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Register a new userPeering through SPHERE Images: A Glance at Contrast Limitations
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Faustine Cantalloube
Publication date
2019
fields
Physics
and research's language is
English
Authors
Faustine Cantalloube
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Various structures are visible within Spectro-Polarimetric High-contrast Exoplanet REsearch instrument (SPHERE) images that are not always straightforward to interpret. In this article we present a review of these features and demonstrate their origin using simulations. We also identify which expected or unexpected features are limiting the contrast reached by the instrument and how they may be tackled. This vision paves the way to designing a future upgrade of the SPHERE instrument and the next generation of high-contrast instruments such as those planned for the Extremely Large Telescope (ELT).
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Context. The wind driven halo is a feature observed within the images delivered by the latest generation of ground-based instruments equipped with an extreme adaptive optics system and a coronagraphic device, such as SPHERE at the VLT. This signature appears when the atmospheric turbulence conditions are varying faster than the adaptive optics loop can correct. The wind driven halo shows as a radial extension of the point spread function along a distinct direction (sometimes referred to as the butterfly pattern). When present, it significantly limits the contrast capabilities of the instrument and prevents the extraction of signals at close separation or extended signals such as circumstellar disks. This limitation is consequential because it contaminates the data a substantial fraction of the time: about 30% of the data produced by the VLT/SPHERE instrument are affected by the wind driven halo.Aims. This paper reviews the causes of the wind driven halo and presents a method to analyze its contribution directly from the scientific images. Its effect on the raw contrast and on the final contrast after post-processing is demonstrated.Methods. We used simulations and on-sky SPHERE data to verify that the parameters extracted with our method are capable of describing the wind driven halo present in the images. We studied the temporal, spatial and spectral variation of these parameters to point out its deleterious effect on the final contrast.Results. The data driven analysis we propose does provide information to accurately describe the wind driven halo contribution in the images. This analysis justifies why this is a fundamental limitation to the final contrast performance reached.Conclusions. With the established procedure, we will analyze a large sample of data delivered by SPHERE in order to propose, in the future, post-processing techniques tailored to remove the wind driven halo.
The objective of the SPHERE Data Center is to optimize the scientific return of SPHERE at the VLT, by providing optimized reduction procedures, services to users and publicly available reduced data. This paper describes our motivation, the implementation of the service (partners, infrastructure and developments), services, description of the on-line data, and future developments. The SPHERE Data Center is operational and has already provided reduced data with a good reactivity to many observers. The first public reduced data have been made available in 2017. The SPHERE Data Center is gathering a strong expertise on SPHERE data and is in a very good position to propose new reduced data in the future, as well as improved reduction procedures.
The major source of noise in high-contrast imaging is the presence of slowly evolving speckles that do not average with time. The temporal stability of the point-spread-function (PSF) is therefore critical to reach a high contrast with extreme adaptive optics (xAO) instruments. Understanding on which timescales the PSF evolves and what are the critical parameters driving the speckle variability allow to design an optimal observing strategy and data reduction technique to calibrate instrumental aberrations and reveal faint astrophysical sources. We have obtained a series of 52 min, AO-corrected, coronagraphically occulted, high-cadence (1.6Hz), H-band images of the star HR 3484 with the SPHERE (Spectro-Polarimeter High-contrast Exoplanet REsearch instrument on the VLT. This is a unique data set from an xAO instrument to study its stability on timescales as short as one second and as long as several tens of minutes. We find different temporal regimes of decorrelation. We show that residuals from the atmospheric turbulence induce a fast, partial decorrelation of the PSF over a few seconds, before a transition to a regime with a linear decorrelation with time, at a rate of several tens parts per million per second (ppm/s). We analyze the spatial dependence of this decorrelation, within the well-corrected radius of the adaptive optics system and show that the linear decorrelation is faster at short separations. Last, we investigate the influence of the distance to the meridian on the decorrelation.
We describe a new instrument that forms the core of a long-term high contrast imaging program at the 200-inch Hale Telescope at Palomar Observatory. The primary scientific thrust is to obtain images and low-resolution spectroscopy of brown dwarfs and young Jovian mass exoplanets in the vicinity of stars within 50 parsecs of the Sun. The instrument is a microlens-based integral field spectrograph integrated with a diffraction limited, apodized-pupil Lyot coronagraph, mounted behind the Palomar adaptive optics system. The spectrograph obtains imaging in 23 channels across the J and H bands (1.06 - 1.78 microns). In addition to obtaining spectra, this wavelength resolution allows suppression of the chromatically dependent speckle noise, which we describe. We have recently installed a novel internal wave front calibration system that will provide continuous updates to the AO system every 0.5 - 1.0 minutes by sensing the wave front within the coronagraph. The Palomar AO system is undergoing an upgrade to a much higher-order AO system (PALM-3000): a 3388-actuator tweeter deformable mirror working together with the existing 241-actuator mirror. This system will allow correction with subapertures as small as 8cm at the telescope pupil using natural guide stars. The coronagraph alone has achieved an initial dynamic range in the H-band of 2 X 10^-4 at 1 arcsecond, without speckle noise suppression. We demonstrate that spectral speckle suppression is providing a factor of 10-20 improvement over this bringing our current contrast at an arcsecond to ~2 X 10^-5. This system is the first of a new generation of apodized pupil coronagraphs combined with high-order adaptive optics and integral field spectrographs (e.g. GPI, SPHERE, HiCIAO), and we anticipate this instrument will make a lasting contribution to high contrast imaging in the Northern Hemisphere for years.
Cross-modality generation is an emerging topic that aims to synthesize data in one modality based on information in a different modality. In this paper, we consider a task of such: given an arbitrary audio speech and one lip image of arbitrary target identity, generate synthesized lip movements of the target identity saying the speech. To perform well in this task, it inevitably requires a model to not only consider the retention of target identity, photo-realistic of synthesized images, consistency and smoothness of lip images in a sequence, but more importantly, learn the correlations between audio speech and lip movements. To solve the collective problems, we explore the best modeling of the audio-visual correlations in building and training a lip-movement generator network. Specifically, we devise a method to fuse audio and image embeddings to generate multiple lip images at once and propose a novel correlation loss to synchronize lip changes and speech changes. Our final model utilizes a combination of four losses for a comprehensive consideration in generating lip movements; it is trained in an end-to-end fashion and is robust to lip shapes, view angles and different facial characteristics. Thoughtful experiments on three datasets ranging from lab-recorded to lips in-the-wild show that our model significantly outperforms other state-of-the-art methods extended to this task.
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