ESA's MADRID-Area Exoplanet Science Meeting (MAESM) 2023

Programme

Abstracts

The PLATO mission: Status and first long pointing field (J. Miguel Mas Hesse, Centro de Astrobiología (CAB/CSIC-INTA))

PLATO is an ESA medium-class mission currently in development with a planned launch date in December 2026. PLATO will use high precision photometric observations to detect and analyse transits of exoplanets down to Earth size and to perform asteroseismology measurements to characterise their host stars. Thanks to its large field of view, PLATO will carry out simultaneous observations of more than hundred thousand bright solar-like stars (V < 13), which will enable unprecedented accurate determinations of the exoplanet radii and stellar ages and, by combining with ground-based observations, of exoplanet masses and, hence, densities. Through long observations (> 2 years) of each sky field, PLATO will be able to discover Earth-size planets orbiting up to the habitable zone of Sun-like stars and derive their bulk properties. 

Major advances have been made in the definition of the PLATO Input Catalogue for the sky areas in which long duration pointings are possible, considering spacecraft and operational constraints. Based on this knowledge, the PLATO Science Working Team selected in June 2023 the location of the first long pointing sky field. In this presentation we will describe the characteristics of this first field, including an analysis of the stellar population and of the targets pre-selected for observation. 

The development of the PLATO spacecraft and payload, and of the corresponding ground-segment, advances according to plan. The camera serial production is well underway, with the objective to deliver about 30% of the 26 flight model cameras for integration with the satellite by the end of 2023. The thermo-mechanical tests of the full spacecraft structural model have been already completed. Integration on the platform of the 26 cameras should be finished by around mid 2025.

Follow-up of Gaia DR3 astrometric exoplanet candidates (Johannes Sahlmann, RHEA Group for ESA, ESAC)

The third data release of ESA's Gaia mission (GDR3) contains roughly 1800 astrometric orbit solutions that are compatible with the presence of substellar companions, including extrasolar super-Jupiters. The determination of the actual status of a candidate companion, i.e. whether it is an exoplanet, a brown-dwarf, or an impostor binary star, often hinges on the use of non-Gaia data, e.g. high-resolution spectra and precision radial velocities. I will present an overview of the first year of community follow-up on GDR3 exoplanet candidates and highlight a few results and their implications.

Searching for low-mass companions with Gaia (Patricia Cruz, Centro de Astrobiología (CAB/CSIC-INTA))

After a discussion during the last MAESM meeting in 2022, we started investigating stellar multiplicity in the low-mass regime using Gaia data, searching for low-mass stars that may have companions, being M dwarfs, brown dwarfs or planets. We adopted a sample of 1843 sources listed as astrometric binary systems, composed of possibly late-type components, published by the Gaia Collaboration et al. (2022). We used tools from the Virtual Observatory (VO) in combination with data from Gaia DR3 and other archive data to search for potential companions as an infrared excess in their spectral energy distributions. We have identified 7 candidates that may have a lower-temperature/mass companion. Spectroscopic follow up is needed to confirm the low-mass nature of the companion candidates.

Exoplanets with CARMENES (Esther González Álvarez, Universidad Complutense de Madrid)

CARMENES (Calar Alto high-Resolution search for M dwarfs with Exoearths with Near-infrared and optical Échelle Spectrographs) is the name of the instrument, the consortium that designed and built it, and of the science project that is being carried out during guaranteed and legacy time observations. The main scientific objective of CARMENES is to carry out a survey of late-type main sequence stars with the goal of detecting low-mass planets in their habitable zones. CAB and UCM in Madrid are part of the CARMENES Consortium that has become famous in the last years for their discoveries. As a member of CARMENES, I will summarize the most relevant discoveries and I will emphasize on the tasks carried out in Madrid.

Multiplicity of stars with planets in the solar neighbourhood (Javier González-Payo, Universidad Complutense de Madrid)

We analyse all the multiple stellar systems (doubles, triples, quadruples...) at d < 100 pc with at least one reported exoplanet. We make extensive use of Gaia DR3. We compile 210 multiple stellar systems with exoplanets, identify 20 new common parallax and proper motion (and radial velocity) companions, and discard several systems that become single, members in open clusters, or that have no exoplanet at all. Our catalogue is useful for investigating the effect of stellar multiplicity on the formation and evolution of exoplanetary systems. As a preliminary result, of the 947 stars with detected exoplanets in the solar neighborhood, about 18% are doubles, 4% are triples, and only 0.2% are quadruples, with no higher-order systems found.

Are all rocky planets really rocky? The case of TOI-244 b and the growing population of low-density super-Earths (Amadeo Castro-González, Centro de Astrobiología (CAB/CSIC-INTA))

Small planets located at the lower mode of the bimodal radius distribution are generally assumed to be composed of iron and silicates in a proportion similar to that of the Earth. However, recent discoveries are revealing a new group of low-density planets that are inconsistent with that description. Their low densities could be explained by a scarcity of iron within their cores, by the presence of a significant amount of volatile elements, or by both effects. Recently, Adibekyan et al. found that stars with higher Mg/Fe and Si/Fe ratios host lighter super-Earths, which indicates a compositional star-planet connection. However, the lowest-dense super-Earths cannot be explained by having an iron-poor core, and instead require a significant amount of volatile elements in their compositions. The reason why those planets have such large amounts of volatiles is still unknown. In this talk, I will present our recent characterization of the unusually low-density super-Earth TOI-244 b based on ESPRESSO and TESS data and discuss its possible composition. Besides, I will present two tentative trends in the density-metallicity and density-insolation parameter space that might hint at the formation and composition of the lowest-density super-Earths.

TESS and ASTEP characterisation of a long-period exoplanet candidate around TOI-4409 as an example of a new data-driven lightcurve analysis tool (Patricio Reller, University College London)

Long-period exoplanets are scientifically compelling as edge cases within the known exoplanet population and are challenging to observe due to the strict scheduling requirements they impose on the observations. TESS and an Antarctica-based telescope called ASTEP have observed 12 transits of the long-period exoplanet candidate TOI-4409 b. We present a combined transit method analysis of these lightcurves to confirm the exoplanet's presence around the star and refine its TESS-derived physical properties. The data-intensive pipeline developed for this project has broader applications beyond this particular case; thus, we will also present its preliminary development status and seek feedback from users on desired features that would be most useful for their scientific use cases.

Understanding the origin and nature of sub-Neptunes (Rafael Luque, University of Chicago)

Sub-Neptune planets, absent in our solar system but ubiquitous in the Galaxy, remain a mystery. Two contesting hypotheses are able to explain their individual and population-level properties, but they make remarkably different predictions about their origin, location at initial formation, and internal composition. Are sub-Neptunes 'gas dwarfs' (Earth-like cores surrounded by large hydrogen-rich envelopes formed near their observed close-in locations) or 'water worlds' (planets formed beyond the snow line composed of a 1:1 mixture of ice and rock by mass)? If the latter exist, what are their demographic and individual properties and how do they depend on stellar host type? Currently, there is no conclusive observational evidence supporting one theory or another, since mass and radius measurements alone are insufficient. In this talk, I will summarize ongoing and upcoming programs aiming at testing the water world hypothesis. A definitive answer seems within reach during this decade thanks to the game-changing observations that will be provided by ground- and space-based observatories.

Time-resolved Optical Polarization Monitoring of the Most Variable Brown Dwarf (Elena Manjavacas, ESA for Space Telescope Science Institute)

Recent atmospheric models for brown dwarfs suggest that the existence of clouds in substellar objects is not needed to reproduce their spectra, nor their rotationally induced photometric variability, believed to be due to the heterogeneous cloud coverage of brown dwarf atmospheres. Cloud-free atmospheric models also predict that their flux should not be polarized, as polarization is produced by the light scattering of particles in the inhomogeneous cloud layers of brown dwarf atmospheres. To shed light on this dichotomy, we monitored the linear polarization and photometric variability of the most variable brown dwarf, 2MASS J21392676+0220226, using the FORS2 at the UT1 telescope. In this talk, I will present the results of this monitoring campaign, and I will justify the need for time-resolved polarimetric observations for a bigger sample of brown dwarfs.

Super-earths orbiting nearby M dwarfs (María Rosa Zapatero Osorio, Centro de Astrobiología (CAB/CSIC-INTA))

We shall present the analysis of two planetary systems formed by early-M dwarf stars and their super-Earth planets. All planets transit in front of their stars according to TESS photometry, and for all we have obtained CARMENES and/or ESPRESSO spectroscopic data, which allow us to derive accurate planetary radii and masses. Preliminary results indicate that the two parent stars may be chemically different; we shall study whether the properties of their rocky planets differ significantly.

Radio observations as a tool to unveil star-planet interaction in M-dwarfs (Miguel Pérez-Torres, Instituto de Astrofísica de Andalucía, CSIC (IAA-CSIC))

Auroral radio emission has been detected from all magnetized planets in the solar system. Since extrasolar giant planets are probably magnetized, like Jupiter, they are expected to produce auroral radio emission via the cyclotron maser mechanism up to a few tens of MHz. Therefore, the direct detection of auroral radio emission from a planet is not only very challenging, but limited to Jupiter-size, or larger planets. Fortunately, sub-Alfvénic star-planet interaction may yield significant auroral radio emission at significantly higher frequencies, even at GHz frequencies.  

I will give an overview of how radio observations can be used to detect new exoplanets, and how the modelling of this radio emission can help in pinning down the mass-loss rate of the host star, or the exoplanetary magnetic field. 

If successful, radio observations will open a new avenue for exoplanet hunting and the study of a new field of exoplanet-star plasma interaction.

ExoAID : Artificial Intelligence (Asier Abreu, ATG Europe B.V.)

The current census of exoplanets has been almost entirely built upon transit and radial velocity detection methods. While astrometric exoplanet detection has been almost anecdotal so far due to the ultra-high (~as) precision required for this detection technique, the arrival of ESA's Gaia mission has radically changed the picture, paving the road for astrometric exoplanet detection at large and over the full-sky. Our project (ExoAID) aims to improve the current statistics and sky-coverage on detected exoplanets by application of machine and deep learning techniques to the Gaia catalog. We want to exploit the expected correlation between the astrometric solution quality and the presence of a sub-stellar mass companion for detection purposes. Using a synthetic dataset that simulates a single keplerian orbit (binary system) and provides the same attributes as the Gaia catalog, we train different type of classifiers to make them learn the underlying relation between those features and a binary class target (positive=candidate to host exoplanet/ negative=unlikely to host exoplanet detectable by Gaia) . The usage of a synthetic dataset has several advantages, allowing an on-demand precision mapping of the orbital parameters space, besides a full control of the otherwise unavoidable class imbalance problem on real data. The trained model is then directly applicable to the existing Gaia DR3 catalog (after adequate preprocessing) and can be used to produce a first list of candidate stars to host exoplanets. We intend to also perform external cross checks against the available Gaia (candidate) exoplanet list and to the list of known stars to host exoplanets (when possibly detectable by Gaia , the later). Future work will concentrate on the characterisation of the candidate list and the synergies with other exoplanet observatories like PLATO and ARIEL.

Exploration of exoplanet atmospheres with machine learning (Antonia Vojtekova, University College London)

In the current era of exoplanetary research, we are witnessing an unprecedented wave in acquiring exoplanet-related data. The field is gradually transitioning into the domain of big data science. Consequently, there is a growing imperative to explore novel data analysis techniques, particularly those involving machine learning.

It is widely recognized that unravelling the complexities of exoplanet atmospheres demands substantial computational resources, which may pose future computational bottlenecks. Machine learning offers a promising way to accelerate these computations without necessarily replacing existing models.

In this presentation, we introduce a project to enhance the efficiency of modelling disequilibrium chemistry in exoplanet atmospheres. Our project's objective is the development of a machine learning algorithm capable of speeding the calculation of species abundances within exoplanetary atmospheres, enabling the transition from equilibrium chemistry (equilibrium model - ACE, Agundez et al. 2012) to disequilibrium chemistry (kinetic model - FRECKLL, Al-Refaie et al. 2022). Before delving into the intricacies of deep learning, we have conducted an in-depth analysis of our dataset to uncover inherent patterns and insights.

Our presentation will delve into the scientific methodologies and strategies employed to achieve faster calculations, thereby contributing to our understanding of exoplanetary atmospheres.

LOCAL INFORMATION

All in-person attendees are invited to arrive at the ESAC security gate (https://www.esa.int/About_Us/ESAC/Como_llegar_a_ESAC) latest by 11:15 CEST to collect their badges for the day. We will walk together from there to the wonderful ESAC canteen, and enjoy a lunch together (self-paid). The presentations will start from 13:00 CEST, with a mix of in-person and virtual presentations. We aim to enjoy a relaxing evening in the Spanish Sun and continue with informal science discussions during a drink at the ESAC K-building Social Club from around 17:00 CEST.

LINKS

Link to the event privacy notice

Link to the event privacy notice for abstract collection

Link to the event recording notice

Link to the code of conduct

Link to the WebEx etiquette