Bayesian Data Analysis for Intensity Mapping and CMB Experiments
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Abstract
In the developing field of line intensity mapping (LIM), an approach to measuring the aggregate emission from various spectral lines in the early universe, as well as when searching for primordial B-modes in the Cosmic Microwave Background, we are looking for a weak signal where we not only need to integrate down large amounts of noise, but also have to control and remove instrumental systematics and foreground emission to a very high precision. This is the main challenge this thesis is grappling with. I outline the data analysis pipeline for COMAP, a LIM experiment targeting line emission from carbon monoxide in star forming regions in the early universe. We discuss everything from filtering and calibration of the raw data, to robust power spectrum estimation and astrophysical inference. Our preliminary results show that the measured power spectrum is consistent with white noise, which means that we are successfully suppressing all systematics to below white noise levels. I also discuss the BeyondPlanck project, an ambitious project to develop an end-to-end Bayesian data analysis pipeline for CMB experiments, where I worked on noise estimation, systematics and calibration.List of papers
Paper I: M. Foss, H. T. Ihle and the COMAP collaboration. “First Season COMAP Results: CO Data Processing” (draft). To be published. The paper is not available in DUO awaiting publishing. |
Paper II: H. T. Ihle and the COMAP collaboration. “First Season COMAP Results: Power spectrum methodology and preliminary data quality assessment” (draft). To be published. The paper is not available in DUO awaiting publishing. |
Paper III: H. T. Ihle, D. Chung, G. Stein and the COMAP collaboration. “Joint Power Spectrum and Voxel Intensity Distribution Forecast on the CO Luminosity Function with COMAP”. In: ApJ, Jan 2019, volume 871, no. 1 p. 75. DOI: 10.3847/1538-4357/aaf4bc. The article is included in the thesis. Also available at: https://doi.org/10.3847/1538-4357/aaf4bc |
Paper IV: The BeyondPlanck collaboration. “BeyondPlanck I. Global Bayesian analysis of the Planck Low Frequency Instrument data”. In: A&A, to be submitted. The paper is not available in DUO awaiting publishing. Preprint available in arXiv: 2011.05609 |
Paper V: H. T. Ihle, M. Bersanelli, C. Franceschet, E. Gjerløw and the BeyondPlanck collaboration. “BeyondPlanck VI. Noise characterization and modelling”. In: A&A, to be submitted. The paper is not available in DUO awaiting publishing. Preprint available in arXiv: 2011.06650 |
Paper VI: E. Gjerløw, H. T. Ihle, S. Galeotta and the BeyondPlanck collaboration. “BeyondPlanck VII. Bayesian estimation of gain and absolute calibration for CMB experiments”. In: A&A, to be submitted. The paper is not available in DUO awaiting publishing. Preprint available in arXiv: 2011.08082 |