Reconstruction of the null-test for the matter density perturbations
Entity
UAM. Departamento de Física TeóricaPublisher
American Physical SocietyDate
2015-01-14Citation
10.1103/PhysRevD.91.023004
Physical Review D 91.2 (2015): 023004
ISSN
1550-7998 (print); 1550-2368 (online)DOI
10.1103/PhysRevD.91.023004Funded by
The authors acknowledge financial support from the Madrid Regional Government (CAM) under the Grant No. HEPHACOS S2009/ESP-1473-02, from MICINN under Grant No. FPA2012-39684-C03-02 and Consolider-Ingenio 2010 PAU (Grant No. CSD2007-00060), as well as from the European Union Marie Curie Initial Training Network UNILHC Grant No. PITN-GA-2009-237920. We also acknowledge the support of the Spanish MINECO’s “Centro de Excelencia Severo Ochoa” Programme under Grant No. SEV-2012-0249Project
Gobierno de España. FPA2012-39684-C03-02; Gobierno de España. CSD2007-00060; info:eu-repo/grantAgreement/EC/FP7/237920; Gobierno de España. SEV-2012-0249; Comunidad de Madrid. S2009/ESP-1473/HEPHACOSEditor's Version
http://dx.doi.org/10.1103/PhysRevD.91.023004Subjects
FísicaNote
Artículo escrito por un elevado número de autores, solo se referencian el que aparece en primer lugar, el nombre del grupo de colaboración, si le hubiere, y los autores pertenecientes a la UAMRights
© 2015 American Physical SocietyAbstract
We systematically study the null-test for the growth rate data first presented in [S. Nesseris and D. Sapone, arXiv:1409.3697.] and we reconstruct it using various combinations of data sets, such as the fσ8 and H(z) or type Ia supernovae data. We perform the reconstruction in two different ways, either by directly binning thedata or by fitting various dark energy models. We also examine how well the null-test can be reconstructed by future data by creating mock catalogs based on the cosmological constant model, a model with strong dark energy perturbations, the f(R) and f(G) models, and the large void Lemaitre-Tolman-Bondi model that exhibit different evolution of the matter perturbations. We find that with future data similar to an LSST-like survey, the null-test will be able to successfully discriminate between these different cases at the 5σ level
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Google Scholar:Nesseris, Savvas
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Sapone, Domenico
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García-Bellido Capdevila, Juan
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