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

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

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

2\langle K \rangle = n\langle U \rangle

2\langle K \rangle = n\langle U \rangle

The Virial Theorem:

U = -\dfrac{GM}{R}

U = -\dfrac{GM}{R}

\langle K \rangle = -\dfrac{1}{2}\langle U \rangle

\langle K \rangle = -\dfrac{1}{2}\langle U \rangle

\dfrac{GM}{R} \approx \sigma^2

\dfrac{GM}{R} \approx \sigma^2

U(r) = ar^n

U(r) = ar^n

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