PIRSA:17010077

Complete Reionization Constraints with Planck 2015 Polarization

APA

He Heinrich, C. (2017). Complete Reionization Constraints with Planck 2015 Polarization. Perimeter Institute for Theoretical Physics. https://pirsa.org/17010077

MLA

He Heinrich, Chen. Complete Reionization Constraints with Planck 2015 Polarization. Perimeter Institute for Theoretical Physics, Jan. 19, 2017, https://pirsa.org/17010077

BibTex

          @misc{ scivideos_PIRSA:17010077,
            doi = {10.48660/17010077},
            url = {https://pirsa.org/17010077},
            author = {He Heinrich, Chen},
            keywords = {Quantum Matter},
            language = {en},
            title = {Complete Reionization Constraints with Planck 2015 Polarization},
            publisher = {Perimeter Institute for Theoretical Physics},
            year = {2017},
            month = {jan},
            note = {PIRSA:17010077 see, \url{https://scivideos.org/index.php/pirsa/17010077}}
          }
          

Chen He Heinrich University of Chicago

Talk numberPIRSA:17010077
Source RepositoryPIRSA

Abstract

I will present a recent analysis of the Planck 2015 data that is complete in the reionization observables from large angle CMB polarization measurements using principal components (PC). By allowing for an arbitrary ionization history, this technique tests the robustness of total optical depth inferences from the usual instantaneous reionization assumption. A reliable measurement of the total optical depth is important for the interpretation of many other cosmological parameters such as the dark energy and neutrino mass. We found that Planck 2015 data not only allow a high redshift z>15 component to the optical depth but prefer it at the 2σ level. This high redshift component contributes to a higher total optical depth than in the instantaneous reionization analysis, illustrating the need for a complete treatment of reionization in CMB data. I will further demonstrate the power of the PC method at efficiently constraining models with ionization history predictions, by applying our fast and effective likelihood code.