arXiv subjects

Ingo P. Waldmann

Publications and source records attributed to Ingo P. Waldmann.

At least 37 records · Page 2Linked to original sources

arXiv2020

Lessons Learned from the 1st ARIEL Machine Learning Challenge: Correcting Transiting Exoplanet Light Curves for Stellar Spots

The last decade has witnessed a rapid growth of the field of exoplanet discovery and characterisation. However, several big challenges remain, many of which could be addressed using machine learning methodology. For instance, the most prolific method for detecting exoplanets and inferring several of their characteristics, transit photometry, is very sensitive to the presence of stellar spots. The current practice in the literature is to identify the effects of spots visually and correct for them manually or discard the affected data. This paper explores a first step towards fully automating the efficient and precise derivation of transit depths from transit light curves in the presence of stellar spots. The methods and results we present were obtained in the context of the 1st Machine Learning Challenge organized for the European Space Agency's upcoming Ariel mission. We first present the problem, the simulated Ariel-like data and outline the Challenge while identifying best practices for organizing similar challenges in the future. Finally, we present the solutions obtained by the top-5 winning teams, provide their code and discuss their implications. Successful solutions either construct highly non-linear (w.r.t. the raw data) models with minimal preprocessing -deep neural networks and ensemble methods- or amount to obtaining meaningful statistics from the light curves, constructing linear models on which yields comparably good predictive performance.

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arXiv2020

Integrating light-curve and atmospheric modelling of transiting exoplanets

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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arXiv2020

On The Compatibility of Ground-based and Space-based Data: WASP-96 b, An Example

The study of exoplanetary atmospheres relies on detecting minute changes in the transit depth at different wavelengths. To date, a number of ground and space based instruments have been used to obtain transmission spectra of exoplanets in different spectral band. One common practice is to combine observations from different instruments in order to achieve a broader wavelength coverage. We present here two inconsistent observations of WASP-96 b, one by Hubble Space Telescope (HST) and the other by the Very Large Telescope (VLT). We present two key findings in our investigation: 1.) a strong water signature is detected via the HST WFC3 observations. 2.) A notable offset in transit depth (> 1100 ppm) can be seen when the ground-based and space-based observations are combined together. The discrepancy raises the question of whether observations from different instruments could indeed be combined together. We attempt to align the observations by including an additional parameter in our retrieval studies but are unable to definitively ascertain that the aligned observations are indeed compatible. The case of WASP-96 b signals that compatibility of instruments should not be assumed. While wavelength overlaps between instruments can help, it should be noted that combining datasets remains a risky business. The difficulty in combining observations also strengthens the need for next generation instruments which will possess broader spectral coverage.

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arXiv2020

Alfnoor: A Retrieval Simulation of the Ariel Target List

In this work, we present Alfnoor, a dedicated tool optimised for population studies of exoplanet atmospheres. Alfnoor combines the latest version of the retrieval algorithm TauREx 3, with the instrument noise simulator ArielRad and enables the simultaneous retrieval analysis of a large sample of exo-atmospheres. We applied this tool to the Ariel list of planetary candidates and focus on hydrogen dominated, cloudy atmospheres observed in transit with the Tier-2 mode (medium Ariel resolution). As a first experiment, we randomised the abundances - ranging from 10$^{-7}$ to 10$^{-2}$ - of the trace gases, which include H$_2$O, CH$_4$, CO, CO$_2$ and NH$_3$. This exercise allowed to estimate the detection limits for Ariel Tier-2 and Tier-3 modes when clouds are present. In a second experiment, we imposed an arbitrary trend between a chemical species and the effective temperature of the planet. A last experiment was run requiring molecular abundances being dictated by equilibrium chemistry at a certain temperature. Our results demonstrate the ability of Ariel Tier-2 and Tier-3 surveys to reveal trends between the chemistry and associated planetary parameters. Future work will focus on eclipse data, on atmospheres heavier than hydrogen and will be applied also to other observatories.

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arXiv2020

KELT-11 b: Abundances of water and constraints on carbon-bearing molecules from the Hubble transmission spectrum

In the past decade, the analysis of exoplanet atmospheric spectra has revealed the presence of water vapour in almost all the planets observed, with the exception of a fraction of overcast planets. Indeed, water vapour presents a large absorption signature in the wavelength coverage of the Hubble Space Telescope's (HST) Wide Field Camera 3 (WFC3), which is the main space-based observatory for atmospheric studies of exoplanets, making its detection very robust. However, while carbon-bearing species such as methane, carbon monoxide and carbon dioxide are also predicted from current chemical models, their direct detection and abundance characterisation has remained a challenge. Here we analyse the transmission spectrum of the puffy, clear hot-Jupiter KELT-11 b from the HST WFC3 camera. We find that the spectrum is consistent with the presence of water vapor and an additional absorption at longer wavelengths than 1.5um, which could well be explained by a mix of carbon bearing molecules. CO2, when included is systematically detected. One of the main difficulties to constrain the abundance of those molecules is their weak signatures across the HST WFC3 wavelength coverage, particularly when compared to those of water. Through a comprehensive retrieval analysis, we attempt to explain the main degeneracies present in this dataset and explore some of the recurrent challenges that are occurring in retrieval studies (e.g: the impact of model selection, the use of free vs self-consistent chemistry and the combination of instrument observations). Our results make this planet an exceptional example of chemical laboratory where to test current physical and chemical models of hot-Jupiters' atmospheres.

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arXiv2020

A comparison of exoplanet spectroscopic retrieval tools

Over the last several years, spectroscopic observations of transiting exoplanets have begun to uncover information about their atmospheres, including atmospheric composition and indications of the presence of clouds and hazes. Spectral retrieval is the leading technique for interpretation of transmission spectra and is employed by several teams using a variety of forward models and parameter estimation algorithms. However, different model suites have mostly been used in isolation and so it is unknown whether the results from each are comparable. As we approach the launch of the James Webb Space Telescope we anticipate advances in wavelength coverage, precision, and resolution of transit spectroscopic data, so it is important that the tools that will be used to interpret these information rich spectra are validated. To this end, we present an inter-model comparison of three retrieval suites: TauREx, NEMESIS and CHIMERA. We demonstrate that the forward model spectra are in good agreement (residual deviations on the order of 20 - 40 ppm), and discuss the results of cross retrievals between the three tools. Generally, the constraints from the cross retrievals are consistent with each other and with input values to within 1 sigma However, for high precision scenarios with error envelopes of order 30 ppm, subtle differences in the simulated spectra result in discrepancies between the different retrieval suites, and inaccuracies in retrieved values of several sigma. This can be considered analogous to substantial systematic/astrophysical noise in a real observation, or errors/omissions in a forward model such as molecular linelist incompleteness or missing absorbers.

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arXiv2020

Pushing the Limits of Exoplanet Discovery via Direct Imaging with Deep Learning

Further advances in exoplanet detection and characterisation require sampling a diverse population of extrasolar planets. One technique to detect these distant worlds is through the direct detection of their thermal emission. The so-called direct imaging technique, is suitable for observing young planets far from their star. These are very low signal-to-noise-ratio (SNR) measurements and limited ground truth hinders the use of supervised learning approaches. In this paper, we combine deep generative and discriminative models to bypass the issues arising when directly training on real data. We use a Generative Adversarial Network to obtain a suitable dataset for training Convolutional Neural Network classifiers to detect and locate planets across a wide range of SNRs. Tested on artificial data, our detectors exhibit good predictive performance and robustness across SNRs. To demonstrate the limits of the detectors, we provide maps of the precision and recall of the model per pixel of the input image. On real data, the models can re-confirm bright source detections.

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arXiv2020

Global Chemistry and Thermal Structure Models for the Hot Jupiter WASP-43b and Predictions for JWST

The James Webb Space Telescope (JWST) is expected to revolutionize the field of exoplanets. The broad wavelength coverage and the high sensitivity of its instruments will allow characterization of exoplanetary atmospheres with unprecedented precision. Following the Call for the Cycle 1 Early Release Science Program, the Transiting Exoplanet Community was awarded time to observe several targets, including WASP-43b. The atmosphere of this hot Jupiter has been intensively observed but still harbors some mysteries, especially concerning the day-night temperature gradient, the efficiency of the atmospheric circulation, and the presence of nightside clouds. We will constrain these properties by observing a full orbit of the planet and extracting its spectroscopic phase curve in the 5--12 $μ$m range with JWST/MIRI. To prepare for these observations, we performed an extensive modeling work with various codes: radiative transfer, chemical kinetics, cloud microphysics, global circulation models, JWST simulators, and spectral retrieval. Our JWST simulations show that we should achieve a precision of 210 ppm per 0.1 $μ$m spectral bin on average, which will allow us to measure the variations of the spectrum in longitude and measure the night-side emission spectrum for the first time. If the atmosphere of WASP-43b is clear, our observations will permit us to determine if its atmosphere has an equilibrium or disequilibrium chemical composition, providing eventually the first conclusive evidence of chemical quenching in a hot Jupiter atmosphere. If the atmosphere is cloudy, a careful retrieval analysis will allow us to identify the cloud composition.

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arXiv2020

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.

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arXiv2019

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 H$_2$O to be the most abundant molecular species, after hydrogen, in the atmospheres of hot, gaseous, extrasolar planets. Being the main molecular carrier of oxygen, H$_2$O is a tracer of the origin and the evolution mechanisms of planets. For temperate, terrestrial planets, the presence of H$_2$O 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$_\oplus$ -- 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 H$_2$O spectroscopic signature in the atmosphere of \planet\ -- an eight M$_\oplus$ planet in the habitable-zone of an M-dwarf -- with high statistical confidence (ADI = 5.0, $\sim$3.6$σ$). 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.

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arXiv2019

Mapping Saturn using deep learning

Clouds and aerosols provide unique insight into the chemical and physical processes of gas-giant planets. Mapping and characterizing the spectral features indicative of the cloud structure and composition enables an understand-ing of a planet's energy budget, chemistry and atmospheric dynamics. Current space missions to Solar System planets produce high-quality datasets, yet the sheer amount of data obtained often prohibits detailed 'by hand' analyses. Current techniques rely mainly on two approaches: identifying the existence of spectral features by dividing the fluxes of two or more spectral channels, and performing full radiative transfer calculations for individual spectra. The first method is not sufficiently accurate and the second is not easily scalable to the entire planetary surface. Here we have developed a deep learning algorithm, PlanetNet, that is able to quickly and accurately map spatial and spectral features across large, heterogeneous areas of a planet. We use PlanetNet to delineate the major components of the 2008 storm on Saturn, enhancing the scope of the area previously studied and indicating regions that can be probed more deeply with radiative transfer models. Our spectral-component maps indicate compositional and cloud variations of the vast region affected by the storm, showing regions of vertical upwelling, and diminished clouds at the centre of compact substorms

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arXiv2018

The Transiting Exoplanet Community Early Release Science Program for JWST

The James Webb Space Telescope (JWST) presents the opportunity to transform our understanding of planets and the origins of life by revealing the atmospheric compositions, structures, and dynamics of transiting exoplanets in unprecedented detail. However, the high-precision, time-series observations required for such investigations have unique technical challenges, and prior experience with other facilities indicates that there will be a steep learning curve when JWST becomes operational. In this paper we describe the science objectives and detailed plans of the Transiting Exoplanet Community Early Release Science (ERS) Program, which is a recently approved program for JWST observations early in Cycle 1. The goal of this project, for which the obtained data will have no exclusive access period, is to accelerate the acquisition and diffusion of technical expertise for transiting exoplanet observations with JWST, while also providing a compelling set of representative datasets that will enable immediate scientific breakthroughs. The Transiting Exoplanet Community ERS Program will exercise the time-series modes of all four JWST instruments that have been identified as the consensus highest priorities, observe the full suite of transiting planet characterization geometries (transits, eclipses, and phase curves), and target planets with host stars that span an illustrative range of brightnesses. The observations in this program were defined through an inclusive and transparent process that had participation from JWST instrument experts and international leaders in transiting exoplanet studies. Community engagement in the project will be centered on a two-phase Data Challenge that culminates with the delivery of planetary spectra, time-series instrument performance reports, and open-source data analysis toolkits in time to inform the agenda for Cycle 2 of the JWST mission.

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arXiv2018

Community targets for JWST's early release science program: evaluation of WASP-63b

We present observations of WASP-63b by the Hubble Space Telescope (HST) as part of "A Preparatory Program to Identify the Single Best Transiting Exoplanet for JWST Early Release Science". WASP-63b is one of the community targets under consideration for the James Webb Space Telescope (JWST) Early Release Science (ERS) program. We present a spectrum derived from a single observation by HST Wide Field Camera 3 in the near infrared. We engaged groups across the transiting exoplanet community to participate in the analysis of the data and present results from each. There is general agreement amongst all results that we find an H2O absorption feature with 3.5-4.0 sigma significance. However, the feature is muted in comparison to a clear atmosphere at solar composition. Although the detection of the water feature is robust, the reasons for the muting of this feature are ambiguous due to a degeneracy between clouds and composition. The data does not yield robust detections of any molecular species other than H2O. The group was motivated to perform an additional set of retrieval exercises to investigate an apparent bump in the spectrum at ~ 1.55 um. We explore possible disequilibrium chemistry and find this feature is consistent with super-solar HCN abundance but it is questionable if the required mixing ratio of HCN is chemically and physically plausible. The ultimate goal of this study is to vet WASP-63b as a potential community target to best demonstrate the capabilities and systematics of JWST instruments for transiting exoplanet science. In the case of WASP-63b, the presence of a detectable water feature indicates that WASP-63b remains a plausible target for ERS observations.

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arXiv2018

A better characterization of the chemical composition of exoplanets atmospheres with ARIEL

Since the discovery of the first extrasolar planet more than twenty years ago, we have discovered nearly four thousand planets orbiting stars other than the Sun. Current observational instruments (on board the Hubble Space Telescope, Spitzer, and on ground-based facilities) have allowed the scientific community to obtain important information on the physical and chemical properties of these planets. However, for a more in-depth characterisation of these worlds, more powerful telescopes are needed. Thanks to the high sensitivity of their instruments, the next generation of space observatories (e.g. JWST, ARIEL) will provide observations of unprecedented quality, allowing us to extract far more information than what was previously possible. Such high quality observations will provide constraints on theoretical models of exoplanet atmospheres and lead to a greater understanding of their physics and chemistry. Important modelling efforts have been carried out during the past few years, showing that numerous parameters and processes (such as the elemental abundances, temperature, mixing, etc.) are likely to affect the atmospheric composition of exoplanets and subsequently the observable spectra. In this manuscript, we review the different parameters that can influence the molecular composition of exoplanet atmospheres. We show that the high-precision of ARIEL observations will improve our view and characterisation of exoplanet atmospheres. We also consider future developments that are necessary to improve atmospheric models, driven by the need to interpret the available observations.

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arXiv2017

VUV-absorption cross section of carbon dioxide from 150 to 800 K and applications to warm exoplanetary atmospheres

Most exoplanets detected so far have atmospheric T significantly higher than 300K. Often close to their star, they receive an intense UV photons flux that triggers important photodissociation processes. The T dependency of VUV absorption cross sections are poorly known, leading to an undefined uncertainty in atmospheric models. Similarly, data measured at low T similar to that of the high atmosphere of Mars, Venus, and Titan are often lacking. Our aim is to quantify the T dependency of the abs. cross section of important molecules in planetary atmospheres. We want to provide both high-resolution data at T prevailing in these media and a simple parameterization of the absorption in order to simplify its use in photochemical models. This study focuses on carbon dioxide. We performed experimental measurements of CO$_2$ absorption cross section with synchrotron radiation for the wavelength range (115--200nm). For longer wavelengths (195--230nm), we used a deuterium lamp and a 1.5m Jobin-Yvon spectrometer. We used these data in our 1D thermo-photochemical model in order to study their impact on the predicted atmospheric compositions. The cross section of CO$_2$ increases with T. It can be separated in two parts: a continuum and a fine structure superimposed on the continuum. The variation of the continuum of absorption can be represented by the sum of three gaussian functions. Using data at high T in thermo-photochemical models modifies significantly the abundance and the photodissociation rates of many species, in addition to CO$_2$, such as methane and ammonia. These deviations have an impact on synthetic transmission spectra, leading to variations of up to 5 ppm. We present a full set of HR ($Δλ$=0.03nm) absorption cross sections of CO$_2$ from 115 to 230nm for T ranging from 150 to 800K.

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arXiv2017

A hybrid line list for CH$_4$ and hot methane continuum

Molecular line lists 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. 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. 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 (34to10), 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.

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arXiv2016

Repeatability of Spitzer/IRAC exoplanetary eclipses with Independent Component Analysis

The research of effective and reliable detrending methods for Spitzer data is of paramount importance for the characterization of exoplanetary atmospheres. To date, the totality of exoplanetary observations in the mid- and far-infrared, at wavelengths $>$3 $μ$m, have been taken with Spitzer. In some cases, in the past years, repeated observations and multiple reanalyses of the same datasets led to discrepant results, raising questions about the accuracy and reproducibility of such measurements. Morello et al. 2014, 2015 proposed a blind-source separation method based on the Independent Component Analysis of pixel time series (pixel-ICA) to analyze IRAC data, obtaining coherent results when applied to repeated transit observations previously debated in the literature. Here we introduce a variant to pixel-ICA through the use of wavelet transform, wavelet pixel-ICA, which extends its applicability to low-S/N cases. We describe the method and discuss the results obtained over twelve eclipses of the exoplanet XO3b observed during the "Warm Spitzer" era in the 4.5 $μ$m band. The final results will be reported also in Ingalls et al. (in prep.), together with results obtained with other detrending methods, and over ten synthetic eclipses that were analyzed for the "IRAC Data Challenge 2015". Our results are consistent within 1 $σ$ with the ones reported in Wong et al. 2014. The self-consistency of individual measurements of eclipse depth and phase curve slope over a span of more than three years proves the stability of Warm Spitzer/IRAC photometry within the error bars, at the level of 1 part in 10$^4$ in stellar flux.

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arXiv2015

Tau-REx II: Retrieval of emission spectra

Tau-REx (Tau Retrieval of Exoplanets) is a novel, fully Bayesian atmospheric retrieval code custom built for extrasolar atmospheres. In Waldmann et al. (2015) the transmission spectroscopic case was introduced, here we present the emission spectroscopy spectral retrieval for the Tau-REx framework. Compared to transmission spectroscopy, the emission case is often significantly more degenerate due to the need to retrieve the full atmospheric temperature-pressure (TP) profile. This is particularly true in the case of current measurements of exoplanetary atmospheres, which are either of low signal-to-noise, low spectral resolution or both. Here we present a new way of combining two existing approaches to the modelling of the said TP profile: 1) the parametric profile, where the atmospheric TP structure is analytically approximated by a few model parameters, 2) the Layer-by-Layer approach, where individual atmospheric layers are modelled. Both these approaches have distinct advantages and disadvantages in terms of convergence properties and potential model biases. The Tau-REx hybrid model presented here is a new two-stage TP profile retrieval, which combines the robustness of the analytic solution with the accuracy of the Layer-by-Layer approach. The retrieval process is demonstrated using simulations of the hot-Jupiter WASP-76b and the hot SuperEarth 55 Cnc e, as well as on the secondary eclipse measurements of HD189733b.

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