6533b835fe1ef96bd12a0170
RESEARCH PRODUCT
Primordial power spectrum features and f(NL) constraints
Stefano GariazzoLaura Lopez-honorezOlga Menasubject
Cosmology and Nongalactic Astrophysics (astro-ph.CO)astro-ph.COFOS: Physical sciencesFísicaAstrophysics::Cosmology and Extragalactic AstrophysicsAstrophysics - Cosmology and Nongalactic Astrophysicsdescription
The simplest models of inflation predict small non-gaussianities and a featureless power spectrum. However, there exist a large number of well-motivated theoretical scenarios in which large non-gaussianties could be generated. In general, in these scenarios the primordial power spectrum will deviate from its standard power law shape. We study, in a model-independent manner, the constraints from future large scale structure surveys on the local non-gaussianity parameter $f_{\rm NL}$ when the standard power law assumption for the primordial power spectrum is relaxed. If the analyses are restricted to the large scale-dependent bias induced in the linear matter power spectrum by non-gaussianites, the errors on the $f_{\rm NL}$ parameter could be increased by $60\%$ when exploiting data from the future DESI survey, if dealing with only one possible dark matter tracer. In the same context, a nontrivial bias $|\delta f_{\rm NL}| \sim 2.5$ could be induced if future data are fitted to the wrong primordial power spectrum. Combining all the possible DESI objects slightly ameliorates the problem, as the forecasted errors on $f_{\rm NL}$ would be degraded by $40\%$ when relaxing the assumptions concerning the primordial power spectrum shape. Also the shift on the non-gaussianity parameter is reduced in this case, $|\delta f_{\rm NL}| \sim 1.6$. The addition of Cosmic Microwave Background priors ensure robust future $f_{\rm NL}$ bounds, as the forecasted errors obtained including these measurements are almost independent on the primordial power spectrum features, and $|\delta f_{\rm NL}| \sim 0.2$, close to the standard single-field slow-roll paradigm prediction.
year | journal | country | edition | language |
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2015-06-17 |