F. Bufano, C. Bordiu, T. Cecconello, M. Munari, A. Hopkins, A. Ingallinera, P. Leto, S. Loru, S. Riggi, E. Sciacca, G. Vizzari, A. Demarco, C. Buemi, F. Cavallaro, C. Trigilio, G. Umana
The Square Kilometre Array precursors are starting to release the first data of their large-field continuum surveys, making clear that also in the field of radio astronomy, deep learning turns as the primary solution for handling an overwhelming volume of data. Within this framework, our research group is taking a forefront position in various research initiatives aimed at assessing the effectiveness of ML techniques on survey data from ASKAP and MeerKAT. In this work we show how an unsupervised multi-stage pipeline is able to discover physically meaningful clusters within the heterogeneous Supernova Remnant (SNR) population: a convolutional autoencoder extracts features from multiwavelength imagery of a SNR sample; then an unsupervised clustering process operates on the latent space. Despite a large number of outliers, we were able to find a new classification system, in which most clusters relate to the presence of certain features regarding not only the morphology but also the relative weight of the different frequencies.
The European Open Science Cloud (EOSC) aims to create a federated environment for hosting and processing research data, supporting science in all disciplines without geographical boundaries, so that data, software, methods and publications can be shared seamlessly as part of an Open Science community. This work presents the ongoing activities related to the implementation and integration into EOSC of Visual Analytics services for astrophysics, specifically addressing challenges related to data management, mapping and structure detection. These services provide visualisation capabilities to manage the data life cycle processes under FAIR principles, integrating data processing for imaging and multidimensional map creation and mosaicking and data analysis supported with machine learning techniques, for detection of structures in large scale multidimensional maps.
The Square Kilometre Array (SKA) project is responsible for developing the SKA Observatory, the world's largest radiotelescope ever built: eventually two arrays of radio antennas - SKA1-Mid and SKA1-Low - will be installed in the South Africa's Karoo region and Western Australia's Murchison Shire, each covering a different range of radio frequencies. In particular SKA1-Mid array will comprise 133 15m diameter dish antennas observing in the 350 MHz-14 GHz range, each locally managed by a Local Monitoring and Control (LMC) system and remotely orchestrated by the SKA Telescope Manager (TM) system. Dish LMC will provide a Graphical User Interface (GUI) to be used for monitoring and Dish control in standalone mode for testing, TM simulation, integration, commissioning and maintenance. This paper gives a status update of the LMC GUI design involving users and tasks analysis, system prototyping, interface evaluation, provides details on the GUI prototypes being developed and technological choices and discuss key challenges in the LMC UI architecture, as well as our approaches to addressing them. In the GUI design task we have adopted a Usage-Centered Design (UCD) approach based on the early involvement of users whose feedback is being iteratively considered in analysis phases, as well as in design and evaluation. An IFML based user interaction modeling approach has been adopted.
KEYWORDS: Telescopes, Control systems, Control systems, Chemical elements, Data centers, Data modeling, Signal processing, Databases, Logic devices, Data storage, Diagnostics
The SKA Telescope Manager (TM) is the core package of the SKA Telescope: it is aimed at scheduling observations, controlling their execution, monitoring the telescope health status, diagnosing and fixing its faults and so on. To do that, TM directly interfaces with the Local Monitoring and Control systems (LMCs) of the various SKA Elements (e.g. Dishes, Low-Frequency Aperture Array, etc.), exchanging commands and data with each of them. TM in turn needs to be monitored and controlled, in order its continuous and proper operation – and therefore that of the whole SKA Telescope – is ensured. It appears indeed that, while the unavailability of one or more instances of any other SKA element should result only in a degraded operation for the whole telescope, a problem in TM could cause a complete stop of any operation. In addition to this higher responsibility, a local monitoring and control system for TM has to collect and display logging data directly to operators, perform lifecycle management of TM applications and directly deal - when possible - with management of TM faults (which also includes a direct handling of TM status and performance data). In this paper, the peculiarities presented by the TM monitoring and control and the consequences they have on the design of a related LMC system are addressed and discussed.
KEYWORDS: Telescopes, Optical instrument design, Control systems, Control systems design, Antennas, Control systems, Sensors, Interfaces, Signal processing, Receivers, Safety
The Square Kilometer Array (SKA) project aims at building the world’s largest radio observatory to observe the sky with unprecedented sensitivity and collecting area. In the first phase of the project (SKA1), an array of dishes, SKA1-MID, will be built in South Africa. It will consist of 133 15m-dishes, which will include the MeerKAT array, for the 0.350-20 GHz frequency band observations. Each antenna will be provided with a local monitor and control system (LMC), enabling operations both to the Telescope Manager remote system, and to the engineers and maintenance staff; it provides different environment for the telescope control (positioning, pointing, observational bands), metadata collection for monitoring and database storaging, operational modes and functional states management for all the telescope capabilities. In this paper we present the LMC software architecture designed for the detailed design phase (DD), where we describe functional and physical interfaces with monitored and controlled sub-elements, and highlight the data flow between each LMC modules and its sub-element controllers from one side, and Telescope Manager on the other side. We also describe the complete Product Breakdown Structure (PBS) created in order to optimize resources allocation in terms of calculus and memory, able to perform required task for each element according to the proper requirements. Among them, time response and system reliability are the most important, considering the complexity of SKA dish network and its isolated placement. Performances obtained by software implementation using TANGO framework will be discussed, matching them with technical requirements derived by SKA science drivers.
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