A new fully non-linear reconstruction algorithm for the accurate recovery of the baryonic acoustic oscillations (BAO) scale in two-point correlation functions is proposed, based on the least action principle and extending the Fast Action Minimisation method by Nusser & Branchini (2000). Especially designed for massive spectroscopic surveys, it is tested on dark matter halo catalogues extracted from the DEUS-FUR Lambda cold dark matter simulation (Reverdy et al. 2015) to trace the trajectories of up to {˜ }207 000 haloes backward in time, well beyond the first-order Lagrangian approximation. The new algorithm successfully recovers the BAO feature in real and redshift space in both the monopole and the anisotropic two-point correlation function, also for anomalous samples showing misplaced or absent signature of BAO. In redshift space, the non-linear displacement parameter ΣNL is reduced from 11.8± 0.3 h^{-1} Mpc at redshift z = 0 to 4.0± 0.5 h^{-1} Mpc at z ≃ 37 after reconstruction. A comparison with the first-order Lagrangian reconstruction is presented, showing that these techniques outperform the linear approximation in recovering an unbiased measurement of the acoustic scale.

Sarpa, E., Schimd, C., Branchini, E., Matarrese, S. (2019). BAO reconstruction: a swift numerical action method for massive spectroscopic surveys. MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, 484(3), 3818-3830 [10.1093/mnras/stz278].

BAO reconstruction: a swift numerical action method for massive spectroscopic surveys

Branchini, E
Membro del Collaboration Group
;
2019-01-01

Abstract

A new fully non-linear reconstruction algorithm for the accurate recovery of the baryonic acoustic oscillations (BAO) scale in two-point correlation functions is proposed, based on the least action principle and extending the Fast Action Minimisation method by Nusser & Branchini (2000). Especially designed for massive spectroscopic surveys, it is tested on dark matter halo catalogues extracted from the DEUS-FUR Lambda cold dark matter simulation (Reverdy et al. 2015) to trace the trajectories of up to {˜ }207 000 haloes backward in time, well beyond the first-order Lagrangian approximation. The new algorithm successfully recovers the BAO feature in real and redshift space in both the monopole and the anisotropic two-point correlation function, also for anomalous samples showing misplaced or absent signature of BAO. In redshift space, the non-linear displacement parameter ΣNL is reduced from 11.8± 0.3 h^{-1} Mpc at redshift z = 0 to 4.0± 0.5 h^{-1} Mpc at z ≃ 37 after reconstruction. A comparison with the first-order Lagrangian reconstruction is presented, showing that these techniques outperform the linear approximation in recovering an unbiased measurement of the acoustic scale.
Sarpa, E., Schimd, C., Branchini, E., Matarrese, S. (2019). BAO reconstruction: a swift numerical action method for massive spectroscopic surveys. MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, 484(3), 3818-3830 [10.1093/mnras/stz278].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11590/346519
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