Large Scale Structure in 2MRS & 6dF Ofer Lahav (University College London) 6dF workshop, AAO/Sydney, April 2005

LSS in 2MRS The Local Group Dipole Wiener reconstruction Future work with 2MRS+2MASS+6dF Pirin Erdogdu (Cambridge/Ankara), John Huchra (CfA), Ofer Lahav (UCL) & the 2MRS/6dF teams

F 2MASS Galactic chart

The Near IR Local Universe

2MRS + mock ZoA ~25000 galaxies K s < Huchra & 2MRS/6dF teams Random ZoA Interpolated ZoA

2MRS vs. PSCz radial selection fn

Spectral PCA types in 2MASS 62% E’s in 2MASS 35% E’s in 2dF Madgwick, OL et al.

Dipole – weighting schemes  m 0.6 /b g / L/ (4  r 2 )  L = ( ) x 10 8 L_sun h Mpc -3

Number and Flux dipoles in the LG frame Mpc/h Mpc/h  m <  < b 2mrs > (for  m = 0.30) Erdogdu et al., In preparation

Out to 200 Mpc/h- LG frame

Number and Flux dipoles in the CMB frame

Out to 200 Mpc/h – CMB frame

Dipole – Wiener reconstruction  0.4  0.6

2MRS dipole 130 Mpc/h

Spherical harmonics

Wiener filtering ) Redshift distortion Signal/(Signal+Noise) Fisher, OL et al (1995)

WF 2000 km/sec Erdogdu et al.

WF 4000 km/sec

WF 6000 km/sec

WF km/sec

WF 2MRS velocity field CMB frame Erdogdu et al.

WF 2MRS velocity field LG frame

The Concordance Model Bulk flows are expected to have in linear theory: For  m < 1 lower amplitude and larger coherence length than in  m =1 universe Bulk flows are not sensitive to Dark Energy

Photometric redshifts

Photo-z Other work: * HYPERZ: Bolozonella et al., 2000, A&A, 363, 476 * Csabai et al,. 2003, AJ, 125, 580 ANNz: * Firth, Lahav & Somerville, 2003, MNRAS, 339, 1195 * Collister & Lahav, 2004, PASP, 116, Applications to: SDSS LRGs, Dark Energy Survey, 2MASS, …

Artificial Neural Network Output: redshift Input: magnitudes

SDSS data (ugriz; r < 17.77) ANNz (5:10:10:1) HYPERZ

DES (griz) 5-yr aloneDES + VISTA (YJHKs) Photo-z with ANNz  z = 0.13  z =0.08

2MASS + photo-z  z = 0.02 z=0 cyan z=0.05 yellow z=0.08 red Collister & Lahav, ANNz

The 2dFGRS Team Members I.J. Baldry, C.M. Baugh, J. Bland-Hawthorn, T.J. Bridges, R.D. Cannon, S. Cole, C.A. Collins, M. Colless (PI),W.J. Couch, N.G.J. Cross, G.B. Dalton, R. DePropris, S.P. Driver, G. Efstathiou, R.S. Ellis, C.S. Frenk, K. Glazebrook, E. Hawkins, C.A. Jackson, O. Lahav, I.J. Lewis, S.L. Lumsden, S. Maddox (PI), D.S. Madgwick, S. Moody, P. Norberg, J.A. Peacock (PI), B.A. Peterson, W. Sutherland, K. Taylor On 2dF Sociology see OL, astro-ph/

2dFGRS PhD students & collaborators Spectral classification (PCA): S. Folkes, S. Ronen, D. Madgwick Biasing from 2dF+CMB: S. Bridle Neutrino mass: O. Elgaroy Wiener Reconstruction: P. Erdogdu Stochastic Biasing: V. Wild Testing the halo model: A. Collister Ofer Lahav, UCL

Future work and London Compare predicted 2MRS peculiar velocities with observed 6dF pec vel. Combine 2MRS with 2MASS photo-z and 6dF Cosmological parameters Halo model & biasing The cosmic web Galaxy spectral classification Alexandra Abate, Sarah Bridle, Ofer Lahav, Anais Rassat

Clustering of Red vs. Blue 2dF galaxies Madgwick, Hawkins, Lahav & 2dFGRS team, astro-ph/

What’s next? The 6dF NIR Galaxy Survey 2MASS NIR selected 150k redshifts (Southern hemisphere) Peculiar Velocities for 15k galaxies  Reconstruction of the MASS distribution

Great Walls of the Universe

The 2dFGRS Power Spectrum 50 Mpc/h8 Mpc/h Linear Non- linear

The latest2dFGRS power spectrum Cole et al. 2005

The SDSS LRG correlation fn (Eisenstein et al 2005)

Weighing Neutrinos with 2dFGRS Free streaming effect:   /  m  < 0.13 Total mass M< 1.8 eV   (Oscillations) (2dF) a Four-Component Universe ? Elgaroy, Lahav & 2dFGRS team, astro-ph/ , PRL   =

Absolute Masses of Neutrinos Based on measured squared mass differences from solar and atmospheric oscillations Assuming m 1 < m 2 < m 3   Elgaroy& Lahav, JCAP 03

Ratio of bulk flows with massive neutrinos  =0.04 Elgaroy&Lahav, NJP, 2005

Principal Component Analysis Projections on the First two eigen- spectra Cf. traditional line indices

PCA for data compression (by a factor ~1000)  = 0.5 pc 1 – pc 2 Madgwick, OL et al.

Correlation Function per Type Madgwick & 2dFGRS Why a power law? dP / n [1+  (r)] dV  r) = (r/r 0 ) - 

An empirical test of the halo model P gal (k) = P gal (1h) (k) + P gal (2h) (k) The 1-halo term depends on the halo mass function, the halo occupation number the radial distribution of the galaxies within the halo The 2-halo also term depends on the above, roughly P gal (2h) (k)= b gal 2 P dm (lin) (k) Each of the three terms can actually be measured directly from e.g 2dFGRS: Is the model satisfied for all, blue and red galaxies? Collister & OL, astro-ph/

2dFGRS galaxy groups Eke et al. 2004

An empirical test of the halo model Non-linear clustering P(k) = P lin (k) + P halo (k) Co-added profile of 2dF groups Truncated NFW fit with C = A. Collister & OL, astro-ph/

The halo model P(k) = P lin (k) + P halo (k) Blue galaxies Red galaxies = (M/M 0 )  for M > M cut  1.05 § 0.19  = 0.88 § 0.17 C=3.9 § 0.5 C=1.3 § 0.2

Relative biasing (Blue/Red)

Future work and UCL Compare predicted 2MRS peculiar velocities with observed 6dF pec vel. Combine 2MRS with 2MASS photo-z and 6dF Cosmological parameters Halo model & biasing The cosmic web Galaxy spectral classification Alexandra Abate, Sarah Bridle, Ofer Lahav, Anais Rassat

University College London UCL 20 academic staff, 15 pos-docs, 35 PhDs, 15 support stuff Research Stellar Astrophysics, Star formation, Cosmology, Astro-Chemistry, Atmospheric Physics, Astro-biology, Instrumentation, Mill Hill Observatory & the MSSL Department