May 23, 2017
11:30AM
-
12:30PM
McPherson 4054
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2017-05-23 10:30:00
2017-05-23 11:30:00
CCAPP Seminar: "Towards accurate cosmology with overlapping galaxy surveys" Ami Choi (OSU)
In cosmological analyses that measure lensing by large-scale structure, knowledge of the underlying redshift distribution of the galaxies is key. A full complement of spectroscopic measurements is expensive, and it is common to use lower resolution photometric information to constrain redshift distributions. However, these estimates can be biased at a level on par with the statistical precision of current lensing data sets. I will discuss how to leverage spatially overlapping CMB and spectroscopic (not necessarily representative of the photometric sample selection) surveys to control this photometric redshift bias and mitigate its effect on output cosmological parameters.
McPherson 4054
OSU ASC Drupal 8
ascwebservices@osu.edu
America/New_York
public
Date Range
2017-05-23 11:30:00
2017-05-23 12:30:00
CCAPP Seminar: "Towards accurate cosmology with overlapping galaxy surveys" Ami Choi (OSU)
In cosmological analyses that measure lensing by large-scale structure, knowledge of the underlying redshift distribution of the galaxies is key. A full complement of spectroscopic measurements is expensive, and it is common to use lower resolution photometric information to constrain redshift distributions. However, these estimates can be biased at a level on par with the statistical precision of current lensing data sets. I will discuss how to leverage spatially overlapping CMB and spectroscopic (not necessarily representative of the photometric sample selection) surveys to control this photometric redshift bias and mitigate its effect on output cosmological parameters.
McPherson 4054
America/New_York
public
In cosmological analyses that measure lensing by large-scale structure, knowledge of the underlying redshift distribution of the galaxies is key. A full complement of spectroscopic measurements is expensive, and it is common to use lower resolution photometric information to constrain redshift distributions. However, these estimates can be biased at a level on par with the statistical precision of current lensing data sets. I will discuss how to leverage spatially overlapping CMB and spectroscopic (not necessarily representative of the photometric sample selection) surveys to control this photometric redshift bias and mitigate its effect on output cosmological parameters.
