2017
DOI: 10.1093/mnras/stx152
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Performance study of Lagrangian methods: reconstruction of large scale peculiar velocities and baryonic acoustic oscillations

Abstract: NoAM for "No Action Method" is a framework for reconstructing the past orbits of observed tracers of the large scale mass density field. It seeks exact solutions of the equations of motion (EoM), satisfying initial homogeneity and the final observed particle (tracer) positions. The solutions are found iteratively reaching a specified tolerance defined as the RMS of the distance between reconstructed and observed positions. Starting from a guess for the initial conditions, NoAM advances particles using standard… Show more

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Cited by 12 publications
(10 citation statements)
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“…We use 30 mock catalogs of 2MRS extracted by Keselman & Nusser (2016) Table 3 in Planck Collaboration et al 2016). These are dark matter only simulations, but baryonic feedback is too weak to play any significant role over the relevant level of accuracy and scales considered (Hellwing et al 2016) The simulations are available with 5 different resolutions.…”
Section: Mock Catalogsmentioning
confidence: 99%
“…We use 30 mock catalogs of 2MRS extracted by Keselman & Nusser (2016) Table 3 in Planck Collaboration et al 2016). These are dark matter only simulations, but baryonic feedback is too weak to play any significant role over the relevant level of accuracy and scales considered (Hellwing et al 2016) The simulations are available with 5 different resolutions.…”
Section: Mock Catalogsmentioning
confidence: 99%
“…It has been shown in Keselman & Nusser (2017) that for scales 5 ℎ −1 Mpc such a linear reconstruction yields generally better results than nonlinear methods when applied to realistic mock redshift catalogues. The authors of Keselman & Nusser (2017) suspect this to be caused by the higher sensitivity of nonlinear reconstructions to the information on small scales, which are more strongly contaminated by non-linear RSDs (e. g. fingers-of-god) and selection effects. Altogether, this yields a numerically very efficient, conservative reconstruction algorithm.…”
Section: Introductionmentioning
confidence: 99%
“…Gravitational evolution modifies the shape of the feature, potentially biasing and degrading the cosmological constraints which current and future datasets can provide. This has driven the development of many algorithms which seek to restore the feature to its original shape [5][6][7][8][9][10][11][12].…”
Section: Introductionmentioning
confidence: 99%