Galaxies, Cosmology and the SKA Catherine Cress (UWC)

Galaxies, Cosmology and the SKA

Catherine Cress (UWC)

Astrophysics People at UWC:

Prof Cress Prof Kilkenny Dr Loubser Dr Johnson Dr Mhlahlo Dr Olivier Prof Koen Dr Faltenbacher Dr Moeketsi

Postgraduates: Sean, Faustino, Fidy, Claudio, Ando, Daniel, Daniel, Solohery, Geoffrey

Undergraduates with SKA bursaries

A. Simulating radio sources: SKA/MeerKAT sources & CMB contamination

B. (New) Science for the SKA

1. Dark energy speed of sound measurements using clustering of HI-selected galaxies and HI-galaxy-CMB cross-correlation

2. Cosmology using the Tully-Fisher relation to measure >108 luminosity distances

Modelling SKA sources in simulations: radio galaxies, IR-bright galaxies application to CMB experiments

Involved in Atacama Cosmology Telescope project (new CMB experiment from WMAP team) to measure CMB fluctuations to 1 arcminute => can identify 1000's of clusters of galaxies via Sunyaev-Zeldovich effect => w constraints

but need to worry about contamination by point sources: starforming galaxies bright in IR and into mm radio galaxies: some bright into mm (most WMAP point sources blazars) => SZ spectral signature more difficult to identify

0 0.5 1 1.5 z

Modelling SKA sources in simulations:

N-body simulation flavours:

Dark Matter only:represent ~105-108 Mas a single particleallow particles to interact gravitationallygives info on non-linear evolution of density fluctuations

Dark Matter+Semi-Analytic Modelsidentify halos (clumps) in dark matter simulationtrace merger history of halosuse basic physics (gas cooling etc.) to paint galaxies

Dark Matter + Smoothed Particle Hydrodynamics model gas explicitly can add in star formation etc., depending on application

Dark Matter Simulation run at CHPC17 million particles, 50Mpc side

for more pictures contact Daniel Cunnama ([email protected])

Modelling AGN and Starforming Galaxies in Simulations

Dark Matter+Semi-Analytic Modelsidentify halos (clumps) in dark matter simulationtrace merger history of halosuse basic physics (gas cooling etc.) to paint galaxies

AGN modelled using radio-mode and quasar mode accretion

radio-mode: hot halo gas slowly accretes onto central black hole model by tracking change in black-hole mass of galaxies in sim

quasar mode: in mergers of galaxies gas driven to centre: rapid accretion model by tracking major mergers of galaxies

Starforming Galaxies: Far-infrared luminosity given be starformation rate (extrapolated to CMB frequencies using known SED's) Radio brightness ~ to FIR in starforming galaxies

Modelling radio-loud AGN in Simulations

AGN modelled using radio-mode and quasar mode accretion

Modelling Starforming Galaxies in Simulations with Daniel Opolot

Far-infrared luminosity given by starformation rate: simulated vs observed densities rho(z):

Consider starforming galaxies nearclusters of galaxies (potential contaminants to CMB)

Modelling Starforming Galaxies in Simulations

Far-infrared luminosity given by starformation rate: LFIR= k.SFR CMB contamination:

typical thermalSZ ~200Ktypical kineticSZ ~20K

=> significant contaminationfrom IR-bright sources

Sources not randomly distributedin clusters as in Sehgal et al 09

Potential to remove sources using optical/IR/radio data.

What do we learn about galaxy evolution?: IR-bright galaxies modelled here consistent with (some) observations => support for galaxy evolution theory used here

Science for SKA 1. What is dark energy? (dark matter = ? with normal gravitational interaction; dark energy=? with weird grav. int.)

Aside: How do you test cosmological models?

1. Expansion rate of universe depends on amount of DM and DE affects how bright objects look and how big they look eg supernovae, BAO

2. Evolution of clustering depends on amount of DM and DE in universe with no DE, structures form late (counting clusters => contraints)

3. Dark matter affects many observables eg. rotation curves, velocity dispersions in clusters, gravitational LENSING

Science for SKA 1. What is dark energy? (dark matter = ? with normal gravitational interaction; dark energy=? with weird grav. int.) Cosmological constant? w=-1 in P=w

Dynamical scalar field? (-1

Science for the SKA 1.

Integrated Sachs Wolfe anisotropiesVarying gravitational potentialMatter-dominated Universecurvature or DE-dominated UniverseCMBInduces a secondary layer of large-scale anisotropiesNo ISWISWPrimary anisotropies

Science for SKA 1.

Clustering to probe dark energy sound speed

galaxiesanisotropiesISWanisotropiesISW-galaxies cross-correlationGalaxy autocorrelationUse of CAMBCMB spectrum: ClTT

Science for the SKA 1

Constraints on DE sound speeds possible for low speeds

Torres-Rodriguez & Cress MNRAS 2007

Science for SKA 1

Fisher matrix analysis with marginalizationUncertainties related to bias questions?

Torres-Rodriguez, Cress & Moodley, MNRAS 2008

Science for the SKA 2: Cosmology using Tully-Fisher relation

Using the Tully-Fisher relation to measure the luminosity distance (dL) to 100's of millions of galaxies. Flux=Luminosity/4 dL2 (also, m-M=5log(dL/10pc))and dL=dL(m,,DE,w0,wa etc)

Tully-Fisher Relation: intrinsic luminosity of spiral galaxy obtained from rotation speed

Rotation speed can be measured by broadening of HI-21cm line

anLog V

Science for the SKA 2: Cosmology using Tully-Fisher relation

Investigate constraints on standard cosmological parameters using HI-survey

Create simulated catalog of galaxies * start with local HI-mass function, model evolution using absorption system info

* assume flux limit=> observable HI-mass (function of z)

* HI+cosmology+modelling =>dark matter halo mass ass'd with HI-mass => rotation velocity

* random inclinations

* assume TFR holds => absolute magnitude in specific band.

* Uncertainties: - assume TFR accurate to 10%, allow 5-10% error on photometry- velocity errors given by spectral resolution & redshift in line fitting simulation

Torres-Rodriguez, Cress & Moodley , submitted


Instead of trying to measure inclination for every galaxy, rather use the fact that inclinationsshould be random on large scales.

Group simulated galaxies into redshift bins and magnitude bins.Consider distribution of velocities:

apparent magnitude vs Vrot at z=0.1,0.5,1

m=24, z=0.2

for 100 sq deg survey


luminosity distance uncertainties:


Constraints on standarddark energy parameters for different surveys specs. Fiducial: dv=30km/s, dz=0.01100 sq deg., dMass=0.01

weff=w0+(1-a)wa

5% Photometric errors:

Dark Energy Task Force Stage IV:

Torres-Rodriguez, Moodley & Cress submitted

Science for the SKA 2: Tully-Fisher

5% Photometric errors:

Dark Energy Task Force Stage IV:



Using TFR: questions

Evolution of the TFR? Stellar mass TFR? Baryonic TFR? Combine Vrot & Vdisp? (ala Kassin)Extinction?

NB: * can marginalise over evolution parameters. * can calibrate TFR at high-z using SNIa


Summary:

IR-bright sources & blazars contaminants for SZ effect

Can produce maps of radio sources from simulation: AGN + IR-bright sources (which are also faint radio sources)

SKA science: Dark energy sound speed from Cgg, Ctt, Cgt : Tully-Fisher to get luminosity distances => strong constraints on dark energy

Future:Publish IR source contamination, more work on radio sourcesGas in CHPC hydrosim: insight into HI evolution

Tully-Fisher details for SKA science

*

Summary:

IR-bright sources & blazars contaminants for SZ effect

Can produce maps of radio sources from simulation: AGN + IR-bright sources (which are also faint radio sources)

SKA science: Dark energy sound speed from Cgg, Ctt, Cgt : Tully-Fisher to get luminosity distances => strong constraints on dark energy

Angel Torres Rodriguez

HI observations with KAT:M31 at z=0.001 with 2km, 500m and 200m baselines

Large beams: confusion, even in redshift space

SKA site bid preparation(using AIPS) (including HI, protoplanetary disk and reionisation research)

Clustering of HI-selected galaxies

* Sean: Clustering of HI-detected galaxies: Useful for SKA predictions and understanding how luminous matter traces dark matter Also working on radio source luminosity functions with Oxford group (NB for MeerKAT and SKA)

Structure Evolution Observations Constrain w

structure = galaxies, clusters of galaxies, superclusters etc

Structure forms through gravitational collapse of density fluctuations seen in the CMB.

How structure evolves and how it appears to us depends on cosmological parameters

Effect of varying w on number density of clusters over a given SZ detection threshold

Top to bottom at peak: w= -1, -0.6, -0.3, 0

Haiman et al (2001)

0 0.5 1 1.5 z

ACT

Need to measure redshifts of clusters and velocity dispersions somass of clusters can be estimated

200 sq. degrees => ~1000 clusters

Spectroscopic follow-up on cluster candidates once SZ data available(including deep imaging in cluster region)

Deep optical survey in whole strip to allow detection of CMB lensingand kinetic SZ effect?

Survey good for other observational projects

Xray Optical SZ at 2mm

SALT and ACTA photometric survey to detect KSZ?

The kinetic SZ-effect:

bulk motion of hot gas upscatters photons to higher frequencies=> probe of velocities=> probe of potentials

Constraints on cosmological params:5-10% errors on w with some infoon w(z) (astroph0511061)

SALT and ACT

A case for a photometric survey in the ACT strip?

Weak lensing of CMB: probe dark matter directly at high-z

Kinetic SZ: stronger constraints on cosmological parameters direct probe of potentials at high-z

Properties of galaxies in outskirts of clusters

Faint QSO properties: implications for black hole growth (lensed) QSO's at very high-z Variability studies: SNIa -> cosmology

Stars

Additional data available: XMM, Galex, SpitzerAdditional support: Indians and Rutgers prepared to commit time

SALT and ACTHPC Simulations

Point source simulations: with Sarah Bryan (PhD student, worked with ACT team in Princeton)and Fidy Ramamonjisoa (NASSP Honours student)

* radio & IR galaxies contaminate CMB signal * so far these sources have been randomly distributed in simulations * need to include clustering (possibly preferentially in clusters)

* Using galaxies simulated in Millenium simulation * investigating the semi-analytic modelling of IR, mm and radio emission in galaxies * aim to include clustering of contaminant sources in CMB maps and to improve SAMs

SALT and PLANCKSpanish Collaboration involving HPC Simulations

Xray Optical SZ at 2mm

SALT and ACTSummary

New generation CMB expt from WMAP team flucts on smaller scales than WMAP

Need to measure redshifts of clusters detected in SZ and and velocity dispersions somass of clusters can be estimated. 200 sq. degrees => ~1000 clusters

Spectroscopic follow-up on cluster candidates once SZ data available(including deep imaging in cluster region)

Deep optical survey in whole strip to allow detection of CMB lensing and kinetic SZ effect - good for other observational projects - varibility (SNIa/stars), qso's, clustersGALEX, XMM, Spitzer? data in same field. India, Rutgers prepared to commit time.

Point source simulations include clustering of radio & IR galaxies as could hamperSZ cluster extractionXray Optical SZ at 2mm

Summary

CMB/Large-scale structure combination probes cosmological parameters and relationship between dark and luminous matter.

ACT: many clusters via SZ effect spectroscopic follow up with SALT photometric survey for KSZ, weak lensing, qso's etc? simulations to include clustering of point sources

SKA: sound speed of dark energy understanding radio source populations

HPC: simulations to look at figure rotation of halos => galactic dynamics new opportunities with CHPC: CMB foregrounds, meerKAT science

Real Galaxies:Galaxies simulated within underlying dark matter structures:Can reproduce properties of galaxies fairly well in Cold Dark Matter scenarioBut some problems eg. Angular momentum problem .. Need additions to simple CDM theory?

Simulating the Radio Sky: two goals

1. Compare predictions of CDM + galaxy evolution models with observations* HI sources* Radio continuum sources* CMB foregrounds - see talks by Opolot and Ramamonjisoa

2. Make fake skies for MeerKAT/SKA Simulations we are working with:

1. DM only simulation on CHPC (2563 particle): test run for CHPC

2. GIMIC simulation on CHPC (with Theuns): Gas + DM, 400*106 particles, 32MPc box

3. Millenium simulation (already run, with semi-analytic modelling to get galaxy properties, query with SQL)

Documents

Galaxies, Cosmology and the SKA Catherine Cress (UWC)