Type ia supernova light-curve inference: Hierarchical bayesian analysis in the near-infrared

Astrophysical Journal

Volumn 704, Issue 1, 2009, Pages 629-651

  Mandel, Kaisey S ^a   Wood Vasey, W Michael ^a,b   Friedman, Andrew S ^a   Kirshner, Robert P ^a  

^a HARVARD SMITHSONIAN CENTER FOR ASTROPHYSICS   (United States)

^b UNIVERSITY OF PITTSBURGH   (United States)

Author keywords

Distance Scale; Supernovae: general

Indexed keywords

EID: 70549097223     PISSN: 0004637X     EISSN: 15384357     Source Type: Journal    
DOI: 10.1088/0004-637X/704/1/629     Document Type: Article

References (81)

1. Astier, P. et al. 2006, A&A, 447, 31
2. Bishop, C. M. 2006, Pattern Recognition and Machine Learning (New York: Springer)
3. Blondin, S. et al. 2008, ApJ, 682, 724
4. Bloom, J. S. et al. 2006, Astronomical Data Analysis Software and Systems XV (ASP Conf. Ser. 351), ed. C. Gabriel, C. Arviset, D. Ponz, & S. Enrique (San Francisco, CA: ASP), 751
5. Cardelli, J. A., Clayton, G. C., & Mathis, J. S. 1989, ApJ, 345, 245
6. Conley, A., Carlberg, R. G., Guy, J., Howell, D. A., Jha, S., Riess, A. G., & Sullivan, M. 2007, ApJ, 664, L13
7. Di Paola, A., Larionov, V., Arkharov, A., Bernardi, F., Caratti, O, Garatti, A., Dolci, M., Di Carlo, E., & Valentini, G. 2002, A&A, 393, L21
8. Efron, B. 1983, J. Am. Stat. Assoc., 78, 316
9. Efron, B. & Tibshirani, R. 1997, J. Am. Stat. Assoc., 92, 548
10. Elias, J. H., Frogel, J. A., Hackwell, J. A., & Persson, S. E. 1981, ApJ, 251, L13
11. Elias, J. H., Matthews, K., Neugebauer, G., & Persson, S. E. 1985, ApJ, 296, 379
12. Elias-Rosa, N. et al. 2006, MNRAS, 369, 1880
13. Elias-Rosa, N. et al. 2008, MNRAS, 384, 107
14. Ford, E. B. 2005, AJ, 129, 1706
15. Freedman, W. L. et al. 2001, ApJ, 553, 47
16. Frieman, J. A., Turner, M. S., & Huterer, D. 2008, ARA&A, 46, 385
17. Frogel, J. A., Gregory, B., Kawara, K., Laney, D., Phillips, M. M., Terndrup, D., Vrba, F., & Whitford, A. E. 1987, ApJ, 315, L129
18. Garnavich, P. M. et al. 1998, ApJ, 509, 74
19. Gelman, A., Carlin, J. B., Stern, H. S., & Rubin, D. B. 2003, Bayesian Data Analysis, 2nd ed. (Boca Raton, FL: Chapman & Hall)
20. Gelman, A. & Rubin, D. B. 1992, Stat. Sci., 7, 457
21. Gilks, W. R., Richardson, S., & Spiegelhalter, D. 1995, Markov Chain Monte Carlo in Practice (Boca Raton, FL: Chapman & Hall)
22. Goldhaber, G. et al. 2001, ApJ, 558, 359
23. Graham, J. R., Meikle, W. P. S., Longmore, A. J., & Williams, P. M. 1988, ApJ, 333, 743
24. Guy, J., Astier, P., Nobili, S., Regnault, N., & Pain, R. 2005, A&A, 443, 781
25. Guy, J. et al. 2007, A&A, 466, 11
26. Hamuy, M. et al. 1996a, AJ, 112, 2408
27. Hamuy, M. et al. 1996b, AJ, 112, 2438
28. Haugbølle, T., Hannestad, S., Thomsen, B., Fynbo, J., Sollerman, J., & Jha, S. 2007, ApJ, 661, 650
29. Hernandez, M. et al. 2000, MNRAS, 319, 223
30. Hicken, M. et al. 2009a, ApJ, 700, 331
31. Hicken, M. et al. 2009b, ApJ, 700, 1097
32. Hillebrandt, W. & Niemeyer, J. C. 2000, ARA&A, 38, 191
33. Holman, M. J. et al. 2006, ApJ, 652, 1715
34. Jensen, F. V. 2001, Bayesian Networks and Decision Graphs (New York: Springer)
35. Jha, S., Riess, A. G., & Kirshner, R. P. 2007, ApJ, 659, 122
36. Jha, S. et al. 1999, ApJS, 125, 73
37. Jha, S. et al. 2006, AJ, 131, 527
38. Kasen, D. 2006, ApJ, 649, 939
39. Kirshner, R. P., Willner, S. P., Becklin, E. E., Neugebauer, G., & Oke, J. B. 1973, ApJ, 180, L97
40. Kowalski, M. et al. 2008, ApJ, 686, 749
41. Krisciunas, K., Hastings, N. C., Loomis, K., McMillan, R., Rest, A., Riess, A. G., & Stubbs, C. 2000, ApJ, 539, 658
42. Krisciunas, K., Phillips, M. M., & Suntzeff, N. B. 2004a, ApJ, 602, L81
43. Krisciunas, K. et al. 2001, AJ, 122, 1616
44. Krisciunas, K. et al. 2003, AJ, 125, 166
45. Krisciunas, K. et al. 2004b, AJ, 127, 1664
46. Krisciunas, K. et al. 2004c, AJ, 128, 3034
47. Krisciunas, K. et al. 2007, AJ, 133, 58
48. Leibundgut, B. 1989, PhD thesis, Univ. of Basel
49. Lewis, A. & Bridle, S. 2002, Phys.Rev.D, 66, 103511
50. Liu, J. S. 2002, Monte Carlo Strategies in Scientific Computing (New York: Springer)
51. Mandel, K. & Agol, E. 2002, ApJ, 580, L171
52. Meikle, W. P. S. 2000, MNRAS, 314, 782
53. Mould, J. R. et al. 2000, ApJ, 529, 786
54. Neill, J. D., Hudson, M. J., & Conley, A. 2007, ApJ, 661, L123
55. Pastorello, A. et al. 2007, MNRAS, 376, 1301
56. Pearl, J. 1988, Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference (San Mateo, CA: Morgan Kaufmann)
57. Perlmutter, S. et al. 1999, ApJ, 517, 565
58. Phillips, M. M. 1993, ApJ, 413, L105
59. Phillips, M. M., Lira, P., Suntzeff, N. B., Schommer, R. A., Hamuy, M., & Maza, J. 1999, AJ, 118, 1766
60. Pignata, G. et al. 2008, MNRAS, 388, 971
61. Press, W. H., Teukolsky, S. A., Vetterling, W. T., & Flannery, B. P. 2007, Numerical Recipes: The Art of Scientific Computing (New York: Cambridge Univ. Press)
62. Prieto, J. L., Rest, A., & Suntzeff, N. B. 2006, ApJ, 647, 501
63. Radburn-Smith, D. J., Lucey, J. R., & Hudson, M. J. 2004, MNRAS, 355, 1378
64. Riess, A. G., Press, W. H., & Kirshner, R. P. 1995, ApJ, 445, L91
65. Riess, A. G., Press, W. H., & Kirshner, R. P. 1996a, ApJ, 473, 88
66. Riess, A. G., Press, W. H., & Kirshner, R. P. 1996b, ApJ, 473, 588
67. Riess, A. G. et al. 1998, AJ, 116, 1009
68. Riess, A. G. et al. 1999, AJ, 117, 707
69. Riess, A. G. et al. 2005, ApJ, 627, 579
70. Riess, A. G. et al. 2009a, ApJ, 699, 539
71. Riess, A. G. et al. 2009b, ApJS, 183, 109
72. Schlegel, D. J., Finkbeiner, D. P., & Davis, M. 1998, ApJ, 500, 525
73. Spergel, D. N. et al. 2007, ApJS, 170, 377
74. Stanishev, V. et al. 2007, A&A, 469, 645
75. Tegmark, M. et al. 2004, Phys.Rev.D, 69, 103501
76. Valentini, G. et al. 2003, ApJ, 595, 779
77. Wang, L., Goldhaber, G., Aldering, G., & Perlmutter, S. 2003, ApJ, 590, 944
78. Wang, X. et al. 2008, ApJ, 675, 626
79. Wang, X. et al. 2009, ApJ, 697, 380
80. Wood-Vasey, W. M. et al. 2007, ApJ, 666, 694
81. Wood-Vasey, W. M. et al. 2008, ApJ, 689, 377