arXiv subjects

K. Al Moulla

Publications and source records attributed to K. Al Moulla.

14 recordsLinked to original sources

arXiv2026

Upside down: GJ3090 b the first retrograde exoplanet around an M dwarf detected with NIRPS

The angle between stellar spin axis and planetary orbital plane can provide key insights into the formation and dynamical evolution of planetary systems. In particular, this measurement in multi-planet systems can be used to further discriminate between different competing migration scenarios. We present six transit observations of the sub-Neptune GJ3090 b obtained with NIRPS and HARPS. GJ3090 b is the inner planet of a confirmed multi-planet system orbiting an M dwarf (M2). Using high spectral resolution and high temporal cadence spectroscopic observations, we analyzed the Rossiter-McLaughlin (RM) effect induced by GJ3090 b to determine its orbital obliquity. Through the RM revolutions technique, we find that the planet is on a retrograde orbit with a derived 3D obliquity of $ψ= 136^{+24}_{-18}\,\mathrm{deg}$. We find no evidence of massive outer planetary or wide stellar binary companions, which disfavors scenarios involving gravitational perturbations from a massive body and instead points toward a primordial misalignment of the protoplanetary disk. Our results establish GJ3090 b as the first planet on a retrograde orbit discovered around an M dwarf and the first highly misaligned confirmed multi-planet system without a known massive companion. We further propose late secondary disk accretion around GJ3090, in which the disk is not expected to be aligned with the stellar spin axis, followed by disk-driven migration as the most likely mechanisms to explain the observed architecture. This work also illustrates the capability of the RM revolutions technique when applied to near-infrared data to probe orbital architectures of the smallest planets around M dwarfs that have remained mostly inaccessible.

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arXiv2026

The impact of numerical derivatives on radial velocity extraction

The radial velocity (RV) method is a widely used technique to infer planetary masses and orbital parameters. One of the most widely used methods to compute RVs is based on the alignment of a high-SNR, data driven, stellar model with individual observations, commonly referred to as template matching. Typically, the alignment is performed through a $χ^2$ minimization, but some approaches rely on the derivative of the stellar template to do so, which is often the case in line-by-line methods. In this paper we aim to explore the limitation of derivative-based methods for RV extraction in the case of using low-SNR stellar models. We use simulated Gaussian profiles to investigate the effect of computing a numerical derivative of the stellar template, in comparison with the usage of an analytical profile. The impact on RV and associated uncertainty is then analyzed as a function of the signal-to-noise ratio (SNR) of the line. Then, using real observations we compare the residuals between a derivative-based RV extraction and a classical template matching implementation, as function of the SNR of the stellar template. We find that on simulated Gaussian profiles the usage of the numerical approach leads to a RV residual at the level of the meter per second, at a per-pixel SNR regime of 100. An increase of the SNR leads to a decrease of this impact, falling under the current noise-floor of state-of-the-art spectrographs at SNR>1000 for a single spectral line. The inclusion of multiple spectral lines in the simulations lead to an overall decrease of the contamination, across all SNR regimes. The application to a real dataset presents a decrease of the RV impact with the increase of the template's SNR, albeit still presenting a 12.5 cm/s difference when including 78 observations in the stellar template.

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arXiv2026

The impact of interpolation in high-resolution spectroscopy -- The overlooked role of interpolation in radial velocity extraction

We explore the impact of spectral interpolation in radial velocity (RV) time-series extracted through template-based methods. We build synthetic datasets with Gaussian profiles to evaluate flux residuals and line asymmetry that are a result from changing the sampling location of the lines. We generate synthetic spectra as a sum of Gaussian functions whose parameters were determined through an observed spectrum. The s-BART pipeline was applied to them, allowing to evaluate any biases in RV extraction introduced by its internal assumptions in line shape. Lastly, we apply the s-BART pipeline to ESPRESSO observations of four stars: two that use high-cadence observations over a single night, and two that have observations spread over multiple nights. When extracting RVs from stellar spectra, we change the interpolation algorithm, used in the process of constructing the stellar template and, afterwards, during RV extraction, comparing them with RVs extracted with a widely-used cubic-spline interpolation. We find that synthetic datasets reveal systematic biases with the largest peak-to-peak amplitudes reaching $\sim$ 20 m/s in low SNR cases, with the amplitude decreasing as the SNR of the spectra increases. In the extreme case of noise-free data, we still recover a systematic bias, albeit at the mm/s level, significantly smaller than the RV precision of state-of-the-art instruments. With real observations we find that those from high-cadence observations with small BERV variation are impacted by the choice of the interpolation algorithm. This impact is smaller in higher-SNR cases, where the peak-to-peak amplitude reaches $\sim$ 1 m/s. In the comparatively lower-SNR case we find peak-to-peak residuals as large as $\sim$ 25 m/s . In cases where the observations are spread over a larger BERV window, we find an upper limit of 20 cm/s of RV scatter for this systematic signal.

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arXiv2026

TILARA: Template-Independent Line-by-line Algorithm for Radial velocity Analysis. I. Description of the code and application on a Sun-like star

Precise radial velocities (RVs) are commonly derived through cross-correlation or template-matching methods, both of which rely on a reference spectrum that can introduce biases when the data are variable, contaminated, or sparsely sampled. Line-by-line methods offer an alternative way to compute RVs but generally still rely on template creation and therefore share its inherent limitations. We introduce TILARA, a template-independent, line-by-line RV extraction code designed to allow us to derive line-by-line RVs and to operate effectively even when spectral template construction is not recommended. While originally motivated by future PoET disk-resolved solar observations, TILARA has been built with the flexibility to work with different stellar spectral types and instruments. A curated list of individual absorption lines is used as a reference to automatically measure line centers with via Gaussian fitting with ARES. Then, using the reference lines list, and the lines measured with ARES on the spectra of the target star, TILARA computes the RVs and applies configurable outlier rejection through sigma-clipping or down-weighting methods. We tested different configurations of the code, RV uncertainty estimation methods, and line selection criteria. The code was applied to 520 ESPRESSO observations of the Sun-like star HD 102365 to evaluate its performance. TILARA was then tested against other RV extraction methods. Both in its sigma-clipping and its down-weighting mode, TILARA provided resulting RV time-series with similar standard deviation and error bars as the ones derived using existing methods that follow different approaches.

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arXiv2026

Activity correlation and temporal variation of small-scale magnetic fields on young Sun-like stars

We aim to evaluate how well the variation of small-scale magnetic fields on the stellar surface can be monitored with time-series observations. Further, we aim to establish to what extent the measured total unsigned magnetic field traces other activity indicators. We measured the total unsigned magnetic field on four young, stars using Zeeman splitting of magnetically sensitive spectral lines from high-resolution spectra obtained with the spectropolarimeters ESPaDOnS at CFHT and NARVAL at TBL. We then characterised the magnetic field variations using both sinusoidal variation and Lomb-Scargle periodograms. We evaluated how the rotational variation of the total unsigned magnetic field strength correlates with the activity indicators S-index, H$α$-index, Ca IRT-index, and the large-scale magnetic field obtained from ZDI maps obtained in earlier studies. We find clear signals of rotational modulation of the total magnetic field on HIP 76768 and tentative detection on Mel 25-5. This is supported both by the sinusoidal fitting and the periodogram. For the other stars, we find no modulation signals of the total magnetic field. We find positive correlations between the total magnetic field and activity indices on all four stars, indicating that indirect magnetic activity indicators trace the underlying magnetic field variability. However, comparing the activity-magnetic field relationship between the stars in our sample shows a significant deviation between activity level and measured magnetic field strength. Small-scale magnetic field variability can be traced using the Zeeman effect on magnetically sensitive lines, provided that the star is sufficiently active. It is also possible to self-consistently recover rotational periods from such measurements. The primary limit for the detection of magnetic field variations is the precision of Zeeman broadening and intensification measurements.

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arXiv2025

A Decade of Solar High-Fidelity Spectroscopy and Precise Radial Velocities from HARPS-N

We recently released 10 years of HARPS-N solar telescope and the goal of this manuscript is to present the different optimisations made to the data reduction, to describe data curation, and to perform some analyses that demonstrate the extreme RV precision of those data. By analysing all the HARPS-N wavelength solutions over 13 years, we bring to light instrumental systematics at the 1 m/s level. After correction, we demonstrate a peak-to-peak precision on the HARPS-N wavelength solution better than 0.75 m/s over 13 years. We then carefully curate the decade of HARPS-N re-reduced solar observations by rejecting 30% of the data affected either by clouds, bad atmospheric conditions or well-understood instrumental systematics. Finally, we correct the curated data for spurious sub-m/s RV effects caused by erroneous instrumental drift measurements and by changes in the spectral blaze function over time. After curation and correction, a total of 109,466 HARPS-N solar spectra and respective RVs over a decade are available. The median photon-noise precision of the RV data is 0.28 m/s and, on daily timescales, the median RV rms is 0.49 m/s, similar to the level imposed by stellar granulation signals. On 10-year timescales, the large RV rms of 2.95 m/s results from the RV signature of the Sun's magnetic cycle. When modelling this long-term effect using the Magnesium II activity index, we demonstrate a long-term RV precision of 0.41 m/s. We also analysed contemporaneous HARPS-N and NEID solar RVs and found the data from both instruments to be of similar quality and precision, with an overall RV differece rms of 0.79 m/s. This decade of high-cadence HARPS-N solar observations with short- and long-term precision below 1 m/s represents a crucial dataset to further understand stellar activity signals in solar-type stars , and to advance other science cases requiring such an extreme precision.

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arXiv2025

ATREIDES I. Embarking on a trek across the exo-Neptunian landscape with the TOI-421 system

The distribution of close-in exoplanets is shaped by the interplay between atmospheric and dynamical processes. The Neptunian Desert, Ridge, and Savanna illustrate the sensitivity of these worlds to such processes, making them ideal to disentangle their roles. Determining how many Neptunes were brought close-in by early disk-driven migration (DDM; maintaining primordial spin-orbit alignment) or late high-eccentricity migration (HEM; generating large misalignments) is essential to understand how much atmosphere they lost. We propose a unified view of the Neptunian landscape to guide its exploration, speculating that the Ridge is a hot spot for evolutionary processes. Low-density Neptunes would mainly undergo DDM, getting fully eroded at shorter periods than the Ridge, while denser Neptunes would be brought to the Ridge and Desert by HEM. We embark on this exploration via ATREIDES, which relies on spectroscopy and photometry of 60 close-in Neptunes, their reduction with robust pipelines, and their interpretation through internal structure, atmospheric, and evolutionary models. We carried out a systematic RM census with VLT/ESPRESSO to measure the distribution of 3D spin-orbit angles, correlate its shape with system properties and thus relate the fraction of aligned-misaligned systems to DDM, HEM, and atmospheric erosion. Our first target, TOI-421c, lies in the Savanna with a neighboring sub-Neptune TOI-421b. We measured their 3D spin-orbit angles (Psib = 57+11-15 deg; Psic = 44.9+4.4-4.1 deg). Together with the eccentricity and possibly large mutual inclination of their orbits, this hints at a chaotic dynamical origin that could result from DDM followed by HEM. ATREIDES will provide the community with a wealth of constraints for formation and evolution models. We welcome collaborations that will contribute to pushing our understanding of the Neptunian landscape forward.

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arXiv2025

Detection and characterisation of a 106-day transiting Jupiter : TOI-2449 b / NGTS-36 b

Only a handful of transiting giant exoplanets with orbital periods longer than 100 days are known. These warm exoplanets are valuable objects as their radius and mass can be measured leading to an in-depth characterisation of the planet's properties. Thanks to low levels of stellar irradiation and large orbital distances, the atmospheric properties and orbital parameters of warm exoplanets remain relatively unaltered by their host star, giving new insights into planetary formation and evolution. We aim at extending the sample of warm giant exoplanets with precise radii and masses. Our goal is to identify suitable candidates in the Transiting Exoplanet Survey Satellite (TESS) data and perform follow-up observations with ground-based instruments. We use the Next Generation Transit Survey (NGTS) to detect additional transits of planetary candidates in order to pinpoint their orbital period. We also monitored the target with several high-resolution spectrographs to measure the planetary mass and eccentricity. We report the discovery of a 106-day period Jupiter-sized planet around the G-type star TOI-2449 / NGTS-36. We jointly modelled the photometric and radial velocity data and find that the planet has a mass of 0.70 Mj and a radius of 1.002 Rj. The planetary orbit has a semi-major axis of 0.449 au and is slightly eccentric. We detect an additional 3-year signal in the radial velocity data likely due to the stellar magnetic cycle. Based on the planetary evolution models considered here, we find that TOI-2449 b / NGTS-36 b contains 11 Me of heavy elements and has a marginal planet-to-star metal enrichment of 3.3. Assuming a Jupiter-like Bond albedo, TOI-2449 b / NGTS-36 b has an equilibrium temperature of 400 K and is a good target for understanding nitrogen chemistry in cooler atmospheres.

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arXiv2025

ARVE: Analyzing Radial Velocity Elements. I. The Code

Context. In order to overcome the radial velocity (RV) precision barrier imposed by stellar variability, there has been a surge of software aimed at simulating and modeling these activity patterns. Aims. We present Analyzing Radial Velocity Elements (ARVE), a Python-based software which enables RV extraction using various customizable techniques, and subsequent analysis of the stellar and planetary signals present in the RVs. One of ARVE's unique features is its library of pre-computed auxiliary data, which includes synthetic spectra and spectral line masks, allowing the code to efficiently perform certain routines with minimal input from the user. Methods. ARVE is a class-based and modular code in which its functionalities are divided between four subclasses: functions, which handles general functions utilized by the other subclasses; data, which reads the input data, loads the auxiliary data, and extracts RVs from input high-resolution spectra; star, which characterizes the stellar activity components present in the RV time series; and planets, which performs fits of Keplerian signals in the data and offers injection-recovery tests of fictitious planets to determine the detection limits. Results. Demonstrations of ARVE are performed on three years of HARPS-N solar data. We show the evolution of granulation and supergranulation characteristic timescales with activity level, and we investigate the differences in planetary period-mass detection limits when extracting RVs with different methods. Conclusions. As stellar activity mitigation techniques grow more diverse, we foresee that a tool like ARVE could greatly benefit the community by offering a user-friendly and multi-functional approach to extract and analyze RV time series. With its current code structure, expanded functionality and increased compatibility with more spectrographs should be easily addable to future versions of ARVE.

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arXiv2025

A systematic bias in template-based RV extraction algorithms

In this paper we identify and explore a previously unidentified, multi meter-per-second, systematic correlation between time and RVs inferred through TM and LBL methods. We evaluate the influence of the data-driven stellar template in the RV bias and hypothesize on the possible sources of this effect. We first use the s-BART pipeline to extract RVs from three different datasets gathered over four nights of ESPRESSO and HARPS observations. Then, we demonstrate that the effect can be recovered on a larger sample of 19 targets, totaling 4124 ESPRESSO observations spread throughout 38 nights. We also showcase the presence of the bias in RVs extracted with the SERVAL and ARVE pipelines. Lastly, we explore the construction of the stellar template through the 5 years of ESPRESSO observations of HD10700, totalling more than 2000 observations. We find that a systematic quasi-linear bias affects the RV extraction with slopes that vary from -0.3 m/s-1/h-1 to -52 m/s-1/h-1 in our sample. This trend is not observed in CCF RVs and appears when all observations of a given star are collected within a short time-period (timescales of hours). We show that this systematic contamination exists in the RV time-series of two different template-matching pipelines, one line-by-line pipeline, and that it is agnostic to the spectrograph. We also find that this effect is connected with the construction of the stellar template, as we are able to mitigate it through a careful selection of the observations used to construct it. Our results suggest that a contamination of micro-telluric features, coupled other sources of correlated noise, could be the driving factor of this effect. We also show that this effect does not impact the usual usage of template-matching for the detection and characterization of exoplanets. Other short-timescale science cases can however be severely affected.

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arXiv2024

The ANTARESS workflow I. Optimal extraction of spatially resolved stellar spectra with high-resolution transit spectroscopy

High-resolution spectrographs open a detailed window onto the atmospheres of stars and planets. As the number of systems observed with different instruments grows, it is crucial to develop a standard in analyzing spectral time series of exoplanet transits and occultations, for the benefit of reproducibility. Here, we introduce the ANTARESS workflow, a set of methods aimed at processing high-resolution spectroscopy datasets in a robust way and extracting accurate exoplanetary and stellar spectra. While a fast preliminary analysis can be run on order-merged 1D spectra and cross-correlation functions (CCFs), the workflow was optimally designed for extracted 2D echelle spectra to remain close to the original detector counts, limit the spectral resampling, and propagate the correlated noise. Input data from multiple instruments and epochs were corrected for relevant environmental and instrumental effects, processed homogeneously, and analyzed independently or jointly. In this first paper, we show how planet-occulted stellar spectra extracted along the transit chord and cleaned from planetary contamination provide a direct comparison with theoretical stellar models and enable a spectral and spatial mapping of the photosphere. We illustrate this application of the workflow to archival ESPRESSO data, using the Rossiter-McLaughlin effect Revolutions (RMR) technique to confirm the spin-orbit alignment of HD\,209458b and unveil biases in WASP-76b's published orbital architecture. Because the workflow is modular and its concepts are general, it can support new methods and be extended to additional spectrographs to find a range of applications beyond the proposed scope. In a companion paper, we will present how planet-occulted spectra can be processed further to extract and analyze planetary spectra decontaminated from the star, providing clean and direct measurements of atmospheric properties.

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arXiv2023

Measuring precise radial velocities on individual spectral lines. IV. Stellar activity correlation with line formation temperature

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.

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arXiv2022

Stellar signal components seen in HARPS and HARPS-N solar radial velocities

Context. Radial velocity (RV) measurements induced by the presence of planets around late-type stars are contaminated by stellar signals that are of the order of a few meters per second in amplitude, even for the quietest stars. Those signals are induced by acoustic oscillations, convective granulation patterns, active regions co-rotating with the stellar surface, and magnetic activity cycles. Aims. This study investigates the properties of all coherent stellar signals seen on the Sun on timescales up to its sidereal rotational period. By combining HARPS and HARPS-N solar data spanning several years, we are able to clearly resolve signals on timescales from minutes to several months. Methods. We use a Markov Chain Monte Carlo (MCMC) mixture model to determine the quality of the solar data based on the expected airmass-magnitude extinction law. We then fit the velocity power spectrum of the cleaned and heliocentric RVs with all known variability sources, to recreate the RV contribution of each component. Results. After rejecting variations caused by poor weather conditions, we are able to improve the average intra-day root mean square (RMS) value by a factor of ~1.8. On sub-rotational timescales, we are able to fully recreate the observed RMS of the RV variations. In order to also include rotational components and their strong alias peaks introduced by nightly sampling gaps, the alias powers are accounted for by being redistributed to the central frequencies of the rotational harmonics. Conclusions. In order to enable a better understanding and mitigation of stellar activity sources, their respective impact on the total RV must be well-measured and characterized. We are able to recreate RV components up to rotational timescales, which can be further used to analyse the impact of each individual source of stellar signals on the detectability of exoplanets.

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arXiv2022

Measuring precise radial velocities on individual spectral lines. III. Dependence of stellar activity signal on line formation temperature

Context. To enable radial velocity (RV) precision on the order of ~0.1 m/s required for the detection of Earth-like exoplanets orbiting solar-type stars, the main obstacle lies in mitigating the impact of stellar activity. Aims. This study investigates the dependence of derived RVs with respect to the formation temperature of spectral line segments. Methods. Using spectral synthesis, we compute for each observed wavelength point of unblended spectral lines the stellar temperature below which 50% of the emergent flux originates. We can then construct RV time series for different temperature ranges, using template matching. Results. With HARPS-N solar data and HARPS $α$ Cen B measurements, we demonstrate on time intervals of prominent stellar activity that the activity-induced RV signal has different amplitude and periodicity depending on the temperature range considered. We compare the solar measurements with simulated contributions from active surface regions seen in simultaneous images, and find that the suppression of convective motion is the dominant effect. Conclusions. From a carefully selected set of spectral lines, we are able to measure the RV impact of stellar activity at various stellar temperatures ranges. We are able to strongly correlate the effect of convective suppression with spectral line segments formed in hotter temperature ranges. At cooler temperatures, the derived RVs exhibit oppositely directed variations compared to the average RV time series and stronger anti-correlations with chromospheric emission.

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