Michael Cretignier

Abstract:

The architecture of planetary systems is a key piece of information to our understanding of their formation and evolution. This information also allows us to place the Solar System in the exoplanet context. An important example is the impact of outer giant planets on the formation of inner super-Earths and sub-Neptunes. Radial velocity (RV) surveys aim at drawing statistical insights into the (anti-)correlations between giants and inner small planets, which remain unclear. These surveys are limited by the completeness of the systems, namely, the sensitivity of the data to planet detections. Here, we show that we can improve the completeness by accounting for orbital stability. We introduce the Algorithm for the Refinement of DEtection limits via N-body stability Threshold (ARDENT), an open-source Python package for detection limits that include the stability constraint. The code computes the classic data-driven detection limits, along with the dynamical limits via both analytical and numerical stability criteria. We present the code strategy and illustrate its performance on TOI-1736 using published SOPHIE RVs. This system contains an eccentric cold giant on a 570-day orbit and an inner sub-Neptune on a 7-day orbit. We demonstrate that no additional planet can exist in this system beyond 150 days due to the gravitational influence of the giant. This outcome allows us to significantly refine the system completeness and also carries implications for RV follow-ups. ARDENT is user-friendly and can be employed across a wide variety of systems to refine our understanding of their architecture.

Abstract:

Context. Active regions on the stellar surface can induce quasi-periodic radial velocity (RV) variations that can mimic planets and mask true planetary signals. These spurious signals can be problematic for RV surveys such as those carried out by the ESPRESSO consortium. Aims. Using ESPRESSO and HARPS RVs and activity indicators, we aim to confirm and characterise two candidate transiting planets from TESS orbiting a K4 star with strong activity signals. Methods. From the ESPRESSO FWHM, TESS photometry, and ASAS-SN photometry, we measure a stellar rotation period of 21.28 ± 0.08 d. We jointly model the TESS photometry, ESPRESSO and HARPS RVs, and activity indicators, applying a multivariate Gaussian process (GP) framework to the spectroscopic data. Results. We are able to disentangle the planetary and activity components, finding that TOI-2322 b has a 11.307170−0.000079+0.000085 d period, close to the first harmonic of the rotation period, a ≤2.03 M⊕ mass upper limit and a 0.994−0.059+0.057 R⊕ radius. TOI-2322 c orbits close to the stellar rotation period, with a 20.225528−0.000044+0.000039 d period; it has a 18.10−5.36+4.34 M⊕ mass and a 1.874−0.057+0.066 R⊕ radius. Conclusions. The multivariate GP framework is crucial to separating the stellar and planetary signals, significantly outperforming a one-dimensional GP. Likewise, the transit data is fundamental to constraining the periods and epochs, enabling the retrieval of the planetary signals in the RVs. The internal structure of TOI-2322 c is very similar to that of Earth, making it one of the most massive planets with an Earth-like composition known.

Abstract:

Abstract As radial velocity (RV) spectrographs reach unprecedented precision and stability below 1 m s−1, the challenge of granulation in the context of exoplanet detection has intensified. Despite promising advancements in post-processing tools, granulation remains a significant concern for the EPRV community. We present a pilot study to detect and characterise granulation using the High-Accuracy Radial-velocity Planet Searcher for the Northern hemisphere (HARPS-N) spectrograph. We observed HD 166620, a K2 star in the Maunder Minimum phase, intensely for two successive nights, expecting granulation to be the dominant nightly noise source in the absence of strong magnetic activity. After correcting for a newly identified instrumental signature, originating from CCD illumination variations under optimal seeing conditions, we detected the granulation signal using structure-function (SF) analysis and a single-component Gaussian Process (GP) model. The granulation signal has a characteristic timescale of $43.65^{+16.9}_{-14.7}$ minutes, within one σ, and a standard deviation of $22.9^{+0.83}_{-0.72}$ cm s−1, within three σ of the predicted value. By examining spectra and RVs as a function of line formation temperature, we investigated the sensitivity of granulation-induced RV variations across different photospheric layers. We extracted RVs from various photospheric depths using both the line-by-line (LBL) and cross-correlation function (CCF) methods to mitigate any extraction method biases. Our findings indicate that granulation variability is detectable in both temperature bins, with the cooler bins, corresponding to the shallower layers of the photosphere, aligning more closely with predicted values.

Abstract:

Abstract Doppler Imaging (DI) is a well-established technique to map a physical field at a stellar surface from a time series of high-resolution spectra. In this proof-of-concept study, we aim to show that traditional DI algorithms, originally designed for rapidly-rotating stars, have also the ability to model the activity of Sun-like stars, when observed with new-generation highly-stable spectrographs, and search for low-mass planets around them. We used DI to retrieve the relative brightness distribution at the surface of the Sun from radial velocity (RV) observations collected by HARPS-N between 2022 and 2024. The brightness maps obtained with DI have a typical angular resolution of ~36○ and are a good match to low-resolution disc-resolved Dopplergrams of the Sun at epochs when the absolute, disc-integrated RV exceeds ~2 m s−1. The RV residuals after DI correction exhibit a dispersion of about 0.6 m s−1, comparable with existing state-of-the-art activity correction techniques. Using planet injection-recovery tests, we also show that DI can be a powerful tool for blind planet searches, so long as the orbital period is larger than ~100 days (i.e. 3 to 4 stellar rotation periods), and that it yields planetary mass estimates with an accuracy comparable to, for example, multi-dimensional Gaussian process regression. Finally, we highlight some limitations of traditional DI algorithms, which should be addressed to make DI a reliable alternative to state-of-the-art RV-based planet search techniques.

Abstract:

With more than a dozen significant detections, the helium triplet has emerged as a key tracer of evaporating exoplanet atmospheres. This near-infrared feature can be observed from the ground and holds great promise, especially with upcoming observations provided by new-generation instruments such as the Near Infrared Planet Searcher (NIRPS). However, as the helium triplet is also present in stellar spectra, careful removal of the average stellar contribution is necessary to accurately characterize the atmospheres of transiting exoplanets. In this study, we analyze multi-epoch observations of the Sun obtained with NIRPS to investigate the temporal variability of the helium triplet. Our findings reveal significant variability across different timescales, ranging from minutes to days. We identify telluric contamination and stellar activity as likely sources for the short-term and long-term variability, respectively. Importantly, we demonstrate that this variability has minimal impact on the retrieval of planetary parameters crucial to the study of atmospheric escape.