18 research outputs found
PynPoint: a modular pipeline architecture for processing and analysis of high-contrast imaging data
The direct detection and characterization of planetary and substellar
companions at small angular separations is a rapidly advancing field. Dedicated
high-contrast imaging instruments deliver unprecedented sensitivity, enabling
detailed insights into the atmospheres of young low-mass companions. In
addition, improvements in data reduction and PSF subtraction algorithms are
equally relevant for maximizing the scientific yield, both from new and
archival data sets. We aim at developing a generic and modular data reduction
pipeline for processing and analysis of high-contrast imaging data obtained
with pupil-stabilized observations. The package should be scalable and robust
for future implementations and in particular well suitable for the 3-5 micron
wavelength range where typically (ten) thousands of frames have to be processed
and an accurate subtraction of the thermal background emission is critical.
PynPoint is written in Python 2.7 and applies various image processing
techniques, as well as statistical tools for analyzing the data, building on
open-source Python packages. The current version of PynPoint has evolved from
an earlier version that was developed as a PSF subtraction tool based on PCA.
The architecture of PynPoint has been redesigned with the core functionalities
decoupled from the pipeline modules. Modules have been implemented for
dedicated processing and analysis steps, including background subtraction,
frame registration, PSF subtraction, photometric and astrometric measurements,
and estimation of detection limits. The pipeline package enables end-to-end
data reduction of pupil-stabilized data and supports classical dithering and
coronagraphic data sets. As an example, we processed archival VLT/NACO L' and
M' data of beta Pic b and reassessed the planet's brightness and position with
an MCMC analysis, and we provide a derivation of the photometric error budget.Comment: 16 pages, 9 figures, accepted for publication in A&A, PynPoint is
available at https://github.com/PynPoint/PynPoin
Comparing Apples with Apples: Robust Detection Limits for Exoplanet High-Contrast Imaging in the Presence of non-Gaussian Noise
Over the past decade, hundreds of nights have been spent on the worlds
largest telescopes to search for and directly detect new exoplanets using
high-contrast imaging (HCI). Thereby, two scientific goals are of central
interest: First, to study the characteristics of the underlying planet
population and distinguish between different planet formation and evolution
theories. Second, to find and characterize planets in our immediate Solar
neighborhood. Both goals heavily rely on the metric used to quantify planet
detections and non-detections.
Current standards often rely on several explicit or implicit assumptions
about the noise. For example, it is often assumed that the residual noise after
data post-processing is Gaussian. While being an inseparable part of the
metric, these assumptions are rarely verified. This is problematic as any
violation of these assumptions can lead to systematic biases. This makes it
hard, if not impossible, to compare results across datasets or instruments with
different noise characteristics.
We revisit the fundamental question of how to quantify detection limits in
HCI. We focus our analysis on the error budget resulting from violated
assumptions. To this end, we propose a new metric based on bootstrapping that
generalizes current standards to non-Gaussian noise. We apply our method to
archival HCI data from the NACO-VLT instrument and derive detection limits for
different types of noise. Our analysis shows that current standards tend to
give detection limit that are about one magnitude too optimistic in the
speckle-dominated regime. That is, HCI surveys may have excluded planets that
can still exist.Comment: After first iteration with the referee, resubmitted to AJ. Comments
welcome
CROCODILE \\ Incorporating medium-resolution spectroscopy of close-in directly imaged exoplanets into atmospheric retrievals via cross-correlation
The investigation of the atmospheres of closely separated, directly imaged
gas giant exoplanets is challenging due to the presence of stellar speckles
that pollute their spectrum. To remedy this, the analysis of medium- to
high-resolution spectroscopic data via cross-correlation with spectral
templates (cross-correlation spectroscopy) is emerging as a leading technique.
We aim to define a robust Bayesian framework combining, for the first time,
three widespread direct-imaging techniques, namely photometry, low-resolution
spectroscopy, and medium-resolution cross-correlation spectroscopy in order to
derive the atmospheric properties of close-in directly imaged exoplanets. Our
framework CROCODILE (cross-correlation retrievals of directly imaged
self-luminous exoplanets) naturally combines the three techniques by adopting
adequate likelihood functions. To validate our routine, we simulated
observations of gas giants similar to the well-studied ~Pictoris~b
planet and we explored the parameter space of their atmospheres to search for
potential biases. We obtain more accurate measurements of atmospheric
properties when combining photometry, low- and medium-resolution spectroscopy
into atmospheric retrievals than when using the techniques separately as is
usually done in the literature. We find that medium-resolution () K-band cross-correlation spectroscopy alone is not suitable to constrain
the atmospheric properties of our synthetic datasets; however, this problem
disappears when simultaneously fitting photometry and low-resolution () spectroscopy between the Y and M bands. Our framework allows the
atmospheric characterisation of directly imaged exoplanets using the
high-quality spectral data that will be provided by the new generation of
instruments such as VLT/ERIS, JWST/MIRI, and ELT/METIS
ISPY-NACO Imaging Survey for Planets around Young stars. The demographics of forming planets embedded in protoplanetary disks
We present the statistical analysis of a subsample of 45 young stars
surrounded by protoplanetary disks (PPDs). This is the largest imaging survey
uniquely focused on PPDs to date. Our goal is to search for young forming
companions embedded in the disk material and to constrain their occurrence rate
in relation to the formation mechanism. We used principal component analysis
based point spread function subtraction techniques to reveal young companions
forming in the disks. We calculated detection limits for our datasets and
adopted a black-body model to derive temperature upper limits of potential
forming planets. We then used Monte Carlo simulations to constrain the
population of forming gas giant companions and compare our results to different
types of formation scenarios. Our data revealed a new binary system (HD38120)
and a recently identified triple system with a brown dwarf companion orbiting a
binary system (HD101412), in addition to 12 known companions. Furthermore, we
detected signals from 17 disks, two of which (HD72106 and TCrA) were imaged for
the first time. We reached median detection limits of L =15.4 mag at 2.0
arcsec, which were used to investigate the temperature of potentially embedded
forming companions. We can constrain the occurrence of forming planets with
semi-major axis a in [20 - 500] au and Teff in [600 - 3000] K, in line with the
statistical results obtained for more evolved systems from other direct imaging
surveys. The NaCo-ISPY data confirm that massive bright planets accreting at
high rates are rare. More powerful instruments with better sensitivity in the
near- to mid-infrared are likely required to unveil the wealth of forming
planets sculpting the observed disk substructures.Comment: 25 pages, 16 figures, 3 tables, accepted for publication in A&
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
Integrated photonic-based coronagraphic systems for future space telescopes
The detection and characterization of Earth-like exoplanets around Sun-like
stars is a primary science motivation for the Habitable Worlds Observatory.
However, the current best technology is not yet advanced enough to reach the
10^-10 contrasts at close angular separations and at the same time remain
insensitive to low-order aberrations, as would be required to achieve
high-contrast imaging of exo-Earths. Photonic technologies could fill this gap,
potentially doubling exo-Earth yield. We review current work on photonic
coronagraphs and investigate the potential of hybridized designs which combine
both classical coronagraph designs and photonic technologies into a single
optical system. We present two possible systems. First, a hybrid solution which
splits the field of view spatially such that the photonics handle light within
the inner working angle and a conventional coronagraph that suppresses
starlight outside it. Second, a hybrid solution where the conventional
coronagraph and photonics operate in series, complementing each other and
thereby loosening requirements on each subsystem. As photonic technologies
continue to advance, a hybrid or fully photonic coronagraph holds great
potential for future exoplanet imaging from space.Comment: Conference Proceedings of SPIE: Techniques and Instrumentation for
Detection of Exoplanets XI, vol. 12680 (2023
Visible extreme adaptive optics on extremely large telescopes: Towards detecting oxygen in Proxima Centauri b and analogs
Looking to the future of exo-Earth imaging from the ground, core technology
developments are required in visible extreme adaptive optics (ExAO) to enable
the observation of atmospheric features such as oxygen on rocky planets in
visible light. UNDERGROUND (Ultra-fast AO techNology Determination for
Exoplanet imageRs from the GROUND), a collaboration built in Feb. 2023 at the
Optimal Exoplanet Imagers Lorentz Workshop, aims to (1) motivate oxygen
detection in Proxima Centauri b and analogs as an informative science case for
high-contrast imaging and direct spectroscopy, (2) overview the state of the
field with respect to visible exoplanet imagers, and (3) set the instrumental
requirements to achieve this goal and identify what key technologies require
further development.Comment: SPIE Proceeding: 2023 / 12680-6
Half-sibling regression meets exoplanet imaging: PSF modeling and subtraction using a flexible, domain knowledge-driven, causal framework
High-contrast imaging of exoplanets hinges on powerful post-processing
methods to denoise the data and separate the signal of a companion from its
host star, which is typically orders of magnitude brighter. Existing
post-processing algorithms do not use all prior domain knowledge that is
available about the problem. We propose a new method that builds on our
understanding of the systematic noise and the causal structure of the
data-generating process. Our algorithm is based on a modified version of
half-sibling regression (HSR), a flexible denoising framework that combines
ideas from the fields of machine learning and causality. We adapt the method to
address the specific requirements of high-contrast exoplanet imaging data
obtained in pupil tracking mode. The key idea is to estimate the systematic
noise in a pixel by regressing the time series of this pixel onto a set of
causally independent, signal-free predictor pixels. We use regularized linear
models in this work; however, other (non-linear) models are also possible. In a
second step, we demonstrate how the HSR framework allows us to incorporate
observing conditions such as wind speed or air temperature as additional
predictors. When we apply our method to four data sets from the VLT/NACO
instrument, our algorithm provides a better false-positive fraction than
PCA-based PSF subtraction, a popular baseline method in the field.
Additionally, we find that the HSR-based method provides direct and accurate
estimates for the contrast of the exoplanets without the need to insert
artificial companions for calibration in the data sets. Finally, we present
first evidence that using the observing conditions as additional predictors can
improve the results. Our HSR-based method provides an alternative, flexible and
promising approach to the challenge of modeling and subtracting the stellar PSF
and systematic noise in exoplanet imaging data.Comment: Accepted for publication in Astronomy & Astrophysic
ISPY: NACO Imaging Survey for Planets around Young stars: The demographics of forming planets embedded in protoplanetary disks
Context. Planet formation is a frequent process, but little observational constraints exist about the mechanisms involved, especially for giant planets at large separation. The NaCo-ISPY large program is a 120 night L ²-band direct imaging survey aimed at investigating the giant planet population on wide orbits (a > 10 au) around stars hosting disks. Aims. Here we present the statistical analysis of a subsample of 45 young stars surrounded by protoplanetary disks (PPDs). This is the largest imaging survey uniquely focused on PPDs to date. Our goal is to search for young forming companions embedded in the disk material and to constrain their occurrence rate in relation to the formation mechanism. Methods. We used principal component analysis based point spread function subtraction techniques to reveal young companions forming in the disks. We calculated detection limits for our datasets and adopted a black-body model to derive temperature upper limits of potential forming planets. We then used Monte Carlo simulations to constrain the population of forming gas giant companions and compare our results to different types of formation scenarios. Results. Our data revealed a new binary system (HD 38120) and a recently identified triple system with a brown dwarf companion orbiting a binary system (HD 101412), in addition to 12 known companions. Furthermore, we detected signals from 17 disks, two of which (HD 72106 and T CrA) were imaged for the first time. We reached median detection limits of L ² = 15.4 mag at 2 ³.0, which were used to investigate the temperature of potentially embedded forming companions. We can constrain the occurrence of forming planets with semi-major axis a in [20-500] au and Teff in [600-3000] K to be 21.2-13.6+24.3%, 14.8-9.6+17.5%, and 10.8-7.0+12.6% for Rp = 2, 3, 5 RJ, which is in line with the statistical results obtained for more evolved systems from other direct imaging surveys. These values are obtained under the assumption that extinction from circumstellar and circumplanetary material does not affect the companion signal, but we show the potential impact these factors might have on the detectability of forming objects. Conclusions. The NaCo-ISPY data confirm that massive bright planets accreting at high rates are rare. More powerful instruments with better sensitivity in the near- to mid-infrared are likely required to unveil the wealth of forming planets sculpting the observed disk substructures.ISSN:0004-6361ISSN:1432-074