SwePub
Sök i SwePub databas

  Extended search

Träfflista för sökning "WFRF:(Sanders Ryan) "

Search: WFRF:(Sanders Ryan)

  • Result 1-10 of 192
Sort/group result
   
EnumerationReferenceCoverFind
1.
  • Villar, V. Ashley, et al. (author)
  • SuperRAENN : A Semisupervised Supernova Photometric Classification Pipeline Trained on Pan-STARRS1 Medium-Deep Survey Supernovae
  • 2020
  • In: Astrophysical Journal. - : American Astronomical Society. - 0004-637X .- 1538-4357. ; 905:2
  • Journal article (peer-reviewed)abstract
    • Automated classification of supernovae (SNe) based on optical photometric light-curve information is essential in the upcoming era of wide-field time domain surveys, such as the Legacy Survey of Space and Time (LSST) conducted by the Rubin Observatory. Photometric classification can enable real-time identification of interesting events for extended multiwavelength follow-up, as well as archival population studies. Here we present the complete sample of 5243 SN-like light curves (in g(P1)r(P1)i(P1)z(P1)) from the Pan-STARRS1 Medium-Deep Survey (PS1-MDS). The PS1-MDS is similar to the planned LSST Wide-Fast-Deep survey in terms of cadence, filters, and depth, making this a useful training set for the community. Using this data set, we train a novel semisupervised machine learning algorithm to photometrically classify 2315 new SN-like light curves with host galaxy spectroscopic redshifts. Our algorithm consists of an RF supervised classification step and a novel unsupervised step in which we introduce a recurrent autoencoder neural network (RAENN). Our final pipeline, dubbed SuperRAENN, has an accuracy of 87% across five SN classes (Type Ia, Ibc, II, IIn, SLSN-I) and macro-averaged purity and completeness of 66% and 69%, respectively. We find the highest accuracy rates for SNe Ia and SLSNe and the lowest for SNe Ibc. Our complete spectroscopically and photometrically classified samples break down into 62.0% Type Ia (1839 objects), 19.8% Type II (553 objects), 4.8% Type IIn (136 objects), 11.7% Type Ibc (291 objects), and 1.6% Type I SLSNe (54 objects).
  •  
2.
  • Kanai, M, et al. (author)
  • 2023
  • swepub:Mat__t
  •  
3.
  •  
4.
  •  
5.
  •  
6.
  • Aad, G., et al. (author)
  • Commissioning of the ATLAS Muon Spectrometer with cosmic rays
  • 2010
  • In: European Physical Journal C. Particles and Fields. - : Springer Science and Business Media LLC. - 1434-6044 .- 1434-6052. ; 70:3, s. 875-916
  • Journal article (peer-reviewed)abstract
    • The ATLAS detector at the Large Hadron Collider has collected several hundred million cosmic ray events during 2008 and 2009. These data were used to commission the Muon Spectrometer and to study the performance of the trigger and tracking chambers, their alignment, the detector control system, the data acquisition and the analysis programs. We present the performance in the relevant parameters that determine the quality of the muon measurement. We discuss the single element efficiency, resolution and noise rates, the calibration method of the detector response and of the alignment system, the track reconstruction efficiency and the momentum measurement. The results show that the detector is close to the design performance and that the Muon Spectrometer is ready to detect muons produced in high energy proton-proton collisions.
  •  
7.
  •  
8.
  •  
9.
  •  
10.
  •  
Skapa referenser, mejla, bekava och länka
  • Result 1-10 of 192
Type of publication
journal article (62)
research review (1)
Type of content
peer-reviewed (181)
other academic/artistic (1)
Author/Editor
Abi, B. (179)
Abramowicz, H. (179)
Abreu, H. (179)
Adelman, J. (179)
Adye, T. (179)
Akimoto, G. (179)
show more...
Akimov, A. V. (179)
Aleksa, M. (179)
Alexandre, G. (179)
Alhroob, M. (179)
Allport, P. P. (179)
Amelung, C. (179)
Anastopoulos, C. (179)
Angerami, A. (179)
Antonaki, A. (179)
Antonelli, M. (179)
Arai, Y. (179)
Arguin, J-F. (179)
Arnaez, O. (179)
Asquith, L. (179)
Assamagan, K. (179)
Azuma, Y. (179)
Bachacou, H. (179)
Bachas, K. (179)
Backes, M. (179)
Baker, O. K. (179)
Banas, E. (179)
Barbero, M. (179)
Barillari, T. (179)
Barisonzi, M. (179)
Barklow, T. (179)
Beau, T. (179)
Beck, H. P. (179)
Beckingham, M. (179)
Bella, G. (179)
Beltramello, O. (179)
Benary, O. (179)
Benekos, N. (179)
Benhammou, Y. (179)
Bentvelsen, S. (179)
Berge, D. (179)
Beringer, J. (179)
Bernius, C. (179)
Berry, T. (179)
Besson, N. (179)
Bethke, S. (179)
Biesiada, J. (179)
Bilokon, H. (179)
Black, K. M. (179)
Blum, W. (179)
show less...
University
Uppsala University (42)
Stockholm University (42)
Lund University (41)
Royal Institute of Technology (38)
Karolinska Institutet (7)
University of Gothenburg (3)
show more...
Umeå University (1)
Linköping University (1)
Swedish University of Agricultural Sciences (1)
show less...
Language
English (192)
Research subject (UKÄ/SCB)
Natural sciences (42)
Medical and Health Sciences (4)

Year

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Close

Copy and save the link in order to return to this view