Dr Carolyn Devereux - Daphne Jackson Fellow Dr Jim Geach Prof. Martin Hardcastle. Centre for Astrophysics Research University of Hertfordshire, UK

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1 Millennium simulation of the cosmic web MEASUREMENTS OF THE LINEAR BIAS OF RADIO GALAXIES USING CMB LENSING FROM PLANCK Dr Carolyn Devereux - Daphne Jackson Fellow Dr Jim Geach Prof. Martin Hardcastle Centre for Astrophysics Research University of Hertfordshire, UK Funded by STFC

2 Matter Bias of Radio Galaxies Talk Outline: Measuring matter bias Galaxy catalogue (baryonic distribution) Planck CMB lensing (matter distribution) Methodology (cross-correlation) and results

3 Galaxy cosmic web 2dFGRS (2003)

4 Matter bias Fractional overdensity of the galaxy distribution (baryonic matter) to the total matter distribution matter bias = mean overdensity of galaxies - - mean overdensity of total matter

5 Bias dependence on galaxy properties Largest galaxies form within largest dark matter halos More luminous galaxies reside in more massive dark matter halos (Zehavi+2005) Red galaxies are more strongly clustered than blue (Zehavi+2011): related to morphology-density relation (early type galaxies are preferentially located in high density environments) Matter bias weakly scale dependent and on large scales bias is constant (linear) (Mann+1998)

6 Radio loud AGN Radio loud AGNs are massive galaxies and are expected to be strong tracers of the matter distribution therefore strongly correlated with CMB lensing AGN important in galaxy evolution (feedback). Curtail growth of bright end of luminosity function. Use Best and Heckman (B&H) (2012) radio galaxy catalogue (low redshift z~0.2) B&H catalogue: 18,286 radio galaxies identified from NVSS/FIRST using SDSS for optical identification (cross-matched to flux density level 5mJy). Catalogue includes redshift, flux density and whether radio-loud AGN or a star-forming galaxy.

7 Previous work on CMB lensing and galaxy cross-correlation WISE quasars/spt & Planck CMB lensing (Geach+2013) bias = 1.61 Galaxy/SPT CMB lensing (Bleem+2012) Wise bias = 0.9; Spitzer bias = 1.7; BCS bias = 1.2 Planck collaboration (2013); NVSS quasars bias = 1.7; SDSS LRGs bias = 2; BCG clusters bias = 3; WISE galaxy catalogue bias = 1 WISE & SDSS quasars/planck CMB lensing (DiPompeo +2015) obscured quasars bias = 2.57; unobscured quasars bias = 1.89

8 Planck CMB gravitational lensing potential map Masked to remove galactic plane and Sunyaev Zel dovich effects (~30% sky)

9 Weak Lensing of CMB Statistical detection of correlations CMB lensing traces the integrated mass along line-of-sight and is used to reconstruct the matter potential (Planck collaboration 2014) Lensing distorts the image of the CMB anisotropies; magnification, shear, rotation Causes smoothing of CMB temperature power spectrum and non- Gaussianity Lensing is weak; Shear ~1% on angular scale of few arc minutes Nearby light sources encounter same LSS so have same distortions and are correlated. Use statistical analysis of the correlations to calculate lensing potential

10 Lensing effect on CMB power spectrum From Anthony Lewis 2017

11 Lensing potential (from Lewis and Challinor 2006) Lensing remaps CMB fluctuations so temp anisotropy T in direction n given by: Tobserved(ñ) = Tunlensed(ñ+ ϕ(ñ)) Lensing potential ϕ: constructed using a quadratic estimator Lensing probes the matter distribution at high z (peaks at z~2)

12 Methodology B&H AGN catalogue used to calculate overdensity of the galaxies and mask to the survey area Cross-correlation of the 2 maps to create power spectrum (Binned) Calculate uncertainty using 100 simulations of the CMB lensing noise (from Planck collaboration). Determine standard deviation (at that angular mode) by calculating the full covariance matrix Model matter bias and optimise using least squares fit

13 Modelling bias Model cross-correlation using fitting formula of Eisenstein and Hu (1999) C(l) = [dz * (dχ/dz) * (1/χ 2 ) * Wk(χ) * Wg(χ) * P(k,z)] P(k,z): linear matter power spectrum (calculated using WMAP7_BAO_H0_mean environment (Kamatsu et al 2011)) Wk(χ): lensing kernel Wk(χ) = 3/2 * Ωm0 * (H0/c) 2 * ( χ/a(χ) )* (χcmb - χ)/(χcmb) Wg(χ): AGN distribution kernel Wg(X) = dz/dx * dn(z)/dz * b(χ) b(χ) is the bias dn(z)/dz is the normalised AGN redshift distribution l is the angular mode χ is the comoving distance z is the redshift k is the wavenumber k = l / ((1+z) * da(z) da = χ /(1+z) (the angular diameter distance) a(χ) is the scale factor = 1 / (1+z) χcmb comoving distance at z~1100 H0 is the Hubble parameter at z=0 Ωm0 ratio of matter density to critical density at z=0

14 Results Best and Heckman catalogue: over 9,000 AGN Size of maps (125 o x 125 o ). Centred on RA=184.6, DEC=32.6 (degrees) AGN redshift distribution Frequency Redshift

15 Cross correlation B&H AGN with Planck CMB lensing θ (degree) Bias = 3.2 ± significance ~ 3 σ Binned correlation data Modelled bias = 1 C l bias = l

16 Analysis Bias = 3 indicates AGN trace similar environment as groups and clusters. Expect AGNs to be within large galaxies and therefore clusters. Significance is low: low number of AGNs lost AGNs due to masking (incl. SZ masking) low redshift of AGN (z~0.2) whereas lensing peaks at z~2

17 Future work Redshift: If have several redshift bins at same luminosities then could see evolution. Luminosity: Is there a correlation between AGN luminosity and environment? More powerful AGN expected in more dense environment. AGN feedback? Statistics: Use LOFAR results; more AGN gives better statistics. Higher sensitivity can give higher significance and enable lower luminosity realm and redshift cuts to be investigated.