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Improving baryon acoustic oscillation measurement with the combination of cosmic voids and galaxies
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Improving baryon acoustic oscillation measurement with the combination of cosmic voids and galaxies
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We develop a methodology to optimise the measurement of Baryon Acoustic Oscillation (BAO) from a given galaxy sample. In our previous work, we demonstrated that one can measure BAO from tracers in under-dense regions (voids). In this study, we combine the over-dense and under-dense tracers (galaxies & voids) to obtain better constraints on the BAO scale. To this end, we modify the de-wiggled BAO model with an additional parameter to describe both the BAO peak and the underlying exclusion pattern of void 2PCFs. We show that after applying BAO reconstruction to galaxies, the BAO peak scale of both galaxies and voids are unbiased using the modified model. Furthermore, we use a new 2PCF estimator for a multi-tracer analysis with galaxies and voids. In simulations, the joint sample improves by about 10% the constraint for the post-reconstruction BAO peak position compared to the result from galaxies alone, which is equivalent to an enlargement of the survey volume by 20%. Applying this method to the BOSS DR12 data, we have an 18% improvement for the low-z sample (0.2<z<0.5), but a worse constraint for the high-z sample (0.5<z<0.75), which is consistent with statistical fluctuations for the current survey volume. Future larger samples will give more robust improvements due to less statistical fluctuations.
Forward citations
Cited by 2 Pith papers
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Cosmic variance or galaxy bias? Disentangling finite-volume and galaxy formation effects in cosmological analysis
Develops a galaxy-biasing formalism for cosmic variance using perturbation theory and tests it on the non-linear BAO shift against N-body simulations.
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Cosmic variance or galaxy bias? Disentangling finite-volume and galaxy formation effects in cosmological analysis
Cosmic variance is modeled as Eulerian bias parameters of a finite-volume realization relative to the ensemble average, disentangling it from galaxy bias in the nonlinear BAO shift.
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