End-to-end simulations play a key role in the analysis of any high-sensitivity CMB experiment, providing high-fidelity systematic error propagation capabilities unmatched by any other means. In this paper, we address an important issue regarding such simula- tions, namely how to define the inputs in terms of sky model and instrument parameters. These may either be taken as a constrained realization derived from the data, or as a random realization independent from the data. We refer to these as Bayesian and fre- quentist simulations, respectively. We show that the two options lead to significantly different correlation structures, as frequentist simulations, contrary to Bayesian simulations, effectively include cosmic variance, but exclude realization-specific correlations from non-linear degeneracies. Consequently, they quantify fundamentally different types of uncertainties, and we argue that they therefore also have different and complementary scientific uses, even if this dichotomy is not absolute; Bayesian simulations are in general more convenient for parameter estimation studies, while frequentist simulations are in general more convenient for model testing. Before BeyondPlanck, most pipelines have used a mix of constrained and random inputs, and used the same hybrid simulations for all applications, even though the statistical justification for this is not always evident. BeyondPlanck represents the first end-to-end CMB simulation framework that is able to generate both types of simulations, and these new capabilities have brought this topic to the forefront. The Bayesian BeyondPlanck simulations and their uses are described extensively in a suite of companion papers. In this paper we consider one important applications of the corresponding frequentist simulations, namely code validation. That is, we gener- ate a set of 1-year LFI 30 GHz frequentist simulations with known inputs, and use these to validate the core low-level BeyondPlanck algorithms; gain estimation, correlated noise estimation, and mapmaking.

BeyondPlanck. IV. Simulations and validation / M. Brilenkov, K.S.F. Fornazier, L.T. Hergt, G.A. Hoerning, A. Marins, T. Murokoshi, F. Rahman, N.-. Stutzer, Y. Zhou, F.B. Abdalla, K.J. Andersen, R. Aurlien, R. Banerji, A. Basyrov, A. Battista, M. Bersanelli, S. Bertocco, S. Bollanos, L.P.L. Colombo, H.K. Eriksen, J.R. Eskilt, M.K. Foss, C. Franceschet, U. Fuskeland, S. Galeotta, M. Galloway, S. Gerakakis, E. Gjerløw, B. Hensle, D. Herman, T.D. Hoang, M. Ieronymaki, H.T. Ihle, J.B. Jewell, A. Karakci, E. Keihänen, R. Keskitalo, G. Maggio, D. Maino, M. Maris, S. Paradiso, B. Partridge, M. Reinecke, A.-. Suur-Uski, T.L. Svalheim, D. Tavagnacco, H. Thommesen, M. Tomasi, D.J. Watts, I.K. Wehus, A. Zacchei. - In: ASTRONOMY & ASTROPHYSICS. - ISSN 0004-6361. - 675:(2023 Jun 28), pp. A4.1-A4.15. [10.1051/0004-6361/202244958]

BeyondPlanck. IV. Simulations and validation

M. Bersanelli;L.P.L. Colombo;C. Franceschet;D. Maino;S. Paradiso
;
M. Tomasi;
2023

Abstract

End-to-end simulations play a key role in the analysis of any high-sensitivity CMB experiment, providing high-fidelity systematic error propagation capabilities unmatched by any other means. In this paper, we address an important issue regarding such simula- tions, namely how to define the inputs in terms of sky model and instrument parameters. These may either be taken as a constrained realization derived from the data, or as a random realization independent from the data. We refer to these as Bayesian and fre- quentist simulations, respectively. We show that the two options lead to significantly different correlation structures, as frequentist simulations, contrary to Bayesian simulations, effectively include cosmic variance, but exclude realization-specific correlations from non-linear degeneracies. Consequently, they quantify fundamentally different types of uncertainties, and we argue that they therefore also have different and complementary scientific uses, even if this dichotomy is not absolute; Bayesian simulations are in general more convenient for parameter estimation studies, while frequentist simulations are in general more convenient for model testing. Before BeyondPlanck, most pipelines have used a mix of constrained and random inputs, and used the same hybrid simulations for all applications, even though the statistical justification for this is not always evident. BeyondPlanck represents the first end-to-end CMB simulation framework that is able to generate both types of simulations, and these new capabilities have brought this topic to the forefront. The Bayesian BeyondPlanck simulations and their uses are described extensively in a suite of companion papers. In this paper we consider one important applications of the corresponding frequentist simulations, namely code validation. That is, we gener- ate a set of 1-year LFI 30 GHz frequentist simulations with known inputs, and use these to validate the core low-level BeyondPlanck algorithms; gain estimation, correlated noise estimation, and mapmaking.
Cosmology: observations; cosmic microwave background; diffuse radiation
Settore FIS/05 - Astronomia e Astrofisica
   Beyond Planck -- delivering state-of-the-art observations of the microwave sky from 30 to 70 GHz for the next decade
   Beyond Planck
   EUROPEAN COMMISSION
   H2020
   776282

   Time-domain Gibbs sampling: From bits to inflationary gravitational waves
   Bits2Cosmology
   European Commission
   Horizon 2020 Framework Programme
   772253

   Cosmoglobe -- mapping the universe from the Milky Way to the Big Bang
   Cosmoglobe
   European Commission
   Horizon 2020 Framework Programme
   819478
28-giu-2023
apr-2023
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/976568
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