The turbulent pressure support in galaxy clusters revisited

Due to their late formation in cosmic history, clusters of galaxies are not fully in hydrostatic equilibrium and the gravitational pull of their mass at a given radius is expected not to be entirely balanced by the thermal gas pressure. Turbulence may supply additional pressure, and recent (X-ray and SZ) hydrostatic mass reconstructions claim a pressure support of $\sim 5-15\%$ of the total pressure at $R_{\rm 200}$. In this work we show that, after carefully disentangling bulk from small-scale turbulent motions in high-resolution simulations of galaxy clusters, we can constrain which fraction of the gas kinetic energy effectively provides pressure support in the cluster's gravitational potential. While the ubiquitous presence of radial inflows in the cluster can lead to significant bias in the estimate of the non-thermal pressure support, we report that only a part of this energy effectively acts as a source of pressure, providing a support of the order of $\sim 10\%$ of the total pressure at $R_{\rm 200}$.Comment: 5 pages, 5 pages, accepted, to appear in MNRAS Letter

Efficiency of Turbulent Reacceleration by Solenoidal Turbulence and Its Application to the Origin of Radio Megahalos in Cluster Outskirts

Recent radio observations with the Low Frequency Array (LOFAR) discovered diffuse emission extending beyond the scale of classical radio halos. The presence of such megahalos indicates that the amplification of the magnetic field and acceleration of relativistic particles are working in the cluster outskirts, presumably due to the combination of shocks and turbulence that dissipate energy in these regions. Cosmological magnetohydrodynamical (MHD) simulations of galaxy clusters suggest that solenoidal turbulence has a significant energy budget in the outskirts of galaxy clusters. In this paper, we explore the possibility that this turbulence contributes to the emission observed in megahalos through second-order Fermi acceleration of relativistic particles and magnetic field amplification by the dynamo. We focus on the case of A2255 and find that this scenario can explain the basic properties of the diffuse emission component that is observed under assumptions that are used in previous literature. More specifically, we conduct a numerical follow-up, solving the Fokker-Planck equation by using a snapshot of an MHD simulation and deducing the synchrotron brightness integrated along the lines of sight. We find that a volume-filling emission, ranging between 30% and almost 100% of the projected area, depending on our assumptions on the particle diffusion and transport, can be detected at LOFAR sensitivities. Assuming a magnetic field B ∼ 0.2 μG, as derived from a dynamo model applied to the emitting region, we find that the observed brightness can be matched when ∼1% of the solenoidal turbulent energy flux is channeled into particle acceleration

A portable platform for accelerated PIC codes and its application to GPUs using OpenACC

We present a portable platform, called PIC_ENGINE, for accelerating Particle-In-Cell (PIC) codes on heterogeneous many-core architectures such as Graphic Processing Units (GPUs). The aim of this development is efficient simulations on future exascale systems by allowing different parallelization strategies depending on the application problem and the specific architecture. To this end, this platform contains the basic steps of the PIC algorithm and has been designed as a test bed for different algorithmic options and data structures. Among the architectures that this engine can explore, particular attention is given here to systems equipped with GPUs. The study demonstrates that our portable PIC implementation based on the OpenACC programming model can achieve performance closely matching theoretical predictions. Using the Cray XC30 system, Piz Daint, at the Swiss National Supercomputing Centre (CSCS), we show that PIC_ENGINE running on an NVIDIA Kepler K20X GPU can outperform the one on an Intel Sandybridge 8-core CPU by a factor of 3.4

A Map-Making Algorithm for the Planck Surveyor

We present a parallel implementation of a map-making algorithm for CMB anisotropy experiments which is both fast and efficient. We show for the first time a Maximum Likelihood, minimum variance map obtained by processing the entire data stream expected from the Planck Surveyor, under the assumption of a symmetric beam profile. Here we restrict ourselves to the case of the 30 GHz channel of the Planck Low Frequency Instrument. The extension to Planck higher frequency channels is straightforward. If the satellite pointing periodicity is good enough to average data that belong to the same sky circle, then the code runs very efficiently on workstations. The serial version of our code also runs on very competitive time-scales the map-making pipeline for current and forthcoming balloon borne experiments.Comment: 11 pages, 10 figures. Reflects accepted A&A versio

VisIVO - Integrated Tools and Services for Large-Scale Astrophysical Visualization

VisIVO is an integrated suite of tools and services specifically designed for the Virtual Observatory. This suite constitutes a software framework for effective visual discovery in currently available (and next-generation) very large-scale astrophysical datasets. VisIVO consists of VisiVO Desktop - a stand alone application for interactive visualization on standard PCs, VisIVO Server - a grid-enabled platform for high performance visualization and VisIVO Web - a custom designed web portal supporting services based on the VisIVO Server functionality. The main characteristic of VisIVO is support for high-performance, multidimensional visualization of very large-scale astrophysical datasets. Users can obtain meaningful visualizations rapidly while preserving full and intuitive control of the relevant visualization parameters. This paper focuses on newly developed integrated tools in VisIVO Server allowing intuitive visual discovery with 3D views being created from data tables. VisIVO Server can be installed easily on any web server with a database repository. We discuss briefly aspects of our implementation of VisiVO Server on a computational grid and also outline the functionality of the services offered by VisIVO Web. Finally we conclude with a summary of our work and pointers to future developments

VisIVOWeb: A WWW Environment for Large-Scale Astrophysical Visualization

This article presents a newly developed Web portal called VisIVOWeb that aims to provide the astrophysical community with powerful visualization tools for large-scale data sets in the context of Web 2.0. VisIVOWeb can effectively handle modern numerical simulations and real-world observations. Our open-source software is based on established visualization toolkits offering high-quality rendering algorithms. The underlying data management is discussed with the supported visualization interfaces and movie-making functionality. We introduce VisIVOWeb Network, a robust network of customized Web portals for visual discovery, and VisIVOWeb Connect, a lightweight and efficient solution for seamlessly connecting to existing astrophysical archives. A significant effort has been devoted for ensuring interoperability with existing tools by adhering to IVOA standards. We conclude with a summary of our work and a discussion on future developments

Artificial neural network for tilting pad journal bearing characterization

Tilting pad journal bearings (TPJBs) are modeled with Reynold-based models or computational fluid dynamics (CFD) approach. In both cases, the estimation of the dynamic coefficients of the oil-film forces and the static characteristic, can be computationally expensive and time consuming. Artificial Intelligence (AI) is assuming a key role in engineering but is rarely applied in fluid film bearing analysis. A properly trained Deep Learning (DL) model can perform very fast predictions of TPJB behavior with accuracy comparable to more time-consuming models. In this case, the main drawback is the time required to build the training dataset. In this work, an Artificial Neural Network (ANN) is trained to predict the dynamic stiffness and damping coefficients along with the main static quantities of TPJBs, such as minimum oil-film thickness and inlet flowrate. At first, a design of experiment is performed to build an appropriate training dataset. Secondly, a Reynolds-based thermo-hydrodynamic (THD) model is used to populate the training dataset and an appropriate test dataset. Then, a feedforward ANN is trained with Levenberg–Marquardt backpropagation and its architecture is optimized to increase accuracy. Finally, the accuracy of the ANN is tested using the test dataset and experimental data. The time and computational effort required by the ANN regression are much less than those required by the THD model. Therefore, the trained ANN is an effective and efficient tool for the characterization of TPJBs

A comparison of cosmological codes: properties of thermal gas and shock waves in large-scale structures

Cosmological hydrodynamical simulations are a valuable tool for understanding the growth of large-scale structure and the observables connected with this. Yet, comparably little attention has been given to validation studies of the properties of shocks and of the resulting thermal gas between different numerical methods something of immediate importance as gravitational shocks are responsible for generating most of the entropy of the large-scale structure in the Universe. Here, we present results for the statistics of thermal gas and the shock wave properties for a large volume simulated with three different cosmological numerical codes: the Eulerian total variations diminishing (TVD) code, the Eulerian piecewise parabolic method based code enzo and the Lagrangian smoothed particle hydrodynamics (SPH) code gadget. Starting from a shared set of initial conditions, we present convergence tests for a cosmological volume of side-length 100 Mpc h-1, studying in detail the morphological and statistical properties of the thermal gas as a function of mass and spatial resolution in all codes. By applying shock-finding methods to each code, we measure the statistics of shock waves and the related cosmic ray acceleration efficiencies, within the sample of simulations and for the results of the different approaches. We discuss the regimes of uncertainties and disagreement among codes, with a particular focus on the results at the scale of galaxy clusters. Even if the bulk of thermal and shock properties is reasonably in agreement among the three codes, yet some significant differences exist (especially between Eulerian methods and SPH). In particular, we report (a) differences of huge factors (similar to 10100) in the values of average gas density, temperature, entropy, Mach number and shock thermal energy flux in the most rarefied regions of the simulations (?/?cr < 1) between grid and SPH methods; (b) the hint of an entropy core inside clusters simulated in grid codes; (c) significantly different phase diagrams of shocked cells in grid codes compared to SPH and (d) sizable differences in the morphologies of accretion shocks between grid and SPH methodsopen393

COSMOS: A Hybrid N-Body/Hydrodynamics Code for Cosmological Problems

We describe a new hybrid N-body/hydrodynamical code based on the particle-mesh (PM) method and the piecewise-parabolic method (PPM) for use in solving problems related to the evolution of large-scale structure, galaxy clusters, and individual galaxies. The code, named COSMOS, possesses several new features which distinguish it from other PM-PPM codes. In particular, to solve the Poisson equation we have written a new multigrid solver which can determine the gravitational potential of isolated matter distributions and which properly takes into account the finite-volume discretization required by PPM. All components of the code are constructed to work with a nonuniform mesh, preserving second-order spatial differences. The PPM code uses vacuum boundary conditions for isolated problems, preventing inflows when appropriate. The PM code uses a second-order variable-timestep time integration scheme. Radiative cooling and cosmological expansion terms are included. COSMOS has been implemented for parallel computers using the Parallel Virtual Machine (PVM) library, and it features a modular design which simplifies the addition of new physics and the configuration of the code for different types of problems. We discuss the equations solved by COSMOS and describe the algorithms used, with emphasis on these features. We also discuss the results of tests we have performed to establish that COSMOS works and to determine its range of validity.Comment: 43 pages, 14 figures, submitted to ApJS and revised according to referee's comment