Repozitorij Univerze v Novi Gorici

Iskanje po repozitoriju
A+ | A- | Pomoč | SLO | ENG

Iskalni niz: išči po
išči po
išči po
išči po
* po starem in bolonjskem študiju

Opcije:
  Ponastavi


1 - 10 / 100
Na začetekNa prejšnjo stran12345678910Na naslednjo stranNa konec
1.
Performance of the Cherenkov Telescope Array in the presence of clouds
Mario Pecimotika, Saptashwa BHATTACHARYYA, Barbara MARČUN, Judit PÉREZ ROMERO, Samo Stanič, Veronika VODEB, Serguei Vorobiov, Gabrijela ZAHARIJAS, Marko Zavrtanik, Danilo Zavrtanik, Miha ŽIVEC, 2021, objavljeni znanstveni prispevek na konferenci

Opis: The Cherenkov Telescope Array (CTA) is the future ground-based observatory for gamma-ray astronomy at very high energies. The atmosphere is an integral part of every Cherenkov telescope. Di˙erent atmospheric conditions, such as clouds, can reduce the fraction of Cherenkov photons produced in air showers that reach ground-based telescopes, which may a˙ect the performance. Decreased sensitivity of the telescopes may lead to misconstructed energies and spectra. This study presents the impact of various atmospheric conditions on CTA performance. The atmospheric transmission in a cloudy atmosphere in the wavelength range from 203 nm to 1000 nm was simulated for di˙erent cloud bases and di˙erent optical depths using the MODerate resolution atmospheric TRANsmission (MODTRAN) code. MODTRAN output files were used as inputs for generic Monte Carlo simulations. The analysis was performed using the MAGIC Analysis and Reconstruction Software (MARS) adapted for CTA. As expected, the e˙ects of clouds are most evident at low energies, near the energy threshold. Even in the presence of dense clouds, high-energy gamma rays may still trigger the telescopes if the first interaction occurs lower in the atmosphere, below the cloud base. A method to analyze very high-energy data obtained in the presence of clouds is presented. The systematic uncertainties of the method are evaluated. These studies help to gain more precise knowledge about the CTA response to cloudy conditions and give insights on how to proceed with data obtained in such conditions. This may prove crucial for alert-based observations and time-critical studies of transient phenomena.
Ključne besede: Cherenkov Telescope Array, very-high energy gamma rays, MODerate resolution atmospheric TRANsmission code, MAGIC Analysis and Reconstruction Software
Objavljeno v RUNG: 18.09.2023; Ogledov: 51; Prenosov: 2
URL Povezava na datoteko
Gradivo ima več datotek! Več...

2.
Performance of a proposed event-type based analysis for the Cherenkov Telescope Array
Tarek Hassan, Saptashwa BHATTACHARYYA, Barbara MARČUN, Judit PÉREZ ROMERO, Samo Stanič, Veronika VODEB, Serguei Vorobiov, Gabrijela ZAHARIJAS, Marko Zavrtanik, Danilo Zavrtanik, Miha ŽIVEC, 2021, objavljeni znanstveni prispevek na konferenci

Opis: The Cherenkov Telescope Array (CTA) will be the next-generation observatory in the field of very-high-energy (20 GeV to 300 TeV) gamma-ray astroparticle physics. Classically, data analysis in the field maximizes sensitivity by applying quality cuts on the data acquired. These cuts, optimized using Monte Carlo simulations, select higher quality events from the initial dataset. Subsequent steps of the analysis typically use the surviving events to calculate one set of instrument response functions (IRFs). An alternative approach is the use of event types, as implemented in experiments such as the Fermi-LAT. In this approach, events are divided into sub-samples based on their reconstruction quality, and a set of IRFs is calculated for each sub-sample. The sub-samples are then combined in a joint analysis, treating them as independent observations. This leads to an improvement in performance parameters such as sensitivity, angular and energy resolution. Data loss is reduced since lower quality events are included in the analysis as well, rather than discarded. In this study, machine learning methods will be used to classify events according to their expected angular reconstruction quality. We will report the impact on CTA high-level performance when applying such an event-type classification, compared to the classical procedure.
Ključne besede: Cherenkov Telescope Array, very-high-energy gamma-rays, event-type based analysis
Objavljeno v RUNG: 18.09.2023; Ogledov: 58; Prenosov: 2
URL Povezava na datoteko
Gradivo ima več datotek! Več...

3.
4.
Connectivity reliability in uncertain networks with stability analysis
Ahmad Hosseini, Eddie Wadbro, 2016, izvirni znanstveni članek

Ključne besede: Traffic network, Uncertainty theory, Reliability, Chance-constrained, Stability analysis
Objavljeno v RUNG: 14.02.2023; Ogledov: 439; Prenosov: 0
Gradivo ima več datotek! Več...

5.
6.
7.
AutoSourceID-Light : Fast optical source localization via U-Net and Laplacian of Gaussian
F. Stoppa, P. Vreeswijk, S. Bloemen, S. Bhattacharyya, S Caron, G. Jóhannesson, R. Ruiz de Austri, C. Van den Oetelaar, G. Zaharijas, P.J. Groot, E. Cator, G. Nelemans, 2022, izvirni znanstveni članek

Opis: 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.
Ključne besede: astronomical databases, data analysis, image processing
Objavljeno v RUNG: 23.01.2023; Ogledov: 590; Prenosov: 0
Gradivo ima več datotek! Več...

8.
Unwrapping Aortic valve dysfunction through complex network analysis: A biophysics approach
Swapna Mohanachandran Nair Sindhu, 2022, izvirni znanstveni članek

Ključne besede: Aortic valve dysfunction, complex network analysis
Objavljeno v RUNG: 14.09.2022; Ogledov: 601; Prenosov: 0
Gradivo ima več datotek! Več...

9.
Yat-alternation and the imperfect tense in Bulgarian. A rule-based analysis.
Danil Khristov, 2022, objavljeni znanstveni prispevek na konferenci

Opis: The paper proposes a rule-based feature analysis of the ya/e phenomenon in Bulgarian. Special attention is paid to the variable ya/е observed in the forms of the imperfect tense. First and second-conjugation verbs whose imperfect forms involve yat-alternation are compared with third-conjugation verbs where this alternation is not observed. The analysis also addresses the role of morphology in the process of adding different imperfect endings to the verb base and the effect of these endings on the variable ya/e. Finally, the phonemic status of soft consonants is discussed in relation to the proposed analysis.
Ključne besede: yat vowel, yat-alternation, variable ya/e, imperfect tense, rule-based analysis, features
Objavljeno v RUNG: 06.09.2022; Ogledov: 768; Prenosov: 0
Gradivo ima več datotek! Več...

10.
Iskanje izvedeno v 0.06 sek.
Na vrh