39 research outputs found
Astronomy in the Cloud: Using MapReduce for Image Coaddition
In the coming decade, astronomical surveys of the sky will generate tens of
terabytes of images and detect hundreds of millions of sources every night. The
study of these sources will involve computation challenges such as anomaly
detection and classification, and moving object tracking. Since such studies
benefit from the highest quality data, methods such as image coaddition
(stacking) will be a critical preprocessing step prior to scientific
investigation. With a requirement that these images be analyzed on a nightly
basis to identify moving sources or transient objects, these data streams
present many computational challenges. Given the quantity of data involved, the
computational load of these problems can only be addressed by distributing the
workload over a large number of nodes. However, the high data throughput
demanded by these applications may present scalability challenges for certain
storage architectures. One scalable data-processing method that has emerged in
recent years is MapReduce, and in this paper we focus on its popular
open-source implementation called Hadoop. In the Hadoop framework, the data is
partitioned among storage attached directly to worker nodes, and the processing
workload is scheduled in parallel on the nodes that contain the required input
data. A further motivation for using Hadoop is that it allows us to exploit
cloud computing resources, e.g., Amazon's EC2. We report on our experience
implementing a scalable image-processing pipeline for the SDSS imaging database
using Hadoop. This multi-terabyte imaging dataset provides a good testbed for
algorithm development since its scope and structure approximate future surveys.
First, we describe MapReduce and how we adapted image coaddition to the
MapReduce framework. Then we describe a number of optimizations to our basic
approach and report experimental results comparing their performance.Comment: 31 pages, 11 figures, 2 table
Spurious Shear in Weak Lensing with LSST
The complete 10-year survey from the Large Synoptic Survey Telescope (LSST)
will image 20,000 square degrees of sky in six filter bands every few
nights, bringing the final survey depth to , with over 4 billion
well measured galaxies. To take full advantage of this unprecedented
statistical power, the systematic errors associated with weak lensing
measurements need to be controlled to a level similar to the statistical
errors.
This work is the first attempt to quantitatively estimate the absolute level
and statistical properties of the systematic errors on weak lensing shear
measurements due to the most important physical effects in the LSST system via
high fidelity ray-tracing simulations. We identify and isolate the different
sources of algorithm-independent, \textit{additive} systematic errors on shear
measurements for LSST and predict their impact on the final cosmic shear
measurements using conventional weak lensing analysis techniques. We find that
the main source of the errors comes from an inability to adequately
characterise the atmospheric point spread function (PSF) due to its high
frequency spatial variation on angular scales smaller than in the
single short exposures, which propagates into a spurious shear correlation
function at the -- level on these scales. With the large
multi-epoch dataset that will be acquired by LSST, the stochastic errors
average out, bringing the final spurious shear correlation function to a level
very close to the statistical errors. Our results imply that the cosmological
constraints from LSST will not be severely limited by these
algorithm-independent, additive systematic effects.Comment: 22 pages, 12 figures, accepted by MNRA
Recommended from our members
The LSST DESC data challenge 1: Generation and analysis of synthetic images for next-generation surveys
Data Challenge 1 (DC1) is the first synthetic data set produced by the Rubin Observatory Legacy Survey of Space and Time (LSST) Dark Energy Science Collaboration (DESC). DC1 is designed to develop and validate data reduction and analysis and to study the impact of systematic effects that will affect the LSST data set. DC1 is comprised of r-band observations of 40 deg2 to 10 yr LSST depth. We present each stage of the simulation and analysis process: (a) generation, by synthesizing sources from cosmological N-body simulations in individual sensor-visit images with different observing conditions; (b) reduction using a development version of the LSST Science Pipelines; and (c) matching to the input cosmological catalogue for validation and testing. We verify that testable LSST requirements pass within the fidelity of DC1. We establish a selection procedure that produces a sufficiently clean extragalactic sample for clustering analyses and we discuss residual sample contamination, including contributions from inefficiency in star-galaxy separation and imperfect deblending. We compute the galaxy power spectrum on the simulated field and conclude that: (i) survey properties have an impact of 50 per cent of the statistical uncertainty for the scales and models used in DC1; (ii) a selection to eliminate artefacts in the catalogues is necessary to avoid biases in the measured clustering; and (iii) the presence of bright objects has a significant impact (2-6) in the estimated power spectra at small scales (> 1200), highlighting the impact of blending in studies at small angular scales in LSST
Software Architecture and System Design of Rubin Observatory
Starting from a description of the Rubin Observatory Data Management System
Architecture, and drawing on our experience with and involvement in a range of
other projects including Gaia, SDSS, UKIRT, and JCMT, we derive a series of
generic design patterns and lessons learned.Comment: 10 pages ADASS XXXII submissio
Probing Spectroscopic Variability of Galaxies & Narrow-Line Active Galactic Nuclei in the Sloan Digital Sky Survey
Under the unified model for active galactic nuclei (AGNs), narrow-line (Type
2) AGNs are, in fact, broad-line (Type 1) AGNs but each with a heavily obscured
accretion disk. We would therefore expect the optical continuum emission from
Type 2 AGN to be composed mainly of stellar light and non-variable on the
time-scales of months to years. In this work we probe the spectroscopic
variability of galaxies and narrow-line AGNs using the multi-epoch data in the
Sloan Digital Sky Survey (SDSS) Data Release 6. The sample contains 18,435
sources for which there exist pairs of spectroscopic observations (with a
maximum separation in time of ~700 days) covering a wavelength range of
3900-8900 angstrom. To obtain a reliable repeatability measurement between each
spectral pair, we consider a number of techniques for spectrophotometric
calibration resulting in an improved spectrophotometric calibration of a factor
of two. From these data we find no obvious continuum and emission-line
variability in the narrow-line AGNs on average -- the spectroscopic variability
of the continuum is 0.07+/-0.26 mag in the g band and, for the emission-line
ratios log10([NII]/Halpha) and log10([OIII]/Hbeta), the variability is
0.02+/-0.03 dex and 0.06+/-0.08 dex, respectively. From the continuum
variability measurement we set an upper limit on the ratio between the flux of
varying spectral component, presumably related to AGN activities, and that of
host galaxy to be ~30%. We provide the corresponding upper limits for other
spectral classes, including those from the BPT diagram, eClass galaxy
classification, stars and quasars.Comment: AJ accepte
LSST Science Book, Version 2.0
A survey that can cover the sky in optical bands over wide fields to faint
magnitudes with a fast cadence will enable many of the exciting science
opportunities of the next decade. The Large Synoptic Survey Telescope (LSST)
will have an effective aperture of 6.7 meters and an imaging camera with field
of view of 9.6 deg^2, and will be devoted to a ten-year imaging survey over
20,000 deg^2 south of +15 deg. Each pointing will be imaged 2000 times with
fifteen second exposures in six broad bands from 0.35 to 1.1 microns, to a
total point-source depth of r~27.5. The LSST Science Book describes the basic
parameters of the LSST hardware, software, and observing plans. The book
discusses educational and outreach opportunities, then goes on to describe a
broad range of science that LSST will revolutionize: mapping the inner and
outer Solar System, stellar populations in the Milky Way and nearby galaxies,
the structure of the Milky Way disk and halo and other objects in the Local
Volume, transient and variable objects both at low and high redshift, and the
properties of normal and active galaxies at low and high redshift. It then
turns to far-field cosmological topics, exploring properties of supernovae to
z~1, strong and weak lensing, the large-scale distribution of galaxies and
baryon oscillations, and how these different probes may be combined to
constrain cosmological models and the physics of dark energy.Comment: 596 pages. Also available at full resolution at
http://www.lsst.org/lsst/sciboo
Recommended from our members
Spurious Shear in Weak Lensing with LSST
The complete 10-year survey from the Large Synoptic Survey Telescope (LSST) will image {approx} 20,000 square degrees of sky in six filter bands every few nights, bringing the final survey depth to r {approx} 27.5, with over 4 billion well measured galaxies. To take full advantage of this unprecedented statistical power, the systematic errors associated with weak lensing measurements need to be controlled to a level similar to the statistical errors. This work is the first attempt to quantitatively estimate the absolute level and statistical properties of the systematic errors on weak lensing shear measurements due to the most important physical effects in the LSST system via high fidelity ray-tracing simulations. We identify and isolate the different sources of algorithm-independent, additive systematic errors on shear measurements for LSST and predict their impact on the final cosmic shear measurements using conventional weak lensing analysis techniques. We find that the main source of the errors comes from an inability to adequately characterise the atmospheric point spread function (PSF) due to its high frequency spatial variation on angular scales smaller than {approx} 10{prime} in the single short exposures, which propagates into a spurious shear correlation function at the 10{sup -4}-10{sup -3} level on these scales. With the large multi-epoch dataset that will be acquired by LSST, the stochastic errors average out, bringing the final spurious shear correlation function to a level very close to the statistical errors. Our results imply that the cosmological constraints from LSST will not be severely limited by these algorithm-independent, additive systematic effects
LSST: from Science Drivers to Reference Design and Anticipated Data Products
(Abridged) We describe here the most ambitious survey currently planned in
the optical, the Large Synoptic Survey Telescope (LSST). A vast array of
science will be enabled by a single wide-deep-fast sky survey, and LSST will
have unique survey capability in the faint time domain. The LSST design is
driven by four main science themes: probing dark energy and dark matter, taking
an inventory of the Solar System, exploring the transient optical sky, and
mapping the Milky Way. LSST will be a wide-field ground-based system sited at
Cerro Pach\'{o}n in northern Chile. The telescope will have an 8.4 m (6.5 m
effective) primary mirror, a 9.6 deg field of view, and a 3.2 Gigapixel
camera. The standard observing sequence will consist of pairs of 15-second
exposures in a given field, with two such visits in each pointing in a given
night. With these repeats, the LSST system is capable of imaging about 10,000
square degrees of sky in a single filter in three nights. The typical 5
point-source depth in a single visit in will be (AB). The
project is in the construction phase and will begin regular survey operations
by 2022. The survey area will be contained within 30,000 deg with
, and will be imaged multiple times in six bands, ,
covering the wavelength range 320--1050 nm. About 90\% of the observing time
will be devoted to a deep-wide-fast survey mode which will uniformly observe a
18,000 deg region about 800 times (summed over all six bands) during the
anticipated 10 years of operations, and yield a coadded map to . The
remaining 10\% of the observing time will be allocated to projects such as a
Very Deep and Fast time domain survey. The goal is to make LSST data products,
including a relational database of about 32 trillion observations of 40 billion
objects, available to the public and scientists around the world.Comment: 57 pages, 32 color figures, version with high-resolution figures
available from https://www.lsst.org/overvie
The Baryon Oscillation Spectroscopic Survey of SDSS-III
The Baryon Oscillation Spectroscopic Survey (BOSS) is designed to measure the
scale of baryon acoustic oscillations (BAO) in the clustering of matter over a
larger volume than the combined efforts of all previous spectroscopic surveys
of large scale structure. BOSS uses 1.5 million luminous galaxies as faint as
i=19.9 over 10,000 square degrees to measure BAO to redshifts z<0.7.
Observations of neutral hydrogen in the Lyman alpha forest in more than 150,000
quasar spectra (g<22) will constrain BAO over the redshift range 2.15<z<3.5.
Early results from BOSS include the first detection of the large-scale
three-dimensional clustering of the Lyman alpha forest and a strong detection
from the Data Release 9 data set of the BAO in the clustering of massive
galaxies at an effective redshift z = 0.57. We project that BOSS will yield
measurements of the angular diameter distance D_A to an accuracy of 1.0% at
redshifts z=0.3 and z=0.57 and measurements of H(z) to 1.8% and 1.7% at the
same redshifts. Forecasts for Lyman alpha forest constraints predict a
measurement of an overall dilation factor that scales the highly degenerate
D_A(z) and H^{-1}(z) parameters to an accuracy of 1.9% at z~2.5 when the survey
is complete. Here, we provide an overview of the selection of spectroscopic
targets, planning of observations, and analysis of data and data quality of
BOSS.Comment: 49 pages, 16 figures, accepted by A