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.
ArielRad, the Ariel radiometric model, is a simulator developed to address the challenges in optimising the space mission science payload and to demonstrate its compliance with the performance requirements. Ariel, the Atmospheric Remote-Sensing Infrared Exoplanet Large-survey, has been selected by ESA as the M4 mission in the Cosmic Vision programme and, during its 4 years primary operation, will provide the first unbiased spectroscopic survey of a large and diverse sample of transiting exoplanet atmospheres. To allow for an accurate study of the mission, ArielRad uses a physically motivated n…
Ariel has been selected as ESA's M4 mission for launch in 2028 and is designed for the characterisation of a large and diverse population of exoplanetary atmospheres to provide insights into planetary formation and evolution within our Galaxy. Here we present a study of Ariel's capability to observe currently-known exoplanets and predicted TESS discoveries. We use the Ariel Radiometric model (ArielRad) to simulate the instrument performance and find that ~2000 of these planets have atmospheric signals which could be characterised by Ariel. This list of potential planets contains a diverse rang…
Automatic scheduling techniques are becoming a crucial tool for the efficient planning of large astronomical surveys. A specific scheduling method is being designed and developed for the Atmospheric Remote-sensing Infrared Exoplanet Large-survey (Ariel) mission planning based on a hybrid meta-heuristic algorithm with global optimization capability to ensure obtaining satisfying results fulfilling all mission constraints. We used this method to simulate the Ariel mission plan, to assess the feasibility of its scientific goals, and to study the outcome of different science scenarios. We conclude…
The ARIEL (Atmospheric Remote-sensing Exoplanet Large-survey) mission concept is one of the three M4 mission candidates selected by the European Space Agency (ESA) for a Phase A study, competing for a launch in 2026. ARIEL has been designed to study the physical and chemical properties of a large and diverse sample of exoplanets, and through those understand how planets form and evolve in our galaxy. Here we describe the assumptions made to estimate an optimal sample of exoplanets - including both the already known exoplanets and the "expected" ones yet to be discovered - observable by ARIEL a…
The Origins of Planets for ArieL (OPAL) Key Science Project: the end-to-end planet formation campaign for the ESA space mission Ariel
INAF - Osservatorio Astrofisico di Torino（意大利国家天体物理研究所都灵天文台）；Centro Nazionale di Ricerca in High Performance Computing, Big Data and Quantum Computing（高性能计算、大数据与量子计算国家研究中心）；INAF - Istituto di Astrofisica e Planetologia Spaziali（意大利国家天体物理研究所天体物理学与行星科学研究所）；INAF - Osservatorio Astronomico di Trieste（意大利国家天体物理研究所的里雅斯特天文台）
The Atmospheric Remote-sensing Infrared Exoplanet Large-survey mission (ARIEL) is one of the three present candidates for the ESA M4 (the fourth medium mission) launch opportunity. The proposed Payload will perform a large unbiased spectroscopic survey from space concerning the nature of exoplanets atmospheres and their interiors to determine the key factors affecting the formation and evolution of planetary systems. ARIEL will observe a large number (>500) of warm and hot transiting gas giants, Neptunes and super-Earths around a wide range of host star types, targeting planets hotter than 600…
The Atmospheric Remote-sensing Infrared Exoplanet Large-survey (Ariel) is the first space mission dedicated to measuring the chemical composition and thermal structures of thousands of transiting exoplanets. Ariel was adopted in 2020 as the M4 mission in ESA "Cosmic Vision" program, with launch expected in 2029. The mission will operate from the Sun-Earth Lagrange Point L2. The scientific payload consists of two instruments: a high resolution spectrometer in the waveband 1.95-7.8 microns, and a fine guidance system / visible photometer / low resolution near-infrared spectrometer. The instrumen…
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 s…
The study of extrasolar planets and of the Solar System provides complementary pieces of the mosaic represented by the process of planetary formation. Exoplanets are essential to fully grasp the huge diversity of outcomes that planetary formation and the subsequent evolution of the planetary systems can produce. The orbital and basic physical data we currently possess for the bulk of the exoplanetary population, however, do not provide enough information to break the intrinsic degeneracy of their histories, as different evolutionary tracks can result in the same final configurations. The lesso…
The recently adopted Ariel ESA mission will measure the atmospheric composition of a large number of exoplanets. This information will then be used to better constrain planetary bulk compositions. While the connection between the composition of a planetary atmosphere and the bulk interior is still being investigated, the combination of the atmospheric composition with the measured mass and radius of exoplanets will push the field of exoplanet characterisation to the next level, and provide new insights of the nature of planets in our galaxy. In this white paper, we outline the ongoing activiti…
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 atmosph…
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 trac…
Machine Learning and Deep Learning for Exoplanet Detection and Atmospheric Characterization with JWST and the Upcoming Ariel Mission
Department of Industrial Physics, Enugu State University of Science and Technology（恩古州科技大学工业物理系）；Department of Physics, Dennis Osadebay University（德尼斯·奥萨德贝大学物理系）
Stellar variability from pulsations and granulation presents a source of correlated noise that can impact the accuracy and precision of multi-band photometric transit observations of exoplanets. This can potentially cause biased measurements in the transmission or emission spectrum or underestimation of the final error bars on the spectrum. ARIEL is a future space telescope and instrument designed to perform a transit spectroscopic survey of a large sample of exoplanets. In this paper we perform simulations to assess the impact of stellar variability arising from pulsations and granulation on …
Launching in 2028, ESA's Atmospheric Remote-sensing Exoplanet Large-survey (ARIEL) survey of $\sim$1000 transiting exoplanets will build on the legacies of Kepler and TESS and complement JWST by placing its high precision exoplanet observations into a large, statistically-significant planetary population context. With continuous 0.5--7.8~$μ$m coverage from both FGS (0.50--0.55, 0.8--1.0, and 1.0--1.2~$μ$m photometry; 1.25--1.95~$μ$m spectroscopy) and AIRS (1.95--7.80~$μ$m spectroscopy), ARIEL will determine atmospheric compositions and probe planetary formation histories during its 3.5-year mi…
Ariel has been selected as the next ESA M4 science mission and it is expected to be launched in 2028. During its 4-year mission, Ariel will observe the atmospheres of a large and diversified population of transiting exoplanets. A key factor for the achievement of the scientific goal of Ariel is the selection strategy for the definition of the input target list. A meaningful choice of the targets requires an accurate knowledge of the planet hosting star properties and this is necessary to be obtained well before the launch. In this work, we present the results of a bench-marking analysis betwee…
Ariel stellar characterisation IV. Fundamental parameters of 18 hot stars in the Ariel mission candidate sample
Space Research Institute, Austrian Academy of Sciences（奥地利科学院空间研究所）；Institute for Theoretical and Computation Physics, Graz University of Technology（格拉茨工业大学理论与计算物理研究所）；Department of Physics and Astronomy G. Galilei, University of Padova（帕多瓦大学伽利略物理学与天文学系）；INAF – Osservatorio Astronomico di Padova（意大利国家天体物理研究所帕多瓦天文台）；Departament d’Astronomia i Astrofísica, Universitat de València（瓦伦西亚大学天文与天体物理系）；INAF – Osservatorio Astrofisico di Arcetri（意大利国家天体物理研究所阿切特里天文台）；INAF – Osservatorio Astrofisico di Torino（意大利国家天体物理研究所都灵天文台）；Instituto de Astrofísica de Canarias（加那利群岛天体物理研究所）；Universidad de La Laguna（拉古纳大学）；Institute for Space Astrophysics and Planetology INAF-IAPS（意大利国家天体物理研究所空间天体物理与行星学研究所）；Department of Physics and Astronomy, University College London（伦敦大学学院物理学与天文学系）
Stellar flares with Ariel: detection prospects and impacts on exoplanet spectroscopy
Konkoly Observatory（孔科利天文台）；HUN-REN Research Centre for Astronomy and Earth Sciences（匈牙利研究网络地球与天文学研究中心）；HUN-REN CSFK MTA Centre of Excellence（匈牙利研究网络 CSFK 马塔科学院卓越中心）；SRON Space Research Organisation Netherlands（荷兰空间研究组织 SRON）
The goal of the Ariel space mission is to observe a large and diversified population of transiting planets around a range of host star types to collect information on their atmospheric composition. The planetary bulk and atmospheric compositions bear the marks of the way the planets formed: Ariel's observations will therefore provide an unprecedented wealth of data to advance our understanding of planet formation in our Galaxy. A number of environmental and evolutionary factors, however, can affect the final atmospheric composition. Here we provide a concise overview of which factors and effec…
On the synergetic use of Ariel and JWST for exoplanet atmospheric science
Kapteyn Institute University of Groningen（格罗宁根大学卡普坦研究所）；Université Paris-Saclay Université Paris Cité CEA CNRS AIM（巴黎萨克雷大学 巴黎西岱大学 CEA CNRS AIM）；King’s College London（伦敦国王学院）；LIRA Observatoire de Paris Université PSL CNRS Sorbonne Université Univ. Paris Cité Sorbonne Paris Cité（巴黎天文台 PSL大学 CNRS 索邦大学 巴黎西岱大学）；Department of Physics McGill University（麦吉尔大学物理系）；Department of Earth & Planetary Sciences McGill University（麦吉尔大学地球与行星科学系）；University of Valencia（瓦伦西亚大学）；INAF Osservatorio Astrofisico di Arcetri（意大利国家天体物理研究所阿切特里天文台）；Space Telescope Science Institute（太空望远镜科学研究所）；SRON Space Research Organisation Netherlands（荷兰空间研究组织）；Astrobiology Center（天体生物学中心）；National Astronomical Observatory of Japan（日本国立天文台）
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 observ…
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-resolut…
The Ariel mission will characterise the chemical and thermal properties of the atmospheres of about a thousand exoplanets transiting their host star(s). The observation of such a large sample of planets will allow to deepen our understanding of planetary and atmospheric formation at the early stages, providing a truly representative picture of the chemical nature of exoplanets, and relating this directly to the type and chemical environment of the host star. Hence, the accurate and precise determination of the host star fundamental properties is essential to Ariel for drawing a comprehensive p…
Identifying deformed exoplanets with JWST and Ariel: A target selection metric for phase curve observations
Leiden University（莱顿大学）；SRON, Space Research Organisation Netherlands（荷兰空间研究组织）；Observatoire astronomique de l’Université de Genève（日内瓦大学天文台）；University of New South Wales（新南威尔士大学）；Universidad de Antioquia（安蒂奥基亚大学）
This is an exciting era for exo-planetary exploration. The recently launched JWST, and other upcoming space missions such as Ariel, Twinkle and ELTs are set to bring fresh insights to the convoluted processes of planetary formation and evolution and its connections to atmospheric compositions. However, with new opportunities come new challenges. The field of exoplanet atmospheres is already struggling with the incoming volume and quality of data, and machine learning (ML) techniques lands itself as a promising alternative. Developing techniques of this kind is an inter-disciplinary task, one t…
Spectropolarimetric characterisation of exoplanet host stars in preparation of the $Ariel$ mission II. The magnetised wind environment of TOI-1860, DS Tuc A, and HD 63433
Ariel, the Atmospheric Remote-sensing Infrared Exoplanet Large-survey, was adopted as the fourth medium-class mission in ESA's Cosmic Vision programme to be launched in 2029. During its 4-year mission, Ariel will study what exoplanets are made of, how they formed and how they evolve, by surveying a diverse sample of about 1000 extrasolar planets, simultaneously in visible and infrared wavelengths. It is the first mission dedicated to measuring the chemical composition and thermal structures of hundreds of transiting exoplanets, enabling planetary science far beyond the boundaries of the Solar …
We present here the first release of the open-source python package ExoTETHyS, which aims to provide a stand-alone set of tools for modeling spectro-photometric observations of the transiting exoplanets. In particular, we describe: (1) a new calculator of stellar limb-darkening coefficients that outperforms the existing software by one order of magnitude in terms of light-curve model accuracy, i.e., down to <10 parts per million (ppm); (2) an exact transit light-curve generator based on the entire stellar intensity profile rather than limb-darkening coefficients. New tools will be added in lat…
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 spect…
Aims: ARCiS, a novel code for the analysis of exoplanet transmission and emission spectra is presented. The aim of the modelling framework is to provide a tool able to link observations to physical models of exoplanet atmospheres. Methods: The modelling philosophy chosen in this paper is to use physical and chemical models to constrain certain parameters while keeping free the parts where our physical understanding is still more limited. This approach, in between full physical modelling and full parameterisation, allows us to use the processes we understand well and parameterise those less und…
With the growing number of spectroscopic observations and observational platforms capable of exoplanet atmospheric characterization, there is a growing need for analysis techniques that can distill information about a large population of exoplanets into a coherent picture of atmospheric trends expressed within the statistical sample. In this work, we develop a Hierarchical Bayesian Atmospheric Retrieval (HBAR) model to infer population-level trends in exoplanet atmospheric characteristics. We demonstrate HBAR on the case of inferring a trend in atmospheric CO2 with incident stellar flux, predi…
Aims. To create a retrieval framework which encapsulates the 3D nature of exoplanet atmospheres, and to apply it to observed emission phase curve and transmission spectra of hot Jupiter exoplanet WASP-43b. Methods. We present our 3D framework, which is freely available as a stand-alone module from GitHub. We use the atmospheric modelling and Bayesian retrieval package ARCiS (ARtful modelling Code for exoplanet Science) to perform 8 3D retrievals on simultaneous transmission (HST/WFC3) and phase-dependent emission (HST/WFC3, Spitzer/IRAC) observations of WASP-43b as a case study. We assess how …
The ExoClock project is an inclusive, integrated, and interactive platform that was developed to monitor the ephemerides of the Ariel targets to increase the mission efficiency. The project makes the best use of all available resources, i.e., observations from ground telescopes, mid-time values from the literature and finally, observations from space instruments. Currently, the ExoClock network includes 280 participants with telescopes capable of observing 85\% of the currently known Ariel candidate targets. This work includes the results of $\sim$1600 observations obtained up to the 31st of D…
The ExoClock project has been created with the aim of increasing the efficiency of the Ariel mission. It will achieve this by continuously monitoring and updating the ephemerides of Ariel candidates over an extended period, in order to produce a consistent catalogue of reliable and precise ephemerides. This work presents a homogenous catalogue of updated ephemerides for 450 planets, generated by the integration of $\sim$18000 data points from multiple sources. These sources include observations from ground-based telescopes (ExoClock network and ETD), mid-time values from the literature and lig…
