We propose a new way of looking at the Baryon Acoustic Oscillation in the large-scale-structure clustering correlation function. We identify a scale SLP that has two fundamental features: its position is insensitive to non-linear gravity, redshift-space distortions and scale-dependent bias at the 0.5 per cent level; it is geometrical, i.e. independent of the power spectrum of the primordial density fluctuation parameters. These two properties together make SLP, called the 'linear point', an excellent cosmological standard ruler. The linear point is also appealing because it is easily identified irrespectively of how non-linearities distort the correlation function. Finally, the correlation function amplitude at SLP is similarly insensitive to nonlinear corrections to within a few per cent. Hence, exploiting the particular baryon features in the correlation function, we propose three new estimators for growth measurements. A preliminary analysis of SLP in current data is encouraging.

Beating non-linearities: improving the baryon acoustic oscillations with the linear point

Stefano Anselmi
;
2015

Abstract

We propose a new way of looking at the Baryon Acoustic Oscillation in the large-scale-structure clustering correlation function. We identify a scale SLP that has two fundamental features: its position is insensitive to non-linear gravity, redshift-space distortions and scale-dependent bias at the 0.5 per cent level; it is geometrical, i.e. independent of the power spectrum of the primordial density fluctuation parameters. These two properties together make SLP, called the 'linear point', an excellent cosmological standard ruler. The linear point is also appealing because it is easily identified irrespectively of how non-linearities distort the correlation function. Finally, the correlation function amplitude at SLP is similarly insensitive to nonlinear corrections to within a few per cent. Hence, exploiting the particular baryon features in the correlation function, we propose three new estimators for growth measurements. A preliminary analysis of SLP in current data is encouraging.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3472941
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