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Gravitational lensing has become one of the most powerful tools available for investigating the 'dark side' of the universe. Cosmological strong gravitational lensing, in particular, probes the properties of the dense cores of dark matter halos over decades in mass and offers the opportunity to study the distant universe at flux levels and spatial resolutions otherwise unavailable. Studies of strongly-lensed variable sources offer yet further scientific opportunities. One of the challenges in realizing the potential of strong lensing is to understand the statistical context of both the individual systems that receive extensive follow-up study, as well as that of the larger samples of strong lenses that are now emerging from survey efforts. Motivated by these challenges, we have developed an image-simulation pipeline, PICS (Pipeline for Images of Cosmological Strong lensing) to generate realistic strong gravitational lensing signals from group and cluster scale lenses. PICS uses a low-noise and unbiased density estimator based on (resampled) Delaunay Tessellations to calculate the density field; lensed images are produced by ray-tracing images of actual galaxies from deep Hubble Space Telescope observations. Other galaxies, similarly sampled, are added to fill in the light cone. The pipeline further adds cluster-member galaxies and foreground stars into the lensed images. The entire image ensemble is then observed using a realistic point spread function which includes appropriate detector artifacts for bright stars. Noise is further added, including such non-Gaussian elements as noise window-paning from mosaiced observations, residual bad pixels, and cosmic rays. The aim is to produced simulated images that appear identical - to the eye (expert or otherwise) - to real observations in various imaging surveys., Comment: 20 pages, 13 figures, published

Current and future surveys of large-scale cosmic structure are associated with a massive and complex datastream to study, characterize, and ultimately understand the physics behind the two major components of the 'Dark Universe', dark energy and dark matter. In addition, the surveys also probe primordial perturbations and carry out fundamental measurements, such as determining the sum of neutrino masses. Large-scale simulations of structure formation in the Universe play a critical role in the interpretation of the data and extraction of the physics of interest. Just as survey instruments continue to grow in size and complexity, so do the supercomputers that enable these simulations. Here we report on HACC (Hardware/Hybrid Accelerated Cosmology Code), a recently developed and evolving cosmology N-body code framework, designed to run efficiently on diverse computing architectures and to scale to millions of cores and beyond. HACC can run on all current supercomputer architectures and supports a variety of programming models and algorithms. It has been demonstrated at scale on Cell- and GPU-accelerated systems, standard multi-core node clusters, and Blue Gene systems. HACC's design allows for ease of portability, and at the same time, high levels of sustained performance on the fastest supercomputers available. We present a description of the design philosophy of HACC, the underlying algorithms and code structure, and outline implementation details for several specific architectures. We show selected accuracy and performance results from some of the largest high resolution cosmological simulations so far performed, including benchmarks evolving more than 3.6 trillion particles., Comment: 23 pages, 20 figures

Remarkable observational advances have established a compelling cross-validated model of the Universe. Yet, two key pillars of this model -- dark matter and dark energy -- remain mysterious. Sky surveys that map billions of galaxies to explore the `Dark Universe', demand a corresponding extreme-scale simulation capability; the HACC (Hybrid/Hardware Accelerated Cosmology Code) framework has been designed to deliver this level of performance now, and into the future. With its novel algorithmic structure, HACC allows flexible tuning across diverse architectures, including accelerated and multi-core systems. On the IBM BG/Q, HACC attains unprecedented scalable performance -- currently 13.94 PFlops at 69.2% of peak and 90% parallel efficiency on 1,572,864 cores with an equal number of MPI ranks, and a concurrency of 6.3 million. This level of performance was achieved at extreme problem sizes, including a benchmark run with more than 3.6 trillion particles, significantly larger than any cosmological simulation yet performed., Comment: 11 pages, 11 figures, final version of paper for talk presented at SC12

[abridged] We present a detailed comparison of fundamental dark matter halo properties retrieved by a substantial number of different halo finders. These codes span a wide range of techniques including friends-of-friends (FOF), spherical-overdensity (SO) and phase-space based algorithms. We further introduce a robust (and publicly available) suite of test scenarios that allows halo finder developers to compare the performance of their codes against those presented here. This set includes mock haloes containing various levels and distributions of substructure at a range of resolutions as well as a cosmological simulation of the large-scale structure of the universe. All the halo finding codes tested could successfully recover the spatial location of our mock haloes. They further returned lists of particles (potentially) belonging to the object that led to coinciding values for the maximum of the circular velocity profile and the radius where it is reached. All the finders based in configuration space struggled to recover substructure that was located close to the centre of the host halo and the radial dependence of the mass recovered varies from finder to finder. Those finders based in phase space could resolve central substructure although they found difficulties in accurately recovering its properties. Via a resolution study we found that most of the finders could not reliably recover substructure containing fewer than 30-40 particles. However, also here the phase space finders excelled by resolving substructure down to 10-20 particles. By comparing the halo finders using a high resolution cosmological volume we found that they agree remarkably well on fundamental properties of astrophysical significance (e.g. mass, position, velocity, and peak of the rotation curve)., Comment: 27 interesting pages, 20 beautiful figures, and 4 informative tables accepted for publication in MNRAS. The high-resolution version of the paper as well as all the test cases and analysis can be found at the web site http://popia.ft.uam.es/HaloesGoingMAD

The advent of large cosmological sky surveys - ushering in the era of precision cosmology - has been accompanied by ever larger cosmological simulations. The analysis of these simulations, which currently encompass tens of billions of particles and up to trillion particles in the near future, is often as daunting as carrying out the simulations in the first place. Therefore, the development of very efficient analysis tools combining qualitative and quantitative capabilities is a matter of some urgency. In this paper we introduce new analysis features implemented within ParaView, a parallel, open-source visualization toolkit, to analyze large N-body simulations. The new features include particle readers and a very efficient halo finder which identifies friends-of-friends halos and determines common halo properties. In combination with many other functionalities already existing within ParaView, such as histogram routines or interfaces to Python, this enhanced version enables fast, interactive, and convenient analyses of large cosmological simulations. In addition, development paths are available for future extensions., Comment: 9 pages, 8 figures

We present a set of ultra-large particle-mesh simulations of the LyA forest targeted at understanding the imprint of baryon acoustic oscillations (BAO) in the inter-galactic medium. We use 9 dark matter only simulations which can, for the first time, simultaneously resolve the Jeans scale of the intergalactic gas while covering the large volumes required to adequately sample the acoustic feature. Mock absorption spectra are generated using the fluctuating Gunn-Peterson approximation which have approximately correct flux probability density functions (PDFs) and small-scale power spectra. On larger scales there is clear evidence in the redshift space correlation function for an acoustic feature, which matches a linear theory template with constant bias. These spectra, which we make publicly available, can be used to test pipelines, plan future experiments and model various physical effects. As an illustration we discuss the basic properties of the acoustic signal in the forest, the scaling of errors with noise and source number density, modified statistics to treat mean flux evolution and misestimation, and non-gravitational sources such as fluctuations in the photo-ionizing background and temperature fluctuations due to HeII reionization., Comment: 11 pages, 10 figures, minor changes to address referee report

Current and upcoming cosmological observations allow us to probe structures on smaller and smaller scales, entering highly nonlinear regimes. In order to obtain theoretical predictions in these regimes, large cosmological simulations have to be carried out. The promised high accuracy from observations make the simulation task very demanding: the simulations have to be at least as accurate as the observations. This requirement can only be fulfilled by carrying out an extensive code validation program. The first step of such a program is the comparison of different cosmology codes including gravitation interactions only. In this paper we extend a recently carried out code comparison project to include five more simulation codes. We restrict our analysis to a small cosmological volume which allows us to investigate properties of halos. For the matter power spectrum and the mass function, the previous results hold, with the codes agreeing at the 10% level over wide dynamic ranges. We extend our analysis to the comparison of halo profiles and investigate the halo count as a function of local density. We introduce and discuss ParaView as a flexible analysis tool for cosmological simulations, the use of which immensely simplifies the code comparison task., Comment: 28 pages, 14 figures