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Context. A low-mass brown dwarf has recently been imaged around HR 2562 (HD 50571), a star hosting a debris disk resolved in the far infrared. Interestingly, the companion location is compatible with an orbit coplanar with the disk and interior to the debris belt. This feature makes the system a valuable laboratory to analyze the formation of substellar companions in a circumstellar disk and potential disk-companion dynamical interactions. Aims. We aim to further characterize the orbital motion of HR 2562 B and its interactions with the host star debris disk. Methods. We performed a monitoring of the system over ~10 months in 2016 and 2017 with the VLT/SPHERE exoplanet imager. Results. We confirm that the companion is comoving with the star and detect for the first time an orbital motion at high significance, with a current orbital motion projected in the plane of the sky of 25 mas (~0.85 au) per year. No orbital curvature is seen in the measurements. An orbital fit of the SPHERE and literature astrometry of the companion without priors on the orbital plane clearly indicates that its orbit is (quasi-)coplanar with the disk. To further constrain the other orbital parameters, we used empirical laws for a companion chaotic zone validated by N-body simulations to test the orbital solutions that are compatible with the estimated disk cavity size. Non-zero eccentricities (>0.15) are allowed for orbital periods shorter than 100 yr, while only moderate eccentricities up to ~0.3 for orbital periods longer than 200 yr are compatible with the disk observations. A comparison of synthetic Herschel images to the real data does not allow us to constrain the upper eccentricity of the companion. [ABSTRACT FROM AUTHOR]

Aims. Compressed sensing realized by means of regularized deconvolution and the finite isotropic wavelet transform is effective and reliable in hard X-ray solar imaging. Methods. The method uses the finite isotropic wavelet transform with the Meyer function as the mother wavelet. Furthermore, compressed sensing is realized by optimizing a sparsity-promoting regularized objective function by means of the fast iterative shrinkage-thresholding algorithm. Eventually, the regularization parameter is selected by means of the Miller criterion. Results. The method is applied against both synthetic data mimicking measurements made with the Spectrometer/Telescope Imaging X-rays (STIX) and experimental observations provided by the Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI). The performances of the method are qualitatively validated by comparing some morphological properties of the reconstructed sources with those of the corresponding synthetic configurations. Furthermore, the results concerning experimental data are compared with those obtained by applying other visibility-based reconstruction methods. Conclusions. The results show that when the new method is applied to synthetic STIX visibility sets, it provides reconstructions with a spatial accuracy comparable to the accuracy provided by the most popular method in hard X-ray solar imaging and with a higher spatial resolution. Furthermore, when it is applied to experimental RHESSI data, the reconstructions are characterized by reliable photometry and by a notable reduction of the ringing effects caused by the instrument point spread function. [ABSTRACT FROM AUTHOR]

Context. Angular differential imaging (ADI) takes advantage of the field rotation naturally induced by altitude-azimuth mounts to reduce static speckle noise. Used with facilities like SPHERE at the VLT, this technique allows one to achieve contrast ratios of 10􀀀6. The ADI method, however, intrinsically limits the useful exposure time on a given target (to about 1–2 h per night). Detecting fainter exoplanets requires the combination of multiple observations acquired on different nights, potentially spread over several weeks or months, but the unknown orbital motion of the planet makes it particularly dififcult to properly combine all observations. In the near future, with the upcoming generation of Extremely Large Telescopes (ELTs) with increased resolution, the orbital motion may even become a problem on a single night. Aims. We present a proof of concept for a new algorithm which can be used to detect exoplanets in high-contrast images. The algorithm properly combines multiple observations acquired during different nights, taking into account the orbital motion of the planet. Methods. We simulate SPHERE/IRDIS time series of observations in which we blindly inject planets on random orbits, at random levels of signal-to-noise ratio (S/N), below the detection limit (down to S=N ' 1:5). We then use an optimization algorithm to “guess” the orbital parameters, and take into account the orbital motion to properly recombine the different images and eventually detect the planets. Results. We show that an optimization algorithm can indeed be used to find undetected planets in temporal sequences of images, even if they are spread over orbital time scales. As expected, the typical gain in S/N is p n, n being the number of observations combined. We find that the K-Stacker algorithm is able de-orbit and combine the images to reach a level of performance similar to what could be expected if the planet was not moving.We find recovery rates of '50% at S=N = 5.We also find that the algorithm is able to determine the position of the planet in individual frames at one pixel precision, even despite the fact that the planet itself is below the detection limit in each frame. Conclusions. Our simulations show that K-Stacker can be used to detect planets at very low S/N level, down to '2 in individual frames, for series of ten images. This could be used to increase the contrast limit of current exoplanet imaging instruments and to discover fainter bodies. We also suggest that the ability of K-Stacker to determine the position of the planet in every image of the time series could be used as part of a new observing strategy in which long exposures would be broken into shorter ones spread over months. This could make it possible to determine the orbital parameters of a planet without multiple high-S/N (>5) detections. [ABSTRACT FROM AUTHOR]

We introduce a new algorithm for colour separation and deblending of multi-band astronomical images called MuSCADeT which is based on Morpho-spectral Component Analysis of multi-band images. The MuSCADeT algorithm takes advantage of the sparsity of astronomical objects in morphological dictionaries such as wavelets and their differences in spectral energy distribution (SED) across multi-band observations. This allows us to devise a model independent and automated approach to separate objects with different colours. We show with simulations that we are able to separate highly blended objects and that our algorithm is robust against SED variations of objects across the field of view. To confront our algorithm with real data, we use HST images of the strong lensing galaxy cluster MACS J1149+2223 and we show that MuSCADeT performs better than traditional profile-fitting techniques in deblending the foreground lensing galaxies from background lensed galaxies. Although the main driver for our work is the deblending of strong gravitational lenses, our method is fit to be used for any purpose related to deblending of objects in astronomical images. An example of such an application is the separation of the red and blue stellar populations of a spiral galaxy in the galaxy cluster Abell 2744. We provide a python package along with all simulations and routines used in this paper to contribute to reproducible research efforts. [ABSTRACT FROM AUTHOR]

Context. Images from adaptive optics systems are generally affected by significant distortions of the point spread function (PSF) across the field of view, depending on the position of natural and artificial guide stars. Image reduction techniques circumventing or mitigating these effects are important tools to take full advantage of the scientific information encoded in adaptive optics images. Aims. The aim of this paper is to propose a method for the deblurring of the astronomical image, given a set of samples of the spacevariant PSF. Methods. The method is based on a partitioning of the image domain into regions of isoplanatism and on applying suitable deconvolution methods with boundary effects correction to each region. Results. The effectiveness of the boundary effects correction is proved. Moreover, the criterion for extending the disjoint sections to partially overlapping sections is validated. The method is applied to simulated images of a stellar system characterized by a spatially variable PSF. We obtain good photometric quality, and therefore good science quality, by performing aperture photometry on the deblurred images. [ABSTRACT FROM AUTHOR]

We report the discovery of the merging cluster, RXCJ2359.3-6042, from the REFLEX II cluster survey and present our results from all three detectors combined in the imaging and spectral analysis of the XMM-Newton data. Also known as Abell 4067, this is a unique system, where a compact bullet penetrates an extended, low density cluster at redshift z = 0.0992 clearly seen from our follow-up XMM-Newton observation. The bullet goes right through the central region of the cluster without being disrupted and we can clearly see how the bullet component is stripped of its layers outside the core. There is an indication of a shock heated region in the east of the cluster with a higher temperature. The bulk temperature of the cluster is about 3.12(±0.13) keV implying a lower mass system. Spearheading the bullet is a cool core centred by a massive early type galaxy. The temperatures and metallicities of a few regions in the cluster derived from the spectral analysis supports our conjecture based on the surface brightness image that a much colder compact component at 1.55(±0.10) keV with large metallicity (0.75 Z⊙) penetrates the main cluster, where the core of the infalling component survived the merger and left stripped gas behind at the centre of the main cluster. We also give an estimate of the total mass within r500, which is about 2 × 1014 M⊙ from the deprojected spherical ß modelling of the cluster in good agreement with other mass estimates from the M - TX and M - sv relations. [ABSTRACT FROM AUTHOR]

Stars with debris disks are intriguing targets for direct-imaging exoplanet searches, owing both to previous detections of wide planets in debris disk systems, and to commonly existing morphological features in the disks themselves that may be indicative of a planetary influence. Here we present observations of three of the most nearby young stars, which are also known to host massive debris disks: Vega, Fomalhaut, and ∊ Eri. The Spitzer Space Telescope is used at a range of orientation angles for each star to supply a deep contrast through angular differential imaging combined with high-contrast algorithms. The observations provide the opportunity to probe substantially colder bound planets (120-330 K) than is possible with any other technique or instrument. For Vega, some apparently very red candidate point sources detected in the 4.5 Ìm image remain to be tested for common proper motion. The images are sensitive to ~2 Mjup companions at 150 AU in this system. The observations presented here represent the first search for planets around Vega using Spitzer. The upper 4.5 μm flux limit on Fomalhaut b could be further constrained relative to previous data. In the case of ∊ Eri, planets below both the effective temperature and the mass of Jupiter could be probed from 80 AU and outward, although no such planets were found. The data sensitively probe the regions around the edges of the debris rings in the systems where planets can be expected to reside. These observations validate previous results showing that more than an order of magnitude improvement in performance in the contrast-limited regime can be acquired with respect to conventional methods by applying sophisticated high-contrast techniques to space-based telescopes, thanks to the high degree of PSF stability provided in this environment. [ABSTRACT FROM AUTHOR]

Context. Images of spatially resolved astrophysical objects contain a wealth of morphological and dynamical information, and effectively extracting this information is of paramount importance for understanding the physics and evolution of these objects. The algorithms and methods currently employed for this purpose (such as Gaussian model fitting) often use simplified approaches to describe the structure of resolved objects. Aims. Automated (unsupervised) methods for structure decomposition and tracking of structural patterns are needed for this purpose to be able to treat the complexity of structure and large amounts of data involved. Methods. We developed a new wavelet-based image segmentation and evaluation (WISE) method for multiscale decomposition, segmentation, and tracking of structural patterns in astronomical images. Results. The method was tested against simulated images of relativistic jets and applied to data from long-term monitoring of parsecscale radio jets in 3C 273 and 3C 120. Working at its coarsest resolution, WISE reproduces the previous results of a model-fitting evaluation of the structure and kinematics in these jets exceptionally well. Extending the WISE structure analysis to fine scales provides the first robust measurements of two-dimensional velocity fields in these jets and indicates that the velocity fields probably reflect the evolution of Kelvin-Helmholtz instabilities that develop in the flow. [ABSTRACT FROM AUTHOR]

The analysis of astronomical images is a non-trivial task. The D³PO algorithm addresses the inference problem of denoising, deconvolving, and decomposing photon observations. Its primary goal is the simultaneous but individual reconstruction of the diffuse and point-like photon flux given a single photon count image, where the fluxes are superimposed. In order to discriminate between these morphologically different signal components, a probabilistic algorithm is derived in the language of information field theory based on a hierarchical Bayesian parameter model. The signal inference exploits prior information on the spatial correlation structure of the diffuse component and the brightness distribution of the spatially uncorrelated point-like sources. A maximum a posteriori solution and a solution minimizing the Gibbs free energy of the inference problem using variational Bayesian methods are discussed. Since the derivation of the solution is not dependent on the underlying position space, the implementation of the D³PO algorithm uses the nifty package to ensure applicability to various spatial grids and at any resolution. The fidelity of the algorithm is validated by the analysis of simulated data, including a realistic high energy photon count image showing a 32 × 32 arcmin² observation with a spatial resolution of 0:1 arcmin. In all tests the D³PO algorithm successfully denoised, deconvolved, and decomposed the data into a diffuse and a point-like signal estimate for the respective photon flux components. [ABSTRACT FROM AUTHOR]

Aims. An experiment was set up at the Concordia station in Antarctica during the winter-over period in 2012 to determine the behaviour of atmospheric optical turbulence in the lower part of the atmospheric boundary layer. The aim of the experiment was to study the influence of turbulence and weather conditions on the quality of astronomical observations. The Concordia station is characterised by the high quality of astronomical images thanks to very low seeing values. The surface layer in the interior of Antarctica during the winter is very stably stratified with the differences of temperature between the surface and the top of the inversion, which reach 20−35◦C. In spite of this strong static stability, considerable thermal optically active turbulence sometimes occurs and extends to several tens of metres above the surface, depending on weather conditions. It is important to know the meteorological characteristics that favour good astronomical observations. Methods. The optical measurements of the seeing made by differential image motion monitors installed at two levels of 8 and 20 m were accompanied by observations of turbulence in the lowest one hundred meters. Turbulence was detected and evaluated using a high-resolution sodar developed specially for this purpose. The statistics of some relevant meteorological variables including the long-wave downward radiation, which indicates cloudiness, were determined. Results. Typical patterns of the vertical and temporal structure of turbulence shown by sodar echograms were identified, analysed, and classified. The statistics of the depth of the surface-based turbulent layer and the turbulent optical factor for different height layers are presented together with the seeing statistics. We analysed the dependence of both seeing and integral turbulence intensity within the first 100 m on temperature and wind speed. Conclusions. Seeing and turbulence intensity in the atmospheric boundary layer appear to be correlated. The best values of the seeing (<1 arcsec) are observed when the sodar shows very low turbulence intensity. The main contribution to the image distortion is due to turbulence generated within the lowest 30−50 m near the surface. The presented statistics of the vertical distribution of the atmospheric optical turbulence can be used to determine the optimal location for astronomical instruments. [ABSTRACT FROM AUTHOR]

Astronomical images suffer a constant presence of multiple defects that are consequences of the atmospheric conditions and of the intrinsic properties of the acquisition equipment. One of the most frequent defects in astronomical imaging is the presence of additive noise which makes a denoising step mandatory before processing data. During the last decade, a particular modeling scheme, based on sparse representations, has drawn the attention of an ever growing community of researchers. Sparse representations offer a promising framework to many image and signal processing tasks, especially denoising and restoration applications. At first, the harmonics, wavelets and similar bases, and overcomplete representations have been considered as candidate domains to seek the sparsest representation. A new generation of algorithms, based on data-driven dictionaries, evolved rapidly and compete now with the off-the-shelf fixed dictionaries. Although designing a dictionary relies on guessing the representative elementary forms and functions, the framework of dictionary learning offers the possibility of constructing the dictionary using the data themselves, which provides us with a more flexible setup to sparse modeling and allows us to build more sophisticated dictionaries. In this paper, we introduce the centered dictionary learning (CDL) method and we study its performance for astronomical image denoising. We show how CDL outperforms wavelet or classic dictionary learning denoising techniques on astronomical images, and we give a comparison of the effects of these different algorithms on the photometry of the denoised images. [ABSTRACT FROM AUTHOR]

Context. The measurement of the Sun’s surface motions with a high spatial and temporal resolution is still a challenge. Aims. We wish to validate horizontal velocity measurements all over the visible disk of the Sun from Solar Dynamics Observatory/Helioseismic and Magnetic Imager (SDO/HMI) data. Methods. Horizontal velocity fields are measured by following the proper motions of solar granules using a newly developed version of the coherent structure tracking (CST) code. The comparison of the surface flows measured at high spatial resolution (Hinode, 0.1 arcsec) and low resolution (SDO/HMI, 0.5 arcsec) allows us to determine corrections to be applied to the horizontal velocity measured from HMI white light data. Results. We derive horizontal velocity maps with spatial and temporal resolutions of respectively 2.5 Mm and 30 min. From the two components of the horizontal velocity vx and vy measured in the sky plane and the simultaneous line of sight component from SDO/HMI dopplergrams vD, we derive the spherical velocity components (vr, vθ, vϕ). The azimuthal component vϕ gives the solar differential rotation with a high precision (± 0.037 km s-1) from a temporal sequence of only three hours. Conclusions. By following the proper motions of the solar granules, we can revisit the dynamics of the solar surface at high spatial and temporal resolutions from hours to months and years with the SDO data. [ABSTRACT FROM AUTHOR]