Evidence for a circumplanetary disk around protoplanet PDS 70 b

We present the first observational evidence for a circumplanetary disk around the protoplanet PDS~70~b, based on a new spectrum in the $K$ band acquired with VLT/SINFONI. We tested three hypotheses to explain the spectrum: Atmospheric emission from the planet with either (1) a single value of extinction or (2) variable extinction, and (3) a combined atmospheric and circumplanetary disk model. Goodness-of-fit indicators favour the third option, suggesting circumplanetary material contributing excess thermal emission --- most prominent at $\lambda \gtrsim 2.3 \mu$m. Inferred accretion rates ($\sim 10^{-7.8}$--$10^{-7.3} M_J$ yr$^{-1}$) are compatible with observational constraints based on the H$\alpha$ and Br$\gamma$ lines. For the planet, we derive an effective temperature of 1500--1600 K, surface gravity $\log(g)\sim 4.0$, radius $\sim 1.6 R_J$, mass $\sim 10 M_J$, and possible thick clouds. Models with variable extinction lead to slightly worse fits. However, the amplitude ($\Delta A_V \gtrsim 3$mag) and timescale of variation ($\lesssim$~years) required for the extinction would also suggest circumplanetary material.Comment: 8 pages, 2 figures, 1 table. This is a pre-copyedited, author-produced PDF of an article accepted for publication in ApJL on 2019 May 1

Direct exoplanet detection and characterization using the ANDROMEDA method: Performance on VLT/NaCo data

Context. The direct detection of exoplanets with high-contrast imaging requires advanced data processing methods to disentangle potential planetary signals from bright quasi-static speckles. Among them, angular differential imaging (ADI) permits potential planetary signals with a known rotation rate to be separated from instrumental speckles that are either statics or slowly variable. The method presented in this paper, called ANDROMEDA for ANgular Differential OptiMal Exoplanet Detection Algorithm is based on a maximum likelihood approach to ADI and is used to estimate the position and the flux of any point source present in the field of view. Aims. In order to optimize and experimentally validate this previously proposed method, we applied ANDROMEDA to real VLT/NaCo data. In addition to its pure detection capability, we investigated the possibility of defining simple and efficient criteria for automatic point source extraction able to support the processing of large surveys. Methods. To assess the performance of the method, we applied ANDROMEDA on VLT/NaCo data of TYC-8979-1683-1 which is surrounded by numerous bright stars and on which we added synthetic planets of known position and flux in the field. In order to accommodate the real data properties, it was necessary to develop additional pre-processing and post-processing steps to the initially proposed algorithm. We then investigated its skill in the challenging case of a well-known target, $\beta$ Pictoris, whose companion is close to the detection limit and we compared our results to those obtained by another method based on principal component analysis (PCA). Results. Application on VLT/NaCo data demonstrates the ability of ANDROMEDA to automatically detect and characterize point sources present in the image field. We end up with a robust method bringing consistent results with a sensitivity similar to the recently published algorithms, with only two parameters to be fine tuned. Moreover, the companion flux estimates are not biased by the algorithm parameters and do not require a posteriori corrections. Conclusions. ANDROMEDA is an attractive alternative to current standard image processing methods that can be readily applied to on-sky data

Auto-RSM: An automated parameter-selection algorithm for the RSM map exoplanet detection algorithm

Context. Most of the high-contrast imaging (HCI) data-processing techniques used over the last 15 years have relied on the angular differential imaging (ADI) observing strategy, along with subtraction of a reference point spread function (PSF) to generate exoplanet detection maps. Recently, a new algorithm called regime switching model (RSM) map has been proposed to take advantage of these numerous PSF-subtraction techniques; RSM uses several of these techniques to generate a single probability map. Selection of the optimal parameters for these PSF-subtraction techniques as well as for the RSM map is not straightforward, is time consuming, and can be biased by assumptions made as to the underlying data set. Aims: We propose a novel optimisation procedure that can be applied to each of the PSF-subtraction techniques alone, or to the entire RSM framework. Methods: The optimisation procedure consists of three main steps: (i) definition of the optimal set of parameters for the PSF-subtraction techniques using the contrast as performance metric, (ii) optimisation of the RSM algorithm, and (iii) selection of the optimal set of PSF-subtraction techniques and ADI sequences used to generate the final RSM probability map. Results: The optimisation procedure is applied to the data sets of the exoplanet imaging data challenge, which provides tools to compare the performance of HCI data-processing techniques. The data sets consist of ADI sequences obtained with three state-of-the-art HCI instruments: SPHERE, NIRC2, and LMIRCam. The results of our analysis demonstrate the interest of the proposed optimisation procedure, with better performance metrics compared to the earlier version of RSM, as well as to other HCI data-processing techniques.EPIC; NNEx

The SHARDDS survey: limits on planet occurrence rates based on point sources analysis via the Auto-RSM framework

In the past decade, HCI surveys provided new insights about the frequency and properties of substellar companions at separation larger than 5 au. In this context, our study aims to detect and characterise potential exoplanets and brown dwarfs within debris disks, by considering the SHARDDS survey, which gathers 55 Main Sequence stars with known bright debris disk. We rely on the AutoRSM framework to perform an in-depth analysis of the targets, via the computation of detection maps and contrast curves. A clustering approach is used to divide the set of targets in multiple subsets, in order to reduce the computation time by estimating a single optimal parametrisation for each considered subset. The use of Auto-RSM allows to reach high contrast at short separations, with a median contrast of 10-5 at 300 mas, for a completeness level of 95%. Detection maps generated with different approaches are used along with contrast curves, to identify potential planetary companions. A new planetary characterisation algorithm, based on the RSM framework, is developed and tested successfully, showing a higher astrometric and photometric precision for faint sources compared to standard approaches. Apart from the already known companion of HD206893 and two point-like sources around HD114082 which are most likely background stars, we did not detect any new companion around other stars. A correlation study between achievable contrasts and parameters characterising HCI sequences highlights the importance of the strehl, wind speed and wind driven halo to define the quality of high contrast images. Finally, planet detection and occurrence frequency maps are generated and show, for the SHARDDS survey, a high detection rate between 10 and 100 au for substellar companions with mass >10MJ

Direct imaging and spectroscopy of exoplanets with the ELT/HARMONI high-contrast module

Combining high-contrast imaging with medium-resolution spectroscopy has been shown to significantly boost the direct detection of exoplanets. HARMONI, one of the first-light instruments to be mounted on ESO’s future extremely large telescope (ELT), will be equipped with a single-conjugated adaptive optics system to reach the diffraction limit of the ELT in the H and K bands, a high-contrast module dedicated to exoplanet imaging, and a medium-resolution (up to R = 17 000) optical and near-infrared integral field spectrograph. When combined, these systems will provide unprecedented contrast limits at separations between 50 and 400 mas. This paper is aimed at estimating the capabilities of the HARMONI high-contrast module for the direct detection of young giant exoplanets. We use an end-to-end model of the instrument to simulate high-contrast observations performed with HARMONI, based on realistic observing scenarios and conditions. We then analyze these data with the so-called “molecule mapping” technique combined with a matched-filter approach in order to disentangle companions from the host star and tellurics and to increase the signal-to-noise ratio (S/N) of the planetary signal. We detected planets above 5σ at contrasts up to 16 mag and separations down to 75 mas in several spectral configurations of the instrument. We show that molecule mapping allows for the detection of companions up to 2.5 mag fainter compared to state-of-the-art high-contrast imaging techniques based on angular differential imaging. We also demonstrate that the performance is not strongly affected by the spectral type of the host star and we show that we are able to reach close sensitivities for the best three quartiles of observing conditions at Armazones, which means that HARMONI could be used in near-critical observations during 60 to 70% of telescope time at the ELT. Finally, we simulated planets from population synthesis models to further explore the parameter space that HARMONI and its high-contrast module will open up and compare this to the current high-contrast instrumentation

GRAVITY Spectro-interferometric Study of the Massive Multiple Stellar System HD 93206 A

Characterization of the dynamics of massive star systems and the astrophysical properties of the interacting components are a prerequisite for understanding their formation and evolution. Optical interferometry at milliarcsecond resolution is a key observing technique for resolving high-mass multiple compact systems. Here, we report on Very Large Telescope Interferometer/GRAVITY, Magellan/Folded-port InfraRed Echellette, and MPG2.2 m/FEROS observations of the late-O/early-B type system HD 93206 A, which is a member of the massive cluster Collinder 228 in the Carina nebula complex. With a total mass of about $90\,{M}_{\odot }$, it is one of the most compact massive quadruple systems known. In addition to measuring the separation and position angle of the outer binary Aa–Ac, we observe Brγ and He i variability in phase with the orbital motion of the two inner binaries. From the differential phase (${{\rm{\Delta }}}_{\phi }$) analysis, we conclude that the Brγ emission arises from the interaction regions within the components of the individual binaries, which is consistent with previous models for the X-ray emission of the system based on wind–wind interaction. With an average 3σ deviation of ${{\rm{\Delta }}}_{\phi }\sim 15^\circ$, we establish an upper limit of p ~ 0.157 mas (0.35 au) for the size of the Brγ line-emitting region. Future interferometric observations with GRAVITY using the 8 m Unit Telescopes will allow us to constrain the line-emitting regions down to angular sizes of 20 μas (0.05 au at the distance of the Carina nebula)

RPBS: a web resource for structural bioinformatics

RPBS (Ressource Parisienne en Bioinformatique Structurale) is a resource dedicated primarily to structural bioinformatics. It is the result of a joint effort by several teams to set up an interface that offers original and powerful methods in the field. As an illustration, we focus here on three such methods uniquely available at RPBS: AUTOMAT for sequence databank scanning, YAKUSA for structure databank scanning and WLOOP for homology loop modelling. The RPBS server can be accessed at and the specific services at

The adaptive optics simulation analysis tool(kit) (AOSAT)

AOSAT is a python package for the analysis of single-conjugate adaptive optics (SCAO) simulation results. Python is widely used in the astronomical community these days, and AOSAT may be used stand-alone, integrated into a simulation environment, or can easily be extended according to a user's needs. Standalone operation requires the user to provide the residual wavefront frames provided by the SCAO simulation package used, the aperture mask (pupil) used for the simulation, and a custom setup file describing the simulation/analysis configuration. In its standard form, AOSAT's "tearsheet" functionality will then run all standard analyzers, providing an informative plot collection on properties such as the point-spread function (PSF) and its quality, residual tip-tilt, the impact of pupil fragmentation, residual optical aberration modes both static and dynamic, the expected high-contrast performance of suitable instrumentation with and without coronagraphs, and the power spectral density of residual wavefront errors. AOSAT fills the gap between the simple numerical outputs provided by most simulation packages, and the full-scale deployment of instrument simulators and data reduction suites operating on SCAO residual wavefronts. It enables instrument designers and end-users to quickly judge the impact of design or configuration decisions on the final performance of down-stream instrumentation.EPI

Exoplanet Imaging Data Challenge, phase II: Characterization of exoplanet signals in high-contrast images

Today, there exists a wide variety of algorithms dedicated to high-contrast imaging, especially for the detection and characterisation of exoplanet signals. These algorithms are tailored to address the very high contrast between the exoplanet signal(s), which can be more than two orders of magnitude fainter than the bright starlight residuals in coronagraphic images. The starlight residuals are inhomogeneously distributed and follow various timescales that depend on the observing conditions and on the target star brightness. Disentangling the exoplanet signals within the starlight residuals is therefore challenging, and new post-processing algorithms are striving to achieve more accurate astrophysical results. The Exoplanet Imaging Data Challenge is a community-wide effort to develop, compare and evaluate algorithms using a set of benchmark high-contrast imaging datasets. After a first phase ran in 2020 and focused on the detection capabilities of existing algorithms, the focus of this ongoing second phase is to compare the characterisation capabilities of state-of-the-art techniques. The characterisation of planetary companions is two-fold: the astrometry (estimated position with respect to the host star) and spectrophotometry (estimated contrast with respect to the host star, as a function of wavelength). The goal of this second phase is to offer a platform for the community to benchmark techniques in a fair, homogeneous and robust way, and to foster collaborations.Comment: Submitted to SPIE Astronomical Telescopes + Instrumentation 2022, Adaptive Optics Systems VIII, Paper 12185-