High-Contrast Imaging Characterization of Exoplanets

Direct imaging of exoplanetary systems and the spectral characterization of exoplanetary atmospheres are amongst the most challenging, as well as rapidly developing fields in astronomy, propelled by new technologies and observational strategies. In this thesis, I contributed to the atmospheric analysis of exoplanets, the development of new algorithms to find faint planet signatures in the data, and the improvement of the fidelity of obtained exoplanet spectra. I performed atmospheric analyses of directly imaged planets observed with the planet imaging instrument VLT/SPHERE. For this purpose, I wrote a statistical inference code (BACON, Bayesian Atmospheric CharacterizatiON), which uses self-consistently computed model atmospheres to derive atmospheric parameters. The planets I studied in this thesis are: 51 Eridani b, one the coldest methane-rich directly imaged planets; PDS 70 b, the first young planet discovered inside the gap of its host star’s transition disk; HIP 65426 b, a planet of similar spectral type to PDS 70 b, but hotter and older; and GJ 504 b, a colder methane-rich companion which, depending on its age, could be a planet or brown dwarf. The new algorithm I developed to detect planets in high-contrast imaging data shifts the focus from an image analysis interpretation of the data, towards a time-domain analysis approach. I show that with this technique (TRAP, Temporal Reference Analysis for Exoplanets), an improvement of up to a factor of six in signal-to-noise can be achieved at very small angular separations between the planet and host star. Furthermore, I adapted the CHARIS instrument pipeline to use with SPHERE-IFS. This pipeline opens new possibilities for improving the quality of spectra obtained for exoplanets using SPHERE. Using this pipeline, I confirm the low flux emitted at around 1 micron previously obtained for 51 Eridani b, consistent with the absorption due to methane and water opacities predicted by models. Lastly, I discuss the future prospects for my work and how these approaches can be combined into a single framework

Spectral cube extraction for the VLT/SPHERE IFS: Open-source pipeline with full forward modeling and improved sensitivity

We present a new open-source data-reduction pipeline to reconstruct spectral data cubes from raw SPHERE integral-field spectrograph (IFS) data. The pipeline is written in Python and based on the pipeline that was developed for the CHARIS IFS. It introduces several improvements to SPHERE data analysis that ultimately produce significant improvements in postprocessing sensitivity. We first used new data to measure SPHERE lenslet point spread functions (PSFs) at the four laser calibration wavelengths. These lenslet PSFs enabled us to forward-model SPHERE data, to extract spectra using a least-squares fit, and to remove spectral crosstalk using the measured lenslet PSFs. Our approach also reduces the number of required interpolations, both spectral and spatial, and can preserve the original hexagonal lenslet geometry in the SPHERE IFS. In the case of least-squares extraction, no interpolation of the data is performed. We demonstrate this new pipeline on the directly imaged exoplanet 51 Eri b and on observations of the hot white dwarf companion to HD 2133. The extracted spectrum of HD 2133B matches theoretical models, demonstrating spectrophotometric calibration that is good to a few percent. Postprocessing on two 51 Eri b data sets demonstrates a median improvement in sensitivity of 80% and 30% for the 2015 and 2017 data, respectively, compared to the use of cubes reconstructed by the SPHERE Data Center. The largest improvements are seen for poorer observing conditions. The new SPHERE pipeline takes less than three minutes to produce a data cube on a modern laptop, making it practical to reprocess all SPHERE IFS data.Comment: 17 pages, 11 figures. Software available at: https://github.com/PrincetonUniversity/charis-de

Applying a temporal systematics model to vector Apodizing Phase Plate coronagraphic data: TRAP4vAPP

The vector Apodizing Phase Plate (vAPP) is a pupil plane coronagraph that suppresses starlight by forming a dark hole in its point spread function (PSF). The unconventional and non-axisymmetrical PSF arising from the phase modification applied by this coronagraph presents a special challenge to post-processing techniques. We aim to implement a recently developed post-processing algorithm, temporal reference analysis of planets (TRAP) on vAPP coronagraphic data. The property of TRAP that uses non-local training pixels, combined with the unconventional PSF of vAPP, allows for more flexibility than previous spatial algorithms in selecting reference pixels to model systematic noise. Datasets from two types of vAPPs are analysed: a double grating-vAPP (dgvAPP360) that produces a single symmetric PSF and a grating-vAPP (gvAPP180) that produces two D-shaped PSFs. We explore how to choose reference pixels to build temporal systematic noise models in TRAP for them. We then compare the performance of TRAP with previously implemented algorithms that produced the best signal-to-noise ratio (S/N) in companion detections in these datasets. We find that the systematic noise between the two D-shaped PSFs is not as temporally associated as expected. Conversely, there is still a significant number of systematic noise sources that are shared by the dark hole and the bright side in the same PSF. We should choose reference pixels from the same PSF when reducing the dgvAPP360 dataset or the gvAPP180 dataset with TRAP. In these datasets, TRAP achieves results consistent with previous best detections, with an improved S/N for the gvAPP180 dataset.Comment: 15 pages, 10 figures, accepted to A&

Constraints on the nearby exoplanet Eps Ind Ab from deep near/mid-infrared imaging limits

© ESO 2021. This is the accepted manuscript version of an article which has been published in final form at https://doi.org/10.1051/0004-6361/202140730The past decade has seen increasing efforts in detecting and characterising exoplanets by high contrast imaging in the near/mid-infrared, which is the optimal wavelength domain for studying old, cold planets. In this work, we present deep AO imaging observations of the nearby Sun-like star $\epsilon$ Ind A with NaCo ($L^{\prime}$) and NEAR (10-12.5 microns) instruments at VLT, in an attempt to directly detect its planetary companion whose presence has been indicated from radial velocity (RV) and astrometric trends. We derive brightness limits from the non-detection of the companion with both instruments, and interpret the corresponding sensitivity in mass based on both cloudy and cloud-free atmospheric and evolutionary models. For an assumed age of 5 Gyr for the system, we get detectable mass limits as low as 4.4 $M_{\rm J}$ in NaCo $L^{\prime}$ and 8.2 $M_{\rm J}$ in NEAR bands at 1.5\arcsec from the central star. If the age assumed is 1 Gyr, we reach even lower mass limits of 1.7 $M_{\rm J}$ in NaCo $L^{\prime}$ and 3.5 $M_{\rm J}$ in NEAR bands, at the same separation. However, based on the dynamical mass estimate (3.25 $M_{\rm J}$) and ephemerides from astrometry and RV, we find that the non-detection of the planet in these observations puts a constraint of 2 Gyr on the lower age limit of the system. NaCo offers the highest sensitivity to the planetary companion in these observations, but the combination with the NEAR wavelength range adds a considerable degree of robustness against uncertainties in the atmospheric models. This underlines the benefits of including a broad set of wavelengths for detection and characterisation of exoplanets in direct imaging studies.Peer reviewe

A Substellar Companion to Pleiades HII 3441

We find a new substellar companion to the Pleiades member star, Pleiades HII 3441, using the Subaru telescope with adaptive optics. The discovery is made as part of the high-contrast imaging survey to search for planetary-mass and substellar companions in the Pleiades and young moving groups. The companion has a projected separation of 0".49 +/- 0".02 (66 +/- 2 AU) and a mass of 68 +/- 5 M_J based on three observations in the J-, H-, and K_S-band. The spectral type is estimated to be M7 (~2700 K), and thus no methane absorption is detected in the H band. Our Pleiades observations result in the detection of two substellar companions including one previously reported among 20 observed Pleiades stars, and indicate that the fraction of substellar companions in the Pleiades is about 10.0 +26.1/-8.8 %. This is consistent with multiplicity studies of both the Pleiades stars and other open clusters.Comment: Main text (14 pages, 4 figures, 4 tables), and Supplementary data (8 pages, 3 tables). Accepted for Publications of Astronomical Society of Japa

Exoplanet imaging data challenge: benchmarking the various image processing methods for exoplanet detection

The Exoplanet Imaging Data Challenge is a community-wide effort meant to offer a platform for a fair and common comparison of image processing methods designed for exoplanet direct detection. For this purpose, it gathers on a dedicated repository (Zenodo), data from several high-contrast ground-based instruments worldwide in which we injected synthetic planetary signals. The data challenge is hosted on the CodaLab competition platform, where participants can upload their results. The specifications of the data challenge are published on our website https://exoplanet-imaging-challenge.github.io/. The first phase, launched on the 1st of September 2019 and closed on the 1st of October 2020, consisted in detecting point sources in two types of common data-set in the field of high-contrast imaging: data taken in pupil-tracking mode at one wavelength (subchallenge 1, also referred to as ADI) and multispectral data taken in pupil-tracking mode (subchallenge 2, also referred to as ADI+mSDI). In this paper, we describe the approach, organisational lessons-learnt and current limitations of the data challenge, as well as preliminary results of the participants’ submissions for this first phase. In the future, we plan to provide permanent access to the standard library of data sets and metrics, in order to guide the validation and support the publications of innovative image processing algorithms dedicated to high-contrast imaging of planetary systems

Exoplanet imaging data challenge, phase II: characterization of exoplanet signals in high-contract images

peer reviewedToday, 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

Direct Imaging Discovery and Dynamical Mass of a Substellar Companion Orbiting an Accelerating Hyades Sun-like Star with SCExAO/CHARIS

We present the direct-imaging discovery of a substellar companion in orbit around a Sun-like star member of the Hyades open cluster. So far, no other substellar companions have been unambiguously confirmed via direct imaging around main-sequence stars in Hyades. The star HIP 21152 is an accelerating star as identified by the astrometry from the Gaia and Hipparcos satellites. We have detected the companion, HIP 21152 B, in multi-epoch using the high-contrast imaging from SCExAO/CHARIS and Keck/NIRC2. We have also obtained the stellar radial-velocity data from the Okayama 188cm telescope. The CHARIS spectroscopy reveals that HIP 21152 B's spectrum is consistent with the L/T transition, best fit by an early T dwarf. Our orbit modeling determines the semi-major axis and the dynamical mass of HIP 21152 B to be 17.5$^{+7.2}_{-3.8}$ au and 27.8$^{+8.4}_{-5.4}$ $M_{\rm{Jup}}$, respectively. The mass ratio of HIP 21152 B relative to its host is $\approx$2\%, near the planet/brown dwarf boundary suggested from recent surveys. Mass estimates inferred from luminosity evolution models are slightly higher (33--42 $M_{\rm{Jup}}$). With a dynamical mass and a well-constrained age due to the system's Hyades membership, HIP 21152 B will become a critical benchmark in understanding the formation, evolution, and atmosphere of a substellar object as a function of mass and age. Our discovery is yet another key proof-of-concept for using precision astrometry to select direct imaging targets.Comment: 21 pages (11 pages in main body), 8 figures (4 figures in main body). Accepted for Publication in ApJL at July 9, 2022 (UT

Indications of M-Dwarf Deficits in the Halo and Thick Disk of the Galaxy

We compared the number of faint stars detected in deep survey fields with the current stellar distribution model of the Galaxy and found that the detected number in the H band is significantly smaller than the predicted number. This indicates that M-dwarfs, the major component, are fewer in the halo and the thick disk. We used archived data of several surveys in both the north and south field of GOODS (Great Observatories Origins Deep Survey), MODS in GOODS-N, and ERS and CANDELS in GOODS-S. The number density of M-dwarfs in the halo has to be 20 +/- 13% relative to that in the solar vicinity, in order for the detected number of stars fainter than 20.5 mag in the H band to match with the predicted value from the model. In the thick disk, the number density of M-dwarfs must be reduced (52 +/- 13%) or the scale height must be decreased (approximately 600 pc). Alternatively, overall fractions of the halo and thick disks can be significantly reduced to achieve the same effect, because our sample mainly consists of faint M-dwarfs. Our results imply that the M-dwarf population in regions distant from the Galactic plane is significantly smaller than previously thought. We then discussed the implications this has on the suitability of the model predictions for the prediction of non-companion faint stars in direct imaging extrasolar planet surveys by using the best-fit number densities