J. R. Peterson

Deep high-resolution X-ray spectra from cool-core clusters

We examine deep XMM-Newton Reflection Grating Spectrometer (RGS) spectra from the cores of three X-ray bright cool-core galaxy clusters, Abell 262, Abell 3581 and HCG 62. Each of the RGS spectra shows Fe XVII emission lines indicating the presence of gas around 0.5 keV. There is no evidence for O VII emission which would imply gas at still cooler temperatures. The range in detected gas temperature in these objects is a factor of 3.7, 5.6 and 2 for Abell 262, Abell 3581 and HCG 62, respectively. The coolest detected gas only has a volume filling fraction of 6 and 3 per cent for Abell 262 and Abell 3581, but is likely to be volume filling in HCG 62. Chandra spatially resolved spectroscopy confirms the low volume filling fractions of the cool gas in Abell 262 and Abell 3581, indicating this cool gas exists as cold blobs. Any volume heating mechanism aiming to prevent cooling would overheat the surroundings of the cool gas by a factor of 4. If the gas is radiatively cooling below 0.5 keV, it is cooling at a rate at least an order of magnitude below that at higher temperatures in Abell 262 and Abell 3581 and two orders of magnitude lower in HCG 62. The gas may be cooling non-radiatively through mixing in these cool blobs, where the energy released by cooling is emitted in the infrared. We find very good agreement between smooth particle inference modelling of the cluster and conventional spectral fitting. Comparing the temperature distribution from this analysis with that expected in a cooling flow, there appears to be an even larger break below 0.5 keV as compared with previous empirical descriptions of the deviations of cooling flow models.

THE THIRD GRAVITATIONAL LENSING ACCURACY TESTING (GREAT3) CHALLENGE HANDBOOK

The GRavitational lEnsing Accuracy Testing 3 (GREAT3) challenge is the third in a series of image analysis challenges, with a goal of testing and facilitating the development of methods for analyzing astronomical images that will be used to measure weak gravitational lensing. This measurement requires extremely precise estimation of very small galaxy shape distortions, in the presence of far larger intrinsic galaxy shapes and distortions due to the blurring kernel caused by the atmosphere, telescope optics, and instrumental effects. The GREAT3 challenge is posed to the astronomy, machine learning, and statistics communities, and includes tests of three specific effects that are of immediate relevance to upcoming weak lensing surveys, two of which have never been tested in a community challenge before. These effects include many novel aspects including realistically complex galaxy models based on high-resolution imaging from space; a spatially varying, physically motivated blurring kernel; and a combination of multiple different exposures. To facilitate entry by people new to the field, and for use as a diagnostic tool, the simulation software for the challenge is publicly available, though the exact parameters used for the challenge are blinded. Sample scripts to analyze the challenge data using existing methods will also be provided. See http://great3challenge.info and http://great3.projects.phys.ucl.ac.uk/leaderboard/ for more information.

CHARACTERIZING THE PROPERTIES OF CLUSTERS OF GALAXIES AS A FUNCTION OF LUMINOSITY AND REDSHIFT

We report the application of the new Monte Carlo method, smoothed particle inference (SPI, described in a pair of companion papers), toward analysis and interpretation of X-ray observations of clusters of galaxies with the XMM-Newton satellite. Our sample consists of publicly available well exposed observations of clusters at redshifts z> 0.069, totaling 101 objects. We determine the luminosity and temperature structure of the X-ray emitting gas, with the goal to quantify the scatter and the evolution of the LX–T relation, as well as to investigate the dependence on cluster substructure with redshift. This work is important for the establishment of the potential robustness of mass estimates from X-ray data which in turn is essential toward the use of clusters for measurements of cosmological parameters. We use the luminosity and temperature maps derived via the SPI technique to determine the presence of cooling cores, via measurements of luminosity and temperature contrast. The LX–T relation is investigated, and we confirm that LX ∝ T 3 . We find a weak redshift dependence (∝ (1 + z) β LT ,β LT = 0.50 ± 0.34), in contrast to some Chandra results. The level of dynamical activity is established using the “power ratio” method, and we compare our results to previous application of this method to Chandra data for clusters. We find signs of evolution in the P3/P0 power ratio. A new method, the “temperature two-point correlation function,” is proposed. This method is used to determine the “power spectrum” of temperature fluctuations in the X-ray emitting gas as a function of spatial scale. We show how this method can be fruitfully used to identify cooling core clusters as well as those with disturbed structures, presumably due to ongoing or recent merger activity.

SIMULATION OF ASTRONOMICAL IMAGES FROM OPTICAL SURVEY TELESCOPES USING A COMPREHENSIVE PHOTON MONTE CARLO APPROACH

We present a comprehensive methodology for the simulation of astronomical images from optical survey telescopes. We use a photon Monte Carlo approach to construct images by sampling photons from models of astronomical source populations, and then simulating those photons through the system as they interact with the atmosphere, telescope, and camera. We demonstrate that all physical effects for optical light that determine the shapes, locations, and brightnesses of individual stars and galaxies can be accurately represented in this formalism. By using large scale grid computing, modern processors, and an efficient implementation that can produce 400,000 photons/second, we demonstrate that even very large optical surveys can be now be simulated. We demonstrate that we are able to: 1) construct kilometer scale phase screens necessary for wide-field telescopes, 2) reproduce atmospheric point-spread-function moments using a fast novel hybrid geometric/Fourier technique for non-diffraction limited telescopes, 3) accurately reproduce the expected spot diagrams for complex aspheric optical designs, and 4) recover system effective area predicted from analytic photometry integrals. This new code, the photon simulator (PhoSim), is publicly available. We have implemented the Large Synoptic Survey Telescope (LSST) design, and it can be extended to other telescopes. We expect that because of the comprehensive physics implemented in PhoSim, it will be used by the community to plan future observations, interpret detailed existing observations, and quantify systematics related to various astronomical measurements. Future development and validation by comparisons with real data will continue to improve the fidelity and usability of the code.

Spurious shear in weak lensing with the large synoptic survey telescope

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.

EFFECT OF MEASUREMENT ERRORS ON PREDICTED COSMOLOGICAL CONSTRAINTS FROM SHEAR PEAK STATISTICS WITH LARGE SYNOPTIC SURVEY TELESCOPE

We study the effect of galaxy shape measurement errors on predicted cosmological constraints from the statistics of shear peak counts with the Large Synoptic Survey Telescope (LSST). We use the LSST Image Simulator in combination with cosmological N-body simulations to model realistic shear maps for different cosmological models. We include both galaxy shape noise and, for the first time, measurement errors on galaxy shapes. We find that the measurement errors considered have relatively little impact on the constraining power of shear peak counts for LSST.

Simulating the LSST system

Extracting science from the LSST data stream requires a detailed knowledge of the properties of the LSST catalogs and images (from their detection limits to the accuracy of the calibration to how well galaxy shapes can be characterized). These properties will depend on many of the LSST components including the design of the telescope, the conditions under which the data are taken and the overall survey strategy. To understand how these components impact the nature of the LSST data the simulations group is developing a framework for high fidelity simulations that scale to the volume of data expected from the LSST. This framework comprises galaxy, stellar and solar system catalogs designed to match the depths and properties of the LSST (to r=28), transient and moving sources, and image simulations that ray-trace the photons from above the atmosphere through the optics and to the camera. We describe here the state of the current simulation framework and its computational challenges.

An end-to-end simulation framework for the Large Synoptic Survey Telescope

The LSST will, over a 10-year period, produce a multi-color, multi-epoch survey of more than 18000 square degrees of the southern sky. It will generate a multi-petabyte archive of images and catalogs of astrophysical sources from which a wide variety of high-precision statistical studies can be undertaken. To accomplish these goals, the LSST project has developed a suite of modeling and simulation tools for use in validating that the design and the as-delivered components of the LSST system will yield data products with the required statistical properties. In this paper we describe the development, and use of the LSST simulation framework, including the generation of simulated catalogs and images for targeted trade studies, simulations of the observing cadence of the LSST, the creation of large-scale simulations that test the procedures for data calibration, and use of end-to-end image simulations to evaluate the performance of the system as a whole.

An integrated modeling framework for the Large Synoptic Survey Telescope (LSST)

All of the components of the LSST subsystems (Telescope and Site, Camera, and Data Management) are in production. The major systems engineering challenges in this early construction phase are establishing the final technical details of the observatory, and properly evaluating potential deviations from requirements due to financial or technical constraints emerging from the detailed design and manufacturing process. To meet these challenges, the LSST Project Systems Engineering team established an Integrated Modeling (IM) framework including (i) a high fidelity optical model of the observatory, (ii) an atmospheric aberration model, and (ii) perturbation interfaces capable of accounting for quasi static and dynamic variations of the optical train. The model supports the evaluation of three key LSST Measures of Performance: image quality, ellipticity, and their impact on image depth. The various feedback loops improving image quality are also included. The paper shows application examples, as an update to the estimated performance of the Active Optics System, the determination of deployment parameters for the wavefront sensors, the optical evaluation of the final M1M3 surface quality, and the feasibility of satisfying the settling time requirement for the telescope structure.

EVIDENCE FOR NONLINEAR GROWTH OF STRUCTURE FROM AN X-RAY-SELECTED CLUSTER SURVEY USING A NOVEL JOINT ANALYSIS OF THE CHANDRA AND XMM-NEWTON ARCHIVES

We present a large X-ray-selected serendipitous cluster survey based on a novel joint analysis of archival Chandra and XMM-Newton data. The survey provides enough depth to reach clusters of flux of ≈10–14ergcm–2s–1 near z≈ 1 and simultaneously a large-enough sample to find evidence for the strong evolution of clusters expected from structure formation theory. We detected a total of 723 clusters of which 462 are newly discovered clusters with greater than 6σ significance. In addition, we also detect and measure 261 previously known clusters and groups that can be used to calibrate the survey. The survey exploits a technique that combines the exquisite Chandra imaging quality with the high throughput of the XMM-Newton telescopes using overlapping survey regions. A large fraction of the contamination from active galactic nucleus point sources is mitigated by using this technique. This results in a higher sensitivity for finding clusters of galaxies with relatively few photons and a large part of our survey has a flux sensitivity between 10–14 and 10–15ergcm–2s–1. The survey covers 41.2 deg2 of overlapping Chandra and XMM-Newton fields and 122.2 deg2 of non-overlapping Chandra data. We measure the log N-log S distribution and fit it with a redshift-dependent model characterized by a luminosity distribution proportional to . We find z 0 to be in the range 0.7-1.3, indicative of rapid cluster evolution, as expected for cosmic structure formation using parameters appropriate to the concordance cosmological model. Confirmation of our cluster detection efficiency through optical follow-up studies currently in progress will help to strengthen this conclusion and eventually allow to use these data to derive tight constraints on cosmological parameters.