Cosmological constraints on nonadiabatic dark energy perturbations

The exact nature of dark energy is currently unknown and its cosmological perturbations, when dark energy is assumed not to be the cosmological constant, are usually modeled as adiabatic. Here we explore the possibility that dark energy might have a nonadiabatic component and we examine how it would...

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Detalles Bibliográficos
Autores: Arjona, Rubén, García-Bellido, Juan, Nesseris, Savvas
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2020
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/233261
Acceso en línea:http://hdl.handle.net/10261/233261
Access Level:acceso abierto
Descripción
Sumario:The exact nature of dark energy is currently unknown and its cosmological perturbations, when dark energy is assumed not to be the cosmological constant, are usually modeled as adiabatic. Here we explore the possibility that dark energy might have a nonadiabatic component and we examine how it would affect several key cosmological observables. We present analytical solutions for the growth rate and growth index of matter density perturbations and compare them to both numerical solutions of the fluid equations and an implementation in the Boltzmann code CLASS, finding that they all agree to well below one percent. We also perform a Monte Carlo analysis to derive constraints on the parameters of the nonadiabatic component using the latest cosmological data, including the temperature and polarization spectra of the cosmic microwave background as observed by Planck, the baryon acoustic oscillations, the Pantheon type Ia supernovae compilation and last, measurements of redshift space distortions (RSDs) of the growth rate of matter perturbations. We find that the amplitude of the nonadiabatic pressure perturbation is consistent with zero within 1σ. Finally, we also present a new, publicly available, RSD likelihood for MONTE PYTHON based on the "Gold 2018"growth-rate data compilation.