High-contrast Imaging Instruments Research Articles

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 developed 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 began by applying a data transform whereby the four-dimensional (two spatial dimensions, one spectral dimension, and one temporal dimension) IFS datasets are replaced by four-dimensional cross-correlation coefficient tensors obtained by cross-correlating our data with young gas giant spectral template spectra. Thus, the spectral dimension is replaced by a radial velocity dimension and the rest of the dimensions are retained `as is'. This transformed data is then used to train machine learning (ML) algorithms. We trained a 2D convolutional neural network with temporally averaged spectral cubes as input, and a convolutional long short-term memory memory network that uses the temporal data as well. We compared these two models with a purely statistical (non-ML) exoplanet detection algorithm, which we developed specifically for four-dimensional datasets, based on the concept of the standardized trajectory intensity mean (STIM) map. We tested our algorithms on simulated young gas giant s inserted into a SINFONI dataset that contains no known exoplanet, and explored the sensitivity of algorithms to detect these exoplanets at contrasts ranging from $10^ $ to $10^ $ for different radial separations. We quantify the relative sensitivity of the algorithms by using modified receiver operating characteristic curves (mROCs). We discovered that the ML algorithms produce fewer false positives and have a higher true positive rate than the STIM-based algorithm. We also show that the true positive rate of ML algorithms is less impacted by changing radial separation than the STIM-based algorithm. Finally, we show that preserving the velocity dimension of the cross-correlation coefficients in the training and inference plays an important role in ML algorithms being more sensitive to the simulated young gas giant s. black In 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 and that the presence of the temporal dimension does not lead to increased sensitivity.

Making the unmodulated Pyramid wavefront sensor smart

Almost all current and future high-contrast imaging instruments will use a Pyramid wavefront sensor (PWFS) as a primary or secondary wavefront sensor. The main issue with the PWFS is its nonlinear response to large phase aberrations, especially under strong atmospheric turbulence. Most instruments try to increase its linearity range by using dynamic modulation, but this leads to decreased sensitivity, most prominently for low-order modes, and makes it blind to petal-piston modes. In the push toward high-contrast imaging of fainter stars and deeper contrasts, there is a strong interest in using the PWFS in its unmodulated form. Here, we present closed-loop lab results of a nonlinear reconstructor for the unmodulated PWFS of the Magellan Adaptive Optics extreme (MagAO-X) system based on convolutional neural networks (CNNs). We show that our nonlinear reconstructor has a dynamic range of >600 nm root-mean-square (RMS), significantly outperforming the linear reconstructor that only has a 50 nm RMS dynamic range. The reconstructor behaves well in closed loop and can obtain >80% Strehl at 875 nm under a large variety of conditions and reaches higher Strehl ratios than the linear reconstructor under all simulated conditions. The CNN reconstructor also achieves the theoretical sensitivity limit of a PWFS, showing that it does not lose its sensitivity in exchange for dynamic range. The current CNN’s computational time is 690 µs, which enables loop speeds of >1 kHz. On-sky tests are foreseen soon and will be important for pushing future high-contrast imaging instruments toward their limits.

A uniform analysis of debris discs with the Gemini Planet Imager II: constraints on dust density distribution using empirically informed scattering phase functions

ABSTRACT Spatially resolved images of debris discs are necessary to determine disc morphological properties and the scattering phase function (SPF) thatantifies the brightness of scattered light as a function of phase angle. Current high-contrast imaging instruments have successfully resolved several dozens of debris discs around other stars, but few studies have investigated trends in the scattered-light, resolved population of debris discs in a uniform and consistent manner. We have combined Karhunen-Loeve Image Projection (KLIP) with radiative-transfer disc forward modelling in order to obtain the highest-quality image reductions and constrain disc morphological properties of eight debris discs imaged by the Gemini Planet Imager at H-band with a consistent and uniformly applied approach. In describing the scattering properties of our models, we assume a common SPF informed from solar system dust scattering measurements and apply it to all systems. We identify a diverse range of dust density properties among the sample, including critical radius, radial width, and vertical width. We also identify radially narrow and vertically extended discs that may have resulted from substellar companion perturbations, along with a tentative positive trend in disc eccentricity with relative disc width. We also find that using a common SPF can achieve reasonable model fits for discs that are axisymmetric and asymmetric when fitting models to each side of the disc independently, suggesting that scattering behaviour from debris discs may be similar to Solar system dust.

Disk Evolution Study Through Imaging of Nearby Young Stars (DESTINYS): HD 34700 A unveils an inner ring

Context. The study of protoplanetary disks is fundamental to understand their evolution and interaction with the surrounding environment, and to constrain planet formation mechanisms. Aims. We aim to characterise the young binary system HD 34700 A, which shows a wealth of structures. Methods. Taking advantage of the high-contrast imaging instruments SPHERE at the VLT, LMIRCam at the LBT, and of ALMA observations, we analyse this system at multiple wavelengths. We study the morphology of the rings and spiral arms and the scattering properties of the dust. We discuss the possible causes of all the observed features. Results. We detect for the first time, in the Hα band, a ring extending from ~65 au to ~120 au, inside the ring which is already known from recent studies. These two have different physical and geometrical properties. Based on the scattering properties, the outer ring may consist of grains with a typical size of aout ≥ 4 µm, while the inner ring has a smaller typical size of ain ≤ 0.4 µm. Two extended logarithmic spiral arms stem from opposite sides of the disk. The outer ring appears as a spiral arm itself, with a variable radial distance from the centre and extended substructures. ALMA data confirm the presence of a millimetric dust substructure centred just outside the outer ring, and detect misaligned gas rotation patterns for HD 34700 A and B. Conclusions. The complexity of HD 34700 A, revealed by the variety of observed features, suggests the existence of one or more disk-shaping physical mechanisms. Our findings are compatible with the presence inside the disk of an as of yet undetected planet of several Jupiter masses and the system interaction with the surroundings, by means of gas cloudlet capture or flybys. Further observations with JWST/MIRI or ALMA (gas kinematics) could shed more light on them.

Detecting Biosignatures in Nearby Rocky Exoplanets Using High-contrast Imaging and Medium-resolution Spectroscopy with the Extremely Large Telescope

In the upcoming decades, one of the primary objectives in exoplanet science is to search for habitable planets and signs of extraterrestrial life in the Universe. Signs of life can be indicated by thermal-dynamical imbalance in terrestrial planet atmospheres. O2 and CH4 in the modern Earth’s atmosphere are such signs, commonly termed biosignatures. These biosignatures in exoplanetary atmospheres can potentially be detectable through high-contrast imaging instruments on future extremely large telescopes. To quantify the signal-to-noise ratio (S/N) with extremely large telescopes, we select up to 10 nearby rocky planets and simulate medium-resolution (R ∼ 1000) direct imaging of these planets using the Mid-infrared ELT Imager and Spectrograph (ELT/METIS, 3–5.6 μm) and the High Angular Resolution Monolithic Optical and Near-infrared Integral field spectrograph (ELT/HARMONI, 0.5–2.45 μm). We calculate the S/N for the detection of biosignatures including CH4, O2, H2O, and CO2. Our results show that GJ 887 b has the highest detection of S/N for biosignatures, and Proxima Cen b exhibits the only detectable CO2 among the targets for ELT/METIS direct imaging. We also investigate the TRAPPIST-1 system, the archetype of nearby transiting rocky planet systems, and compare the biosignature detection of transit spectroscopy with JWST versus direct spectroscopy with ELT/HARMONI. Our findings indicate JWST is more suitable for detecting and characterizing the atmospheres of transiting planet systems such as TRAPPIST-1 that are relatively further away and have smaller angular separations than more nearby nontransiting planets.

Implicit electric field conjugation: Data-driven focal plane control

Context.Direct imaging of Earth-like planets is one of the main science cases for the next generation of extremely large telescopes. This is very challenging due to the star-planet contrast that has to be overcome. Most current high-contrast imaging instruments are limited in sensitivity at small angular separations due to non-common path aberrations (NCPA). The NCPA leak through the corona-graph and create bright speckles that limit the on-sky contrast and therefore also the post-processed contrast.Aims.We aim to remove the NCPA by active focal plane wavefront control using a data-driven approach.Methods.We developed a new approach to dark hole creation and maintenance that does not require an instrument model. This new approach is called implicit Electric Field Conjugation (iEFC) and it can be empirically calibrated. This makes it robust for complex instruments where optical models might be difficult to realize. Numerical simulations have been used to explore the performance of iEFC for different coronagraphs. The method was validated on the internal source of the Magellan Adaptive Optics extreme (MagAO-X) instrument to demonstrate iEFC’s performance on a real instrument.Results.Numerical experiments demonstrate that iEFC can achieve deep contrast below 10−9with several coronagraphs. The method is easily extended to broadband measurements and the simulations show that a bandwidth up to 40% can be handled without problems. Lab experiments with MagAO-X showed a contrast gain of a factor 10 in a broadband light and a factor 20–200 in narrowband light. A contrast of 5 × 10−8was achieved with the Phase Apodized Pupil Lyot Coronagraph at 7.5λ/D.Conclusions.The new iEFC method has been demonstrated to work in numerical and lab experiments. It is a method that can be empirically calibrated and it can achieve deep contrast. This makes it a valuable approach for complex ground-based high-contrast imaging systems.

Polarization aberrations in next-generation giant segmented mirror telescopes (GSMTs)

Context. Next-generation large segmented mirror telescopes are expected to perform direct imaging and characterization of Earth-like rocky planets, which requires contrast limits of 10−7 to 10−8 at wavelengths from I to J band. One critical aspect affecting the raw on-sky contrast are polarization aberrations (i.e., polarization-dependent phase and amplitude patterns in the pupil) arising from the reflection from the telescope’s mirror surfaces and instrument optics. These polarization aberrations induce false signals for polarimetry that can be calibrated to a certain degree, but they can also fundamentally limit the achievable contrast of coronagraphic systems. Aims. We simulate the polarization aberrations and estimate their effect on the achievable contrast for three next-generation ground-based large segmented mirror telescopes. Methods. We performed ray-tracing in Zemax® and computed the polarization aberrations and Jones pupil maps using the polarization ray-tracing algorithm. The impact of these aberrations on the contrast is estimated by propagating the Jones pupil maps through a set of idealized coronagraphs using hcipy, a physical optics-based simulation framework. Results. The optical modeling of the giant segmented mirror telescopes (GSMTs) shows that polarization aberrations create significant leakage through a coronagraphic system. The dominant aberration is retardance defocus, which originates from the steep angles on the primary and secondary mirrors. The retardance defocus limits the contrast to 10−5 to 10−4 at 1 λ/D at visible wavelengths, and 10−5 to 10−6 at infrared wavelengths. The simulations also show that the coating plays a major role in determining the strength of the aberrations. Conclusions. Polarization aberrations will need to be considered during the design of high-contrast imaging instruments for the next generation of extremely large telescopes. This can be achieved either through compensation optics, robust coronagraphs, specialized coatings, calibration, and data analysis approaches, or by incorporating polarimetry with high-contrast imaging to measure these effects.

A deep learning approach for focal-plane wavefront sensing using vortex phase diversity

Context. The performance of high-contrast imaging instruments is limited by wavefront errors, in particular by non-common path aberrations (NCPAs). Focal-plane wavefront sensing (FPWFS) is appropriate to handle NCPAs because it measures the aberration where it matters the most, that is to say at the science focal plane. Phase retrieval from focal-plane images results, nonetheless, in a sign ambiguity for even modes of the pupil-plane phase. Aims. The phase diversity methods currently used to solve the sign ambiguity tend to reduce the science duty cycle, that is, the fraction of observing time dedicated to science. In this work, we explore how we can combine the phase diversity provided by a vortex coronagraph with modern deep learning techniques to perform efficient FPWFS without losing observing time. Methods. We applied the state-of-the-art convolutional neural network EfficientNet-B4 to infer phase aberrations from simulated focal-plane images. The two cases of scalar and vector vortex coronagraphs (SVC and VVC) were considered using a single post-coronagraphic point spread function (PSF) or two PSFs obtained by splitting the circular polarization states, respectively. Results. The sign ambiguity has been properly lifted in both cases even at low signal-to-noise ratios (S/Ns). Using either the SVC or the VVC, we have reached a very similar performance compared to using phase diversity with a defocused PSF, except for high levels of aberrations where the SVC slightly underperforms compared to the other approaches. The models finally show great robustness when trained on data with a wide range of wavefront errors and noise levels. Conclusions. The proposed FPWFS technique provides a 100% science duty cycle for instruments using a vortex coronagraph and does not require any additional hardware in the case of the SVC.

Toward on-sky adaptive optics control using reinforcement learning

Context. The direct imaging of potentially habitable exoplanets is one prime science case for the next generation of high contrast imaging instruments on ground-based, extremely large telescopes. To reach this demanding science goal, the instruments are equipped with eXtreme Adaptive Optics (XAO) systems which will control thousands of actuators at a framerate of kilohertz to several kilohertz. Most of the habitable exoplanets are located at small angular separations from their host stars, where the current control laws of XAO systems leave strong residuals. Aims. Current AO control strategies such as static matrix-based wavefront reconstruction and integrator control suffer from a temporal delay error and are sensitive to mis-registration, that is, to dynamic variations of the control system geometry. We aim to produce control methods that cope with these limitations, provide a significantly improved AO correction, and, therefore, reduce the residual flux in the coronagraphic point spread function (PSF). Methods. We extend previous work in reinforcement learning for AO. The improved method, called the Policy Optimization for Adaptive Optics (PO4AO), learns a dynamics model and optimizes a control neural network, called a policy. We introduce the method and study it through numerical simulations of XAO with Pyramid wavefront sensor (PWFS) for the 8-m and 40-m telescope aperture cases. We further implemented PO4AO and carried out experiments in a laboratory environment using Magellan Adaptive Optics eXtreme system (MagAO-X) at the Steward laboratory. Results. PO4AO provides the desired performance by improving the coronagraphic contrast in numerical simulations by factors of 3–5 within the control region of deformable mirror and PWFS, both in simulation and in the laboratory. The presented method is also quick to train, that is, on timescales of typically 5–10 s, and the inference time is sufficiently small (<ms) to be used in real-time control for XAO with currently available hardware even for extremely large telescopes.

Optimal design of the annular groove phase mask central region.

Vortex phase masks have been shown to be an efficient means to reduce the blinding stellar light in high-contrast imaging instruments. Once placed at the focal plane of the telescope, the helical phase ramp of a vortex phase mask diffracts the light of a bright on-axis source outside the re-imaged telescope pupil, while transmitting the light of a faint off-axis companion nearly unaffected. The Annular Groove Phase Mask (AGPM) is a broadband metasurface implementation of a vector vortex phase mask using the artificial birefringence of a circular subwavelength grating etched onto a diamond substrate. To date, the AGPM design has been optimized using rigorous coupled-wave analysis (RCWA), which is a valid tool to simulate periodic straight gratings. However, we have now reached a performance level where the curvature of the grating lines at the center becomes a limiting factor. Here, we use a finite-difference time-domain (FDTD) method to correctly describe the AGPM performance, including the effect of the curved grating close to its center. We confirm the validity of this simulation framework by comparing its predictions with experimental results obtained on our infrared coronagraphic test bench, and we show that RCWA fails at reproducing correctly the central AGPM performance, confirming the need for a full 3d simulation tool such as FDTD. Finally, we use FDTD to optimize the grating parameters at the AGPM center, and conclude with a new optimal design.

Laboratory demonstration of real-time focal plane wavefront control of residual atmospheric speckles

Current and future high contrast imaging instruments aim to detect exoplanets at closer orbital separations, lower masses, and/or older ages than their predecessors. However, continually evolving speckles in the coronagraphic science image limit contrasts of state-of-the-art ground-based exoplanet imaging instruments. For ground-based adaptive optics (AO) instruments, it remains challenging for most speckle suppression techniques to attenuate both the dynamic atmospheric as well as quasistatic instrumental speckles on-sky. We have proposed a focal plane wavefront sensing and control algorithm to address this challenge, called the fast atmospheric selfcoherent camera (SCC) technique (FAST), which in theory enables the SCC to operate down to millisecond timescales even when only a few photons are detected per speckle. Here, we present the first experimental results of FAST on the Santa Cruz Extreme AO Laboratory (SEAL) testbed. In particular, we illustrate the benefit of “second stage” AO-based focal plane wavefront control, demonstrating up to 5 × contrast improvement with FAST closed-loop compensation of evolving residual atmospheric turbulence—both for low and high order spatial modes—down to 20-ms timescales.

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.

The Mysterious Lives of Speckles. I. Residual Atmospheric Speckle Lifetimes in Ground-based Coronagraphs

High-contrast imaging observations are fundamentally limited by the spatially and temporally correlated noise source called speckles. Suppression of speckle noise is the key goal of wavefront control and adaptive optics (AO), coronagraphy, and a host of post-processing techniques. Speckles average at a rate set by the statistical speckle lifetime, and speckle-limited integration time in long exposures is directly proportional to this lifetime. As progress continues in post-coronagraph wavefront control, residual atmospheric speckles will become the limiting noise source in high-contrast imaging, so a complete understanding of their statistical behavior is crucial to optimizing high-contrast imaging instruments. Here we present a novel power spectral density method for calculating the lifetime, and develop a semi-analytic method for predicting intensity PSDs behind a coronagraph. Considering a frozen-flow turbulence model, we analyze the residual atmosphere speckle lifetimes in a MagAO-X-like AO system as well as 25–39 m giant segmented mirror telescope scale systems. We find that standard AO control shortens atmospheric speckle lifetime from ∼130 ms to ∼50 ms, and predictive control will further shorten the lifetime to ∼20 ms on 6.5 m MagAO-X. We find that speckle lifetimes vary with diameter, wind speed, seeing, and location within the AO control region. On bright stars lifetimes remain within a rough range of ∼20 ms to ∼100 ms. Due to control system dynamics there are no simple scaling laws which apply across a wide range of system characteristics. Finally, we use these results to argue that telemetry-based post-processing should enable ground-based telescopes to achieve the photon-noise limit in high-contrast imaging.

Self-optimizing adaptive optics control with reinforcement learning for high-contrast imaging

Current and future high-contrast imaging instruments require extreme adaptive optics systems to reach contrasts necessary to directly imaged exoplanets. Telescope vibrations and the temporal error induced by the latency of the control loop limit the performance of these systems. One way to reduce these effects is to use predictive control. We describe how model-free reinforcement learning can be used to optimize a recurrent neural network controller for closed-loop predictive control. First, we verify our proposed approach for tip–tilt control in simulations and a lab setup. The results show that this algorithm can effectively learn to mitigate vibrations and reduce the residuals for power-law input turbulence as compared to an optimal gain integrator. We also show that the controller can learn to minimize random vibrations without requiring online updating of the control law. Next, we show in simulations that our algorithm can also be applied to the control of a high-order deformable mirror. We demonstrate that our controller can provide two orders of magnitude improvement in contrast at small separations under stationary turbulence. Furthermore, we show more than an order of magnitude improvement in contrast for different wind velocities and directions without requiring online updating of the control law.

The SPHERE infrared survey for exoplanets (SHINE)

Context.Large surveys with new-generation high-contrast imaging instruments are needed to derive the frequency and properties of exoplanet populations with separations from ~5 to 300 au. A careful assessment of the stellar properties is crucial for a proper understanding of when, where, and how frequently planets form, and how they evolve. The sensitivity of detection limits to stellar age makes this a key parameter for direct imaging surveys.Aims.We describe the SpHere INfrared survey for Exoplanets (SHINE), the largest direct imaging planet-search campaign initiated at the VLT in 2015 in the context of the SPHERE Guaranteed Time Observations of the SPHERE consortium. In this first paper we present the selection and the properties of the complete sample of stars surveyed with SHINE, focusing on the targets observed during the first phase of the survey (from February 2015 to February 2017). This early sample composed of 150 stars is used to perform a preliminary statistical analysis of the SHINE data, deferred to two companion papers presenting the survey performance, main discoveries, and the preliminary statistical constraints set by SHINE.Methods.Based on a large database collecting the stellar properties of all young nearby stars in the solar vicinity (including kinematics, membership to moving groups, isochrones, lithium abundance, rotation, and activity), we selected the original sample of 800 stars that were ranked in order of priority according to their sensitivity for planet detection in direct imaging with SPHERE. The properties of the stars that are part of the early statistical sample wererevisited, including for instance measurements from theGaiaData Release 2. Rotation periods were derived for the vast majority of the late-type objects exploiting TESS light curves and dedicated photometric observations.Results.The properties of individual targets and of the sample as a whole are presented.

Direct Imaging of Exoplanets beyond the Radial Velocity Limit: Application to the HD 134987 System

Abstract Future direct imaging missions will primarily observe planets that have been previously detected, mostly via the radial velocity (RV) technique, to characterize planetary atmospheres. In the meantime, direct imaging may discover new planets within existing planetary systems that have bright enough reflected flux but insufficient signals for other methods to detect. Here we investigate the parameter space within which planets are unlikely to be detected by RV in the near future due to precision limitations but could be discovered through reflected light with future direct imaging missions. We use the HD 134987 system as a working example, combine RV and direct imaging detection limit curves in the same parameter space through various assumptions, and insert a fictitious planet into the system while ensuring that it lies between the RV and imaging detection limits. Planet validity tested through dynamical simulations and retrieval tests revealed that the planet could indeed be detected by imaging while remaining hidden from RV surveys. Direct imaging retrieval was carried out using starshade simulations for two mission concepts: the Starshade Rendezvous Probe, which could be coupled with the Nancy Grace Roman Space Telescope, and the Habitable Exoplanet Observatory. This method is applicable to all other systems and high-contrast direct imaging instruments and could help inform future imaging observations and data analysis on the discovery of new exoplanets.

Improved Contrast in Images of Exoplanets Using Direct Signal-to-noise Ratio Optimization

Abstract Direct imaging of exoplanets is usually limited by quasi-static speckles. These uncorrected aberrations in a star’s point-spread function (PSF) obscure faint companions and limit the sensitivity of high-contrast imaging instruments. Most current approaches to processing differential imaging sequences like angular differential imaging and spectral differential imaging produce a self-calibrating data set that is combined using a linear least-squares solution to minimize the noise. Due to temporal and chromatic evolution of a telescope’s PSF, the best correlated reference images are usually the most contaminated by the planet, leading to self-subtraction and reducing the planet throughput. In this paper, we present an algorithm that directly optimizes the nonlinear equation for planet signal-to-noise ratio (S/N). This new algorithm does not require us to reject adjacent reference images and optimally balances noise reduction with self-subtraction. We then show how this algorithm can be applied to multiple images simultaneously for a further reduction in correlated noise, directly maximizing the S/N of the final combined image. Finally, we demonstrate the technique on an illustrative sequence of HR8799 using the new Julia-based Signal to Noise Analysis Pipeline. We show that S/N optimization can provide up to a 5× improvement in contrast close to the star. Applicable to both new and archival data, this technique will allow for the detection of fainter, lower mass, and closer-in companions, or achieve the same sensitivity with less telescope time.

Spatial linear dark field control on Subaru/SCExAO

Context. One of the key challenges facing direct exoplanet imaging is the continuous maintenance of the region of high contrast within which light from the exoplanet can be detected above the stellar noise. In high-contrast imaging systems, the dominant source of aberrations is the residual wavefront error that arises due to non-common path aberrations (NCPA) to which the primary adaptive optics (AO) system is inherently blind. Slow variations in the NCPA generate quasi-static speckles in the post-AO corrected coronagraphic image resulting in the degradation of the high-contrast dark hole created by the coronagraph. Aims. In this paper, we demonstrate spatial linear dark field control (LDFC) with an asymmetric pupil vector apodizing phase plate (APvAPP) coronagraph as a method to sense time-varying NCPA using the science image as a secondary wavefront sensor (WFS) running behind the primary AO system. By using the science image as a WFS, the NCPA to which the primary AO system is blind can be measured with high sensitivity and corrected, thereby suppressing the quasi-static speckles which corrupt the high contrast within the dark hole. Methods. On the Subaru Coronagraphic Extreme Adaptive Optics instrument (SCExAO), one of the coronagraphic modes is an APvAPP which generates two PSFs, each with a 180° D-shaped dark hole with approximately 10−4 contrast at λ = 1550 nm. The APvAPP was utilized to first remove the instrumental NCPA in the system and increase the high contrast within the dark holes. Spatial LDFC was then operated in closed-loop to maintain this high contrast in the presence of a temporally-correlated, evolving phase aberration with a root-mean-square wavefront error of 80 nm. In the tests shown here, an internal laser source was used, and the deformable mirror was used both to introduce random phase aberrations into the system and to then correct them with LDFC in closed-loop operation. Results. The results presented here demonstrate the ability of the APvAPP combined with spatial LDFC to sense aberrations in the high amplitude regime (∼80 nm). With LDFC operating in closed-loop, the dark hole is returned to its initial contrast and then maintained in the presence of a temporally-evolving phase aberration. We calculated the contrast in 1 λ/D spatial frequency bins in both open-loop and closed-loop operation, and compared the measured contrast in these two cases. This comparison shows that with LDFC operating in closed-loop, there is a factor of ∼3x improvement (approximately a half magnitude) in contrast across the full dark hole extent from 2−10 λ/D. This improvement is maintained over the full duration (10 000 iterations) of the injected temporally-correlated, evolving phase aberration. Conclusions. This work marks the first deployment of spatial LDFC on an active high-contrast imaging instrument. Our SCExAO testbed results show that the combination of the APvAPP with LDFC provides a powerful new focal plane wavefront sensing technique by which high-contrast imaging systems can maintain high contrast during long observations. This conclusion is further supported by a noise analysis of LDFC’s performance with the APvAPP in simulation.

The polarization-encoded self-coherent camera

Context. The exploration of circumstellar environments by means of direct imaging to search for Earth-like exoplanets is one of the challenges of modern astronomy. One of the current limitations are evolving non-common path aberrations (NCPA) that originate from optics downstream of the main wavefront sensor. Measuring these NCPA with the science camera during observations is the preferred solution for minimizing the non-common path and maximizing the science duty cycle. The self-coherent camera (SCC) is an integrated coronagraph and focal-plane wavefront sensor that generates wavefront information-encoding Fizeau fringes in the focal plane by adding a reference hole (RH) in the Lyot stop. However, the RH is located at least 1.5 pupil diameters away from the pupil center, which requires the system to have large optic sizes and results in low photon fluxes in the RH. Aims. Here, we aim to show that by featuring a polarizer in the RH and adding a polarizing beamsplitter downstream of the Lyot stop, the RH can be placed right next to the pupil. This greatly increases the photon flux in the RH and relaxes the requirements on the optics size due to a smaller beam footprint. We refer to this new variant of the SCC as the polarization-encoded self-coherent camera (PESCC). Methods. We study the performance of the PESCC analytically and numerically, and compare it, where relevant, to the SCC. We look into the specific noise sources that are relevant for the PESCC and quantify their effect on wavefront sensing and control (WFSC). Results. We show analytically that the PESCC relaxes the requirements on the focal-plane sampling and spectral resolution with respect to the SCC by a factor of 2 and 3.5, respectively. Furthermore, we find via our numerical simulations that the PESCC has effectively access to ∼16 times more photons, which improves the sensitivity of the wavefront sensing by a factor of ∼4. We identify the need for the parameters related to the instrumental polarization and differential aberrations between the beams to be tightly controlled – otherwise, they limit the instrument’s performance. We also show that without additional measurements, the RH point-spread function (PSF) can be calibrated using PESCC images, enabling coherent differential imaging (CDI) as a contrast-enhancing post-processing technique for every observation. In idealized simulations (clear aperture, charge two vortex coronagraph, perfect DM, no noise sources other than phase and amplitude aberrations) and in circumstances similar to those of space-based systems, we show that WFSC combined with CDI can achieve a 1σ raw contrast of ∼3 × 10−11 − 8 × 10−11 between 1 and 18 λ/D. Conclusions. The PESCC is a powerful, new focal-plane wavefront sensor that can be relatively easily integrated into existing ground-based and future space-based high-contrast imaging instruments.

Three New Late-type Stellar Companions to Very Dusty WISE Debris Disks Identified with SPHERE Imaging

Abstract Debris disk stars are good targets for high-contrast imaging searches for planetary systems, since debris disks have been shown to have a tentative correlation with giant planets. We selected 20 stars identified as debris disk hosts by the WISE mission, with particularly high levels of warm dust. We observed these with the VLT/SPHERE high-contrast imaging instrument with the goal of finding planets and imaging the disks in scattered light. Our survey reaches a median 5σ sensitivity of 10.4 M J at 25 au and 5.9 M J at 100 au. We identified three new stellar companions (HD 18378B, HD 19257B, and HD 133778B): two are mid-M-type stars and one is a late-K or early-M star. Three additional stars have very widely separated stellar companions (all at >2000 au) identified in the Gaia catalog. The stars hosting the three SPHERE-identified companions are all older (≳700 Myr), with one having recently left the main sequence and one a giant star. We infer that the high volumes of dust observed around these stars has been caused by a recent collision between the planets and planetesimal belts in the system, although for the most evolved star, mass loss could also be responsible for the infrared excess. Future mid-infrared spectroscopy or polarimetric imaging may allow the positions and spatial extent of these dust belts to be constrained, thereby providing evidence as to the true cause of the elevated levels of dust around these old systems. None of the disks in this survey is resolved in scattered light.