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Olivier Absil

Publications and source records attributed to Olivier Absil.

At least 55 records · Page 3Linked to original sources

Vortex coronagraph: revisiting the phase retrieval properties via Zernike analysis

High contrast imaging (HCI) is fundamentally limited by wavefront aberrations, and the ability to perform wavefront sensing from focal plane images is key to reach the full potential of ground and space-based instruments. Vortex focal plane mask coupled with downstream pupil (Lyot) stop stands as one of the best small-angle coronagraphs, but is also sensitive to low-order aberrations. Here, we revisit the behavior of the vortex phase mask, from entrance pupil down to the final detector plane, with Zernike polynomials as input phase aberrations. In particular we develop a second-order expansion that allows us to analyze the phase retrieval properties in a more intuitive and accurate way than previously proposed. With this formalism, we show how the azimuthal vortex modulation modifies the phase retrieval properties compared to normal imaging. In particular, our results suggest that images obtained with a scalar vortex coronagraph can be used for unambiguous focal-plane wavefront sensing in any practical situation. We compare our results with numerical simulations and discuss practical implementation in coronagraphic instruments.

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The VLT/ERIS vortex coronagraph: design, pointing control, and on-sky performance

The Enhanced Resolution Imager and Spectrograph (ERIS) is the new near-infrared instrument at the VLT-UT4. ERIS replaces and extends the observational capabilities formerly provided by SINFONI and NACO: integral field spectroscopy at 1 - 2.5 $μ$m, imaging at 1 - 5 $μ$m with several options for high-contrast imaging, and long-slit spectroscopy. In particular, a vortex coronagraph is now available for high contrast observations at L and M band. It is implemented using annular groove (or vortex) phase masks (one for each of the L and M bands) in a focal plane, and a Lyot stop in a downstream pupil plane. The vortex coronagraph has a discovery space starting already at $\sim$1$λ/D$, and works well in broadbands. However, to reach its optimal performance, it is critical to correct for slow pointing errors onto the vortex phase mask, which mandates a dedicated pointing control strategy. To do so, a control loop based on the QACITS algorithm has been developed and commissioned for ERIS. Good pointing stability is now regularly achieved with errors between 0.01 and 0.02 $λ/D$ and a correction rate of 0.2 Hz. In this contribution, we first review the design of the ERIS vortex coronagraph. We then detail the implementation of the QACITS algorithm describing the entire observing sequence, including the calibration steps, the initial centering, and the stabilization during the observing template. We then discuss performance based on commissioning data in terms of pointing accuracy and stability. Finally, we present post-processed contrast curves obtained during commissioning and compare them with NACO vortex data, showing a significant improvement of about 1 mag at all separations.

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Combining reference-star and angular differential imaging for high-contrast imaging of extended sources

High-contrast imaging (HCI) is a technique designed to observe faint signals near bright sources, such as exoplanets and circumstellar disks. The primary challenge in revealing the faint circumstellar signal near a star is the presence of quasi-static speckles, which can produce patterns on the science images that are as bright, or even brighter, than the signal of interest. Strategies such as angular differential imaging (ADI) or reference-star differential imaging (RDI) aim to provide a means of removing the quasi-static speckles in post-processing. In this paper, we present and discuss the adaptation of state-of-the-art algorithms, initially designed for ADI, to jointly leverage angular and reference-star differential imaging (ARDI) for direct high-contrast imaging of circumstellar disks. Using a collection of high-contrast imaging data sets, we assess the performance of ARDI in comparison to ADI and RDI based on iterative principal component analysis (IPCA). These diverse data sets are acquired under various observing conditions and include the injection of synthetic disk models at various contrast levels. Our results demonstrate that ARDI with IPCA improves the quality of recovered disk images and the sensitivity to planets embedded in disks, compared to ADI or RDI individually. This enhancement is particularly pronounced when dealing with extended sources exhibiting highly ambiguous structures that cannot be accurately retrieved using ADI alone, and when the quality of the reference frames is suboptimal, leading to an underperformance of RDI. We finally apply our method to a sample of real observations of protoplanetary disks taken in star-hopping mode, and propose to revisit the protoplanetary claims associated with these disks.

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MINDS. Hydrocarbons detected by JWST/MIRI in the inner disk of Sz28 consistent with a high C/O gas-phase chemistry

With the advent of JWST, we acquire unprecedented insights into the physical and chemical structure of the inner regions of planet-forming disks where terrestrial planet formation occurs. The very low-mass stars (VLMS) are known to have a high occurrence rate of the terrestrial planets around them. Exploring the chemical composition of the gas in these inner regions of the disks can aid a better understanding of the connection between planet-forming disks and planets. The MIRI mid-Infrared Disk Survey (MINDS) project is a large JWST Guaranteed Time program to characterize the chemistry and physical state of planet-forming and debris disks. We use the JWST-MIRI/MRS spectrum to investigate the gas and dust composition of the planet-forming disk around the very low-mass star Sz28 (M5.5, 0.12\,M$_{\odot}$). We use the dust-fitting tool (DuCK) to determine the dust continuum and to get constraints on the dust composition and grain sizes. We use 0D slab models to identify and fit the molecular spectral features, yielding estimates on the temperature, column density and the emitting area. To test our understanding of the chemistry in the disks around VLMS, we employ the thermo-chemical disk model {P{\tiny RO}D{\tiny I}M{\tiny O}} and investigate the reservoirs of the detected hydrocarbons. We explore how the C/O ratio affects the inner disk chemistry. JWST reveals a plethora of hydrocarbons, including \ce{CH3}, \ce{CH4}, \ce{C2H2}, \ce{^{13}CCH2}, \ce{C2H6}, \ce{C3H4}, \ce{C4H2} and \ce{C6H6} suggesting a disk with a gaseous C/O\,>\,1. Additionally, we detect \ce{CO2}, \ce{^{13}CO2}, \ce{HCN}, and \ce{HC3N}. \ce{H2O} and OH are absent in the spectrum. We do not detect PAHs. Photospheric stellar absorption lines of \ce{H2O} and \ce{CO} are identified. Notably, our radiation thermo-chemical disk models are able to produce these detected hydrocarbons in the surface layers of the disk when the ...

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METIS high-contrast imaging: from final design to manufacturing and testing

The Mid-infrared ELT Imager and Spectrograph (METIS) is one of the first-generation scientific instruments for the ELT, built under the supervision of ESO by a consortium of research institutes across and beyond Europe. Designed to cover the 3 to 13 $μ$m wavelength range, METIS had its final design reviewed in Fall 2022, and has then entered in earnest its manufacture, assembly, integration, and test (MAIT) phase. Here, we present the final design of the METIS high-contrast imaging (HCI) modes. We detail the implementation of the two main coronagraphic solutions selected for METIS, namely the vortex coronagraph and the apodizing phase plate, including their combination with the high-resolution integral field spectrograph of METIS, and briefly describe their respective backup plans (Lyot coronagraph and shaped pupil plate). We then describe the status of the MAIT phase for HCI modes, including a review of the final design of individual components such as the vortex phase masks, the grayscale ring apodizer, and the apodizing phase plates, as well as a description of their on-going performance tests and of our plans for system-level integration and tests. Using end-to-end simulations, we predict the performance that will be reached on sky by the METIS HCI modes in presence of various environmental and instrumental disturbances, including non-common path aberrations and water vapor seeing, and discuss our strategy to mitigate these various effects. We finally illustrate with mock observations and data processing that METIS should be capable of directly imaging temperate rocky planets around the nearest stars.

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L-band nulling interferometry at the VLTI with Asgard/NOTT: status and plans

NOTT (formerly Hi-5) is the L'-band (3.5-4.0~microns) nulling interferometer of Asgard, an instrument suite in preparation for the VLTI visitor focus. The primary scientific objectives of NOTT include characterizing (i) young planetary systems near the snow line, a critical region for giant planet formation, and (ii) nearby main-sequence stars close to the habitable zone, with a focus on detecting exozodiacal dust that could obscure Earth-like planets. In 2023-2024, the final warm optics have been procured and assembled in a new laboratory at KU Leuven. First fringes and null measurements were obtained using a Gallium Lanthanum Sulfide (GLS) photonic chip that was also tested at cryogenic temperatures. In this paper, we present an overall update of the NOTT project with a particular focus on the cold mechanical design, the first results in the laboratory with the final NOTT warm optics, and the ongoing Asgard integration activities. We also report on other ongoing activities such as the characterization of the photonic chip (GLS, LiNbO3, SiO), the development of the exoplanet science case, the design of the dispersion control module, and the progress with the self-calibration data reduction software.

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Generic data reduction for nulling interferometry package: the grip of a single data reduction package on all the nulling interferometers

Nulling interferometry is a powerful observing technique to reach exoplanets and circumstellar dust at separations too small for direct imaging with single-dish telescopes and too large for indirect methods. With near-future instrumentation, it bears the potential to detect young, hot planets near the snow lines of their host stars. A future space mission could detect and characterize a large number of rocky, habitable-zone planets around nearby stars at thermal-infrared wavelengths. The null self-calibration is a method aiming at modelling the statistical distribution of the nulled signal. It has proven to be more sensitive and accurate than average-based data reduction methods in nulling interferometry. This statistical approach opens the possibility of designing a GPU-based Python package to reduce the data from any of these instruments, by simply providing the data and a simulator of the instrument. GRIP is a toolbox to reduce nulling and interferometric data based on the statistical self-calibration method. In this article, we present the main features of GRIP as well as applications on real data.

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The JWST Early Release Science Program for Direct Observations of Exoplanetary Systems II: A 1 to 20 Micron Spectrum of the Planetary-Mass Companion VHS 1256-1257 b

We present the highest fidelity spectrum to date of a planetary-mass object. VHS 1256 b is a $<$20 M$_\mathrm{Jup}$ widely separated ($\sim$8\arcsec, a = 150 au), young, planetary-mass companion that shares photometric colors and spectroscopic features with the directly imaged exoplanets HR 8799 c, d, and e. As an L-to-T transition object, VHS 1256 b exists along the region of the color-magnitude diagram where substellar atmospheres transition from cloudy to clear. We observed VHS 1256~b with \textit{JWST}'s NIRSpec IFU and MIRI MRS modes for coverage from 1 $μ$m to 20 $μ$m at resolutions of $\sim$1,000 - 3,700. Water, methane, carbon monoxide, carbon dioxide, sodium, and potassium are observed in several portions of the \textit{JWST} spectrum based on comparisons from template brown dwarf spectra, molecular opacities, and atmospheric models. The spectral shape of VHS 1256 b is influenced by disequilibrium chemistry and clouds. We directly detect silicate clouds, the first such detection reported for a planetary-mass companion.

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Machine Learning for Exoplanet Detection in High-Contrast Spectroscopy: Revealing Exoplanets by Leveraging Hidden Molecular Signatures in Cross-Correlated Spectra with Convolutional Neural Networks

The new generation of observatories and instruments (VLT/ERIS, JWST, ELT) motivate the development of robust methods to detect and characterise faint and close-in exoplanets. Molecular mapping and cross-correlation for spectroscopy use molecular templates to isolate a planet's spectrum from its host star. However, reliance on signal-to-noise ratio (S/N) metrics can lead to missed discoveries, due to strong assumptions of Gaussian independent and identically distributed noise. We introduce machine learning for cross-correlation spectroscopy (MLCCS); the method aims to leverage weak assumptions on exoplanet characterisation, such as the presence of specific molecules in atmospheres, to improve detection sensitivity for exoplanets. MLCCS methods, including a perceptron and unidimensional convolutional neural networks, operate in the cross-correlated spectral dimension, in which patterns from molecules can be identified. We test on mock datasets of synthetic planets inserted into real noise from SINFONI at K-band. The results from MLCCS show outstanding improvements. The outcome on a grid of faint synthetic gas giants shows that for a false discovery rate up to 5%, a perceptron can detect about 26 times the amount of planets compared to an S/N metric. This factor increases up to 77 times with convolutional neural networks, with a statistical sensitivity shift from 0.7% to 55.5%. In addition, MLCCS methods show a drastic improvement in detection confidence and conspicuity on imaging spectroscopy. Once trained, MLCCS methods offer sensitive and rapid detection of exoplanets and their molecular species in the spectral dimension. They handle systematic noise and challenging seeing conditions, can adapt to many spectroscopic instruments and modes, and are versatile regarding atmospheric characteristics, which can enable identification of various planets in archival and future data.

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Machine learning for exoplanet detection in high-contrast spectroscopy Combining cross correlation maps and deep learning on medium-resolution integral-field spectra

The advent of high-contrast imaging instruments combined with medium-resolution spectrographs allows spectral and temporal dimensions to be combined with spatial dimensions to detect and potentially characterize exoplanets with higher sensitivity. We develop a new method to effectively leverage the spectral and spatial dimensions in integral-field spectroscopy (IFS) datasets using a supervised deep-learning algorithm to improve the detection sensitivity to high-contrast exoplanets. We begin by applying a data transform whereby the IFS datasets are replaced by cross-correlation coefficient tensors obtained by cross-correlating our data with young gas giant spectral template spectra. This transformed data is then used to train machine learning (ML) algorithms. We train a 2D CNN and 3D LSTM with our data. We compare the ML models with a non-ML algorithm, based on the STIM map of arXiv:1810.06895. We test our algorithms on simulated young gas giants in a dataset that contains no known exoplanet, and explore the sensitivity of algorithms to detect these exoplanets at contrasts ranging from 1e-3 to 1e-4 at different radial separations. We quantify the sensitivity using modified receiver operating characteristic curves (mROC). We discover that the ML algorithms produce fewer false positives and have a higher true positive rate than the STIM-based algorithm, and the true positive rate of ML algorithms is less impacted by changing radial separation. We discover that the velocity dimension is an important differentiating factor. Through this paper, we demonstrate that ML techniques have the potential to improve the detection limits and reduce false positives for directly imaged planets in IFS datasets, after transforming the spectral dimension into a radial velocity dimension through a cross-correlation operation.

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MINDS: Mid-infrared atomic and molecular hydrogen lines in the inner disk around a low-mass star

This work aims to measure the mass accretion rate, the accretion luminosity, and more generally the physical conditions of the warm emitting gas in the inner disk of the very low-mass star 2MASS-J16053215-1933159. We investigate the source mid-infrared spectrum for atomic and molecular hydrogen line emission. We present the full James Webb Space Telescope (JWST) Mid-InfraRed Instrument (MIRI) Medium Resolution Spectrometer (MRS) spectrum of the protoplanetary disk around the very low-mass star 2MASS-J16053215-1933159 from the MINDS GTO program, previously shown to be abundant in hydrocarbon molecules. We analyzed the atomic and molecular hydrogen lines in this source by fitting one or multiple Gaussian profiles. We then built a rotational diagram for the H2 lines to constrain the rotational temperature and column density of the gas. Finally, we compared the observed atomic line fluxes to predictions from two standard emission models. We identify five molecular hydrogen pure rotational lines and 16 atomic hydrogen recombination lines. The spectrum indicates optically thin emission for both species. We use the molecular hydrogen lines to constrain the mass and temperature of the warm emitting gas. The HI (7-6) recombination line is used to measure the mass accretion rate and luminosity onto the central source. HI recombination lines can also be used to derive the physical properties of the gas using atomic recombination models. The JWST-MIRI MRS observations for the very low-mass star 2MASS-J16053215-1933159 reveal a large number of emission lines, many originating from atomic and molecular hydrogen because we are able to look into the disk warm molecular layer. Their analysis constrains the physical properties of the emitting gas and showcases the potential of JWST to deepen our understanding of the physical and chemical structure of protoplanetary disks

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MINDS. The DR Tau disk I: combining JWST-MIRI data with high-resolution CO spectra to characterise the hot gas

The MRS mode of the JWST-MIRI instrument has been shown to be a powerful tool to characterise the molecular gas emission of the inner region of planet-forming disks. Here, we analyse the spectrum of the compact T-Tauri disk DR Tau, which is complemented by high spectral resolution (R~60000-90000) CO ro-vibrational observations. Various molecular species, including CO, CO$_2$, HCN, and C$_2$H$_2$ are detected in the JWST-MIRI spectrum, for which excitation temperatures of T~325-900 K are retrieved using LTE slab models. The high-resolution CO observations allow for a full treatment of the line profiles, which show evidence for two components of the main isotopologue, $^{12}$CO: a broad component tracing the Keplerian disk and a narrow component tracing a slow disk wind. Rotational diagrams yield excitation temperatures of T>725 K for CO, with consistently lower temperatures found for the narrow components, suggesting that the disk wind is launched from a larger distance. The inferred excitation temperatures for all molecules suggest that CO originates from the highest atmospheric layers close to the host star, followed by HCN and C$_2$H$_2$, which emit, together with $^{13}$CO, from slightly deeper layers, whereas the CO$_2$ originates from even deeper inside or further out in the disk. Additional analysis of the $^{12}$CO line wings hint at a misalignment between the inner (i~20 degrees) and outer disk (i~5 degrees). Finally, we emphasise the need for complementary high-resolution CO observations, as in combination with the JWST-MIRI observations they can be used to characterise the CO kinematics and the physical and chemical conditions of the other observed molecules with respect to CO.

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MINDS: The JWST MIRI Mid-INfrared Disk Survey

The study of protoplanetary disks has become increasingly important with the Kepler satellite finding that exoplanets are ubiquitous around stars in our galaxy and the discovery of enormous diversity in planetary system architectures and planet properties. High-resolution near-IR and ALMA images show strong evidence for ongoing planet formation in young disks. The JWST MIRI mid-INfrared Disk Survey (MINDS) aims to (1) investigate the chemical inventory in the terrestrial planet-forming zone across stellar spectral type, (2) follow the gas evolution into the disk dispersal stage, and (3) study the structure of protoplanetary and debris disks in the thermal mid-IR. The MINDS survey will thus build a bridge between the chemical inventory of disks and the properties of exoplanets. The survey comprises 52 targets (Herbig Ae stars, T Tauri stars, very low-mass stars and young debris disks). We primarily obtain MIRI/MRS spectra with high S/N (~100-500) covering the complete wavelength range from 4.9 to 27.9 μm. For a handful of selected targets we also obtain NIRSpec IFU high resolution spectroscopy (2.87-5.27 μm). We will search for signposts of planet formation in thermal emission of micron-sized dust - information complementary to near-IR scattered light emission from small dust grains and emission from large dust in the submillimeter wavelength domain. We will also study the spatial structure of disks in three key systems that have shown signposts for planet formation, TW Hya and HD 169142 using the MIRI coronagraph at 15.5 μm and 10.65 μm respectively and PDS70 using NIRCam imaging in the 1.87 μm narrow and the 4.8 μm medium band filter. ...

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The JWST Early Release Science Program for Direct Observations of Exoplanetary Systems IV: NIRISS Aperture Masking Interferometry Performance and Lessons Learned

We present a performance analysis for the aperture masking interferometry (AMI) mode on board the James Webb Space Telescope Near Infrared Imager and Slitless Spectrograph (JWST/NIRISS). Thanks to self-calibrating observables, AMI accesses inner working angles down to and even within the classical diffraction limit. The scientific potential of this mode has recently been demonstrated by the Early Release Science (ERS) 1386 program with a deep search for close-in companions in the HIP 65426 exoplanetary system. As part of ERS 1386, we use the same data set to explore the random, static, and calibration errors of NIRISS AMI observables. We compare the observed noise properties and achievable contrast to theoretical predictions. We explore possible sources of calibration errors and show that differences in charge migration between the observations of HIP 65426 and point-spread function calibration stars can account for the achieved contrast curves. Lastly, we use self-calibration tests to demonstrate that with adequate calibration NIRISS F380M AMI can reach contrast levels of $\sim9-10$ mag at $\gtrsim λ/D$. These tests lead us to observation planning recommendations and strongly motivate future studies aimed at producing sophisticated calibration strategies taking these systematic effects into account. This will unlock the unprecedented capabilities of JWST/NIRISS AMI, with sensitivity to significantly colder, lower-mass exoplanets than lower-contrast ground-based AMI setups, at orbital separations inaccessible to JWST coronagraphy.

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The JWST Early Release Science Program for Direct Observations of Exoplanetary Systems V: Do Self-Consistent Atmospheric Models Represent JWST Spectra? A Showcase With VHS 1256 b

The unprecedented medium-resolution (R~1500-3500) near- and mid-infrared (1-18um) spectrum provided by JWST for the young (140+/-20Myr) low-mass (12-20MJup) L-T transition (L7) companion VHS1256b gives access to a catalogue of molecular absorptions. In this study, we present a comprehensive analysis of this dataset utilizing a forward modelling approach, applying our Bayesian framework, ForMoSA. We explore five distinct atmospheric models to assess their performance in estimating key atmospheric parameters: Teff, log(g), [M/H], C/O, gamma, fsed, and R. Our findings reveal that each parameter's estimate is significantly influenced by factors such as the wavelength range considered and the model chosen for the fit. This is attributed to systematic errors in the models and their challenges in accurately replicating the complex atmospheric structure of VHS1256b, notably the complexity of its clouds and dust distribution. To propagate the impact of these systematic uncertainties on our atmospheric property estimates, we introduce innovative fitting methodologies based on independent fits performed on different spectral windows. We finally derived a Teff consistent with the spectral type of the target, considering its young age, which is confirmed by our estimate of log(g). Despite the exceptional data quality, attaining robust estimates for chemical abundances [M/H] and C/O, often employed as indicators of formation history, remains challenging. Nevertheless, the pioneering case of JWST's data for VHS1256b has paved the way for future acquisitions of substellar spectra that will be systematically analyzed to directly compare the properties of these objects and correct the systematics in the models.

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15NH3 in the atmosphere of a cool brown dwarf

Brown dwarfs serve as ideal laboratories for studying the atmospheres of giant exoplanets on wide orbits as the governing physical and chemical processes in them are nearly identical. Understanding the formation of gas giant planets is challenging, often involving the endeavour to link atmospheric abundance ratios, such as the carbon-to-oxygen (C/O) ratio, to formation scenarios. However, the complexity of planet formation requires additional tracers, as the unambiguous interpretation of the measured C/O ratio is fraught with complexity. Isotope ratios, such as deuterium-to-hydrogen and 14N/15N, offer a promising avenue to gain further insight into this formation process, mirroring their utility within the solar system. For exoplanets only a handful of constraints on 12C/13C exist, pointing to the accretion of 13C-rich ice from beyond the disks' CO iceline. Here we report on the mid-infrared detection of the 14NH3 and 15NH3 isotopologues in the atmosphere of a cool brown dwarf with an effective temperature of 380 K in a spectrum taken with the Mid-InfraRed Instrument of the James Webb Space Telescope. As expected, our results reveal a 14N/15N value consistent with star-like formation by gravitational collapse, demonstrating that this ratio can be accurately constrained. Since young stars and their planets should be more strongly enriched in the 15N isotope, we expect that 15NH3 will be detectable in a number of cold, wide-separation exoplanets.

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MINDS. Abundant water and varying C/O across the disk of Sz 98 as seen by JWST/MIRI

MIRI/MRS on board the JWST allows us to probe the inner regions of protoplanetary disks. Here we examine the disk around the classical T Tauri star Sz 98, which has an unusually large dust disk in the millimetre with a compact core. We focus on the H$_2$O emission through both its ro-vibrational and pure rotational emission. Furthermore, we compare our chemical findings with those obtained for the outer disk from Atacama Large Millimeter/submillimeter Array (ALMA) observations. In order to model the molecular features in the spectrum, the continuum was subtracted and LTE slab models were fitted. The spectrum was divided into different wavelength regions corresponding to H$_2$O lines of different excitation conditions, and the slab model fits were performed individually per region. We confidently detect CO, H$_2$O, OH, CO$_2$, and HCN in the emitting layers. The isotopologue H$^{18}_2$O is not detected. Additionally, no other organics, including C$_2$H$_2$, are detected. This indicates that the C/O ratio could be substantially below unity, in contrast with the outer disk. The H$_2$O emission traces a large radial disk surface region, as evidenced by the gradually changing excitation temperatures and emitting radii. The OH and CO$_2$ emission are relatively weak. It is likely that H$_2$O is not significantly photodissociated; either due to self-shielding against the stellar irradiation, or UV-shielding from small dust particles. The relative emitting strength of the different identified molecular features point towards UV-shielding of H$_2$O in the inner disk of Sz 98, with a thin layer of OH on top. The majority of the organic molecules are either hidden below the dust continuum, or not present. In general, the inferred composition points to a sub-solar C/O ratio (<0.5) in the inner disk, in contrast with the larger than unity C/O ratio in the gas in the outer disk found with ALMA.

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NA-SODINN: a deep learning algorithm for exoplanet image detection based on residual noise regimes

Supervised deep learning was recently introduced in high-contrast imaging (HCI) through the SODINN algorithm, a convolutional neural network designed for exoplanet detection in angular differential imaging (ADI) datasets. The benchmarking of HCI algorithms within the Exoplanet Imaging Data Challenge (EIDC) showed that (i) SODINN can produce a high number of false positives in the final detection maps, and (ii) algorithms processing images in a more local manner perform better. This work aims to improve the SODINN detection performance by introducing new local processing approaches and adapting its learning process accordingly. We propose NA-SODINN, a new deep learning binary classifier based on a convolutional neural network (CNN) that better captures image noise correlations in ADI-processed frames by identifying noise regimes. Our new approach was tested against its predecessor, as well as two SODINN-based hybrid models and a more standard annular-PCA approach, through local receiving operating characteristics (ROC) analysis of ADI sequences from the VLT/SPHERE and Keck/NIRC-2 instruments. Results show that NA-SODINN enhances SODINN in both sensitivity and specificity, especially in the speckle-dominated noise regime. NA-SODINN is also benchmarked against the complete set of submitted detection algorithms in EIDC, in which we show that its final detection score matches or outperforms the most powerful detection algorithms.Throughout the supervised machine learning case, this study illustrates and reinforces the importance of adapting the task of detection to the local content of processed images.

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