The Atacama Cosmology Telescope: Probing the large scale structure with ACT DR6 CMB lensing and cross-correlation with unWISE
APA
Farren, G. (2023). The Atacama Cosmology Telescope: Probing the large scale structure with ACT DR6 CMB lensing and cross-correlation with unWISE. Perimeter Institute. https://pirsa.org/23100120
MLA
Farren, Gerrit. The Atacama Cosmology Telescope: Probing the large scale structure with ACT DR6 CMB lensing and cross-correlation with unWISE. Perimeter Institute, Oct. 31, 2023, https://pirsa.org/23100120
BibTex
@misc{ pirsa_PIRSA:23100120, doi = {10.48660/23100120}, url = {https://pirsa.org/23100120}, author = {Farren, Gerrit}, keywords = {Cosmology}, language = {en}, title = {The Atacama Cosmology Telescope: Probing the large scale structure with ACT DR6 CMB lensing and cross-correlation with unWISE}, publisher = {Perimeter Institute}, year = {2023}, month = {oct}, note = {PIRSA:23100120 see, \url{https://pirsa.org}} }
I will present work on probing the large scale structure of the universe using CMB lensing from the upcoming Data Release 6 of the Atacama Cosmology Telescope (ACT) and cross-correlations with galaxies from the unWISE galaxy catalog. My talk will focus on how our highly competitive constraints from CMB lensing and CMB lensing cross-correlations can provide insight into the widely discussed “S8/sigma8 tension”. For this purpose I will briefly introduce the high fidelity CMB lensing reconstruction obtained by the ACT Collaboration and results from the analysis of the lensing auto-correlation. I will discuss new results from the cross-correlation between ACT CMB lensing and unWISE galaxies, highlighting improvements to the analysis pipeline compared to previous work on the cross-correlation between Planck CMB lensing and unWISE by some of my collaborators (Krolewski et al. 2021). I will also show a reanalysis of Planck CMB lensing x unWISE and a joined analysis of the ACT and Planck CMB lensing cross-correlations with unWISE.
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Zoom link https://pitp.zoom.us/j/99192611116?pwd=TU9iMjhrejVESjNRdi92M0ZXN2ZEQT09