Many areas of astrophysics, including exoplanetary studies, rely on precise and accurate stellar parameters. This demands that uncertainties on these parameters truly reflect all biases and systematics. Within this second work of the gr8stars collaboration, we take a set of 585 bright FGK type dwarfs with high resolution, high signal-to-noise ratio spectra from the SOPHIE (Spectrographe pour l'Observation desPh & eacute;nom & eacute;nes des Int & eacute;rieurs stellaires et des Exoplan & egrave;tes) spectrograph. We determine stellar effective temperature, surface gravity, and metallicity using five different spectroscopic methods for each star, with an additional method used for comparisons. We find a typical scatter of 76 K in T-eff, 0.14 dex in log g, and 0.07 dex in [Fe/H]. These deviations are significantly larger than the average precision error on these parameters. We furthermore use isochrone fitting to determine mass, radius, and age for all 585 stars, using input from all results. We use the radii determined by SED (Spectral Energy Distribution) fitting in the first gr8stars paper as a comparison to our isochronal radii from this work, in addition to comparing the isochronal log g to spectroscopic log g. The scatter in mass and radius from the use of different spectroscopic methods is investigated and propagated to exoplanetary parameters. The induced fractional uncertainties in planetary radius (less than or similar to 3 per cent) and mass (less than or similar to 5 per cent) are found to be below those typically found in the literature. We estimate a lower limit on planetary equilibrium temperature fractional uncertainty of $\approx$ 4 per cent, a noise floor that is currently not sufficiently represented in the literature.

Young planets offer a unique window into the early stages of planetary evolution. AU Mic is one of the nearest (9.8 pc) pre-main-sequence stars (similar to 20 Myr), hosting two transiting Neptune-sized planets and a debris disk. Previous studies have shown that the rotations of the central star, the debris disk, and the inner planet b are all aligned, suggesting that the system has not undergone violent evolution. Here we report new Rossiter-McLaughlin measurements for both AU Mic b and c, which happened to transit back-to-back on 2024 August 24 and 25, using the Magellan Planet Finder Spectrograph, together with contemporaneous photometry from LCOGT and CHEOPS. We confirm the aligned orbit of AU Mic b (lambda(b) = 1 degrees +/- 12 degrees) and find two possible solutions for AU Mic c: we slightly favor an aligned solution (lambda(c) = -10 degrees +/- 16 degrees) but cannot rule out a polar solution ( lambda(c)=87 degrees(+36 degrees)(-29 degrees)). Broader considerations, including dynamical stability and transit possibility, also support the mutually aligned scenario. An unexpected stellar signal during ingress and the poor transit-timing variation predictions of AU Mic c prevent a precise constraint on its obliquity, and various attempts using chromatic spectral analyses fail to outperform simple data exclusion in mitigating stellar contamination. Our observation highlights the importance of understanding stellar activity across multiple timescales and channels when characterizing young, active systems. A robust solution for the AU Mic architecture will require either a better understanding of stellar activity or future observations fortuitously free from strong stellar contamination.

We revisit the TOI-2134 planetary system with three new high-cadence TESS sectors and 98 more spectra. This new analysis confirms the two orbiting planets by simultaneously modelling a total of eight sectors of corrected TESS photometry and 280 HARPS-N and SOPHIE radial velocities: an inner mini-Neptune in a near-circular 9.229198 +/- 0.000003 d orbit, and an outer temperate sub-Saturn orbiting with a 95.852840 +/- 0.000042 d period and eccentricity of 0.31 +/- 0.01. The masses and radii of the planets were computed to be 9.37 +/- 0.54 M-circle plus and 2.735 +/- 0.068 R-circle plus for planet b, and 58.3 +/- 1.9 M-circle plus and 7.35 +/- 0.18 R-circle plus for planet c. The new data not only improves the detection significance and precisions on the planetary orbits, but also breaks the original multimodality in the eccentricity solution for the outer planet. We also detect a long-term trend in the radial velocity data, which we attribute to a stellar magnetic cycle. We investigate the spin-orbit alignment of the system via observations of the Rossiter-McLaughlin (RM) effect for TOI-2134 b with EXPRES and TOI2134 c with PARAS-2. No RM effect was detected for planet b, but we find a 4.7 sigma detection of a 59 +/- 31 degrees obliquity for planet c. Finally, we examine the architecture of the system, assess its completeness, investigate the planetary interior, and their suitability for follow-up atmospheric analysis

Context. Stellar activity remains one of the main limitations in the detection of Earth-like planets using radial velocity (RV) measurements. The Sun, as the only star for which surface features can be spatially resolved, offers a unique testbed for studying the impact of active regions on RV and photometric variability. Aims. Using SOAPv4 (Spot Oscillation And Planet), we modelled solar RV and photometric variability induced by spots and faculae over long timescales. Our goal is to verify whether present-day, state-of-the-art models of the cross-correlation function correctly reproduce the observed variability. Moreover, we aim to assess how the choice of input data and identification technique influences the agreement between simulated and observed signals. Methods. To simulate solar RV and photometric time series, we first identified active regions in SDO images. This was done using mathematical morphological transforms applied to SDO/HMI and AIA images. Mathematical morphological identification was validated against other state-of-the-art identification methods. Using these inputs, we ran SOAPv4 to simulate solar RVs and photometry, and we validated the results with HARPS-N RV observations, as well as with VIRGO/SPM photometric measurements. Results. The simulations that use mathematical morphological identification achieved the best match with the observed RV time series, yielding residuals with a measured standard deviation of similar to 0.91 m/s. Other state-of-the-art methods produced higher filling factors and, consequently, larger discrepancies. The photometric simulations reproduced the overall variability trends. Conclusions. We demonstrate that mathematical morphological transforms accurately identify solar active regions. Using these inputs, SOAPv4 reproduces the observed solar RV variability with a measured standard deviation of the residuals of similar to 0.91 m/s. Photometric simulations capture the overall variability trends, confirming that SOAP can reliably model the impact of both spots and faculae on solar RVs and photometry.

Context . Detecting the tiny Doppler shifts induced by Earth-mass planets in stellar radial-velocity measurements remains extremely challenging due to stellar activity. Despite substantial progress in statistical and machine-learning techniques, many deep-learning methods performing well on simulated data remain difficult to apply reliably on real stellar spectra. Aims . The aim of this work is to develop a deep-learning framework that generalizes to real, unseen spectra and improves the detectability of Earth-mass planets in radial-velocity data. Methods . We train artificial neural networks on HARPS-N solar spectra with injected planetary signals, using physics-motivated spectral representations based on flux and line-formation temperature, together with their velocity gradients. Two training strategies are explored: hold-out testing, which provides a direct assessment of generalization to unseen spectra, and cross-validation, which evaluates performance across multiple folds of the dataset. The robustness of the model is enhanced by optimizing the hyperparameters based on genetic-algorithms, and the predictive uncertainty is quantified using the Monte Carlo dropout. Results . Our most precise neural network model reliably retrieves, under the cross-validation strategy, the amplitudes, phases, and orbital periods of planetary signals with amplitudes greater than or equal to 25 cm/s and periods between 10 and 550 days. In addition, in all cases tested here, the successfully recovered signals correspond to the most significant peaks in the periodograms of the Doppler-shift predictions. Temperature-based spectral-shell representations consistently outperform flux-based shells, particularly in terms of predictive uncertainty and generalization to unseen data. As a byproduct, we release doppleriann , a Python package that implements the proposed framework. Conclusions . Our results demonstrate that combining physically motivated spectral representations with deep learning provides a promising pathway toward the detection of Earth-mass planets in radial-velocity data from real observations, supported by a modeling framework that is both physically grounded and statistically rigorous, incorporating uncertainty quantification and optimized training strategies.

The young TOI-451 planetary system, aged 125 Myr, provides a unique opportunity to test theories of planetary internal structures and atmospheric mass-loss through examination of its three transiting planets. We present an exhaustive photometric and spectroscopic follow-up to determine the orbital and physical properties of the system. We perform multidimensional Gaussian Process regression with the code pyaneti on spectroscopic time-series and NGTS/LCO light curves to disentangle the stellar and planetary signal in ESPRESSO radial velocities. We show how contemporaneous photometry serves as an activity indicator to inform RV modelling within a multidimensional Gaussian Processes framework. We argue that this can be exploited when spectroscopic observations are adversely affected by low signal-to-noise and/or poor sampling. We estimate the Doppler semi-amplitudes of $k_{\rm b}=$ $2.6_{-1.2}<^>{+1.1}$ $\mathrm{m\, s<^>{-1}}$, $k_{\rm c}=$ $1.2_{-0.8}<^>{+1.0}$ $\mathrm{m\, s<^>{-1}}$ , and $k_{\rm d}=$ $2.7 \pm 1.2$ $\mathrm{m\, s<^>{-1}}$ . This translates in 2$\sigma$ mass estimates for TOI-451 b and d of $M_{\rm b}=$ $4.7_{-2.2}<^>{+2.1}$ $\mathrm{M_{\rm{\oplus }}}$ and $M_{\rm d}=$ $10.2_{-4.5}<^>{+4.6}$ $\mathrm{M_{\rm{\oplus }}}$; as well as a mass upper limit for TOI-451 c of $M_{\rm c} \lt 11.5\, M_{\rm{\oplus }}$. The derived planetary properties suggest that planets c and d contain significant hydrogen-rich envelopes. The inferred parameters of TOI-451 b are consistent with either a rocky world that still retains a small hydrogen envelope or a water world. These insights make the TOI-451 system an ideal laboratory for future follow-up studies aimed at measuring atmospheric compositions, detecting atmospheric mass-loss signatures, and further exploring planetary formation and evolution processes.

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, also have 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 (High Accuracy Radial velocity Planet Searcher for the Northern hemisphere) between 2022 and 2024. The brightness maps obtained with DI have a typical angular resolution of similar to 36 (omicron )and are a good match to low-resolution disc-resolved Dopplergrams of the Sun at epochs when the absolute, disc-integrated RV exceeds similar to 2m 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 similar to 100 d (i.e. 3-4 yr stellar rotation periods), and that it yields planetary mass estimates with an accuracy comparable to, for example, multidimensional 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.

In recent years supergranulation has emerged as one of the biggest challenges for the detection of Earth-twins in radial velocity planet searches. We used eight years of Sun-as-a-star radial velocity observations from HARPS-N to measure the quiet-Sun's granulation and supergranulation properties of most of its 11-year activity cycle, after correcting for the effects of magnetically active regions using two independent methods. In both cases, we observe a clear, order of magnitude variation in the time-scale of the supergranulation component, which is largest at activity minimum and is strongly anti-correlated with the relative Sunspot number. We also explored a range of observational strategies which could be employed to characterise supergranulation in stars other than the Sun, showing that a comparatively long observing campaign of at least 23 nights is required, but that up to 10 stars can be monitored simultaneously in the process. We conclude by discussing plausible explanations for the "supergranulation" cycle.

Context. One of the main obstacles in exoplanet detection when using the radial velocity (RV) technique is the presence of stellar activity signal induced by magnetic regions. As the most advanced techniques to mitigate this signal are reaching a level better than one meter per second, it is difficult to evaluate their performance: instrumental systematics start to be similar in magnitude, and therefore it is impossible to know the ground truth of the stellar activity signal. In this context, a realistic simulated dataset that can provide photometry and spectroscopic outputs is needed for method development. Aims. The goal of this paper is to describe two realistic simulations of solar activity obtained from SOAP-GPU and to compare them with real data obtained from the HARPS-N solar telescope. For this purpose, both simulated spectral time series cover the time window of HARPS-N solar observation, but nothing prevents SOAP-GPU from modeling the data over different time spans. Methods. We describe two different methods of modeling solar activity using SOAP-GPU. The first models the evolution of active regions based on the spot number as a function of time. Other physical parameters are either drawn from observed solar distributions or modeled with empirical relations. The second method relies on the extraction of active regions from the Solar Dynamics Observatory (SDO) data. The location of spots and faculae on the solar disk at each timestamp are derived from the magnetogram and intensity maps and are fed into SOAP-GPU to simulate the corresponding spectra. Results. The simulated spectral time series generated with the first method shows a long-term RV behavior similar to that seen in the HARPS-N solar observations. The effect of stellar activity induced by stellar rotation is also well modeled with prominent periodicities at the stellar rotation period and its first harmonic. The comparison between the simulated spectral time series generated using SDO images and the HARPS-N solar spectra shows that SOAP-GPU can precisely model the RV time series of the Sun to a precision better than 0.9 m/s. By studying the width and depth variations of each spectral line in the HARPS-N solar and SOAP-GPU data, we find a strong correlation between the observation and the simulation for strong spectral lines, therefore supporting the modeling of the stellar activity effect at the spectral level. The correlations are weaker for shallow lines, although it is likely that their lower signal-to-noise ratio does not allow a meaningful comparison. Conclusions. We introduce two methods for modeling solar activity using SOAP-GPU. With only sunspot numbers as input, we accurately capture the long-term magnetic cycle and rotational features. Additionally, we effectively model shift and depth variations at the spectral line level by using data from SDO. These simulated solar spectral time series serve as a useful test bed for evaluating spectral-level stellar activity mitigation techniques.

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.

As radial velocity (RV) spectrographs reach unprecedented precision and stability below 1 ms(-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 (extremely precise radial velocity) community. We present a pilot study to detect and characterize 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 time-scale of 43 . 65(-14.7)(+ 16 . 9) min, within 1 sigma, and a standard deviation of 22 . 9(-0.72)(+ 0 . 83) cm s(-1), within 3 sigma 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 and cross-correlation function 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.

Coronal Mass Ejections (CMEs) remain a focal point of solar and stellar research due to their significant impact on space weather dynamics and exoplanet habitability. Unfortunately, it has so far proven difficult to measure these events on other stars, with only a handful of confirmed detections. On the Sun, strong flares (X1-class and above) are almost always accompanied by a CME. This connection has not been found for other stars, where strong flares are regularly detected without a CME counterpart. To investigate this discrepancy we compare resolved solar observations taken from the Swedish 1-m Solar Telescope with disk-integrated Sun-as-a-star observations taken from the HARPS-N solar telescope. We studied two strong X-class flares, one of which was accompanied by a large (halo)CME, and one that was not. While we have successfully detected flare-related signatures in the activity indices and the radial velocity profile in the Sun-as-a-star data, we detect no significant differences between the two flares and no indications of the presence of the CME, despite other works having previously detected CMEs in Sun-as-a-star data.We propose that the absence of CME signatures in our data is due to a geometric effect. CMEs far enough away from the disk center are likely to be oriented in such a way that they have limited line-of-sight velocity, and thus cannot produce a strong enough Doppler signature. Therefore, we believe that the lack of observed stellar CMEs is at least partly an observational limitation and does not necessarily represent the underlying physical reality.

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.

The old G3V star Kepler-10 is known to host two transiting planets, the ultra-short-period super-Earth Kepler-10 b (P-b = 0.837 d; R-b = 1.47 R-circle plus) and the long-period sub-Neptune Kepler-10 c (P-c = 45.294 d; R-c = 2.35 R-circle plus), and a non-transiting planet that causes variations in the Kepler-10 c transit times. Measurements of the mass of Kepler-10 c in the literature have shown disagreement, depending on the radial-velocity dataset and/or the modeling technique used. Here we report on the analysis of almost 300 high-precision radial velocities gathered with the HARPS-N spectrograph at the Telescopio Nazionale Galileo over similar to 11 years, and extracted with the YARARA-v2 tool, which corrects for possible systematics and/or low-level activity variations at the spectrum level. To model these radial velocities, we used three different noise models and various numerical techniques, which all converged to the solution: M-b = 3.24 +/- 0.32 M-circle plus (10 sigma) and rho(b) = 5.54 +/- 0.64 g cm(-3 )for planet b; M-c = 11.29 +/- 1.24 M-circle plus (9 sigma) and rho(c) = 4.75 +/- 0.53 g cm(-3) for planet c; and Md sin i = 12.00 +/- 2.15 M-circle plus (6 sigma) and Pd = 151.06 +/- 0.48 d for the non-transiting planet Kepler-10 d. This solution is further supported by the analysis of the Kepler-10 c transit timing variations and their simultaneous modeling with the HARPS-N radial velocities. While Kepler-10 b is consistent with a rocky composition and a small or no iron core, Kepler-10 c may be a water world that formed beyond the water snowline and subsequently migrated inward.

Close-by Earth analogs and super-Earths are of primary importance because they will be preferential targets for the next generation of direct imaging instruments. Bright and close-by G-to-M type stars are preferential targets in radial velocity surveys to find Earth analogs. We present an analysis of the RV data of the star HD 20794, a target whose planetary system has been extensively debated in the literature. The broad time span of the observations makes it possible to find planets with signal semi-amplitudes below 1 m/s in the habitable zone. We monitored the system with ESPRESSO. We joined ESPRESSO data with the HARPS data, including archival data and new measurements from a recent program. We applied the post-processing pipeline YARARA to HARPS data to correct systematics, improve the quality of RV measurements, and mitigate the impact of stellar activity. Results. We confirm the presence of three planets, with periods of 18.3142 +/- 0.0022 d, 89.68 +/- 0.10 d, and 647.6 +/- 2.6 d, along with masses of 2.15 +/- 0.17 MEarth, 2.98 +/- 0.29 MEarth, and 5.82 +/- 0.57 MEarth respectively. For the outer planet, we find an eccentricity of 0.45 +/- 0.10, whereas the inner planets are compatible with circular orbits. The latter is likely to be a rocky planet in the habitable zone of HD 20794. From the analysis of activity indicators, we find evidence of a magnetic cycle with a period around 3000 d, along with evidence pointing to a rotation period around 39 d. We have determined the presence of a system of three planets orbiting the solar-type star HD 20794. This star is bright (V=4.34 mag) and close (d = 6.04 pc), and HD 20794 d resides in the stellar habitable zone, making this system a high-priority target for future atmospheric characterization with direct imaging facilities.

Stellar magnetic activity induces both distortions and Doppler-shifts in the absorption line profiles of Sun-like stars. Those effects produce apparent radial velocity (RV) signals which greatly hamper the search for potentially habitable, Earth-like planets. In this work, we investigate these distortions in the Sun using cross-correlation functions (CCFs), derived from intensive monitoring with the high-precision spectrograph HARPS-N. We show that the RV signal arising from line-shape variations on time-scales associated with the solar rotation and activity cycle can be robustly extracted from the data, reducing the RV dispersion by half. Once these have been corrected, activity-induced Doppler-shifts remain, that are modulated at the solar rotation period, and that are most effectively modelled in the time domain, using Gaussian Processes (GPs). Planet signatures are still best retrieved with multi-dimensonal GPs, when activity is jointly modelled from the raw RVs and indicators of the line width or of the Ca II H and K emission. After GP modelling, the residual RVs exhibit a dispersion of 0.6-0.8 m/s, likely to be dominated by signals induced by super-granulation. Finally, we find that the statistical properties of the RVs evolve significantly over time, and that this evolution is primarily driven by sunspots, which control the smoothness of the signal. Such evolution, which reduces the sensitivity to long-period planet signatures, is no longer seen in the activity-induced Doppler-shifts, which is promising for long term RV monitoring surveys such as the Terra Hunting Experiment or the PLATO follow-up campaign.

Context. Radial velocities (RVs) of stars contain both the Doppler reflex motion of potential planetary companions and the drowning and sometimes imitating effect of stellar activity. To separate the two, previous efforts have sought for proxys which only trace the activity signals, yet the sub-meter-per-second floor required for the detection of Earth-like planets remains difficult to break. Aims. In this work, we analyze a sample of 12 G- to early M-type stars in order to investigate the feasibility of detecting a differential effect of stellar activity with photospheric depth, as traced by the spectral line-forming temperature, for observations with different sampling and noise levels. Methods. We computed the average line formation temperature for each point in the observed wavelength grids using the spectral synthesis code PySME. The final line selection was curated to exclude blended and poorly synthesized lines. We thereafter computed the convective blueshift (CB) of the line cores of our master spectra (composed of the stacked individual spectra for each star). Finally, we extract RV time series for certain intervals of formation temperature using a template-matching approach. Results. We find the CB to follow a linear relation with the formation temperature of the line cores, and the CB slope to be steeper with increasing effective temperature. For the RV time series derived for different intervals of formation temperature, we find the RVs of line parts formed at higher temperatures, close to the spectral continuum, to be generally correlated with the S index, and RVs of line parts formed at cooler temperatures, close to the spectral line cores, to be generally anti-correlated, especially for stars with low noise levels and significant variations over their magnetic cycles.

Context. Many novel methods have been proposed to mitigate stellar activity for exoplanet detection as the presence of stellar activity in radial velocity (RV) measurements is the current major limitation. Unlike traditional methods that model stellar activity in the RV domain, more methods are moving in the direction of disentangling stellar activity at the spectral level. As deep neural networks have already been proven to be one of the most effective tools in data mining, in this work, we explore their potential in the context of Earth-like planet detection in RV measurements. Aims. The goal of this paper is to present a novel convolutional neural network-based algorithm that efficiently models stellar activity signals at the spectral level, enhancing the detection of Earth-like planets. Methods. Based on the idea that the presence of planets can only produce a Doppler shift at the spectral level while the presence of stellar activity can introduce a variation in the profile of spectral lines (asymmetry and depth change), we trained a convolutional neural network to build the correlation between the change in the spectral line profile and the corresponding RV, full width at half maximum (FWHM) and bisector span (BIS) values derived from the classical cross-correlation function. Results. This algorithm has been tested on three intensively observed stars: Alpha Centauri B (HD 128621), Tau ceti (HD 10700), and the Sun. By injecting simulated planetary signals at the spectral level, we demonstrate that our machine learning algorithm can achieve, for HD 128621 and HD 10700, a detection threshold of 0.5 m s −1 in semi-amplitude for planets with periods ranging from 10 to 300 days. This threshold would correspond to the detection of a ~4 M ⊕ in the habitable zone of those stars. On the HARPS-N solar dataset, thanks to significantly more data, our algorithm is even more efficient at mitigating stellar activity signals and can reach a threshold of 0.2 m s −1 , which would correspond to a 2.2 M ⊕ planet on the orbit of the Earth. Conclusions. To the best of our knowledge, it is the first time that such low detection thresholds are reported for the Sun, but also for other stars, and therefore this highlights the efficiency of our convolutional neural network-based algorithm at mitigating stellar activity in RV measurements.

Context. Planets with radii of between 2-4 RE closely orbiting solar-type stars are of significant importance for studying the transition from rocky to giant planets. Aims. Our goal is to determine the mass of a transiting planet around the very bright F6 star HD 73344 . This star exhibits high activity and has a rotation period that is close to the orbital period of the planet. Methods. The transiting planet, initially a K2 candidate, is confirmed through TESS observations . We refined its parameters and rule out a false positive with Spitzer observations. We analyzed high-precision RV data from the SOPHIE and HIRES spectrographs. We conducted separate and joint analyses using the PASTIS software. We used a novel observing strategy, targeting the star at high cadence for two consecutive nights with SOPHIE to understand the short-term stellar variability. We modeled stellar noise with two Gaussian processes. Results. High-cadence RV observations provide better constraints on stellar variability and precise orbital parameters for the transiting planet. The derived mean density suggests a sub-Neptune-type composition, but uncertainties in the planet's mass prevent a detailed characterization. In addition, we find a periodic signal in the RV data that we attribute to the signature of a nontransiting exoplanet, without totally excluding the possibility of a nonplanetary origin. Dynamical analyses confirm the stability of the two-planet system and provide constraints on the inclination of the candidate planet; these findings favor a near-coplanar system. Conclusions. While the transiting planet orbits the bright star at a short period, stellar activity prevented us from precise mass measurements. Long-term RV tracking of this planet could improve this measurement, as well as our understanding of the activity of the host star.

We present an exhaustive photometric and spectroscopic analysis of TOI-837, a F9/G0 35 Myr young star, hosting a transiting exoplanet, TOI-837b, with an orbital period of 8.32d. Utilising data from TESS and ground-based observations, we determine a planetary radius of 0.82 R_J for TOI-837b. Through detailed HARPS spectroscopic time series analysis, we derive a Doppler semi-amplitude of 36 m/s, corresponding to a planetary mass of 0.39 M_J. The derived planetary properties suggest a substantial core of approximately 70 M_E, constituting about 60 significant challenge to existing theoretical models of core formation. We propose that future atmospheric observations with JWST could provide insights into resolving ambiguities of TOI-837b, offering new perspectives on its composition, formation, and evolution.