3 research outputs found

    Tentative co-orbital submillimeter emission within the Lagrangian region L5 of the protoplanet PDS 70 b

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    Context: High-spatial resolution Atacama Large Millimeter/submillimeter Array (ALMA) data have revealed a plethora of substructures in protoplanetary disks. Some of those features are thought to trace the formation of embedded planets. One example is the gas and dust that accumulated in the co-orbital Lagrangian regions L4L_4/L5L_5, which were tentatively detected in recent years and might be the pristine material for the formation of Trojan bodies. Aims: This work is part of the TROY project, whose ultimate goal is to find robust evidence of exotrojan bodies and study their implications in the exoplanet field. Here, we focus on the early stages of the formation of these bodies by inspecting the iconic system PDS 70, the only confirmed planetary system in formation. Methods: We reanalyzed archival high-angular resolution Band 7 ALMA observations from PDS 70 by doing an independent imaging process to look for emission in the Lagrangian regions of the two detected gas giant protoplanets, PDS 70 b and c. We then projected the orbital paths and visually inspected emission features at the regions around the L4L_4/L5L_5 locations as defined by ±\pm 60^{\circ} in azimuth from the planet position. Results: We found emission at a \sim4-σ\sigma level (\sim6-σ\sigma when correcting from a cleaning effect) at the position of the L5L_{5} region of PDS 70 b. This emission corresponds to a dust mass in a range of 0.03- 2 MMoon_{Moon}, which potentially accumulated in this gravitational well. Conclusions: The tentative detection of the co-orbital dust trap that we report requires additional observations to be confirmed. We predict that we could detect the co-orbital motion of PDS 70 b and the dust presumably associated with L5L_5 by observing again with the same sensitivity and angular resolution as early as February 2026.Comment: 8 pages, 5 figures, 2 tables. Published in Astronomy & Astrophysic

    KOBEsim: A Bayesian observing strategy algorithm for planet detection in radial velocity blind-search surveys

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    Context. Ground-based observing time is precious in the era of exoplanet follow-up and characterization, especially in high-precision radial velocity instruments. Blind-search radial velocity surveys thus require a dedicated observational strategy in order to optimize the observing time, which is particularly crucial for the detection of small rocky worlds at large orbital periods. Aims. We developed an algorithm with the purpose of improving the efficiency of radial velocity observations in the context of exoplanet searches, and we applied it to the K-dwarfs Orbited By habitable Exoplanets experiment. Our aim is to accelerate exoplanet confirmations or, alternatively, reject false signals as early as possible in order to save telescope time and increase the efficiency of both blind-search surveys and follow-up of transiting candidates. Methods. Once a minimum initial number of radial velocity datapoints is reached in such a way that a periodicity starts to emerge according to generalized Lomb-Scargle periodograms, that period is targeted with the proposed algorithm, named KOBEsim. The algorithm selects the next observing date that maximizes the Bayesian evidence for this periodicity in comparison with a model with no Keplerian orbits. Results. By means of simulated data, we proved that the algorithm accelerates the exoplanet detection, needing 29-33% fewer observations and a 41-47% smaller time span of the full dataset for low-mass planets (mp < 10 M⊕) in comparison with a conventional monotonic cadence strategy. For 20 M⊕ planets we found a 16% enhancement in the number of datapoints. We also tested KOBEsim with real data for a particular KOBE target and for the confirmed planet HD 102365 b. These two tests demonstrate that the strategy is capable of speeding up the detection by up to a factor of 2 (i.e., reducing both the time span and number of observations by half).14 página

    Project goals, target selection, and stellar characterization

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    The detection of habitable worlds is one of humanitya-s greatest endeavors. Thus far, astrobiological studies have shown that one of the most critical components for allowing life to develop is liquid water. Its chemical properties and its capacity to dissolve and, hence, transport other substances makes this constituent a key piece in this regard. As a consequence, looking for life as we know it is directly related to the search for liquid water. For a remote detection of life in distant planetary systems, this essentially means looking for planets in the so-called habitable zone. In this sense, K-dwarf stars are the perfect hosts to search for planets in this range of distances. Contrary to G-dwarfs, the habitable zone is closer, thus making planet detection easier using transit or radial velocity techniques. Contrary to M-dwarfs, stellar activity is on a much smaller scale, hence, it has a smaller impact in terms of both the detectability and the true habitability of the planet. Also, K-dwarfs are the quietest in terms of oscillations, and granulation noise. In spite of this, there is a dearth of planets in the habitable zone of K-dwarfs due to a lack of observing programs devoted to this parameter space. In response to a call for legacy programs of the Calar Alto observatory, we have initiated the first dedicated and systematic search for habitable planets around these stars: K-dwarfs Orbited By habitable Exoplanets (KOBE). This survey is monitoring the radial velocity of 50 carefully pre-selected K-dwarfs with the CARMENES instrument over five semesters, with an average of 90 data points per target. Based on planet occurrence rates convolved with our detectability limits, we expect to find 1.68 ± 0.25 planets per star in the KOBE sample. Furthermore, in half of the sample, we expect to find one of those planets within the habitable zone. Here, we describe the motivations, goals, and target selection for the project as well as the preliminary stellar characterization. © 2022 EDP Sciences. All rights reserved
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