Forecast And Analysis Of The Cosmological Redshift Drift

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Ikusi/Ireki
Data
2018-01-08
Egilea
Lazcoz Sáez, Ruth ORCID
Leanizbarrutia Alonso, Iker
Salzano, Vincenzo
Metadata
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European Physical Journal C 78(1) : (2018) // Article ID 11
URI
http://hdl.handle.net/10810/27725
Laburpena
The cosmological redshift drift could lead to the next step in high-precision cosmic geometric observations, becoming a direct and irrefutable test for cosmic acceleration. In order to test the viability and possible properties of this effect, also called Sandage-Loeb (SL) test, we generate a model-independent mock data set in order to compare its constraining power with that of the future mock data sets of Type Ia Supernovae (SNe) and Baryon Acoustic Oscillations (BAO). The performance of those data sets is analyzed by testing several cosmological models with the Markov chain Monte Carlo (MCMC) method, both independently as well as combining all data sets. Final results show that, in general, SL data sets allow for remarkable constraints on the matter density parameter today Omega(m) on every tested model, showing also a great complementarity with SNe and BAO data regarding dark energy parameters.
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This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecomm ons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Funded by SCOAP3. Attribution 4.0 International (CC BY 4.0) Share — copy and redistribute the material in any medium or format Adapt — remix, transform, and build upon the material for any purpose, even commercially.
Bestelakorik adierazi ezean, itemaren baimena horrela deskribatzen da:This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecomm ons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Funded by SCOAP3. Attribution 4.0 International (CC BY 4.0) Share — copy and redistribute the material in any medium or format Adapt — remix, transform, and build upon the material for any purpose, even commercially.