no code implementations • 12 Jan 2018 • A. Vafaei Sadr, M. Farhang, S. M. S. Movahed, B. Bassett, M. Kunz
We explore the use of random forest and gradient boosting, two powerful tree-based machine learning algorithms, for the detection of cosmic strings in maps of the cosmic microwave background (CMB), through their unique Gott-Kaiser-Stebbins effect on the temperature anisotropies. The information in the maps is compressed into feature vectors before being passed to the learning units.
no code implementations • 21 Aug 2007 • Masao Sako, B. Bassett, A. Becker, D. Cinabro, F. DeJongh, D. L. Depoy, B. Dilday, M. Doi, J. A. Frieman, P. M. Garnavich, C. J. Hogan, J. Holtzman, S. Jha, R. Kessler, K. Konishi, H. Lampeitl, J. Marriner, G. Miknaitis, R. C. Nichol, J. L. Prieto, A. G. Riess, M. W. Richmond, R. Romani, D. P. Schneider, M. Smith, M. SubbaRao, N. Takanashi, K. Tokita, K. van der Heyden, N. Yasuda, C. Zheng, J. Barentine, H. Brewington, C. Choi, J. Dembicky, M. Harnavek, Y. Ihara, M. Im, W. Ketzeback, S. J. Kleinman, J. Krzesiński, D. C. Long, E. Malanushenko, V. Malanushenko, R. J. McMillan, T. Morokuma, A. Nitta, K. Pan, G. Saurage, S. A. Snedden
In the first two seasons, 476 sources were selected for spectroscopic observations, of which 403 were identified as SNe.