Hostname: page-component-cd9895bd7-dzt6s Total loading time: 0 Render date: 2024-12-25T16:00:45.427Z Has data issue: false hasContentIssue false

Precision cosmology, Accuracy cosmology and Statistical cosmology

Published online by Cambridge University Press:  01 July 2015

Licia Verde*
Affiliation:
ICREA & Instituto de ciencias del Cosmos, Iniversitat de Barcelona ICC-UB IEEC Institute of Theoretical Astrophysics, University of Oslo, 0315 Oslo, Norway email: [email protected]
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

The avalanche of data over the past 10-20 years has propelled cosmology into the “precision era”. The next challenge cosmology has to meet is to enter the era of accuracy. Because of the intrinsic nature of studying the Cosmos and the sheer amount of data available now and coming soon, the only way to meet this challenge is by developing suitable and specific statistical techniques. The road from precision Cosmology to accurate Cosmology goes through statistical Cosmology. I will outline some open challenges and discuss some specific examples.

Type
Contributed Papers
Copyright
Copyright © International Astronomical Union 2015 

References

Planck Collaboration et al., 2013, arXiv, arXiv:1303.5076Google Scholar
Planck Collaboration et al., 2013, arXiv, arXiv:1303.5062Google Scholar
The COrE Collaboration, Armitage-Caplan, C., Avillez, M., et al. 2011, arXiv:1102.2181Google Scholar
André, P., Baccigalupi, C., Banday, A., et al. 2014, JCAP, 2, 6Google Scholar
Box, George, Norman, E. P., Draper, R. (1987). Empirical Model-Building and Response Surfaces, p. 424, Wiley.Google Scholar
Peebles, P. J. E. 2002, arXiv:astro-ph/0208037Google Scholar
Elsner, F. & Wandelt, B. D., Astrophys. J. 724, 1262 (2010) [arXiv:1010.1254 [astro-ph.CO]].CrossRefGoogle Scholar
Elsner, F., Wandelt, B. D. & Schneider, M. D., Astron. Astrophys. 513, A59 (2010) [arXiv:1002.1713 [astro-ph.CO]].CrossRefGoogle Scholar
Ensslin, T. A., Frommert, M., & Kitaura, F. S., Phys. Rev. D 80 (2009) 105005 [arXiv:0806.3474 [astro-ph]].CrossRefGoogle Scholar
Verde, L., Jimenez, R., Alvarez-Gaume, L., Heavens, A. F., & Matarrese, S. 2013a, JCAP, 6, 23Google Scholar
Regan, D. M., Shellard, E. P. S., & Fergusson, J. R. 2010, PRD, 82, 023520Google Scholar
Marshall, P., Rajguru, N., & Slosar, A., Phys. Rev. D 73, 067302 (2006)Google Scholar
March, M. C., Trotta, R., Amendola, L., & Huterer, D., Mon. Not. Roy. Astron. Soc. 415, 143 (2011)Google Scholar
Verde, L., Protopapas, P., & Jimenez, R. 2013b, Physics of the Dark Universe, 2, 166Google Scholar
Jeffreys, H., 1973. Scientific Inference. Cambridge University Press.Google Scholar
Kass, R. E. & Raftery, A. E., 1995, Bayes factors. JASA 90, 430, 773795.Google Scholar
Leistedt, B., Peiris, H. V., & Verde, L., 2014, arXiv:1404.5950Google Scholar
Otto, S., Politzer, H. D., & Wise, M. B., 1986, Physical Review Letters, 56, 1878CrossRefGoogle Scholar
Rice, S. O., 1944, Bell Systems Tech. J., Volume 23, p. 282332, 23, 282Google Scholar
Rice, S. O., 1945, Bell Systems Tech. J., Volume 24, p. 46156, 24, 46CrossRefGoogle Scholar
Adler, R. J., 1981, The Geometry of Random Fields. Chichester: WileyGoogle Scholar
Bardeen, J. M., Bond, J. R., Kaiser, N., & Szalay, A. S., 1986, ApJ, 304, 15Google Scholar
Jensen, L. G. & Szalay, A. S., 1986, ApJLett, 305, L5Google Scholar
Kaiser, N., 1984, ApJL, 284, L9CrossRefGoogle Scholar
Peacock, J. A. & Heavens, A. F., 1985, MNRAS, 217, 805CrossRefGoogle Scholar
Noreña, J., Verde, L., Jimenez, R., Peña-Garay, C., & Gomez, C. 2012, MNRAS, 419, 1040Google Scholar
Wilson, K. G. & Kogut, J., 1974, PhR, 12, 75Google Scholar