Cluster Cosmology from Velocity Dispersions
Joe Hollowed
DePaul University Science Showcase
November 4 2016
The Theory
Galaxy Clusters
- Largest and most recently collapsed objects in the universe (up to ~10 M☉ )
- Deriving estimators of cluster mass allows us to do cosmology
15
Hubble Space Telescope
November 2004
Heitmann et. al. 2015
The Data
South Pole Telescope
- Microwave, millimeter, submillimeter
- SPT-SZ Survey
- SPT-GMOS spectroscopic followup
SDSS 2.5m Telescope
Optical -
Sloan Digital Sky Survey -
BOSS -
Jose Francisco Salgado
kicp.uchicago.edu
Brian L. Lee
astro.ufl.edu
The Simulations
Q Continuum Simulation (1/16384 full sim)
Argonne National Laboratory
- Simulates gravity between trillions of particles over time, exhibits formation of clusters and the large scale "cosmic web"
- MIRA Supercomputer at ANL; 1.1 trillion mass particles resolving to ~10 M☉ in ~3Gpc box
9
Analysis and Correlation
Analysis
- SZ effect
- Richness
- Xray
- Weak Lensing
- Velocity Dispersions
Observational Analysis -
Analysis
Compare
Core Tracking -
Mock Catalogs -
Cluster Finders -
Observational Analysis -
Analysis
Compare
Core Tracking -
Mock Catalogs -
Cluster Finders -
Velocity Dispersions
The Virial Theorem:
Analysis
Velocity dispersion measurements done for SPT clusters with at least 15 member galaxies (83 of 104)
Analysis
Passive Galaxies
Post-starbust
Star-forming
Post-starburst +
Star-forming
Analysis
A trend can be seen in dispersion vs. mass plot, but we are lacking in both sample size and mass range
Error in dispersion measurement vs. cluster's spectroscopic member sample size
Analysis
- 209 additional clusters from SDSS via redMaPPer cluster catalog with >15 spectroscopic members
- Pair-wise analysis on clusters with <15 spec members, depending on valid BCG spectroscopic data
Analysis
- Velocity dispersions won't be reliable indicators of mass with poor statistics (clusters with <10-15 spectroscopic members).
- But even these clusters do have much larger photometric sample sizes; reliable richness estimates
- Pair-wise velocity dispersions (PVD's) measured on stacked clusters binned by richness allow relation to mass
Analysis
- 560 clusters total
- First time combining SPT-SZ and redmaPPer clusters for velocity dispersion mass scaling
- Relation looks promising
- Interested in potential sources of outliers with high member counts
Future Work
Further analysis of observational data:
- Quantify scatter and outliers in both the mass- dispersion relation, and the mass-richness relation
- Perhaps reduce scatter - more sophisticated interloper removal and velocity distribution fitting
- Quantify BCG bias on clusters which have sufficient data to find a reliable cluster redshift, independent of BCG selection
Future Work
Analysis
- SZ effect
- Richness
- Xray
- Weak Lensing
- Velocity Dispersions
Observational Analysis -
Analysis
Compare
Core Tracking -
Mock Catalogs -
Cluster Finders -
Observational Analysis -
Analysis
Correlation
Core Tracking -
Mock Catalogs -
Cluster Finders -
Future Work
- Comparisons in simulated/observed mass relations, and the scatter in this relation, between core-tracked mock catalogs and SDSS/SPT data, learn more about velocity bias
- Comparisons between stacked cluster analyses, including PVD analysis on mock catalogs as was done with SDSS data, learn more about BCG bias
Future Work
- Further comparisons to SPT- GMOS data once hydro sims are ready
- Paper? Would serve as a nice followup to previous work