Estimating redshift distributions using Hierarchical Logistic Gaussian processes

@article{Rau2020EstimatingRD,
  title={Estimating redshift distributions using Hierarchical Logistic Gaussian processes},
  author={M. Rau and S. Wilson and R. Mandelbaum},
  journal={Monthly Notices of the Royal Astronomical Society},
  year={2020},
  volume={491},
  pages={4768-4782}
}
  • M. Rau, S. Wilson, R. Mandelbaum
  • Published 2020
  • Physics
  • Monthly Notices of the Royal Astronomical Society
  • This work uses hierarchical logistic Gaussian processes to infer true redshift distributions of samples of galaxies, through their cross-correlations with spatially overlapping spectroscopic samples. We demonstrate that this method can accurately estimate these redshift distributions in a fully Bayesian manner jointly with galaxy-dark matter bias models. We forecast how systematic biases in the redshift-dependent galaxy-dark matter bias model affect redshift inference. Using published galaxy… CONTINUE READING
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