Montage: a grid portal and software toolkit for science-grade astronomical image mosaicking

Montage is a portable software toolkit for constructing custom, science-grade mosaics by composing multiple astronomical images. The mosaics constructed by Montage preserve the astrometry (position) and photometry (intensity) of the sources in the input images. The mosaic to be constructed is specified by the user in terms of a set of parameters, including dataset and wavelength to be used, location and size on the sky, coordinate system and projection, and spatial sampling rate. Many astronomical datasets are massive, and are stored in distributed archives that are, in most cases, remote with respect to the available computational resources. Montage can be run on both single- and multi-processor computers, including clusters and grids. Standard grid tools are used to run Montage in the case where the data or computers used to construct a mosaic are located remotely on the Internet. This paper describes the architecture, algorithms, and usage of Montage as both a software toolkit and as a grid portal. Timing results are provided to show how Montage performance scales with number of processors on a cluster computer. In addition, we compare the performance of two methods of running Montage in parallel on a grid.Comment: 16 pages, 11 figure

An investigation of the Eigenvalue Calibration Method (ECM) using GASP for non-imaging and imaging detectors

Polarised light from astronomical targets can yield a wealth of information about their source radiation mechanisms, and about the geometry of the scattered light regions. Optical observations, of both the linear and circular polarisation components, have been impeded due to non-optimised instrumentation. The need for suitable observing conditions and the availability of luminous targets are also limiting factors. GASP uses division of amplitude polarimeter (DOAP) (Compain and Drevillon) to measure the four components of the Stokes vector simultaneously, which eliminates the constraints placed upon the need for moving parts during observation, and offers a real-time complete measurement of polarisation. Results from the GASP calibration are presented in this work for both a 1D detector system, and a pixel-by-pixel analysis on a 2D detector system. Following Compain et al. we use the Eigenvalue Calibration Method (ECM) to measure the polarimetric limitations of the instrument for each of the two systems. Consequently, the ECM is able to compensate for systematic errors introduced by the calibration optics, and it also accounts for all optical elements of the polarimeter in the output. Initial laboratory results of the ECM are presented, using APD detectors, where errors of 0.2% and 0.1{\deg} were measured for the degree of linear polarisation and polarisation angle respectively. Channel-to-channel image registration is an important aspect of 2-D polarimetry. We present our calibration results of the measured Mueller matrix of each sample, used by the ECM. A set of Zenith flat-field images were recorded during an observing campaign at the Palomar 200 inch telescope in November 2012. From these we show the polarimetric errors from the spatial polarimetry indicating both the stability and absolute accuracy of GASP.Comment: Accepted for publication in Experimental Astronom

New Techniques for High-Contrast Imaging with ADI: the ACORNS-ADI SEEDS Data Reduction Pipeline

We describe Algorithms for Calibration, Optimized Registration, and Nulling the Star in Angular Differential Imaging (ACORNS-ADI), a new, parallelized software package to reduce high-contrast imaging data, and its application to data from the SEEDS survey. We implement several new algorithms, including a method to register saturated images, a trimmed mean for combining an image sequence that reduces noise by up to ~20%, and a robust and computationally fast method to compute the sensitivity of a high-contrast observation everywhere on the field-of-view without introducing artificial sources. We also include a description of image processing steps to remove electronic artifacts specific to Hawaii2-RG detectors like the one used for SEEDS, and a detailed analysis of the Locally Optimized Combination of Images (LOCI) algorithm commonly used to reduce high-contrast imaging data. ACORNS-ADI is written in python. It is efficient and open-source, and includes several optional features which may improve performance on data from other instruments. ACORNS-ADI requires minimal modification to reduce data from instruments other than HiCIAO. It is freely available for download at www.github.com/t-brandt/acorns-adi under a BSD license.Comment: 15 pages, 9 figures, accepted to ApJ. Replaced with accepted version; mostly minor changes. Software update

Speckle statistics in adaptive optics images at visible wavelengths

Residual speckles in adaptive optics (AO) images represent a well-known limitation on the achievement of the contrast needed for faint source detection. Speckles in AO imagery can be the result of either residual atmospheric aberrations, not corrected by the AO, or slowly evolving aberrations induced by the optical system. We take advantage of the high temporal cadence (1 ms) of the data acquired by the System for Coronagraphy with High-order Adaptive Optics from R to K bands-VIS forerunner experiment at the Large Binocular Telescope to characterize the AO residual speckles at visible wavelengths. An accurate knowledge of the speckle pattern and its dynamics is of paramount importance for the application of methods aimed at their mitigation. By means of both an automatic identification software and information theory, we study the main statistical properties of AO residuals and their dynamics. We therefore provide a speckle characterization that can be incorporated into numerical simulations to increase their realism and to optimize the performances of both real-time and postprocessing techniques aimed at the reduction of the speckle noise

Comprehensive Determination of the Hinode/EIS Roll Angle

We present a new coalignment method for the EUV Imaging Spectrometer (EIS) on board the Hinode spacecraft. In addition to the pointing offset and spacecraft jitter, this method determines the roll angle of the instrument, which has never been systematically measured, and is therefore usually not corrected. The optimal pointing for EIS is computed by maximizing the cross-correlations of the Fe XII 195.119 \r{A} line with images from the 193 \r{A} band of the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory (SDO). By coaligning 3336 rasters with high signal-to-noise ratio, we estimate the rotation angle between EIS and AIA and explore the distribution of its values. We report an average value of (-0.387 $\pm$ 0.007)\deg. We also provide a software implementation of this method that can be used to coalign any EIS raster.Comment: Accepted for publication in Solar Physics, 11 pages, 7 figure

K-Band Galaxy Counts in the South Galactic Pole Region

We present new K-band galaxy number counts from K=13 to 20.5 obtained from $K'$-band surveys in the south galactic pole region, which cover 180.8 arcmin$^2$ to a limiting magnitude of K=19, and 2.21 arcmin$^2$ to K=21. These are currently the most precise K-band galaxy counts at $17.5<K<19.0$ because the area of coverage is largest among the existing surveys for this magnitude range. The completeness and photometry corrections are estimated from the recovery of simulated galaxy and stellar profiles added to the obtained field image. Many simulations were carried out to construct a probability matrix which corrects the galaxy counts at the faint-end magnitudes of the surveys so the corrected counts can be compared with other observations. The K-band star counts in the south galactic pole region to $K=17.25$ are also presented for use to constrain the vertical structure of the Galaxy.Comment: accepted for publication in ApJ. 26 pages with 4 figures, and 2 plates are not included. All documents and figures can be retrieved from http://merope.mtk.nao.ac.jp/~minezaki/mine_paper.htm

A review of parallel computing for large-scale remote sensing image mosaicking

Interest in image mosaicking has been spurred by a wide variety of research and management needs. However, for large-scale applications, remote sensing image mosaicking usually requires significant computational capabilities. Several studies have attempted to apply parallel computing to improve image mosaicking algorithms and to speed up calculation process. The state of the art of this field has not yet been summarized, which is, however, essential for a better understanding and for further research of image mosaicking parallelism on a large scale. This paper provides a perspective on the current state of image mosaicking parallelization for large scale applications. We firstly introduce the motivation of image mosaicking parallel for large scale application, and analyze the difficulty and problem of parallel image mosaicking at large scale such as scheduling with huge number of dependent tasks, programming with multiple-step procedure, dealing with frequent I/O operation. Then we summarize the existing studies of parallel computing in image mosaicking for large scale applications with respect to problem decomposition and parallel strategy, parallel architecture, task schedule strategy and implementation of image mosaicking parallelization. Finally, the key problems and future potential research directions for image mosaicking are addressed

Efficient Bayesian-based Multi-View Deconvolution

Light sheet fluorescence microscopy is able to image large specimen with high resolution by imaging the sam- ples from multiple angles. Multi-view deconvolution can significantly improve the resolution and contrast of the images, but its application has been limited due to the large size of the datasets. Here we present a Bayesian- based derivation of multi-view deconvolution that drastically improves the convergence time and provide a fast implementation utilizing graphics hardware.Comment: 48 pages, 20 figures, 1 table, under review at Nature Method