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Billy Edwards

Publications and source records attributed to Billy Edwards.

At least 55 records · Page 3Linked to original sources

The Ariel Target List: The Impact of TESS and the Potential for Characterising Multiple Planets Within a System

The ESA Ariel mission has been adopted for launch in 2029 and will conduct a survey of around one thousand exoplanetary atmospheres during its primary mission life. By providing homogeneous datasets, with a high SNR and wide wavelength coverage, Ariel will unveil the atmospheric demographics of these far-away worlds, helping to constrain planet formation and evolution processes on a galactic scale. Ariel seeks to undertake a statistical survey of a diverse population of planets and, therefore, the sample of planets from which this selection can be made is of the utmost importance. While many suitable targets have already been found, hundreds more will be discovered before the mission is operational. Previous studies have used predictions of exoplanet detections to forecast the available planet population by the launch date of Ariel, with the most recent noting that the Transiting Exoplanet Survey Satellite (TESS) alone should provide over a thousand potential targets. In this work, we consider the planet candidates found to date by TESS to show that, with the addition of already confirmed planets, Ariel will already have a more than sufficient sample to choose its target list from once these candidates are validated. We showcase the breadth of this population as well as exploring, for the first time, the ability of Ariel to characterise multiple planets within a single system. Comparative planetology of worlds orbiting the same star, as well as across the wider population, will undoubtedly revolutionise our understanding of planet formation and evolution.

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ESA-Ariel Data Challenge NeurIPS 2022: Inferring Physical Properties of Exoplanets From Next-Generation Telescopes

The study of extra-solar planets, or simply, exoplanets, planets outside our own Solar System, is fundamentally a grand quest to understand our place in the Universe. Discoveries in the last two decades have re-defined our understanding of planets, and helped us comprehend the uniqueness of our very own Earth. In recent years the focus has shifted from planet detection to planet characterisation, where key planetary properties are inferred from telescope observations using Monte Carlo-based methods. However, the efficiency of sampling-based methodologies is put under strain by the high-resolution observational data from next generation telescopes, such as the James Webb Space Telescope and the Ariel Space Mission. We are delighted to announce the acceptance of the Ariel ML Data Challenge 2022 as part of the NeurIPS competition track. The goal of this challenge is to identify a reliable and scalable method to perform planetary characterisation. Depending on the chosen track, participants are tasked to provide either quartile estimates or the approximate distribution of key planetary properties. To this end, a synthetic spectroscopic dataset has been generated from the official simulators for the ESA Ariel Space Mission. The aims of the competition are three-fold. 1) To offer a challenging application for comparing and advancing conditional density estimation methods. 2) To provide a valuable contribution towards reliable and efficient analysis of spectroscopic data, enabling astronomers to build a better picture of planetary demographics, and 3) To promote the interaction between ML and exoplanetary science. The competition is open from 15th June and will run until early October, participants of all skill levels are more than welcomed!

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Five key exoplanet questions answered via the analysis of 25 hot Jupiter atmospheres in eclipse

Population studies of exoplanets are key to unlocking their statistical properties. So far the inferred properties have been mostly limited to planetary, orbital and stellar parameters extracted from, e.g., Kepler, radial velocity, and GAIA data. More recently an increasing number of exoplanet atmospheres have been observed in detail from space and the ground. Generally, however, these atmospheric studies have focused on individual planets, with the exception of a couple of works which have detected the presence of water vapor and clouds in populations of gaseous planets via transmission spectroscopy. Here, using a suite of retrieval tools, we analyse spectroscopic and photometric data of 25 hot Jupiters, obtained with the Hubble and Spitzer Space Telescopes via the eclipse technique. By applying the tools uniformly across the entire set of 25 planets, we extract robust trends in the thermal structure and chemical properties of hot Jupiters not obtained in past studies. With the recent launch of JWST and the upcoming missions Twinkle, and Ariel, population based studies of exoplanet atmospheres, such as the one presented here, will be a key approach to understanding planet characteristics, formation, and evolution in our galaxy.

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The transmission spectrum of WASP-17 b from the optical to the near-infrared wavelengths: combining STIS, WFC3 and IRAC datasets

We present the transmission spectrum of the inflated hot-Jupiter WASP-17 b, observed with the STIS and WFC3 instruments aboard the Hubble Space Telescope, allowing for a continuous wavelength coverage from ~0.4 to ~1.7 um. Observations taken with IRAC channel 1 and 2 on the Spitzer Space Telescope are also included, adding photometric measurements at 3.6 and 4.5 um. HST spectral data was analysed with Iraclis, a pipeline specialised in the reduction of STIS and WFC3 transit and eclipse observations. Spitzer photometric observations were reduced with the TLCD-LSTM method, utilising recurrent neural networks. The outcome of our reduction produces incompatible results between STIS visit 1 and visit 2, which leads us to consider two scenarios for G430L. Additionally, by modelling the WFC3 data alone, we can extract atmospheric information without having to deal with the contrasting STIS datasets. We run separate retrievals on the three spectral scenarios with the aid of TauREx 3, a fully Bayesian retrieval framework. We find that, independently of the data considered, the exoplanet atmosphere displays strong water signatures and potentially, the presence of aluminium oxide (AlO) and titanium hydride (TiH). A retrieval that includes an extreme photospheric activity of the host star is the preferred model, but we recognise that such a scenario is unlikely for an F6-type star. Due to the incompleteness of all STIS spectral lightcurves, only further observations with this instrument would allow us to properly constrain the atmospheric limb of WASP-17 b, before JWST or Ariel will come online.

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A retrieval challenge exercise for the Ariel mission

The Ariel mission, due to launch in 2029, will obtain spectroscopic information for 1000 exoplanets, providing an unprecedented opportunity for comparative exoplanetology. Retrieval codes - parameteric atmospheric models coupled with an inversion algorithm - represent the tool of choice for interpreting Ariel data. Ensuring that reliable and consistent results can be produced by these tools is a critical preparatory step for the mission. Here, we present the results of a retrieval challenge. We use five different exoplanet retrieval codes to analyse the same synthetic datasets, and test a) the ability of each to recover the correct input solution and b) the consistency of the results. We find that generally there is very good agreement between the five codes, and in the majority of cases the correct solutions are recovered. This demonstrates the reproducibility of retrievals for transit spectra of exoplanets, even when codes are not previously benchmarked against each other.

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Cross-sections for heavy atmospheres: H$_2$O self-broadening

The discovery of super-Earth and mini-Neptune exoplanets means that atmospheric signals from low-mass, temperate exoplanets are being increasingly studied. The signal acquired as the planet transits its host star, known as the transit depth, is smaller for these planets and, as such, more difficult to analyze. The launch of the space telescopes James Webb (JWST) & Ariel will give rise to an explosion in the quality and quantity of spectroscopic data available for an unprecedented number of exoplanets in our galaxy. Accurately extracting the information content, thereby permitting atmospheric science, of such data-sets will require robust models and techniques. We present here the analysis of simulated transmission spectra for water-rich atmospheres, giving evidence for non-negligible differences in simulated transit depths when self-broadening of H$_2$O is correctly accounted for, compared with the currently typically accepted standard of using H$_2$ and He-broadened cross-sections. Our case-study analysis is carried out on two super-Earths, focusing on water-based atmospheres, ranging from H$_2$-rich to H$_2$O-rich. The transit depth is considerably affected, increasing values by up to 60 ppm, which is shown to be detectable with JWST and Ariel. The differences are most pronounced for the lighter (i.e. $mu$ $\sim$ 4) atmospheres. Our work illustrates that it is imperative that the field of exoplanet spectroscopy moves toward adapted cross-sections, increasingly optimized for high-mu atmospheres for studies of super-Earths and mini-Neptunes.

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Observations of PAHs in the atmospheres of discs and exoplanets

Polycyclic aromatic hydrocarbons (PAHs) play a key role in the chemical and hydrodynamical evolution of the atmospheres of exoplanets and planet-forming discs. If they can survive the planet formation process, PAHs are likely to be involved in pre-biotic chemical reactions eventually leading to more complex molecules such as amino acids and nucleotides, which form the basis for life as we know it. However, the abundance and specific role of PAHs in these environments is largely unknown due to limitations in sensitivity and range of wavelength of current and previous space-borne facilities. Upcoming infrared space spectroscopy missions, such as Twinkle and Ariel, present a unique opportunity to detect PAHs in the atmospheres of exoplanets and planet-forming discs. In this work we present synthetic observations based on conservative numerical modeling of typical planet-forming discs and a transiting hot Saturnian planet around solar type star. Our models show that Twinkle and Ariel might both be able to detect the 3.3 micron PAH feature within reasonable observing time in discs and transiting planets, assuming that PAHs are present with an abundance of at least one tenth of the interstellar medium value.

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On-sky validation of image-based adaptive optics wavefront sensor referencing

Differentiating between an exoplanet signal and residual speckle noise is a key challenge in high-contrast imaging. Speckles are due to a combination of fast, slow and static wavefront aberrations introduced by atmospheric turbulence and instrument optics. While wavefront control techniques developed over the last decade have shown promise in minimizing fast atmospheric residuals, slow and static aberrations such as non-common path aberrations (NCPAs) remain a key limiting factor for exoplanet detection. NCPA are not seen by the wavefront sensor (WFS) of the adaptive optics (AO) loop, hence the difficulty in correcting them. We propose to improve the identification and rejection of those aberrations. The algorithm DrWHO, performs frequent compensation of static and quasi-static aberrations to boost image contrast. By changing the WFS reference at every iteration of the algorithm, DrWHO changes the AO point of convergence to lead it towards a compensation of the static and slow aberrations. References are calculated using an iterative lucky-imaging approach, where each iteration updates the WFS reference, ultimately favoring high-quality focal plane images. We validate this concept through numerical simulations and on-sky testing on the SCExAO instrument at the 8.2-m Subaru telescope. Simulations show a rapid convergence towards the correction of 82% of the NCPAs. On-sky tests are performed over a 10-minute run in the visible (750 nm). We introduce a flux concentration (FC) metric to quantify the point spread function (PSF) quality and measure a 15.7% improvement. The DrWHO algorithm is a robust focal-plane wavefront sensing calibration method that has been successfully demonstrated on sky. It does not rely on a model nor requires wavefront sensor calibration or linearity. It is compatible with different wavefront control methods, and can be further optimized for speed and efficiency.

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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. The three solutions are a primary cloudy atmosphere with traces of water vapour (cloudy sub-Neptune), a secondary atmosphere with a substantial amount (up to 50% Volume Mixing Ratio) of H2O (icy/water world) and/or an undetectable gas such as N2 (super-Earth). 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 James Webb Space Telescope (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 mass planets.

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Peeking inside the Black Box: Interpreting Deep Learning Models for Exoplanet Atmospheric Retrievals

Deep learning algorithms are growing in popularity in the field of exoplanetary science due to their ability to model highly non-linear relations and solve interesting problems in a data-driven manner. Several works have attempted to perform fast retrievals of atmospheric parameters with the use of machine learning algorithms like deep neural networks (DNNs). Yet, despite their high predictive power, DNNs are also infamous for being 'black boxes'. It is their apparent lack of explainability that makes the astrophysics community reluctant to adopt them. What are their predictions based on? How confident should we be in them? When are they wrong and how wrong can they be? In this work, we present a number of general evaluation methodologies that can be applied to any trained model and answer questions like these. In particular, we train three different popular DNN architectures to retrieve atmospheric parameters from exoplanet spectra and show that all three achieve good predictive performance. We then present an extensive analysis of the predictions of DNNs, which can inform us - among other things - of the credibility limits for atmospheric parameters for a given instrument and model. Finally, we perform a perturbation-based sensitivity analysis to identify to which features of the spectrum the outcome of the retrieval is most sensitive. We conclude that for different molecules, the wavelength ranges to which the DNN's predictions are most sensitive, indeed coincide with their characteristic absorption regions. The methodologies presented in this work help to improve the evaluation of DNNs and to grant interpretability to their predictions.

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An exploration of model degeneracies with a unified phase curve retrieval analysis: The light and dark sides of WASP-43 b

The analysis of exoplanetary atmospheres often relies upon the observation of transit or eclipse events. While very powerful, these snapshots provide mainly 1-dimensional information on the planet structure and do not easily allow precise latitude-longitude characterisations. The phase curve technique, which consists of measuring the planet emission throughout its entire orbit, can break this limitation and provide useful 2-dimensional thermal and chemical constraints on the atmosphere. As of today however, computing performances have limited our ability to perform unified retrieval studies on the full set of observed spectra from phase curve observations at the same time. Here, we present a new phase curve model that enables fast, unified retrieval capabilities. We apply our technique to the combined phase curve data from the Hubble and Spitzer space telescopes of the hot-Jupiter WASP-43 b. We tested different scenarios and discussed the dependence of our solution to different assumptions in the model. Our more comprehensive approach suggests that multiple interpretation of this dataset are possible but our more complex model is consistent with the presence of thermal inversions and a metal rich atmosphere, contrasting with previous data analyses, although this likely depends on the Spitzer data reduction. The detailed constraints extracted here demonstrate the importance of developing and understanding advanced phase curve techniques, which we believe will unlock access to a richer picture of exoplanet atmospheres.

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ARES V: No Evidence For Molecular Absorption in the HST WFC3 Spectrum of GJ 1132 b

We present a study on the spatially scanned spectroscopic observations of the transit of GJ 1132 b, a warm ($\sim$500 K) Super-Earth (1.13 R$_\oplus$) that was obtained with the G141 grism (1.125 - 1.650 $μ$m) of the Wide Field Camera 3 (WFC3) onboard the Hubble Space Telescope. We used the publicly available Iraclis pipeline to extract the planetary transmission spectra from the five visits and produce a precise transmission spectrum. We analysed the spectrum using the TauREx3 atmospheric retrieval code with which we show that the measurements do not contain molecular signatures in the investigated wavelength range and are best-fit with a flat-line model. Our results suggest that the planet does not have a clear primordial, hydrogen-dominated atmosphere. Instead, GJ 1132 b could have a cloudy hydrogen-dominated envelope, a very enriched secondary atmosphere, be airless, or have a tenuous atmosphere that has not been detected. Due to the narrow wavelength coverage of WFC3, these scenarios cannot be distinguished yet but the James Webb Space Telescope may be capable of detecting atmospheric features, although several observations may be required to provide useful constraints.

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Detectability of Rocky-Vapour Atmospheres on Super-Earths with Ariel

Ariel will mark the dawn of a new era as the first large-scale survey characterising exoplanetary atmospheres with science objectives to address fundamental questions about planetary composition, evolution and formation. In this study, we explore the detectability of atmospheres vaporised from magma oceans on dry, rocky Super-Earths orbiting very close to their host stars. The detection of such atmospheres would provide a definitive piece of evidence for rocky planets but are challenging measurements with currently available instruments due to their small spectral signatures. However, some of the hottest planets are believed to have atmospheres composed of vaporised rock, such as Na and SiO, with spectral signatures bright enough to be detected through eclipse observations with planned space-based telescopes. In this study, we find that rocky super-Earths with a irradiation temperature of 3000 K and a distance from Earth of up to 20 pc, as well as planets hotter than 3500 K and closer than 50 pc, have SiO features which are potentially detectable in eclipse spectra observed with Ariel.

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A survey of exoplanet phase curves with Ariel

The ESA-Ariel mission will include a tier dedicated to exoplanet phase curves corresponding to ~10% of the science time. We present here the current observing strategy for studying exoplanet phase curves with Ariel. We define science questions, requirements and a list of potential targets. We also estimate the precision of phase curve reconstruction and atmospheric retrieval using simulated phase curves. Based on this work, we found that full-orbit phase variations for 35-40 exoplanets could be observed during the 3.5-yr mission. This statistical sample would provide key constraints on atmospheric dynamics, composition, thermal structure and clouds of warm exoplanets, complementary to the scientific yield from spectroscopic transits/eclipses measurements.

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Terminus: A Versatile Simulator for Space-based Telescopes

Space-based telescopes offer unparalleled opportunities for characterising exoplanets, Solar System bodies and stellar objects. However, observatories in low Earth orbits (e.g. Hubble, CHEOPS, Twinkle and an ever increasing number of cubesats) cannot always be continuously pointed at a target due to Earth obscuration. For exoplanet observations consisting of transit, or eclipse, spectroscopy this causes gaps in the light curve, which reduces the information content and can diminish the science return of the observation. Terminus, a time-domain simulator, has been developed to model the occurrence of these gaps to predict the potential impact on future observations. The simulator is capable of radiometrically modelling exoplanet observations as well as producing light curves and spectra. Here, Terminus is baselined on the Twinkle mission but the model can be adapted for any space-based telescope and is especially applicable to those in a low-Earth orbit. Terminus also has the capability to model observations of other targets such as asteroids or brown dwarfs.

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The Hubble WFC3 Emission Spectrum of the Extremely-Hot Jupiter, KELT-9b

Recent studies of ultra hot-Jupiters suggested that their atmospheres could have thermal inversions due to the presence of optical absorbers such as TiO, VO, FeH and other metal hydride/oxides. However, it is expected that these molecules would thermally dissociate at extremely high temperatures, thus leading to featureless spectra in the infrared. KELT-9b, the hottest exoplanet discovered so far, is thought to belong to this regime and host an atmosphere dominated by neutral Hydrogen from dissociation and atomic/ionic species. Here, we analysed the eclipse spectrum obtained using the Hubble Space Telescope's Wide Field Camera 3 (WFC3) and, by utilising the atmospheric retrieval code TauREx3, found that the spectrum is consistent with the presence of molecular species and is poorly fitted by a simple blackbody. In particular, we find that a combination of TiO, VO, FeH and H- provides the best-fit when considering HST, Spitzer and TESS datasets together. Aware of potential biases when combining instruments, we also analysed the HST spectrum alone and found that TiO and VO only were needed in this case. These findings paint a more complex picture of the atmospheres of ultra-hot planets than previously thought

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ExoClock Project: An open platform for monitoring the ephemerides of Ariel targets with contributions from the public

The Ariel mission will observe spectroscopically around 1000 exoplanets to further characterise their atmospheres. For the mission to be as efficient as possible, a good knowledge of the planets' ephemerides is needed before its launch in 2028. While ephemerides for some planets are being refined on a per-case basis, an organised effort to collectively verify or update them when necessary does not exist. In this study, we introduce the ExoClock project, an open, integrated and interactive platform with the purpose of producing a confirmed list of ephemerides for the planets that will be observed by Ariel. The project has been developed in a manner to make the best use of all available resources: observations reported in the literature, observations from space instruments and, mainly, observations from ground-based telescopes, including both professional and amateur observatories. To facilitate inexperienced observers and at the same time achieve homogeneity in the results, we created data collection and validation protocols, educational material and easy to use interfaces, open to everyone. ExoClock was launched in September 2019 and now counts over 140 participants from more than 15 countries around the world. In this release, we report the results of observations obtained until the 15h of April 2020 for 119 Ariel candidate targets. In total, 632 observations were used to either verify or update the ephemerides of 83 planets. Additionally, we developed the Exoplanet Characterisation Catalogue (ECC), a catalogue built in a consistent way to assist the ephemeris refinement process. So far, the collaborative open framework of the ExoClock project has proven to be highly efficient in coordinating scientific efforts involving diverse audiences. Therefore, we believe that it is a paradigm that can be applied in the future for other research purposes, too.

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Hubble WFC3 Spectroscopy of the Habitable-zone Super-Earth LHS 1140 b

Atmospheric characterisation of temperate, rocky planets is the holy grail of exoplanet studies. These worlds are at the limits of our capabilities with current instrumentation in transmission spectroscopy and challenge our state-of-the-art statistical techniques. Here we present the transmission spectrum of the temperate Super-Earth LHS 1140b using the Hubble Space Telescope (HST). The Wide Field Camera 3 (WFC3) G141 grism data of this habitable zone (T$_{\rm{eq}}$ = 235 K) Super-Earth (R = 1.7 $R_\oplus$), shows tentative evidence of water. However, the signal-to-noise ratio, and thus the significance of the detection, is low and stellar contamination models can cause modulation over the spectral band probed. We attempt to correct for contamination using these models and find that, while many still lead to evidence for water, some could provide reasonable fits to the data without the need for molecular absorption although most of these cause also features in the visible ground-based data which are nonphysical. Future observations with the James Webb Space Telescope (JWST) would be capable of confirming, or refuting, this atmospheric detection.

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