arXiv subjects

Michael Cretignier

Publications and source records attributed to Michael Cretignier.

18 recordsLinked to original sources

arXiv2026

Understanding eccentric temperate giants: an in-depth study of the architecture and stellar obliquity of the TOI-2134 system

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 $9.229198\pm0.000003$ days orbit, and an outer temperate sub-Saturn orbiting with a $95.852840\pm0.000042$ days period and eccentricity of $0.31\pm0.01$. The masses and radii of the planets were computed to be $9.37\pm0.54$ Me and $2.735\pm0.068$ Re for planet b, and $58.3\pm1.9$ Me and $7.35\pm0.18$ Re 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 effect for TOI-2134~b with EXPRES and TOI-2134~c with PARAS-2. No RM effect was detected for planet b, but we find a 4.7$\sigma$ detection of a $59\pm31^{\circ}$ 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.

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arXiv2026

Modeling Doppler Shifts in Radial-Velocity Data with Deep Learning toward Earth-mass Exoplanet Detection

Detecting the tiny Doppler shifts induced by Earth-mass planets in stellar radial-velocity measurements remains extremely challenging due to stellar activity. Many deep-learning methods performing well on simulated data remain difficult to apply reliably on real stellar spectra. 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. 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 and cross-validation. Model robustness is enhanced through genetic-algorithm-based hyperparameter optimization, and predictive uncertainty is quantified using Monte Carlo dropout. 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. We also release doppleriann, a Python package implementing the proposed framework. 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.

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arXiv2026

gr8stars II : judgement day for spectroscopic parameter model systematics

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 \texttt{gr8stars} collaboration, we take a set of 585 bright FGK dwarfs with high resolution, high signal-to-noise ratio spectra from the SOPHIE 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 \teff, 0.14 dex in \logg, and 0.07 dex in \feh. 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 fitting in the first \texttt{gr8stars} paper as a comparison to our isochronal radii from this work, in addition to comparing the isochronal \logg to spectroscopic \logg. 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 ($\lesssim$ 3 \%) and mass ($\lesssim$ 5\%) 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\%, a noise floor that is currently not sufficiently represented in the literature.

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arXiv2026

Spin-Orbit Geometry of AU Mic b and c from Back-to-Back Transits Observed Contemporaneously with Magellan PFS, LCOGT, and CHEOPS

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 (~20 Myr), hosting two transiting Neptune-sized planets and a debris disk. Previous studies have shown that the rotation 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 (RM) measurements for both AU Mic b and c, which happened to transit back-to-back on Aug 24 and 25, 2024, using the Magellan Planet Finder Spectrograph (PFS), accompanioned with contanporaneous photometry from LCOGT and CHEOPS. We confirm the aligned orbit of AU Mic b ($\lambda_b=1{\deg} \pm 12{\deg}$) and finding two possible solutions for AU Mic c: we slightly favor an aligned solution ($\lambda_c=-10{\deg} \pm 16{\deg}$) but cannot rule out a polar solution ($\lambda_c=87{\deg}\ ^{+36{\deg}}_{-29{\deg}}$). Broader considerations, including dynamical stability and transit possibility, also support the mutually aligned scenario. An unexpected stellar signal during ingress and the poor TTV 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 the 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.

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arXiv2026

Modelling solar radial velocities and photometric variability with SOAPv4

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. Using SOAPv4, 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. To simulate solar RV and photometric time series, we first identified active regions in SDO images. This was done using mathematical morphological (MM) transforms applied to SDO/HMI and AIA images. MM 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. The simulations that use MM identification achieved the best match with the observed RV time series, yielding residuals with a measured standard deviation of ~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. We demonstrate that MM 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 ~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.

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arXiv2026

Mass estimates of the young TOI-451 transiting planets: Multidimensional Gaussian Process on stellar spectroscopic and photometric signals

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 Kb = 2.6(+1.1,-1.2) m/s, Kc = 1.2(+1.0,-0.8) m/s and Kd = 2.7 +/- 1.2 m/s. This translates into 2-sigma mass estimates for TOI-451 b and d of Mb = 4.7(+2.1,-2.2) Earth masses and Md = 10.2(+4.6,-4.5) Earth masses, as well as a mass upper limit for TOI-451 c of Mc < 11.5 Earth masses. 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.

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arXiv2025

Granulation on a quiet K dwarf: HD 166620 I. Spectral signatures as a function of line-formation temperature

As Radial velocity (RV) spectrographs reach unprecedented precision and stability below 1 m/s, 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 HD166620, 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. Following the correction for a newly identified instrumental signature arising from illumination variations across the CCD, we detected the granulation signal using structure functions and a one-component Gaussian Process (GP) model. The granulation signal exhibits a characteristic timescale of 43.65$\pm$15.8 minutes, within one $\sigma$, and a standard deviation of 22.9$\pm$0.77 cm/s, with in three $\sigma$ 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 (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.

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arXiv2025

Using Doppler Imaging to model stellar activity and search for planets around Sun-like stars

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 about 36 degrees 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. The RV residuals after DI correction exhibit a dispersion of about 0.6 m/s, 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 ~100days (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.

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arXiv2025

Studying the variability of the He triplet to understand the detection limits of evaporating exoplanet atmospheres

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.

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arXiv2025

Measuring the Suns radial velocity variability due to supergranulation over a magnetic cycle

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.

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arXiv2024

Precise and efficient modeling of stellar-activity-affected solar spectra using SOAP-GPU

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. In this context, a realistic simulated dataset that can provide photometry and spectroscopic outputs is needed for method development. 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. 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. The second method relies on the extraction of active regions from the Solar Dynamics Observatory (SDO) data. 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. These simulated solar spectral time series serve as a useful test bed for evaluating spectral-level stellar activity mitigation techniques.

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arXiv2024

A Gaussian process model for stellar activity in 2-D line profile time-series

Stellar active regions like spots and faculae can distort the shapes of spectral lines, inducing variations in the radial velocities that are often orders of magnitude larger than the signals from Earth-like planets. Efforts to mitigate these activity signals have hitherto focused on either the time or the velocity (wavelength) domains. We present a physics-driven Gaussian process (GP) framework to model activity signals directly in time series of line profiles or Cross-Correlation Functions (CCFs). Unlike existing methods which correct activity signals in line profile time series, our approach exploits the time correlation between velocity (wavelength) bins in the line profile variations, and is based on a simplified but physically motivated model for the origin of these variations. When tested on both synthetic and real data sets with signal-to-noise ratios down to $\sim$ 100, our method was able to separate the planetary signal from the activity signal, even when their periods were identical. We also conducted injection/recovery tests using two years of realistically sampled HARPS-N solar data, demonstrating the ability of the method to accurately recover a signal induced by a 1.5-Earth mass planet with a semi-amplitude of 0.3 m/s and a period of 33 days during high solar activity.

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arXiv2024

The K2 and TESS Synergy III: search and rescue of the lost ephemeris for K2's first planet

K2-2 b/HIP 116454 b, the first exoplanet discovery by K2 during its Two-Wheeled Concept Engineering Test, is a sub-Neptune (2.5 $\pm$ 0.1 $R_\oplus$, 9.7 $\pm$ 1.2 $M_\oplus$) orbiting a relatively bright (KS = 8.03) K-dwarf on a 9.1 day period. Unfortunately, due to a spurious follow-up transit detection and ephemeris degradation, the transit ephemeris for this planet was lost. In this work, we recover and refine the transit ephemeris for K2-2 b, showing a $\sim40{\sigma}$ discrepancy from the discovery results. To accurately measure the transit ephemeris and update the parameters of the system, we jointly fit space-based photometric observations from NASA's K2, TESS, and Spitzer missions with new photometric observations from the ground, as well as radial velocities from HARPS-N that are corrected for stellar activity using a new modeling technique. Ephemerides becoming lost or significantly degraded, as is the case for most transiting planets, highlights the importance of systematically updating transit ephemerides with upcoming large efforts expected to characterize hundreds of exoplanet atmospheres. K2-2 b sits at the high-mass peak of the known radius valley for sub-Neptunes, and is now well-suited for transmission spectroscopy with current and future facilities. Our updated transit ephemeris will ensure no more than a 13-minute uncertainty through 2030.

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arXiv2024

Improving Earth-like planet detection in radial velocity using deep learning

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. 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. 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. This algorithm has been tested on three intensively observed stars: Alpha Centauri B (HD128621), Tau ceti (HD10700), and the Sun. By injecting simulated planetary signals at the spectral level, we demonstrate that our machine learning algorithm can achieve, for HD128621 and HD10700, a detection threshold of 0.5 m/s in semi-amplitude for planets with periods ranging from 10 to 300 days. This threshold would correspond to the detection of a $\sim$4$\mathrm{M}_{\oplus}$ in the habitable zone of those stars. On the HARPS-N solar dataset, our algorithm is even more efficient at mitigating stellar activity signals and can reach a threshold of 0.2 m/s, which would correspond to a 2.2$\mathrm{M}_{\oplus}$ planet on the orbit of the Earth. 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.

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arXiv2024

Investigating stellar activity through eight years of Sun-as-a-star observations

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.

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arXiv2024

TOI-837b is a Young Saturn-sized Exoplanet with a Massive 70 $M_{\oplus}$ Core

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 35 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% of the planet's total mass. This finding poses a 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.

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arXiv2024

Modelling stellar variability in archival HARPS data: I -- Rotation and activity properties with multi-dimensional Gaussian Processes

Although instruments for measuring the radial velocities (RVs) of stars now routinely reach sub-meter per second accuracy, the detection of low-mass planets is still very challenging. The rotational modulation and evolution of spots and/or faculae can induce variations in the RVs at the level of a few m/s in Sun-like stars. To overcome this, a multi-dimensional Gaussian Process framework has been developed to model the stellar activity signal using spectroscopic activity indicators together with the RVs. A recently published computationally efficient implementation of this framework, S+LEAF 2, enables the rapid analysis of large samples of targets with sizeable data sets. In this work, we apply this framework to HARPS observations of 268 well-observed targets with precisely determined stellar parameters. Our long-term goal is to quantify the effectiveness of this framework to model and mitigate activity signals for stars of different spectral types and activity levels. In this first paper in the series, we initially focus on the activity indicators (S-index and Bisector Inverse Slope), and use them to a) measure rotation periods for 49 slow rotators in our sample, b) explore the impact of these results on the spin-down of middle-aged late F, G & K stars, and c) explore indirectly how the spot to facular ratio varies across our sample. Our results should provide valuable clues for planning future RV planet surveys such as the Terra Hunting Experiment or the PLATO ground-based follow-up observations program, and help fine-tune current stellar structure and evolution models.

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arXiv2020

RASSINE: Interactive tool for normalising stellar spectra I. Description and performance of the code

Aims: We provide an open-source code allowing an easy, intuitive, and robust normalisation of spectra. Methods: We developed RASSINE, a Python code for normalising merged 1D spectra through the concepts of convex hulls. The code uses six parameters that can be easily fine-tuned. The code also provides a complete user-friendly interactive interface, including graphical feedback, that helps the user to choose the parameters as easily as possible. To facilitate the normalisation even further, RASSINE can provide a first guess for the parameters that are derived directly from the merged 1D spectrum based on previously performed calibrations. Results: For HARPS spectra of the Sun that were obtained with the HELIOS solar telescope, a continuum accuracy of 0.20% on line depth can be reached after normalisation with RASSINE. This is three times better than with the commonly used method of polynomial fitting. For HARPS spectra of $α$ Cen B, a continuum accuracy of 2.0% is reached. This rather poor accuracy is mainly due to molecular band absorption and the high density of spectral lines in the bluest part of the merged 1D spectrum. When wavelengths shorter than 4500 Åare excluded, the continuum accuracy improves by up to 1.2%. The line-depth precision on individual spectrum normalisation is estimated to be 0.15%, which can be reduced to the photon-noise limit (0.10%) when a time series of spectra is given as input for RASSINE. Conclusions: With a continuum accuracy higher than the polynomial fitting method and a line-depth precision compatible with photon noise, RASSINE is a tool that can find applications in numerous cases, for example stellar parameter determination, transmission spectroscopy of exoplanet atmospheres, or activity-sensitive line detection.

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