Deutsch
 
Hilfe Datenschutzhinweis Impressum
  DetailsucheBrowse

Datensatz

DATENSATZ AKTIONENEXPORT

Freigegeben

Zeitschriftenartikel

Cosmology inference from a biased density field using the EFT-based likelihood

MPG-Autoren
/persons/resource/persons16100

Elsner,  Franz
Cosmology, MPI for Astrophysics, Max Planck Society;

/persons/resource/persons133110

Schmidt,  Fabian
High Energy Astrophysics, MPI for Astrophysics, Max Planck Society;

/persons/resource/persons230599

Nguyen,  Nhat Minh
Physical Cosmology, MPI for Astrophysics, Max Planck Society;

Externe Ressourcen
Es sind keine externen Ressourcen hinterlegt
Volltexte (beschränkter Zugriff)
Für Ihren IP-Bereich sind aktuell keine Volltexte freigegeben.
Volltexte (frei zugänglich)
Es sind keine frei zugänglichen Volltexte in PuRe verfügbar
Ergänzendes Material (frei zugänglich)
Es sind keine frei zugänglichen Ergänzenden Materialien verfügbar
Zitation

Elsner, F., Schmidt, F., Jasche, J., Lavaux, G., & Nguyen, N. M. (2020). Cosmology inference from a biased density field using the EFT-based likelihood. Journal of Cosmology and Astroparticle Physics, 2020(1): 029. doi:10.1088/1475-7516/2020/01/029.


Zitierlink: https://hdl.handle.net/21.11116/0000-0006-8FA9-B
Zusammenfassung
The effective-field-theory (EFT) approach to the clustering of galaxies and other biased tracers allows for an isolation of the cosmological information that is protected by symmetries, in particular the equivalence principle, and thus is robust to the complicated dynamics of dark matter, gas, and stars on small scales. All existing implementations proceed by making predictions for the lowest-order n-point functions of biased tracers, as well as their covariance, and comparing with measurements. Recently, we presented an EFT-based expression for the conditional probability of the density field of a biased tracer given the matter density field, which in principle uses information from arbitrarily high order n-point functions. Here, we report results based on this likelihood by applying it to halo catalogs in real space, specifically an inference of the power spectrum normalization σ8. We include bias terms up to second order as well as the leading higher-derivative term. For a cutoff value of Λ = 0.1 hMpc−1, we recover the ground-truth value of σ8 to within 95% CL for different halo samples and redshifts. We discuss possible sources for the remaining systematic bias in σ8 as well as future developments.