Круглосуточный радио обзор неба на 110 МГц: база данных наблюдений и статистический анализ импульсных явлений в 2012-2013 гг.
One of the most sensitive radio telescopes at the frequency of 110 MHz is a Big Scanning Antenna (BSA) in Pushchino Radio Astronomy Observatory of Lebedev Physical Institute (PRAO LPI, Moscow region, Russia). Since 2012 in the BSA the continuous survey observation was started in multibeam mode in the frequency band of 109–112 MHz. Now 96 beams covering from −8 and up to +42° in declination are used. The number of frequency bands are 6 with a time resolution of 0.1 s and 32 bands with the time resolution of 0.0125 s. In a fast mode (32 bands, 0.0125 s) daily data flow is 87.5 GB (32 TB per year). The data provide a great opportunity for both short-term and long-term monitoring of the various radio sources. The sources are fast radio transients of different nature, such as fast radio bursts (FRB), possible counterparts of gamma-ray bursts (GRB), and sources of gravitational waves, the Earth’s ionosphere, interplanetary and interstellar plasma. Based on the BSA observations the database is constructed. We discuss data base prop- erties, the methods of transient search and allocation in database. Using this database we were able to detect 83096 individual transient events in the period of July 2012 – October 2013, which may correspond to pulsars, scintillating sources and fast radio transients. We also present first results and statistics of transients classification. In particular we report parameters of two candidates in new RRAT pulsars.
In the process of astronomical observations are collected vast amounts of data. BSA (Big Scanning Antenna) LPI used in the study of impulse phenomena, daily logs 87.5 GB of data (32 TB per year). Experts classified 83096 individual observations (on the segment of the study July 2012 - October 2013). Over 75% of the sample correspond to pulsars, twinkling springs and rapid radiotransmitter, and all other classes of observations belong to hardware failures, interference, the flight of the Earth satellite and aircraft. There were allocated 15 classes of observations.
Such a sample, divided into classes allows using the machine learning algorithms. It has become possible to develop an automated service for short-term/long-term monitoring of various classes of radio sources (including radiotransmitted different nature), monitoring the Earth's ionosphere, the interplanetary and the interstellar plasma, the search and monitoring of different classes of radio sources. Monitoring in this case refers to the automatic filtering and detection of a previously unclassified impulse phenomena.
Currently, for automatic filtering, statistical analysis methods are used. This report examines an alternative method supposed to be using neural network machine learning algorithm that processes the input into raw data and after processing by the hidden layer through the output layer determines the class of pulse phenomena.
Creating a neural network model, trained on a sample and performing a classification of previously unclassified impulse phenomena is performed using the cloud service Microsoft Azure Machine Learning Studio. The Web service has been created based on the model allows classifying single impulse phenomena in real time (Request / Reply) and data sampling for a certain period (Batch processing).
Modern astronomical research programs need high-speed data transmission. The problem of the development and modernization of local networks and main channels is discussed.
On the Pushchino Radio Astronomy Observatory of Lebedev Physical Institute by radio telescope BSA (Big Scanning Antenna) in 2012 started daily multi-beam observations at the frequency range 109- 112 MHz. The number of frequency bands range from 6 to 32, while the time constants range from 0.1 to 0.0125 sec. This data is an enormous opportunity for both short and long-term monitoring of various classes of radio sources (including radio transients), the Earth's ionosphere, interplanetary and interstellar plasma monitoring, search and monitoring for different classes of radio sources, etc. A specialized database was constructed to facilitate the large amount of observational data (http://astro.prao.ru/ cgi/out_img.cgi ). We discuss in this paper method of allocation from the database for impulse data of various types. By using the database allocated 83096 individual impulses in declination from +3 to +42 degrees for July 2012 – October 2013 from pulsars, scintillation sources and so one. In result we constructed homogeneous sample suitable for statistical analyzes.