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1.
Faceless machines: early recognition media and entangled bodies : lecture at the "Relatifs" lecture series, Kepler Salon, Johannes Kepler Universität Linz, Österreich, 16. 1. 2024
Eszter Polónyi, 2024, invited lecture at foreign university

Abstract: Eszter Polonyis Vortrag behandelt frühe Systeme automatisierter Identitätserkennung. Einen Fokus bilden Experimente zur Stimmerkennung, wie sie in der Mitte des 20. Jahrhunderts von US-amerikanische Telekommunikationsunternehmen unternommen wurden. Sie geht dabei auch den Verbindungen zur Arbeit mit „noise“ von Medienkünstler*innen nach, darunter Tony Conrad, John Cage und Kurt Kren.
Keywords: media studies, surveillance studies, art history, critical data studies, avant-garde and experimental art
Published in RUNG: 12.02.2024; Views: 417; Downloads: 2
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2.
With AugerPrime to the phase II of the Pierre Auger Observatory
Daniele Martello, Andrej Filipčič, Jon Paul Lundquist, Shima Ujjani Shivashankara, Samo Stanič, Serguei Vorobiov, Danilo Zavrtanik, Marko Zavrtanik, 2023, published scientific conference contribution

Abstract: AugerPrime, the upgrade of the Pierre Auger Observatory, is nearing completion and the Observatory is now prepared to collect physics data after the commissioning of the new components. The Pierre Auger Observatory has demonstrated, based on the data collected thus far, the existence of the cutoff in the spectrum with high accuracy. However, the origin of this cutoff remains incompletely understood. The upgraded Observatory is designed to address the unresolved questions regarding the nature of the cosmic ray flux cutoff thanks to its capability to disentangle the muon and electromagnetic components of extensive air showers. Furthermore, the measurement of the muon component at ground level can verify the accuracy of hadronic interaction models currently used. This presentation will provide an overview of the status of the Observatory and the accurate commissioning done before the start of the physics run. Furthermore, we will present the initial data from Phase II data mainly dedicated to proving the continuity of operation of the Observatory from Phase I to Phase II.
Keywords: Pierre Auger Observatory, ultra-high energy cosmic rays, AugerPrime detector upgrade, Pierre Auger data
Published in RUNG: 24.01.2024; Views: 440; Downloads: 6
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3.
Portals to data of the Pierre Auger Observatory
P. L. Ghia, Andrej Filipčič, Jon Paul Lundquist, Shima Ujjani Shivashankara, Samo Stanič, Serguei Vorobiov, Danilo Zavrtanik, Marko Zavrtanik, 2023, published scientific conference contribution

Abstract: The Pierre Auger Collaboration has embraced the concept of open access to their data from its foundation. As early as 2007, when the Observatory was almost complete, a portal to 1% of the data from the surface detector was created and updated every year for over ten years. Meant for educational purposes, the portal was the first step towards making data public by the FAIR (Findable, Accessible, Interoperable, and Reusable) principles. A new portal was opened in February 2021, at the end of the first phase of operation. Presented for the first time at the ICRC 2021, it includes not only 10% of the data–raw and processed–from the different instruments of the Observatory, but also a visualisation tool, documentation to make the data user-friendly, and analyses codes that can be readily used and modified. Since 2021, the portal has been updated three times: new data, documentation, and codes have been added. Moreover, the portal has become dual, with one part dedicated to scientists and the other to educational users. Furthermore, a catalog containing details of the 100 highest-energy cosmic rays has been included. At this conference we will discuss these new features, as well as our intentions for the future. We will also share our approach and methods for making data public and understandable to external users, from simplifying the data structure to translating codes from in-house computing architecture into popular available software.
Keywords: Pierre Auger Observatory, ultra-high energy cosmic rays, portals to data
Published in RUNG: 24.01.2024; Views: 362; Downloads: 6
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4.
AutoSourceID-Classifier : star-galaxy classification using a convolutional neural network with spatial information
F. Stoppa, Saptashwa Bhattacharyya, R. Ruiz de Austri, P. Vreeswijk, S. Caron, Gabrijela Zaharijas, S. Bloemen, G. Principe, D. Malyshev, Veronika Vodeb, 2023, original scientific article

Abstract: Aims: Traditional star-galaxy classification techniques often rely on feature estimation from catalogs, a process susceptible to introducing inaccuracies, thereby potentially jeopardizing the classification’s reliability. Certain galaxies, especially those not manifesting as extended sources, can be misclassified when their shape parameters and flux solely drive the inference. We aim to create a robust and accurate classification network for identifying stars and galaxies directly from astronomical images. Methods: The AutoSourceID-Classifier (ASID-C) algorithm developed for this work uses 32x32 pixel single filter band source cutouts generated by the previously developed AutoSourceID-Light (ASID-L) code. By leveraging convolutional neural networks (CNN) and additional information about the source position within the full-field image, ASID-C aims to accurately classify all stars and galaxies within a survey. Subsequently, we employed a modified Platt scaling calibration for the output of the CNN, ensuring that the derived probabilities were effectively calibrated, delivering precise and reliable results. Results: We show that ASID-C, trained on MeerLICHT telescope images and using the Dark Energy Camera Legacy Survey (DECaLS) morphological classification, is a robust classifier and outperforms similar codes such as SourceExtractor. To facilitate a rigorous comparison, we also trained an eXtreme Gradient Boosting (XGBoost) model on tabular features extracted by SourceExtractor. While this XGBoost model approaches ASID-C in performance metrics, it does not offer the computational efficiency and reduced error propagation inherent in ASID-C’s direct image-based classification approach. ASID-C excels in low signal-to-noise ratio and crowded scenarios, potentially aiding in transient host identification and advancing deep-sky astronomy.
Keywords: astronomical databases, data analysis, statistics, image processing
Published in RUNG: 12.12.2023; Views: 527; Downloads: 4
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5.
AutoSourceID-FeatureExtractor : optical image analysis using a two-step mean variance estimation network for feature estimation and uncertainty characterisation
F. Stoppa, R. Ruiz de Austri, P. Vreeswijk, Saptashwa Bhattacharyya, S. Caron, S. Bloemen, Gabrijela Zaharijas, G. Principe, Veronika Vodeb, P. J. Groot, E. Cator, G. Nelemans, 2023, original scientific article

Abstract: Aims: In astronomy, machine learning has been successful in various tasks such as source localisation, classification, anomaly detection, and segmentation. However, feature regression remains an area with room for improvement. We aim to design a network that can accurately estimate sources' features and their uncertainties from single-band image cutouts, given the approximated locations of the sources provided by the previously developed code AutoSourceID-Light (ASID-L) or other external catalogues. This work serves as a proof of concept, showing the potential of machine learning in estimating astronomical features when trained on meticulously crafted synthetic images and subsequently applied to real astronomical data. Methods: The algorithm presented here, AutoSourceID-FeatureExtractor (ASID-FE), uses single-band cutouts of 32x32 pixels around the localised sources to estimate flux, sub-pixel centre coordinates, and their uncertainties. ASID-FE employs a two-step mean variance estimation (TS-MVE) approach to first estimate the features and then their uncertainties without the need for additional information, for example the point spread function (PSF). For this proof of concept, we generated a synthetic dataset comprising only point sources directly derived from real images, ensuring a controlled yet authentic testing environment. Results: We show that ASID-FE, trained on synthetic images derived from the MeerLICHT telescope, can predict more accurate features with respect to similar codes such as SourceExtractor and that the two-step method can estimate well-calibrated uncertainties that are better behaved compared to similar methods that use deep ensembles of simple MVE networks. Finally, we evaluate the model on real images from the MeerLICHT telescope and the Zwicky Transient Facility (ZTF) to test its transfer learning abilities.
Keywords: data analysis, image processing, astronomical databases
Published in RUNG: 08.11.2023; Views: 519; Downloads: 7
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6.
Outreach activities at the Pierre Auger Observatory
K.S. Caballero-Mora, Jon Paul Lundquist, 2022, published scientific conference contribution

Abstract: The Pierre Auger Observatory, sited in Malargüe, Argentina, is the largest observatory available for measuring ultra-high-energy cosmic rays (UHECR). The Auger Collaboration has measured and analysed an unprecedented number of UHECRs. Along with making important scientific discoveries, for example, the demonstration that cosmic rays above 8 EeV are of extragalactic origin and the observation of a new feature in the energy spectrum at around 13 EeV, outreach work has been carried out across the 18 participating countries and online. This program ranges from talks to a varied audience, to the creation of a local Visitor Center, which attracts 8000 visitors annually, to initiating masterclasses. Permanent and temporary exhibitions have been prepared both in reality and virtually. Science fairs for elementary- and high-school students have been organised, together with activities associated with interesting phenomena such as eclipses. In addition, we participate in international events such as the International Cosmic Day, Frontiers from H2020, and the International Day of Women and Girls in Science. Part of the Collaboration website is aimed at the general public. Here the most recent articles published are summarised. Thus the Collaboration informs people about work in our field, which may seem remote from everyday life. Furthermore, the Auger Observatory has been a seed for scientific and technological activities in and around Malargüe. Different outreach ventures that already have been implemented and others which are foreseen will be described.
Keywords: Pierre Auger Observatory, indirect detection, ultra-high energy, cosmic rays, outreach, open data
Published in RUNG: 26.09.2023; Views: 601; Downloads: 5
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7.
The Monitoring, Logging, and Alarm system for the Cherenkov Telescope Array
Alessandro Costa, Saptashwa Bhattacharyya, Barbara MARČUN, Judit Pérez Romero, Samo Stanič, Veronika Vodeb, Serguei Vorobiov, Gabrijela Zaharijas, Marko Zavrtanik, Danilo Zavrtanik, Miha Živec, 2021, published scientific conference contribution

Abstract: We present the current development of the Monitoring, Logging and Alarm subsystems in the framework of the Array Control and Data Acquisition System (ACADA) for the Cherenkov Tele-scope Array (CTA). The Monitoring System (MON) is the subsystem responsible for monitoring and logging the overall array (at each of the CTA sites) through the acquisition of monitoring and logging information from the array elements. The MON allows us to perform a systematic approach to fault detection and diagnosis supporting corrective and predictive maintenance to minimize the downtime of the system. We present a unified tool for monitoring data items from the telescopes and other devices deployed at the CTA array sites. Data are immediately available for the operator interface and quick-look quality checks and stored for later detailed inspection. The Array Alarm System (AAS) is the subsystem that provides the service that gathers, filters, exposes, and persists alarms raised by both the ACADA processes and the array elements su-pervised by the ACADA system. It collects alarms from the telescopes, the array calibration, the environmental monitoring instruments and the ACADA systems. The AAS sub-system also creates new alarms based on the analysis and correlation of the system software logs and the status of the system hardware providing the filter mechanisms for all the alarms. Data from the alarm system are then sent to the operator via the human-machine interface.
Keywords: Cherenkov Telescope Array, Array Control and Data Acquisition System, Monitoring System, Array Alarm System
Published in RUNG: 18.09.2023; Views: 553; Downloads: 4
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8.
9.
A catalog of the highest-energy cosmic rays recorded during Phase I of operation of the Pierre Auger Observatory
A. Abdul Halim, Andrej Filipčič, Jon Paul Lundquist, Shima Ujjani Shivashankara, Samo Stanič, Serguei Vorobiov, Danilo Zavrtanik, Marko Zavrtanik, 2023, original scientific article

Abstract: A catalog containing details of the highest-energy cosmic rays recorded through the detection of extensive air showers at the Pierre Auger Observatory is presented with the aim of opening the data to detailed examination. Descriptions of the 100 showers created by the highest-energy particles recorded between 2004 January 1 and 2020 December 31 are given for cosmic rays that have energies in the range 78–166 EeV. Details are also given on a further nine very energetic events that have been used in the calibration procedure adopted to determine the energy of each primary. A sky plot of the arrival directions of the most energetic particles is shown. No interpretations of the data are offered.
Keywords: ultra-high-energy cosmic rays, cosmic ray air showers, experimental data, catalogs, Pierre Auger Observatory
Published in RUNG: 09.02.2023; Views: 1162; Downloads: 16
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10.
AutoSourceID-Light : Fast optical source localization via U-Net and Laplacian of Gaussian
F. Stoppa, P. Vreeswijk, S. Bloemen, Saptashwa Bhattacharyya, S Caron, G. Jóhannesson, R. Ruiz de Austri, C. Van den Oetelaar, Gabrijela Zaharijas, P.J. Groot, E. Cator, G. Nelemans, 2022, original scientific article

Abstract: Aims: With the ever-increasing survey speed of optical wide-field telescopes and the importance of discovering transients when they are still young, rapid and reliable source localization is paramount. We present AutoSourceID-Light (ASID-L), an innovative framework that uses computer vision techniques that can naturally deal with large amounts of data and rapidly localize sources in optical images. Methods: We show that the ASID-L algorithm based on U-shaped networks and enhanced with a Laplacian of Gaussian filter provides outstanding performance in the localization of sources. A U-Net network discerns the sources in the images from many different artifacts and passes the result to a Laplacian of Gaussian filter that then estimates the exact location. Results: Using ASID-L on the optical images of the MeerLICHT telescope demonstrates the great speed and localization power of the method. We compare the results with SExtractor and show that our method outperforms this more widely used method rapidly detects more sources not only in low and mid-density fields, but particularly in areas with more than 150 sources per square arcminute. The training set and code used in this paper are publicly available.
Keywords: astronomical databases, data analysis, image processing
Published in RUNG: 23.01.2023; Views: 1205; Downloads: 0
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