Now showing items 1-2 of 2

    • Supernova simulations and strategies for the dark energy survey. 

      Bernstein, J. P.; Kessler, R.; Kuhlmann, S.; Biswas, R.; Kovacs, E.; Aldering, G.; Crane, I.; D'Andrea, C. B.; Finley, D. A.; Frieman, J. A.; Hufford, T.; Jarvis, M.J.; Kim, A. G.; Marriner, J.; Mukherjee, P.; Nichol, R.C.; Nugent, P.; Parkinson, D.; Reis, R. R. R.; Sako, M.; Spinka, H.; Sullivan, M. (2012-07-10)
      We present an analysis of supernova light curves simulated for the upcoming Dark Energy Survey (DES) supernova search. The simulations employ a code suite that generates and fits realistic light curves in order to obtain ...
    • Transfer learning for galaxy morphology from one survey to another 

      Sánchez, H. Domínguez; Huertas-Company, M.; Bernardi, M.; Kaviraj, S.; Fischer, J. L.; Abbott, T. M. C.; Abdalla, F. B.; Annis, J.; Avila, S.; Buckley-Geer, E.; Rosell, A. Carnero; Kind, M. Carrasco; Carretero, J.; Cunha, C. E.; D'Andrea, C. B.; Costa, L. N. da; Davis, C.; Vicente, J. De; Doel, P.; Evrard, A. E.; Fosalba, P.; Frieman, J.; García-Bellido, J.; Gaztanaga, E.; Gerdes, D. W.; Gruen, D.; Gruendl, R. A.; Gschwend, J.; Gutierrez, G.; Hartley, W. G.; Hollowood, D. L.; Honscheid, K.; Hoyle, B.; Kuehn, K.; Kuropatkin, N.; Lahav, O.; Maia, M. A. G.; March, M.; Melchior, P.; Menanteau, F.; Miquel, R.; Nord, B.; Plazas, A. A.; Sanchez, E.; Scarpine, V.; Schindler, R.; Schubnell, M.; Soares-Santos, M.; Sobreira, F.; Suchyta, E.; Swanson, M. E. C.; Tarle, G.; Walker, A. R.; Zuntz, J. (2018-12-28)
      Deep Learning (DL) algorithms for morphological classification of galaxies have proven very successful, mimicking (or even improving) visual classifications. However, these algorithms rely on large training samples of ...