### Abstract

We study the methodology and potential theoretical systematics of measuring baryon acoustic oscillations (BAO) using the angular correlation functions in tomographic bins. We calibrate and optimize the pipeline for the Dark Energy Survey Year 1 data set using 1800 mocks. We compare the BAO fitting results obtained with three estimators: the Maximum Likelihood Estimator (MLE), Profile Likelihood, and Markov ChainMonte Carlo. The fit results from the MLE are the least biased and their derived 1σ error bar are closest to the Gaussian distribution value after removing the extreme mocks with non-detected BAOsignal. We showthat incorrect assumptions in constructing the template, such as mismatches from the cosmology of themocks or the underlying photo-z errors, can lead to BAO angular shifts. We find that MLE is the method that best traces this systematic biases, allowing to recover the true angular distance values. In a real survey analysis, it may happen that the final data sample properties are slightly different from those of the mock catalogue. We show that the effect on the mock covariance due to the sample differences can be corrected with the help of the Gaussian covariance matrix or more effectively using the eigenmode expansion of the mock covariance. In the eigenmode expansion, the eigenmodes are provided by some proxy covariance matrix. The eigenmode expansion is significantly less susceptible to statistical fluctuations relative to the direct measurements of the covariance matrix because of the number of free parameters is substantially reduced.

Original language | English (US) |
---|---|

Pages (from-to) | 3031-3051 |

Number of pages | 21 |

Journal | Monthly Notices of the Royal Astronomical Society |

Volume | 480 |

Issue number | 3 |

DOIs | |

State | Published - Jan 1 2018 |

### Fingerprint

### Keywords

- Cosmology: observations
- Large-scale structure of Universe

### ASJC Scopus subject areas

- Astronomy and Astrophysics
- Space and Planetary Science

### Cite this

*Monthly Notices of the Royal Astronomical Society*,

*480*(3), 3031-3051. https://doi.org/10.1093/MNRAS/STY2036

**BAO from angular clustering : Optimization and mitigation of theoretical systematics.** / DES Collaboration.

Research output: Contribution to journal › Article

*Monthly Notices of the Royal Astronomical Society*, vol. 480, no. 3, pp. 3031-3051. https://doi.org/10.1093/MNRAS/STY2036

}

TY - JOUR

T1 - BAO from angular clustering

T2 - Optimization and mitigation of theoretical systematics

AU - DES Collaboration

AU - Chan, K. C.

AU - Crocce, M.

AU - Ross, A. J.

AU - Avila, S.

AU - Elvin-Poole, J.

AU - Manera, M.

AU - Percival, W. J.

AU - Rosenfeld, R.

AU - Abbott, T. M.C.

AU - Abdalla, F. B.

AU - Allam, S.

AU - Bertin, E.

AU - Brooks, D.

AU - Burke, D. L.

AU - Rosell, A. Carnero

AU - Kind, M. Carrasco

AU - Carretero, J.

AU - Castander, F. J.

AU - Cunha, C. E.

AU - D'Andrea, C. B.

AU - da Costa, L. N.

AU - Davis, C.

AU - De Vicente, J.

AU - Eifler, T. F.

AU - Estrada, J.

AU - Flaugher, B.

AU - Fosalba, P.

AU - Frieman, J.

AU - García-Bellido, J.

AU - Gaztanaga, E.

AU - Gerdes, D. W.

AU - Gruen, D.

AU - Gruendl, R. A.

AU - Gschwend, J.

AU - Gutierrez, G.

AU - Hartley, W. G.

AU - Honscheid, K.

AU - Hoyle, B.

AU - James, D. J.

AU - Krause, E.

AU - Kuehn, K.

AU - Lahav, O.

AU - Lima, M.

AU - March, M.

AU - Menanteau, F.

AU - Miller, C. J.

AU - Miquel, R.

AU - Plazas, A. A.

AU - Reil, K.

AU - Roodman, A.

PY - 2018/1/1

Y1 - 2018/1/1

N2 - We study the methodology and potential theoretical systematics of measuring baryon acoustic oscillations (BAO) using the angular correlation functions in tomographic bins. We calibrate and optimize the pipeline for the Dark Energy Survey Year 1 data set using 1800 mocks. We compare the BAO fitting results obtained with three estimators: the Maximum Likelihood Estimator (MLE), Profile Likelihood, and Markov ChainMonte Carlo. The fit results from the MLE are the least biased and their derived 1σ error bar are closest to the Gaussian distribution value after removing the extreme mocks with non-detected BAOsignal. We showthat incorrect assumptions in constructing the template, such as mismatches from the cosmology of themocks or the underlying photo-z errors, can lead to BAO angular shifts. We find that MLE is the method that best traces this systematic biases, allowing to recover the true angular distance values. In a real survey analysis, it may happen that the final data sample properties are slightly different from those of the mock catalogue. We show that the effect on the mock covariance due to the sample differences can be corrected with the help of the Gaussian covariance matrix or more effectively using the eigenmode expansion of the mock covariance. In the eigenmode expansion, the eigenmodes are provided by some proxy covariance matrix. The eigenmode expansion is significantly less susceptible to statistical fluctuations relative to the direct measurements of the covariance matrix because of the number of free parameters is substantially reduced.

AB - We study the methodology and potential theoretical systematics of measuring baryon acoustic oscillations (BAO) using the angular correlation functions in tomographic bins. We calibrate and optimize the pipeline for the Dark Energy Survey Year 1 data set using 1800 mocks. We compare the BAO fitting results obtained with three estimators: the Maximum Likelihood Estimator (MLE), Profile Likelihood, and Markov ChainMonte Carlo. The fit results from the MLE are the least biased and their derived 1σ error bar are closest to the Gaussian distribution value after removing the extreme mocks with non-detected BAOsignal. We showthat incorrect assumptions in constructing the template, such as mismatches from the cosmology of themocks or the underlying photo-z errors, can lead to BAO angular shifts. We find that MLE is the method that best traces this systematic biases, allowing to recover the true angular distance values. In a real survey analysis, it may happen that the final data sample properties are slightly different from those of the mock catalogue. We show that the effect on the mock covariance due to the sample differences can be corrected with the help of the Gaussian covariance matrix or more effectively using the eigenmode expansion of the mock covariance. In the eigenmode expansion, the eigenmodes are provided by some proxy covariance matrix. The eigenmode expansion is significantly less susceptible to statistical fluctuations relative to the direct measurements of the covariance matrix because of the number of free parameters is substantially reduced.

KW - Cosmology: observations

KW - Large-scale structure of Universe

UR - http://www.scopus.com/inward/record.url?scp=85055143485&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85055143485&partnerID=8YFLogxK

U2 - 10.1093/MNRAS/STY2036

DO - 10.1093/MNRAS/STY2036

M3 - Article

AN - SCOPUS:85055143485

VL - 480

SP - 3031

EP - 3051

JO - Monthly Notices of the Royal Astronomical Society

JF - Monthly Notices of the Royal Astronomical Society

SN - 0035-8711

IS - 3

ER -