these exoplanets. To determine statistical significance, we used
the python package PyMC3 to find the posterior distribution for our data with
Gaussian, Rayleigh, and joint function curves and plotting it against our
collected flux.
After completing this analysis, we were unable to constrain the radii of the
exoplanets, as the forward scattering by dust dominates over dust extinction.
However, this does mean that we were able better able to constrain the
astrophysical variability and its maximum with our analysis.
We study two intriguing disintegrating exoplanets, Kepler-1520b and K2-22b,
and attempt to constrain the size of the underlying objects. These two planets
are being disintegrated by their host stars, spewing dust and debris pulled
from their surface into tails that trail and precede the exoplanet in its
orbit, making it difficult to discern the true nature of the object. We
attempted to peer through the dust cloud to put a constraint on the maximum
radii of these exoplanets. While previous studies have done this in the past by
selecting shallow transit events, we attempt a new statistical approach to
model the intrinsic astrophysical and photon noise distributions
simultaneously. We assume that the lightcurve flux distribution is distributed
as a convolution of a Gaussian photon noise component and a Raleigh
astrophysical component. The Raleigh curve has a finite flux maximum, which we
fit with a Hamiltonian Markov Chain. With these methods, a more accurate flux
maximum may be estimated, producing a more accurate and better final value for
the size of these exoplanets. To determine statistical significance, we used
the python package PyMC3 to find the posterior distribution for our data with
Gaussian, Rayleigh, and joint function curves and plotting it against our
collected flux.
After completing this analysis, we were unable to constrain the radii of the
exoplanets, as the forward scattering by dust dominates over dust extinction.
However, this does mean that we were able better able to constrain the
astrophysical variability and its maximum with our analysis.
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