62 research outputs found
A new look at Spitzer primary transit observations of the exoplanet HD189733b
Blind source separation techniques are used to reanalyse two exoplanetary
transit lightcurves of the exoplanet HD189733b recorded with the IR camera IRAC
on board the Spitzer Space Telescope at 3.6m during the "cold" era. These
observations, together with observations at other IR wavelengths, are crucial
to characterise the atmosphere of the planet HD189733b. Previous analyses of
the same datasets reported discrepant results, hence the necessity of the
reanalyses. The method we used here is based on the Independent Component
Analysis (ICA) statistical technique, which ensures a high degree of
objectivity. The use of ICA to detrend single photometric observations in a
self-consistent way is novel in the literature. The advantage of our reanalyses
over previous work is that we do not have to make any assumptions on the
structure of the unknown instrumental systematics. Such "admission of
ignorance" may result in larger error bars than reported in the literature, up
to a factor . This is a worthwhile trade-off for much higher objectivity,
necessary for trustworthy claims. Our main results are (1) improved and robust
values of orbital and stellar parameters, (2) new measurements of the transit
depths at 3.6m, (3) consistency between the parameters estimated from the
two observations, (4) repeatability of the measurement within the photometric
level of in the IR, (5) no evidence of stellar
variability at the same photometric level within 1 year.Comment: 43 pages, 18 figure
PyLightcurve-torch: a transit modelling package for deep learning applications in PyTorch
We present a new open source python package, based on PyLightcurve and
PyTorch, tailored for efficient computation and automatic differentiation of
exoplanetary transits. The classes and functions implemented are fully
vectorised, natively GPU-compatible and differentiable with respect to the
stellar and planetary parameters. This makes PyLightcurve-torch suitable for
traditional forward computation of transits, but also extends the range of
possible applications with inference and optimisation algorithms requiring
access to the gradients of the physical model. This endeavour is aimed at
fostering the use of deep learning in exoplanets research, motivated by an ever
increasing amount of stellar light curves data and various incentives for the
improvement of detection and characterisation techniques.Comment: 7 pages, 3 figures; submission status updated, fig 2 caption adde
Impact of planetary mass uncertainties on exoplanet atmospheric retrievals
In current models used to interpret exoplanet atmospheric observations, the
planet mass is treated as a prior and is estimated independently with external
methods, such as RV or TTV techniques. This approach is necessary as available
spectroscopic data do not have sufficient wavelength coverage and/or SNR to
infer the planetary mass. We examine here the impact of mass uncertainties on
spectral retrieval analyses for a host of atmospheric scenarios. Our approach
is both analytical and numerical: we first use simple approximations to extract
analytically the influence of each parameter to the wavelength-dependent
transit depth. We then adopt a fully Bayesian retrieval model to quantify the
propagation of the mass uncertainty onto other atmospheric parameters. We found
that for clear-sky, gaseous atmospheres the posterior distributions are the
same when the mass is known or retrieved. The retrieved mass is very accurate,
with a precision of more than 10%, provided the wavelength coverage and S/N are
adequate. When opaque clouds are included in the simulations, the uncertainties
in the retrieved mass increase, especially for high altitude clouds. However
atmospheric parameters such as the temperature and trace-gas abundances are
unaffected by the knowledge of the mass. Secondary atmospheres are more
challenging due to the higher degree of freedom for the atmospheric main
component, which is unknown. For broad wavelength range and adequate SNR, the
mass can still be retrieved accurately and precisely if clouds are not present,
and so are all the other atmospheric/planetary parameters. When clouds are
added, we find that the mass uncertainties may impact substantially the
retrieval of the mean molecular weight: an independent characterisation of the
mass would therefore be helpful to capture/confirm the main atmospheric
constituent.Comment: 19 pages, 12 figures, Accepted in Ap
Detrending Exoplanetary Transit Light Curves with Long Short-Term Memory Networks
The precise derivation of transit depths from transit light curves is a key
component for measuring exoplanet transit spectra, and henceforth for the study
of exoplanet atmospheres. However, it is still deeply affected by various kinds
of systematic errors and noise. In this paper we propose a new detrending
method by reconstructing the stellar flux baseline during transit time. We
train a probabilistic Long Short-Term Memory (LSTM) network to predict the next
data point of the light curve during the out-of-transit, and use this model to
reconstruct a transit-free light curve - i.e. including only the systematics -
during the in-transit. By making no assumption about the instrument, and using
only the transit ephemeris, this provides a general way to correct the
systematics and perform a subsequent transit fit. The name of the proposed
model is TLCD-LSTM, standing for Transit Light Curve Detrending LSTM. Here we
present the first results on data from six transit observations of HD 189733b
with the IRAC camera on board the Spitzer Space Telescope, and discuss some of
its possible further applications.Comment: 12 pages, 10 figures, 4 tables, accepted for publication in The
Astronomical Journa
Blind extraction of an exoplanetary spectrum through Independent Component Analysis
Blind-source separation techniques are used to extract the transmission
spectrum of the hot-Jupiter HD189733b recorded by the Hubble/NICMOS instrument.
Such a 'blind' analysis of the data is based on the concept of independent
component analysis. The de-trending of Hubble/NICMOS data using the sole
assumption that nongaussian systematic noise is statistically independent from
the desired light-curve signals is presented. By not assuming any prior, nor
auxiliary information but the data themselves, it is shown that spectroscopic
errors only about 10 - 30% larger than parametric methods can be obtained for
11 spectral bins with bin sizes of ~0.09 microns. This represents a reasonable
trade-off between a higher degree of objectivity for the non-parametric methods
and smaller standard errors for the parametric de-trending. Results are
discussed in the light of previous analyses published in the literature. The
fact that three very different analysis techniques yield comparable spectra is
a strong indication of the stability of these results.Comment: ApJ accepte
A Hybrid Line List for CH4 and Hot Methane Continuum
Molecular line lists (a catalogue of transition frequencies and line strengths) are important for modelling absorption and emission processes in atmospheres of different astronomical objects, such as cool stars and exoplanets. In order to be applicable for high temperatures, line lists for molecules like methane must contain billions of transitions, which makes their direct (line-by-line) application in radiative transfer calculations impracticable. Here we suggest a new, hybrid line list format to mitigate this problem, based on the idea of temperature-dependent absorption continuum. Methods. The line list is partitioned into a large set of relatively weak lines and a small set of important, stronger lines. The weaker lines are then used either to construct a temperature-dependent (but pressure-independent) set of intensity cross sections or are blended into a greatly reduced set of super-lines. The strong lines are kept in the form of temperature independent Einstein A coefficients. Results. A line list for methane is constructed as a combination of 17 million strong absorption lines relative to the reference absorption spectra and a background methane continuum in two temperature-dependent forms, of cross sections and super-lines. This approach eases the use of large high temperature line lists significantly as the computationally expensive calculation of pressure dependent profiles only need to be performed for a relatively small number of lines. Both the line list and cross sections were generated using a new 34 billion methane line list (34 to10), which extends the 10to10 line list to higher temperatures (up to 2000 K). The new hybrid scheme can be applied to any large line lists containing billions of transitions. We recommend to use super-lines generated on a high resolution grid based on resolving power R = 1,000,000 to model the molecular continuum as a more flexible alternative to the temperature dependent cross sections
Water vapour in the atmosphere of the habitable-zone eight Earth-mass planet K2-18 b
In the past decade, observations from space and ground have found HO to
be the most abundant molecular species, after hydrogen, in the atmospheres of
hot, gaseous, extrasolar planets. Being the main molecular carrier of oxygen,
HO is a tracer of the origin and the evolution mechanisms of planets. For
temperate, terrestrial planets, the presence of HO is of great significance
as an indicator of habitable conditions. Being small and relatively cold, these
planets and their atmospheres are the most challenging to observe, and
therefore no atmospheric spectral signatures have so far been detected.
Super-Earths -- planets lighter than ten M -- around later-type stars
may provide our first opportunity to study spectroscopically the
characteristics of such planets, as they are best suited for transit
observations. Here we report the detection of an HO spectroscopic signature
in the atmosphere of \planet\ -- an eight M planet in the
habitable-zone of an M-dwarf -- with high statistical confidence (ADI = 5.0,
3.6). In addition, the derived mean molecular weight suggests an
atmosphere still containing some hydrogen. The observations were recorded with
the Hubble Space Telescope/WFC3 camera, and analysed with our dedicated,
publicly available, algorithms. While the suitability of M-dwarfs to host
habitable worlds is still under discussion, \planet\ offers an unprecedented
opportunity to get insight into the composition and climate of habitable-zone
planets.Comment: Published in Nature Astronom
Disentangling Atmospheric Compositions of K2-18 b with Next Generation Facilities
Recent analysis of the planet K2-18b has shown the presence of water vapour
in its atmosphere. While the H2O detection is significant, the Hubble Space
Telescope (HST) WFC3 spectrum suggests three possible solutions of very
different nature which can equally match the data. These solutions include a
primary cloudy atmosphere with traces of water vapour and a secondary
atmosphere with a substantial amount of H2O and/or an undetectable gas such as
N2. Additionally, the atmospheric pressure and the possible presence of a
liquid/solid surface cannot be investigated with currently available
observations. In this paper we used the best fit parameters from Tsiaras et al.
(2019) to build JWST and Ariel simulations of the three scenarios. We have
investigated 18 retrieval cases, which encompass the three scenarios and
different observational strategies with the two observatories. Retrieval
results show that twenty combined transits should be enough for the Ariel
mission to disentangle the three scenarios, while JWST would require only two
transits if combining NIRISS and NIRSpec data. This makes K2-18b an ideal
target for atmospheric follow-ups by both facilities and highlights the
capabilities of the next generation of space-based infrared observatories to
provide a complete picture of low gravity planets.Comment: 12 pages, 12 figure
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