In this communication, we report on the results of the second phase of the Exoplanet Imaging Data Challenge started in 2019. This second phase focuses on the characterization of point sources (exoplanet signals) within multispectral high-contrast images from ground-based telescopes. We collected eight data sets from two high-contrast integral field spectrographs (namely Gemini-S/GPI and VLT/SPHERE-IFS) that we calibrated homogeneously and in which we injected a handful of synthetic planetary signals (ground truth) to be characterized by the data challenge participants. The tasks of the participants consist of (1) extracting the precise astrometry of each injected planetary signals, and (2) extracting the precise spectro-photometry of each injected planetary signal. Additionally, the participants may provide the 1-sigma uncertainties on their estimation for further analyses. When available, the participants can also provide the posterior distribution used to estimate the position/spectrum and uncertainties. The data are permanently available on a Zenodo repository and the participants can submit their results through the EvalAI platform. The EvalAI submission platform opened on April 2022 and closed on the 31st of May 2024. In total, we received 4 valid submissions for the astrometry estimation and 4 valid submissions for the spectrophotometry (each submission, corresponding to one pipeline, has been submitted by a unique participant). In this communication, we present an analysis and interpretation of the results.
The Spectro-Polarimetric High-contrast Exoplanet REsearch (SPHERE) instrument is a high-contrast imager designed for detecting exoplanets. It has been operational at the Very Large Telescope since 2014. To make the most of the extensive data generated by SPHERE, improve future observation planning, and advance instrument development, it is crucial to understand how its performance is affected by various environmental factors. The primary goal of this project is to use machine learning and deep learning techniques to predict detection limits, measured by the contrast between exoplanets and their host stars. Two types of models will be developed : random forest models and Multi-Layer Perceptron (MLP) models. The aim is to better understand the relationship between input parameters and detection limits, providing deeper insights into this field. Additionally, a neural network will be used to capture uncertainties in the input features, thus providing confidence intervals for its predictions.
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 μm 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.
The first generation of ELT instruments includes an optical-infrared high resolution spectrograph, indicated as ELT-HIRES and recently christened ANDES (ArmazoNes high Dispersion Echelle Spectrograph). ANDES consists of three fibre-fed spectrographs ([U]BV, RIZ, YJH) providing a spectral resolution of ∼100,000 with a minimum simultaneous wavelength coverage of 0.4-1.8 μm with the goal of extending it to 0.35-2.4 μm with the addition of an U arm to the BV spectrograph and a separate K band spectrograph. It operates both in seeing- and diffraction-limited conditions and the fibre-feeding allows several, interchangeable observing modes including a single conjugated adaptive optics module and a small diffraction-limited integral field unit in the NIR. Modularity and fibre-feeding allows ANDES to be placed partly on the ELT Nasmyth platform and partly in the Coudé room. ANDES has a wide range of groundbreaking science cases spanning nearly all areas of research in astrophysics and even fundamental physics. Among the top science cases there are the detection of biosignatures from exoplanet atmospheres, finding the fingerprints of the first generation of stars, tests on the stability of Nature’s fundamental couplings, and the direct detection of the cosmic acceleration. The ANDES project is carried forward by a large international consortium, composed of 35 Institutes from 13 countries, forming a team of almost 300 scientists and engineers which include the majority of the scientific and technical expertise in the field that can be found in ESO member states.
Ground-based thermal infrared observations face substantial challenges in correcting the predominant background emitted as thermal radiation from the atmosphere and the telescope itself. This study aims to investigate the impact of thermal backgrounds on ground-based observations and identify possible limiting factors induced by it. Specifically, we evaluate temporal and spatial characteristics of backgrounds in thermal infrared data obtained from three distinct datasets, acquired using VLT/NACO and KECK/NIRC2 data. We show that the integrated thermal backgrounds do not combine ideally, thereby introducing additional losses in possible detection limits. Our analysis reveals that the backgrounds exhibit pronounced spatial intensity structures attributed to the presence of adaptive optics corrections. Additionally, we observe a strong linear relationship between the background variances and deformable mirror variability. We conclude that the applied modulation of the deformable mirror on the background is responsible for the observed spatial intensity structures which ultimately limit the detection capabilities from ground.
SPHERE+ is a proposed upgrade of the SPHERE instrument at VLT, which will boost the current performances of detection and characterization of exoplanets and disks, and will serve as a demonstrator for the future planet finder (PCS) of the European ELT. The performance gain will be delivered by a second-stage AO module (SAXO+), including a dedicated wavefront sensor and deformable mirror to remove the residual wavefront errors left by the primary AO loop. This paper is focused on the optical and mechanical implementation of SAXO+ and describes the baseline design concept, selected from trade-off analysis of different options.
SPHERE+ is a proposed upgrade of the SPHERE instrument on the ESO’s Very Large Telescope which aims at improving detection and characterization capabilities of young giant planets by means of a second-stage AO system, including dedicated wavefront sensor and deformable mirror to remove the residual wavefront errors left by the primary AO loop. This paper is focused on the numerical simulations of the second stage (SAXO+) and conclude on the impact of the main AO parameters used to build the design strategy.
KEYWORDS: Planets, Stars, Exoplanets, Signal to noise ratio, Signal detection, Coronagraphy, Point spread functions, Detection and tracking algorithms, Atmospheric modeling, Surface conduction electron emitter displays
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.
The imaging and characterization of a larger range of exoplanets, down to young Jupiters and exo-Earths will require accessing very high contrasts at small angular separations with an increased robustness to aberrations, three constraints that drive current instrumentation development. This goal relies on efficient coronagraphs set up on extremely large diameter telescopes such as the Thirty Meter Telescope (TMT), the Giant Magellan Telescope (GMT), or the Extremely Large Telescope (ELT). However, they tend to be subject to specific aberrations that drastically deteriorate the coronagraph performance: their primary mirror segmentation implies phasing errors or even missing segments, and the size of the telescope imposes large spiders, generating low-wind effect as already observed on the Very Large Telescope (VLT)/SPHERE instrument or at the Subaru telescope, or adaptive-optics-due petaling, studied in simulations in the ELT case. The ongoing development of coronagraphs has then to take into account their sensitivity to such errors. We propose an innovative method to generate coronagraphs robust to primary mirror phasing errors and low-wind and adaptive-optics-due petaling effect. This method is based on the apodization of the segment or petal instead of the entire pupil, this apodization being then repeated to mimic the pupil redundancy. We validate this so-called Redundant Apodized Pupil (RAP) method on a James Webb Space Telescope-like pupil composed of 18 hexagonal segments segments to align, and on the VLT architecture in the case of residual low-wind effect.
The first generation of ELT instruments includes an optical-infrared high resolution spectrograph, indicated as ELT-HIRES and recently christened ANDES (ArmazoNes high Dispersion Echelle Spectrograph). ANDES consists of three fibre-fed spectrographs (UBV, RIZ, YJH) providing a spectral resolution of ∼100,000 with a minimum simultaneous wavelength coverage of 0.4-1.8 µm with the goal of extending it to 0.35-2.4 µm with the addition of a K band spectrograph. It operates both in seeing- and diffraction-limited conditions and the fibre-feeding allows several, interchangeable observing modes including a single conjugated adaptive optics module and a small diffraction-limited integral field unit in the NIR. Its modularity will ensure that ANDES can be placed entirely on the ELT Nasmyth platform, if enough mass and volume is available, or partly in the Coudé room. ANDES has a wide range of groundbreaking science cases spanning nearly all areas of research in astrophysics and even fundamental physics. Among the top science cases there are the detection of biosignatures from exoplanet atmospheres, finding the fingerprints of the first generation of stars, tests on the stability of Nature’s fundamental couplings, and the direct detection of the cosmic acceleration. The ANDES project is carried forward by a large international consortium, composed of 35 Institutes from 13 countries, forming a team of more than 200 scientists and engineers which represent the majority of the scientific and technical expertise in the field among ESO member states.
SPHERE+ is a proposed upgrade of the SPHERE instrument at the VLT, which is intended to boost the current performances of detection and characterization for exoplanets and disks. SPHERE+ will also serve as a demonstrator for the future planet finder (PCS) of the European ELT. The main science drivers for SPHERE+ are 1/ to access the bulk of the young giant planet population down to the snow line (3 − 10 au), to bridge the gap with complementary techniques (radial velocity, astrometry); 2/ to observe fainter and redder targets in the youngest (1 − 10 Myr) associations compared to those observed with SPHERE to directly study the formation of giant planets in their birth environment; 3/ to improve the level of characterization of exoplanetary atmospheres by increasing the spectral resolution in order to break degeneracies in giant planet atmosphere models. Achieving these objectives requires to increase the bandwidth of the xAO system (from ~1 to 3 kHz) as well as the sensitivity in the infrared (2 to 3 mag). These features will be brought by a second stage AO system optimized in the infrared with a pyramid wavefront sensor. As a new science instrument, a medium resolution integral field spectrograph will provide a spectral resolution from 1000 to 5000 in the J and H bands. This paper gives an overview of the science drivers, requirements and key instrumental tradeoff that were done for SPHERE+ to reach the final selected baseline concept.
The High-contrast End-to-End Performance Simulator (HEEPS) is an open-source python-based software with a modular and extensible architecture, that creates end-to-end simulations of high contrast imaging (HCI) instruments. It uses the wavefront Fresnel propagation package PROPER, the telescope instrument data simulator ScopeSim, and the HCI image processing package VIP. In this paper, we present the design of HEEPS, and motivate its baseline structure with the implementation of the Mid-infrared ELT Imager and Spectrograph (METIS) HCI modes, including coronagraphic components such as vortex phase masks, ring apodizers, and apodizing phase plates. Then, we present the key results of our thorough end-to-end simulations starting from 1-hour AO residual phase screens produced with the end-to-end AO simulator COMPASS. We analyze various undesirable effects such as pupil effects (stability, uniformity, drift) and noncommon path phase and amplitude errors. Finally, the coronagraphic performance including all effects is shown for all the METIS HCI modes as 5-sigma sensitivity contrast curves after ADI post-processing.
Combining adaptive optics and interferometric observations results in a considerable contrast gain compared to single-telescope, extreme AO systems. Taking advantage of this, the ExoGRAVITY project is a survey of known young giant exoplanets located in the range of 0.1” to 2” from their stars. The observations provide astrometric data of unprecedented accuracy, being crucial for refining the orbital parameters of planets and illuminating their dynamical histories. Furthermore, GRAVITY will measure non-Keplerian perturbations due to planet-planet interactions in multi-planet systems and measure dynamical masses. Over time, repetitive observations of the exoplanets at medium resolution (R = 500) will provide a catalogue of K-band spectra of unprecedented quality, for a number of exoplanets. The K-band has the unique properties that it contains many molecular signatures (CO, H2O, CH4, CO2). This allows constraining precisely surface gravity, metallicity, and temperature, if used in conjunction with self-consistent models like Exo-REM. Further, we will use the parameter-retrieval algorithm petitRADTRANS to constrain the C/O ratio of the planets. Ultimately, we plan to produce the first C/O survey of exoplanets, kick-starting the difficult process of linking planetary formation with measured atomic abundances.
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.
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.
With the advent of 30- to 40-m class ground-based telescopes in the mid-2020s, direct imaging of exoplanets is bound to take a new major leap. Among the approved projects, the Mid-infrared Extremely Large Telescope (ELT) Imager and Spectrograph (METIS) instrument for the ELT holds a prominent spot; by observing in the mid-infrared regime, it will be perfectly suited to study a variety of exoplanets and protoplanetary disks around nearby stars. Equipped with two of the most advanced coronagraphs, the vortex coronagraph and the apodizing phase plate, METIS will provide high-contrast imaging (HCI) in L-, M- and N-bands, and a combination of high-resolution spectroscopy and HCI in L- and M-bands. We present the expected HCI performance of the METIS instrument, considering realistic adaptive optics residuals, and investigate the effect of the main instrumental errors. The most important sources of degradation are identified and realistic sensitivity limits in terms of planet/star contrast are derived.
The Coronagraph Instrument (CGI) for NASA's Wide Field Infrared Survey Telescope (WFIRST) will constitute a dramatic step forward for high-contrast imaging, integral field spectroscopy, and polarimetry of exoplanets and circumstellar disks, aiming to improve upon the sensitivity of current ground-based direct imaging facilities by 2-3 orders of magnitude. Furthermore, CGI will serve as a pathfinder for future exo-Earth imaging and characterization missions by demonstrating wavefront control, coronagraphy, and spectral retrieval in a new contrast regime, and by validating instrument and telescope models at unprecedented levels of precision. To achieve this jump in performance, it is critical to draw on the experience of ground-based high-contrast facilities. We discuss several areas of relevant commonalities, including: wavefront control, post-processing of integral field unit data, and calibration and observing strategies.
The SPHERE instrument, dedicated to high contrast imaging on VLT, has been routinely operated for more than 3 years, over a large range of conditions and producing observations from visible to NIR. A central part of the instrument is the high order adaptive optics system, named SAXO, designed to deliver high Strehl image quality with a balanced performance budget for bright stars up to magnitude R=9.
We take benefit now from the very large set of observations to revisit the assumptions and analysis made at the time of the design phase: we compare the actual AO behavior as a function of expectations. The data set consists of the science detector data, for both coronagraphic images and non-coronagraphic PSF calibrations, but also of AO internal data from the high frequency sensors and statistics computations from the real-time computer which are systematically archived, and finally of environmental data, monitored at VLT level. This work is supported and made possible by the SPHERE « Data Center » infrastructure hosted at Grenoble which provides an efficient access and the capability for the homogeneous analysis of this large and statistically-relevant data set.
We review in a statistical manner the actual AO performance as a function of external conditions for different regimes and we discuss the possible performance metrics, either derived from AO internal data or directly from the high contrast images. We quantify the dependency of the actual performance on the most relevant environmental parameters. By comparison to earlier expectations, we conclude on the reliability of the usual AO modeling. We propose some practical criteria to optimize the queue scheduling and the expression of observer requirements ; finally, we revisit what could be the most important AO specifications for future high contrast imagers as a function of the primary science goals, the targets and the turbulence properties.
The low wind effect is a phenomenon disturbing the phase of the wavefront in the pupil of a large telescope obstructed by spiders, in the absence of wind. It can be explained by the radiative cooling of the spiders, creating air temperature inhomogeneities across the pupil. Because it is unseen by traditional adaptive optics (AO) systems, thus uncorrected, it significantly degrades the quality of AO-corrected images. We provide a statistical analysis of the strength of this effect as seen by VLT/SPHERE after 4 years of operations. We analyse its dependence upon the wind and temperature conditions. We describe the mitigation strategy implemented in 2017: a specific coating with low thermal emissivity in the mid-infrared was applied on the spiders of Unit Telescope 3. We quantify the improvement in terms of image quality, contrast and wave front error using both focal plane images and measured phase maps.
METIS is the Mid-infrared Extremely large Telescope Imager and Spectrograph, one of the first generation instruments of ESO’s 39m ELT. All scientific observing modes of METIS require adaptive optics (AO) correction close to the diffraction limit. Demanding constraints are introduced by the foreseen coronagraphy modes, which require highest angular resolution and PSF stability. Further design drivers for METIS and its AO system are imposed by the wavelength regime: observations in the thermal infrared require an elaborate thermal, baffling and masking concept. METIS will be equipped with a Single-Conjugate Adaptive Optics (SCAO) system. An integral part of the instrument is the SCAO module. It will host a pyramid type wavefront sensor, operating in the near-IR and located inside the cryogenic environment of the METIS instrument. The wavefront control loop as well as secondary control tasks will be realized within the AO Control System, as part of the instrument. Its main actuators will be the adaptive quaternary mirror and the field stabilization mirror of the ELT. In this paper we report on the phase B design work for the METIS SCAO system; the opto-mechanical design of the SCAO module as well as the control loop concepts and analyses. Simulations were carried out to address a number of important aspects, such as the impact of the fragmented pupil of the ELT on wavefront reconstruction. The trade-off that led to the decision for a pyramid wavefront sensor will be explained, as well as the additional control tasks such as pupil stabilization and compensation of non-common path aberrations.
The resolution of coronagraphic high contrast exoplanet imaging devices such as SPHERE is limited by quasistatic aberrations. These aberrations produce speckles that can be mistaken for planets in the image. In order to design instruments, correct quasi-static aberrations or analyze data, the expression of the point spread function of a coronagraphic telescope in the presence of residual turbulence is useful. We have derived an analytic formula for this point spread function. We explain physically its structure, we validate it by numerical simulations and we show that it is computationally efficient.
KEYWORDS: Sensors, Planets, Optical spheres, Gemini Planet Imager, Surface conduction electron emitter displays, Point spread functions, Data modeling, Signal detection, Fourier transforms, Signal to noise ratio
Exo-planet detection is a signal processing problem that can be addressed by several detection approaches. This paper provides a review of methods from detection theory that can be applied to detect exo-planets in coronographic images such as those provided by SPHERE and GPI. In a first part, we recall the basics of signal detection and describe how to derive a fast and robust detection criterion based on a heavy tail model that can account for outliers in the residuals. In a second part, we derive detectors that handle jointly several wavelengths and exposures and focus on an approach that prevents from interpolating the data, thereby preserving the statistics of the original data.
A liquid atmospheric dispersion corrector (LADC) is investigated to compensate atmospheric dispersion for modern
extremely large telescopes (ELTs). The LADC uses a pair of immiscible liquids in a small glass container which can be
placed very close to the telescope focal plane. A pair of liquid prisms is formed and the apex of the two prisms varies
with telescope zenith because of gravity. The idea is that a large number of independent deployable units (e.g., AAO's
'Starbugs') would each carry its own LADC. Three pairs of liquids were identified that were found suitable for use in an
LADC after thousands of chemicals were investigated. We have theoretically and experimentally verified that LADC
can correct atmospheric dispersion adaptively. It is demonstrated that a LADC can correct a simulated atmospheric
dispersion of 0.34° at a Zenith of 48°, over a wavelength range of 370nm to 655nm. The experimental results show very
good agreement with the optical (Zemax) model.
The Subaru Coronagraphic Extreme Adaptive Optics (SCExAO) system is an instrument designed to be inserted
between the Subaru AO188 system and the infrared HiCIAO camera in order to greatly improve the contrast
in the very close (less than 0.5") neighbourhood of stars. Next to the infrared coronagraphic path, a visible
scientific path, based on a EMCCD camera, has been implemented. Benefiting from both Adaptive Optics (AO)
correction and new data processing techniques, it is a powerful tool for high angular resolution imaging and
opens numerous new science opportunities. We propose here a new image processing algorithm, based on the
selection of the best signal for each spatial frequency. A factor 2 to 3 in Strehl ratio is obtained compared to
the AO long exposure time depending on the image processing algorithm used and the seeing conditions. The
system is able to deliver diffraction limited images at 650 nm (17 mas FWHM).We also demonstrate that this
approach offers significantly better results than the classical select, shift and add approach (lucky imaging).
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