Deep Full-sky Coadds from Three Years of WISE and NEOWISE Observations [IMA]

http://arxiv.org/abs/1705.06746


We have reprocessed over 100 terabytes of single-exposure WISE/NEOWISE images to create the deepest ever full-sky maps at 3-5 microns. We incorporate all publicly available W1 and W2 imaging – a total of ~8 million exposures in each band – from ~37 months of observations spanning 2010 January to 2015 December. Our coadds preserve the native WISE resolution and feature depth of coverage ~3 times greater than that of the AllWISE Atlas stacks. Our coadds are designed to enable deep forced photometry, in particular for the Dark Energy Camera Legacy Survey (DECaLS) and Mayall z-Band Legacy Survey (MzLS), both of which are being used to select targets for the Dark Energy Spectroscopic Instrument (DESI). We describe newly introduced processing steps aimed at leveraging added redundancy to remove artifacts, with the intent of facilitating uniform target selection and searches for rare/exotic objects (e.g. high-redshift quasars and distant galaxy clusters). Forced photometry depths achieved with these coadds extend 0.56 (0.46) magnitudes deeper in W1 (W2) than is possible with only pre-hibernation WISE imaging.

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A. Meisner, D. Lang and D. Schlegel
Mon, 22 May 17
27/51

Comments: data release available at this http URL

Simple Stabilized Radio-Frequency Transfer with Optical Phase Actuation [IMA]

http://arxiv.org/abs/1705.06734


We describe and experimentally evaluate a stabilized radio-frequency transfer technique that employs optical phase sensing and optical phase actuation. This technique can be achieved by modifying existing stabilized optical frequency equipment and also exhibits advantages over previous stabilized radio-frequency transfer techniques in terms of size and complexity. We demonstrate the stabilized transfer of a 160 MHz signal over an 166 km fiber optical link, achieving an Allan deviation of 9.7×10^-12 Hz/Hz at 1 s of integration, and 3.9×10^-1414 Hz/Hz at 1000 s. This technique is being considered for application to the Square Kilometre Array SKA1-low radio telescope.

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D. Gozzard, S. Schediwy, R. Whitaker, et. al.
Mon, 22 May 17
32/51

Comments: 4 pages, 2 figures, submitted to Optics Letters

JP3D compression of solar data-cubes: photospheric imaging and spectropolarimetry [IMA]

http://arxiv.org/abs/1705.06611


Hyperspectral imaging is an ubiquitous technique in solar physics observations and the recent advances in solar instrumentation enabled us to acquire and record data at an unprecedented rate. The huge amount of data which will be archived in the upcoming solar observatories press us to compress the data in order to reduce the storage space and transfer times. The correlation present over all dimensions, spatial, temporal and spectral, of solar data-sets suggests the use of a 3D base wavelet decomposition, to achieve higher compression rates. In this work, we evaluate the performance of the recent JPEG2000 Part 10 standard, known as JP3D, for the lossless compression of several types of solar data-cubes. We explore the differences in: a) The compressibility of broad-band or narrow-band time-sequence; I or V stokes profiles in spectropolarimetric data-sets; b) Compressing data in [x,y,$\lambda$] packages at different times or data in [x,y,t] packages of different wavelength; c) Compressing a single large data-cube or several smaller data-cubes; d) Compressing data which is under-sampled or super-sampled with respect to the diffraction cut-off.

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D. Moro, L. Giovannelli, E. Pietropaolo, et. al.
Fri, 19 May 17
1/62

Comments: N/A

Large Area X-ray Proportional Counter (LAXPC) Instrument on AstroSat [IMA]

http://arxiv.org/abs/1705.06440


Large Area X-ray Proportional Counter (LAXPC) is one of the major AstroSat payloads. LAXPC instrument will provide high time resolution X-ray observations in 3 to 80 keV energy band with moderate energy resolution. A cluster of three co-aligned identical LAXPC detectors is used in AstroSat to provide large collection area of more than 6000 cm2 . The large detection volume (15 cm depth) filled with xenon gas at about 2 atmosphere pressure, results in detection efficiency greater than 50%, above 30 keV. With its broad energy range and fine time resolution (10 microsecond), LAXPC instrument is well suited for timing and spectral studies of a wide variety of known and transient X-ray sources in the sky. We have done extensive calibration of all LAXPC detectors using radioactive sources as well as GEANT4 simulation of LAXPC detectors. We describe in brief some of the results obtained during the payload verification phase along with LXAPC capabilities.

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J. Yadav, P. Agrawal, H. Antia, et. al.
Fri, 19 May 17
37/62

Comments: 8 pages, 3 figures, To appear in Current Science 2017

Large Area X-ray Proportional Counter (LAXPC) Instrument on AstroSat and Some Preliminary Results from its performance in the orbit [IMA]

http://arxiv.org/abs/1705.06446


Large Area X-ray Propositional Counter (LAXPC) instrument on AstroSat is aimed at providing high time resolution X-ray observations in 3 to 80 keV energy band with moderate energy resolution. To achieve large collecting area, a cluster of three co-aligned identical LAXPC detectors, is used to realize an effective area in access of about 6000 cm2 at 15 keV. The large detection volume of the LAXPC detectors, filled with xenon gas at about 2 atmosphere pressure, results in detection efficiency greater than 50%, above 30 keV. In this article, we present salient features of the LAXPC detectors, their testing and characterization in the laboratory prior to launch and calibration in the orbit. Some preliminary results on timing and spectral characteristics of a few X-ray binaries and other type of sources, are briefly discussed to demonstrate that the LAXPC instrument is performing as planned in the orbit.

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P. Agrawal, J. Yadav, H. Antia, et. al.
Fri, 19 May 17
54/62

Comments: 11 pages, 15 Figures, Accepted for publication in Journal of Astronomy and Astrophysics

VIP: Vortex Image Processing package for high-contrast direct imaging [IMA]

http://arxiv.org/abs/1705.06184


We present the Vortex Image Processing (VIP) library, a python package dedicated to astronomical high-contrast imaging. Our package relies on the extensive python stack of scientific libraries and aims to provide a flexible framework for high-contrast data and image processing. In this paper, we describe the capabilities of VIP related to processing image sequences acquired using the angular differential imaging (ADI) observing technique. VIP implements functionalities for building high-contrast data processing pipelines, encompass- ing pre- and post-processing algorithms, potential sources position and flux estimation, and sensitivity curves generation. Among the reference point-spread function subtraction techniques for ADI post-processing, VIP includes several flavors of principal component analysis (PCA) based algorithms, such as annular PCA and incremental PCA algorithm capable of processing big datacubes (of several gigabytes) on a computer with limited memory. Also, we present a novel ADI algorithm based on non-negative matrix factorization (NMF), which comes from the same family of low-rank matrix approximations as PCA and provides fairly similar results. We showcase the ADI capabilities of the VIP library using a deep sequence on HR8799 taken with the LBTI/LMIRCam and its recently commissioned L-band vortex coronagraph. Using VIP we investigated the presence of additional companions around HR8799 and did not find any significant additional point source beyond the four known planets. VIP is available at this http URL and is accompanied with Jupyter notebook tutorials illustrating the main functionalities of the library.

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C. Gonzalez, O. Wertz, O. Absil, et. al.
Thu, 18 May 17
7/60

Comments: N/A

LensExtractor: A Convolutional Neural Network in Search of Strong Gravitational Lenses [IMA]

http://arxiv.org/abs/1705.05857


In this work, we present our classification algorithm to identify strong gravitational lenses from wide-area surveys using machine learning convolutional neural network; LensExtractor. We train and test the algorithm using a wide variety of strong gravitational lens configurations from simulations of lensing events. Images are processed through multiple convolutional layers which extract feature maps necessary to assign a lens probability to each image. LensExtractor provides a ranking scheme for all sources which could be used to identify potential gravitational lens candidates significantly reducing the number of images that have to be visually inspected. We further apply our algorithm to the \textit{HST}/ACS i-band observations of the COSMOS field and present our sample of identified lensing candidates. The developed machine learning algorithm is much more computationally efficient than classical lens identification algorithms and is ideal for discovering such events across wide areas from current and future surveys such as LSST and WFIRST.

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M. Pourrahmani, H. Nayyeri and H. Nayyeri
Thu, 18 May 17
9/60

Comments: 10 Pages, 9 Figures, 1 Table, Submitted to ApJ