اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدThe Data Lab: A Science Platform for the analysis of ground-based astronomical survey data
78
0
0.0
(
0
)
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
The next decade will feature a growing number of massive ground-based photometric, spectroscopic, and time-domain surveys, including those produced by DECam, DESI, and LSST. The NOAO Data Lab was launched in 2017 to enable efficient exploration and analysis of large surveys, with particular focus on the petabyte-scale holdings of the NOAO Archive and their associated catalogs. The Data Lab mission and future development align well with two of the NSFs Big Ideas, namely Harnessing Data for 21st Century Science and Engineering and as part of a network to contribute to Windows on the Universe: The Era of Multi-messenger Astrophysics. Along with other Science Platforms, the Data Lab will play a key role in scientific discoveries from surveys in the next decade, and will be crucial to maintaining a level playing field as datasets grow in size and complexity.
قيم البحث
اقرأ أيضاً
We present a high-performance, graphics processing unit (GPU)-based framework for the efficient analysis and visualization of (nearly) terabyte (TB)-sized 3-dimensional images. Using a cluster of 96 GPUs, we demonstrate for a 0.5 TB image: (1) volume
rendering using an arbitrary transfer function at 7--10 frames per second; (2) computation of basic global image statistics such as the mean intensity and standard deviation in 1.7 s; (3) evaluation of the image histogram in 4 s; and (4) evaluation of the global image median intensity in just 45 s. Our measured results correspond to a raw computational throughput approaching one teravoxel per second, and are 10--100 times faster than the best possible performance with traditional single-node, multi-core CPU implementations. A scalability analysis shows the framework will scale well to images sized 1 TB and beyond. Other parallel data analysis algorithms can be added to the framework with relative ease, and accordingly, we present our framework as a possible solution to the image analysis and visualization requirements of next-generation telescopes, including the forthcoming Square Kilometre Array pathfinder radiotelescopes.
In the multi-messenger era, astronomical projects share information about transients phenomena issuing science alerts to the Scientific Community through different communications networks. This coordination is mandatory to understand the nature of th
ese physical phenomena. For this reason, astrophysical projects rely on real-time analysis software pipelines to identify as soon as possible transients (e.g. GRBs), and to speed up external alerts reaction time. These pipelines can share and receive the science alerts through the Gamma-ray Coordinates Network. This work presents a framework designed to simplify the development of real-time scientific analysis pipelines. The framework provides the architecture and the required automatisms to develop a real-time analysis pipeline, allowing the researchers to focus more on the scientific aspects. The framework has been successfully used to develop real-time pipelines for the scientific analysis of the AGILE space mission data. It is planned to reuse this framework for the Super-GRAWITA and AFISS projects. A possible future use for the Cherenkov Telescope Array (CTA) project is under evaluation.
Founded in 2010, the Taiwan Extragalactic Astronomical Data Center (TWEA-DC) has for goal to propose access to large amount of data for the Taiwanese and International community, focusing its efforts on Extragalactic science. In continuation with ind
ividual efforts in Taiwan over the past few years, this is the first steppingstone towards the building of a National Virtual Observatory. Taking advantage of our own fast indexing algorithm (BLINK), based on a octahedral meshing of the sky coupled with a very fast kd-tree and a clever parallelization amongst available resources, TWEA-DC will propose from spring 2013 a service of on-the-fly matching facility, between on-site and user-based catalogs. We will also offer access to public and private raw and reducible data available to the Taiwanese community. Finally, we are developing high-end on-line analysis tools, such as an automated photometric redshifts and SED fitting code (APz), and an automated groups and clusters finder (APFoF).
The Near-Infrared Spectrograph (NIRSpec) is one of four instruments aboard the James Webb Space Telescope (JWST). NIRSpec is developed by ESA with AIRBUS Defence & Space as prime contractor. The calibration of its various observing modes is a fundame
ntal step to achieve the mission science goals and provide users with the best quality data from early on in the mission. Extensive testing of NIRSpec on the ground, aided by a detailed model of the instrument, allow us to derive initial corrections for the foreseeable calibrations. We present a snapshot of the current calibration scheme that will be revisited once JWST is in orbit.
We present an analysis of meteorological data from the second generation of the Kunlun Automated Weather Station (KLAWS-2G) at Dome A, Antarctica during 2015 and 2016. We find that a strong temperature inversion exists for all the elevations up to 14
m that KLAWS-2G can reach, and lasts for more than 10 hours for 50% or more of the time when temperature inversion occurs. The average wind speeds at 4 m elevation are 4.2 m/s and 3.8 m/s during 2015 and 2016, respectively. The strong temperature inversion and moderate wind speed lead to a shallow turbulent boundary layer height at Dome A. By analyzing the temperature and wind shear profiles, we note telescopes should be elevated by at least 8 m above the ice. We also find that the duration of temperature
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
