161. iPTF Discovery of Recent Type Ia SupernovaeL. Hangard, Tanja Petrushevska, 2016, other component parts Abstract: The intermediate Palomar Transient Factory (ATel #4807) reports the discovery and classification of the following Type Ia SNe. Our automated candidate vetting to distinguish a real astrophysical source (1.0) from bogus artifacts (0.0) is powered by three generations of machine learning algorithms: RB2 (Brink et al. 2013MNRAS.435.1047B), RB4 (Rebbapragada et al. 2015AAS...22543402R) and RB5 (Wozniak et al. 2013AAS...22143105W).
Keywords: Supernovae, Transients
Published in RUNG: 24.01.2018; Views: 3021; Downloads: 0
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162. iPTF Discoveries of Recent Type Ia SupernovaeRaphael Ferretti, Tanja Petrushevska, 2016, other component parts Abstract: The intermediate Palomar Transient Factory (ATel #4807) reports the discovery and classification of the following Type Ia SNe. Our automated candidate vetting to distinguish a real astrophysical source (1.0) from bogus artifacts (0.0) is powered by three generations of machine learning algorithms: RB2 (Brink et al. 2013MNRAS.435.1047B), RB4 (Rebbapragada et al. 2015AAS...22543402R) and RB5 (Wozniak et al. 2013AAS...22143105W).
Keywords: Supernovae, Transients
Published in RUNG: 23.01.2018; Views: 3125; Downloads: 0
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163. iPTF Discoveries of Recent Type Ia SupernovaeS. Papadogiannakis, Tanja Petrushevska, 2016, other component parts Abstract: Abstract
The intermediate Palomar Transient Factory (ATel #4807) reports the discovery and classification of the following Type Ia SNe. Our automated candidate vetting to distinguish a real astrophysical source (1.0) from bogus artifacts (0.0) is powered by three generations of machine learning algorithms: RB2 (Brink et al. 2013MNRAS.435.1047B), RB4 (Rebbapragada et al. 2015AAS...22543402R) and RB5 (Wozniak et al. 2013AAS...22143105W).
Keywords: Supernovae, Transients
Published in RUNG: 23.01.2018; Views: 3299; Downloads: 0
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164. Art or Science? Images of scientific research : Photography contestTanja Petrushevska, 2017, artistic work Abstract: Looking at the pinking of a sky at sunset we see a delicate impressionist watercolor or rather the spectacular effect of the refraction of the sun on the particles of the atmosphere? Can the extraordinary geometries of the cubic lattices of a salt crystal be considered a perfect composition deserving of admiration like a cubist painting? All the "infinite forms, ever more beautiful and wonderful" of life, as defined by the famous naturalist Charles Darwin, are art or science?
The Art or Science photo contest? was born to emphasize the contamination between these two fields, only apparently distant, of human knowledge, exalting the beauty of scientific research and rewarding the photographic talent of those who work in science.
The 2017 edition of the competition, conceived and promoted by the University of Trieste and Immaginario Scientifico, has collected 116 images of students and scientists from universities and research institutions. Among these were selected 30 photos, exhibited from 18 to 23 September 2017 in Trieste, at Palazzo Costanzi, as part of the Trieste Next-Festival of Scientific Research.
Keywords: art and science
Published in RUNG: 23.01.2018; Views: 3133; Downloads: 0
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165. iPTF Discoveries of Recent Type Ia SupernovaeTanja Petrushevska, 2016, other component parts Abstract: The intermediate Palomar Transient Factory (ATel #4807) reports the discovery and classification of the following Type Ia SNe. Our automated candidate vetting to distinguish a real astrophysical source (1.0) from bogus artifacts (0.0) is powered by three generations of machine learning algorithms: RB2 (Brink et al. 2013MNRAS.435.1047B), RB4 (Rebbapragada et al. 2015AAS...22543402R) and RB5 (Wozniak et al. 2013AAS...22143105W).
Keywords: Supernovae, Transients
Published in RUNG: 23.01.2018; Views: 3178; Downloads: 0
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166. iPTF Discovery of Recent Type Ia SupernovaeLaura Hangard, Tanja Petrushevska, 2016, other component parts Abstract: The intermediate Palomar Transient Factory (ATel #4807) reports the discovery and classification of the following Type Ia SNe. Our automated candidate vetting to distinguish a real astrophysical source (1.0) from bogus artifacts (0.0) is powered by three generations of machine learning algorithms: RB2 (Brink et al. 2013MNRAS.435.1047B), RB4 (Rebbapragada et al. 2015AAS...22543402R) and RB5 (Wozniak et al. 2013AAS...22143105W).
Keywords: Supernovae, Transient
Published in RUNG: 23.01.2018; Views: 2933; Downloads: 0
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167. iPTF Discoveries of Recent Type Ia SupernovaeRaphael Ferretti, Tanja Petrushevska, 2016, other component parts Abstract: The intermediate Palomar Transient Factory (ATel #4807) reports the discovery and classification of the following Type Ia SNe. Our automated candidate vetting to distinguish a real astrophysical source (1.0) from bogus artefacts (0.0) is powered by three generations of machine learning algorithms: RB2 (Brink et al. 2013MNRAS.435.1047B), RB4 (Rebbapragada et al. 2015AAS...22543402R) and RB5 (Wozniak et al. 2013AAS...22143105W).
Keywords: Supernovae, Transient
Published in RUNG: 23.01.2018; Views: 3005; Downloads: 0
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169. iPTF Discoveries of Recent Core-Collapse SupernovaeFrancesco Taddia, Tanja Petrushevska, 2016, other component parts Abstract: Abstract
The intermediate Palomar Transient Factory (ATel #4807) reports the discovery and classification of the following core-collapse SNe. Our automated candidate vetting to distinguish a real astrophysical source (1.0) from bogus artifacts (0.0) is powered by three generations of machine learning algorithms: RB2 (Brink et al. 2013MNRAS.435.1047B), RB4 (Rebbapragada et al. 2015AAS...22543402R) and RB5 (Wozniak et al. 2013AAS...22143105W).
Keywords: Supernovae, Transient
Published in RUNG: 23.01.2018; Views: 2963; Downloads: 0
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170. iPTF Discoveries of Recent Type Ia Supernovae Authors:Semeli Papadogiannakis, Tanja Petrushevska, 2016, other component parts Abstract: The intermediate Palomar Transient Factory (ATel #4807) reports the discovery and classification of the following Type Ia SNe. Our automated candidate vetting to distinguish a real astrophysical source (1.0) from bogus artefacts (0.0) is powered by three generations of machine learning algorithms: RB2 (Brink et al. 2013MNRAS.435.1047B), RB4 (Rebbapragada et al. 2015AAS...22543402R) and RB5 (Wozniak et al. 2013AAS...22143105W).
Keywords: Supernovae, Transient
Published in RUNG: 23.01.2018; Views: 3038; Downloads: 0
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