Optimal Compression of Floating-point Astronomical Images Without Significant Loss of Information

We describe a compression method for floating-point astronomical images that gives compression ratios of 6 -- 10 while still preserving the scientifically important information in the image. The pixel values are first preprocessed by quantizing them into scaled integer intensity levels, which removes some of the uncompressible noise in the image. The integers are then losslessly compressed using the fast and efficient Rice algorithm and stored in a portable FITS format file. Quantizing an image more coarsely gives greater image compression, but it also increases the noise and degrades the precision of the photometric and astrometric measurements in the quantized image. Dithering the pixel values during the quantization process can greatly improve the precision of measurements in the images. This is especially important if the analysis algorithm relies on the mode or the median which would be similarly quantized if the pixel values are not dithered. We perform a series of experiments on both synthetic and real astronomical CCD images to quantitatively demonstrate that the magnitudes and positions of stars in the quantized images can be measured with the predicted amount of precision. In order to encourage wider use of these image compression methods, we have made available a pair of general-purpose image compression programs, called fpack and funpack, which can be used to compress any FITS format image.Comment: Accepted PAS

Lossless Astronomical Image Compression and the Effects of Noise

We compare a variety of lossless image compression methods on a large sample of astronomical images and show how the compression ratios and speeds of the algorithms are affected by the amount of noise in the images. In the ideal case where the image pixel values have a random Gaussian distribution, the equivalent number of uncompressible noise bits per pixel is given by Nbits =log2(sigma * sqrt(12)) and the lossless compression ratio is given by R = BITPIX / Nbits + K where BITPIX is the bit length of the pixel values and K is a measure of the efficiency of the compression algorithm. We perform image compression tests on a large sample of integer astronomical CCD images using the GZIP compression program and using a newer FITS tiled-image compression method that currently supports 4 compression algorithms: Rice, Hcompress, PLIO, and GZIP. Overall, the Rice compression algorithm strikes the best balance of compression and computational efficiency; it is 2--3 times faster and produces about 1.4 times greater compression than GZIP. The Rice algorithm produces 75%--90% (depending on the amount of noise in the image) as much compression as an ideal algorithm with K = 0. The image compression and uncompression utility programs used in this study (called fpack and funpack) are publicly available from the HEASARC web site. A simple command-line interface may be used to compress or uncompress any FITS image file.Comment: 20 pages, 9 figures, to be published in PAS

The Future is Hera! Analyzing Astronomical Over the Internet

Hera is the data processing facility provided by the High Energy Astrophysics Science Archive Research Center (HEASARC) at the NASA Goddard Space Flight Center for analyzing astronomical data. Hera provides all the pre-installed software packages, local disk space, and computing resources need to do general processing of FITS format data files residing on the users local computer, and to do research using the publicly available data from the High ENergy Astrophysics Division. Qualified students, educators and researchers may freely use the Hera services over the internet of research and educational purposes

Feasibility and performances of compressed-sensing and sparse map-making with Herschel/PACS data

The Herschel Space Observatory of ESA was launched in May 2009 and is in operation since. From its distant orbit around L2 it needs to transmit a huge quantity of information through a very limited bandwidth. This is especially true for the PACS imaging camera which needs to compress its data far more than what can be achieved with lossless compression. This is currently solved by including lossy averaging and rounding steps on board. Recently, a new theory called compressed-sensing emerged from the statistics community. This theory makes use of the sparsity of natural (or astrophysical) images to optimize the acquisition scheme of the data needed to estimate those images. Thus, it can lead to high compression factors. A previous article by Bobin et al. (2008) showed how the new theory could be applied to simulated Herschel/PACS data to solve the compression requirement of the instrument. In this article, we show that compressed-sensing theory can indeed be successfully applied to actual Herschel/PACS data and give significant improvements over the standard pipeline. In order to fully use the redundancy present in the data, we perform full sky map estimation and decompression at the same time, which cannot be done in most other compression methods. We also demonstrate that the various artifacts affecting the data (pink noise, glitches, whose behavior is a priori not well compatible with compressed-sensing) can be handled as well in this new framework. Finally, we make a comparison between the methods from the compressed-sensing scheme and data acquired with the standard compression scheme. We discuss improvements that can be made on ground for the creation of sky maps from the data.Comment: 11 pages, 6 figures, 5 tables, peer-reviewed articl

Evidence That the P\u3csub\u3ei\u3c/sub\u3e Release Event Is the Rate-Limiting Step in the Nitrogenase Catalytic Cycle

Nitrogenase reduction of dinitrogen (N2) to ammonia (NH3) involves a sequence of events that occur upon the transient association of the reduced Fe protein containing two ATP molecules with the MoFe protein that includes electron transfer, ATP hydrolysis, Pi release, and dissociation of the oxidized, ADP-containing Fe protein from the reduced MoFe protein. Numerous kinetic studies using the nonphysiological electron donor dithionite have suggested that the rate-limiting step in this reaction cycle is the dissociation of the Fe protein from the MoFe protein. Here, we have established the rate constants for each of the key steps in the catalytic cycle using the physiological reductant flavodoxin protein in its hydroquinone state. The findings indicate that with this reductant, the rate-limiting step in the reaction cycle is not protein–protein dissociation or reduction of the oxidized Fe protein, but rather events associated with the Pi release step. Further, it is demonstrated that (i) Fe protein transfers only one electron to MoFe protein in each Fe protein cycle coupled with hydrolysis of two ATP molecules, (ii) the oxidized Fe protein is not reduced when bound to MoFe protein, and (iii) the Fe protein interacts with flavodoxin using the same binding interface that is used with the MoFe protein. These findings allow a revision of the rate-limiting step in the nitrogenase Fe protein cycle

Chandra Observation of Luminous and Ultraluminous X-ray Binaries in M101

X-ray binaries in the Milky Way are among the brightest objects on the X-ray sky. With the increasing sensitivity of recent missions, it is now possible to study X-ray binaries in nearby galaxies. We present data on six luminous sources in the nearby spiral galaxy, M101, obtained with the Chandra ACIS-S. Of these, five appear to be similar to ultraluminous sources in other galaxies, while the brightest source, P098, shows some unique characteristics. We present our interpretation of the data in terms of an optically thick outflow, and discuss implications.Comment: Accepted for publication in Astrophysical Journal (16 pages including 4 figures

Cognitive Phenotypes and the Evolution of Animal Decisions

Despite the clear fitness consequences of animal decisions, the science of animal decision making in evolutionary biology is underdeveloped compared with decision science in human psychology. Specifically, the field lacks a conceptual framework that defines and describes the relevant components of a decision, leading to imprecise language and concepts. The ‘judgment and decision-making’ (JDM) framework in human psychology is a powerful tool for framing and understanding human decisions, and we apply it here to components of animal decisions, which we refer to as ‘cognitive phenotypes’. We distinguish multiple cognitive phenotypes in the context of a JDM framework and highlight empirical approaches to characterize them as evolvable traits

Cognitive Phenotypes and the Evolution of Animal Decisions

Despite the clear fitness consequences of animal decisions, the science of animal decision making in evolutionary biology is underdeveloped compared with decision science in human psychology. Specifically, the field lacks a conceptual framework that defines and describes the relevant components of a decision, leading to imprecise language and concepts. The ‘judgment and decision-making’ (JDM) framework in human psychology is a powerful tool for framing and understanding human decisions, and we apply it here to components of animal decisions, which we refer to as ‘cognitive phenotypes’. We distinguish multiple cognitive phenotypes in the context of a JDM framework and highlight empirical approaches to characterize them as evolvable traits

A multi-coloured survey of NGC 253 with XMM-Newton: testing the methods used for creating luminosity functions from low-count data

NGC 253 is a local, star-bursting spiral galaxy with strong X-ray emission from hot gas, as well as many point sources. We have conducted a spectral survey of the X-ray population of NGC 253 using a deep XMM-Newton observation.NGC 253 only accounts for ~20% of the XMM-Newton EPIC field of view, allowing us to identify ~100 X-ray sources that are unlikely to be associated with NGC\thinspace 253. Hence we were able to make a direct estimate of contamination from e.g. foreground stars and background galaxies. X-ray luminosity functions (XLFs) of galaxy populations are often used to characterise their properties. There are several methods for estimating the luminosities of X-ray sources with few photons. We have obtained spectral fits for the brightest 140 sources in the 2003 XMM-Newton observation of NGC 253, and compare the best fit luminosities of those 69 non-nuclear sources associated with NGC 253 with luminosities derived using other methods. We find the luminosities obtained from these various methods to vary systematically by a factor of up to three for the same data; this is largely due to differences in absorption. We therefore conclude that assuming Galactic absorption is probably unwise; rather, one should measure the absorption for the population. A remarkable correlation has been reported between the XLFs of galaxies and their star formation rates. However, the XLFs used in that study were obtained using several different methods. If the sample galaxies were revisited and a single method were applied, then this correlation may become stronger still.Comment: Accepted for publication in the Monthly Notices of the Royal Astronomical Society (MNRAS). 17 pages, 7 figure