Astronomy Domain Research Articles

A Survey of Big Data Archives in Time-Domain Astronomy

The rise of big data has resulted in the proliferation of numerous heterogeneous data stores. Even though multiple models are used for integrating these data, combining such huge amounts of data into a single model remains challenging. There is a need in the database management archives to manage such huge volumes of data without any particular structure which comes from unconnected and unrelated sources. These data are growing in size and thus demand special attention. The speed with which these data are growing as well as the varied data types involved and stored in scientific archives is posing further challenges. Astronomy is also increasingly becoming a science which is now based on a lot of data processing and involves assorted data. These data are now stored in domain-specific archives. Many astronomical studies are producing large-scale archives of data and these archives are then published in the form of data repositories. These mainly consist of images and text without any structure in addition to data with some structure such as relations with key values. When the archives are published as remote data repositories, it is challenging work to organize the data against their increased diversity and to meet the information demands of users. To address this problem, polystore systems present a new model of data integration and have been proposed to access unrelated data repositories using an uniform single query language. This article highlights the polystore system for integrating large-scale heterogeneous data in the astronomy domain.

The Cherenkov Telescope Array production system proto-type for large-scale data processing and simulations

The Cherenkov Telescope Array (CTA) is the next-generation instrument in the very-high energy gamma ray astronomy domain. It will consist of tens of Cherenkov telescopes deployed in 2 arrays at La Palma (Spain) and Paranal (ESO, Chile) respectively. Currently under construction, CTA will start operations around 2023 for a duration of about 30 years. During operations CTA is expected to produce about 2 PB of raw data per year plus 5-20 PB of Monte Carlo data. The global data volume to be managed by the CTA archive, including all versions and copies, is of the order of 100 PB with a smooth growing profile. The associated processing needs are also very high, of the order of hundreds of millions of CPU HS06 hours per year. In order to optimize the instrument design and study its performances, during the preparatory phase (2010-2017) and the current construction phase, the CTA consortium has run massive Monte Carlo productions on the EGI grid infrastructure. In order to handle these productions and the future data processing, we have developed a production system based on the DIRAC framework. The current system is the result of several years of hardware infrastructure upgrades, software development and integration of different services like CVMFS and FTS. In this paper we present the current status of the CTA production system and its exploitation during the latest large-scale Monte Carlo campaigns.

Characterization of silicon photomultipliers for new high-energy space telescopes

Photon detection is a major issue of high-energy astronomy instrumentation. One classical setup that has proven successful in space missions is the combination of photomultiplier tubes (PMTs) with scintillators, converting incoming high-energy photons into visible light, which is converted in an electrical impulse. Although being extremely sensitive and rapid, PMTs have the drawback of being bulky, fragile, and requiring a high-voltage power supply of thousands volts. The silicon photomultipliers (SiPM) appear to be a promising alternative to PMTs in many applications such as small satellites. We have started a R&D program to assess the possibility of using SiPMs for space-based applications in the high-energy astronomy domain. We present here the results of our characterization of SiPMs coming from several manufacturers. Each detector has been tested at low temperature and pressure to study its performance in a representative space environment. For this, we developed a dedicated vacuum chamber with a specific mechanical and thermal controlled system. Once dark current, dark count rate and PDE were measured, we made irradiation tests on two selected detectors to understand the susceptibility of SiPM to radiation damage. Finally, we aim to perform thermal cycling and mechanical tests on detectors and study their coupling to scintillators, in parallel with their space qualification.

We’re Working On It: Transferring the Sloan Digital Sky Survey from Laboratory to Library

This article reports on the transfer of a massive scientific dataset from a national laboratory to a university library, and from one kind of workforce to another. We use the transfer of the Sloan Digital Sky Survey (SDSS) archive to examine the emergence of a new workforce for scientific research data management. Many individuals with diverse educational backgrounds and domain experience are involved in SDSS data management: domain scientists, computer scientists, software and systems engineers, programmers, and librarians. These types of positions have been described using terms such as research technologist, data scientist, e-science professional, data curator, and more. The findings reported here are based on semi-structured interviews, ethnographic participant observation, and archival studies from 2011-2013. The library staff conducting the data storage and archiving of the SDSS archive faced two performance problems. The preservation specialist and the system administrator worked together closely to discover and implement solutions to the slow data transfer and verification processes. The team overcame these slow-downs by problem solving, working in a team, and writing code. The library team lacked the astronomy domain knowledge necessary to meet some of their preservation and curation goals. The case study reveals the variety of expertise, experience, and individuals essential to the SDSS data management process. A variety of backgrounds and educational histories emerge in the data managers studied. Teamwork is necessary to bring disparate expertise together, especially between those with technical and domain education. The findings have implications for data management education, policy and relevant stakeholders. This article is part of continuing research on Knowledge Infrastructures.

Agile parallel bioinformatics workflow management using Pwrake

BackgroundIn bioinformatics projects, scientific workflow systems are widely used to manage computational procedures. Full-featured workflow systems have been proposed to fulfil the demand for workflow management. However, such systems tend to be over-weighted for actual bioinformatics practices. We realize that quick deployment of cutting-edge software implementing advanced algorithms and data formats, and continuous adaptation to changes in computational resources and the environment are often prioritized in scientific workflow management. These features have a greater affinity with the agile software development method through iterative development phases after trial and error.Here, we show the application of a scientific workflow system Pwrake to bioinformatics workflows. Pwrake is a parallel workflow extension of Ruby's standard build tool Rake, the flexibility of which has been demonstrated in the astronomy domain. Therefore, we hypothesize that Pwrake also has advantages in actual bioinformatics workflows.FindingsWe implemented the Pwrake workflows to process next generation sequencing data using the Genomic Analysis Toolkit (GATK) and Dindel. GATK and Dindel workflows are typical examples of sequential and parallel workflows, respectively. We found that in practice, actual scientific workflow development iterates over two phases, the workflow definition phase and the parameter adjustment phase. We introduced separate workflow definitions to help focus on each of the two developmental phases, as well as helper methods to simplify the descriptions. This approach increased iterative development efficiency. Moreover, we implemented combined workflows to demonstrate modularity of the GATK and Dindel workflows.ConclusionsPwrake enables agile management of scientific workflows in the bioinformatics domain. The internal domain specific language design built on Ruby gives the flexibility of rakefiles for writing scientific workflows. Furthermore, readability and maintainability of rakefiles may facilitate sharing workflows among the scientific community. Workflows for GATK and Dindel are available at http://github.com/misshie/Workflows.

NECTAr: New electronics for the Cherenkov Telescope Array

The European astroparticle physics community aims to design and build the next generation array of Imaging Atmospheric Cherenkov Telescopes (IACTs), that will benefit from the experience of the existing H.E.S.S. and MAGIC detectors, and further expand the very-high energy astronomy domain. In order to gain an order of magnitude in sensitivity in the 10 GeV to > 100 TeV range, the Cherenkov Telescope Array (CTA) will employ 50–100 mirrors of various sizes equipped with 1000–4000 channels per camera, to be compared with the 6000 channels of the final H.E.S.S. array. A 3-year program, started in 2009, aims to build and test a demonstrator module of a generic CTA camera. We present here the NECTAr design of front-end electronics for the CTA, adapted to the trigger and data acquisition of a large IACTs array, with simple production and maintenance. Cost and camera performances are optimized by maximizing integration of the front-end electronics (amplifiers, fast analog samplers, ADCs) in an ASIC, achieving several GS/s and a few μ s readout dead-time. We present preliminary results and extrapolated performances from Monte Carlo simulations.

PathGrid: a service-orientated architecture for microscopy image analysis

This paper describes 'PathGrid'--an analysis and data integration system, developed initially to meet the demands in the analysis of medical microscopy imaging data. An overview of the current system is given, describing the techniques used in developing the data handling infrastructure and the analysis algorithm development. The use of software created in the context of systems designed for the astronomy domain is noted, specifically infrastructure from the astronomy virtual observatory movement for data discovery, access and workflow management, and astronomical image analysis software adapted for the analysis of high-throughput astronomy imaging surveys. This paper notes the applicability of the techniques from the astronomy domain. The testbed infrastructure deployment is described, emphasizing its speed and ease of use and support. The validity of the analysis techniques is confirmed through the pilot study described here--with the application to a large sample of immunohistochemistry microscopy data obtained in part for assessing the oestrogen receptor status of breast cancers. The analysis showed that the specificity and sensitivity values for the automatic scoring using PathGrid were within the errors of those obtained via a 'gold standard' manual pathologist scoring.

In-flight calibrations of IBIS/PICsIT

PICsIT (Pixellated Imaging CaeSium Iodide Telescope) is the high energy detector of the IBIS telescope on-board the INTEGRAL satellite. It consists of 4096 independent detection units, ~0.7 cm^2 in cross-section, operating in the energy range between 175 keV and 10 MeV. The intrinsically low signal to noise ratio in the gamma-ray astronomy domain implies very long observations, lasting 10^5-10^6 s. Moreover, the image formation principle on which PICsIT works is that of coded imaging in which the entire detection plane contributes to each decoded sky pixel. For these two main reasons, the monitoring, and possible correction, of the spatial and temporal non-uniformity of pixel performances, expecially in terms of gain and energy resolution, is of paramount importance. The IBIS on-board 22Na calibration source allows the calibration of each pixel at an accuracy of <0.5% by integrating the data from a few revolutions at constant temperature. The two calibration lines, at 511 and 1275 keV, allow also the measurement and monitoring of the PICsIT energy resolution which proves to be very stable at ~19% and ~9% (FWHM) respectively, and consistent with the values expected analytical predictions checked against pre-launch tests.