Gong-Bo Zhao ICG, Portsmouth (PRL submitted) (PRL 11) (PRD 11) (PASP 11) (PRL 09) Understanding the Cosmic Acceleration using KDUST

My main collaborators Robert Crittenden (Portsmouth), Zuhui Fan (PKU) Aireza Hojjati (SFU), Kazuya Koyama (Portsmouth) Baojiu Li (Durham, Cambridge),Yinzhe Ma (UBC, Cambridge)Jeremiah Ostriker (Princeton, Cambridge), Levon Pogosian (SFU) Alessandra Silvestri (MIT), Lifan Wang (TAMU), Hu Zhan (NAOC) Xinmin Zhang (IHEP) Nov 9, 2011 KDUST workshop, IHEP, Beijing

Nov 9, 2011 KDUST workshop, IHEP, Beijing Nobel Prize, 2011

Cosmic Acceleration Nov 9, 2011 KDUST workshop, IHEP, Beijing DE MG

Nov 9, 2011 KDUST workshop, IHEP, Beijing Weak Lensing Galaxy Counts ISW KDUST

KDUST is useful for DE Nov 9, 2011 KDUST workshop, IHEP, Beijing

Nov 9, 2011 KDUST workshop, IHEP, Beijing LSST sq. deg. Ugrizy GBZ, H.Zhan, L. Wang, Z. Fan, X.Zhang, , PASP sq. deg.: n(z) ~ z 2 exp(-z/0.5) Photo-z rms:  z =0.04(1+z) Photo-z bias prior:  P (  z)=0.2  z Shear calibration error: ±0.003 Residual shear power: 6×10 -10

Nov 9, 2011 KDUST workshop, IHEP, Beijing 5000 sq. deg.: n(z) ~ z 2 exp(-z/0.6) Photo-z rms:  z =0.03(1+z) Photo-z bias prior:  P (  z)=0.2  z Shear calibration error: ±0.002 Residual shear power: 4× sq. deg.: n(z) ~ z 2 exp(-z/0.5) Photo-z rms:  z =0.04(1+z) Photo-z bias prior:  P (  z)=0.2  z Shear calibration error: ±0.003 Residual shear power: 6× KDUST JH + LSST ugrizy

Nov 9, 2011 KDUST workshop, IHEP, Beijing sq. deg.: n(z) ~ z 2 exp(-z/0.6) Photo-z rms:  z =0.03(1+z) Photo-z bias prior:  P (  z)=0.2  z Shear calibration error: ±0.002 Residual shear power: 4× sq. deg.: n(z) ~ z 2 exp(-z/0.5) Photo-z rms:  z =0.04(1+z) Photo-z bias prior:  P (  z)=0.2  z Shear calibration error: ±0.003 Residual shear power: 6× KDUST JH + LSST ugrizy

Nov 9, 2011 KDUST workshop, IHEP, Beijing 5000 sq. deg.: n(z) ~ z 2 exp(-z/0.6) Photo-z rms:  z =0.03(1+z) Photo-z bias prior:  P (  z)=0.2  z Shear calibration error: ±0.002 Residual shear power: 4× sq. deg.: n(z) ~ z 2 exp(-z/0.5) Photo-z rms:  z =0.04(1+z) Photo-z bias prior:  P (  z)=0.2  z Shear calibration error: ±0.003 Residual shear power: 6× KDUST JH + LSST ugrizy SNe: (z < 1.5) KDUST—LSST Synergy credit: Hu Zhan

Nov 9, 2011 KDUST workshop, IHEP, Beijing Reconstructing w(a) precisely R.Crittenden, GBZ, L.Pogosian, L.Samushia, X.Zhang To appear soon see Levon’s talk Straightforward to apply to KDUST data!

KDUST is useful for MG Nov 9, 2011 KDUST workshop, IHEP, Beijing

On linear scale PCA (see Levon’s talk) Cosmic Mach Number Nov 9, 2011 KDUST workshop, IHEP, Beijing

arXiv: with Yinzhe Ma (UBC, Cambridge) Jeremiah Ostriker (Princeton and Cambridge) Cosmic Mach Number: A robust tool to test Einstein Gravity

What is Mach Number?? Nov 9, 2011 KDUST workshop, IHEP, Beijing

Cosmic Mach Number (CMN) Ostriker & Suto 1990 Nov 9, 2011 KDUST workshop, IHEP, Beijing

Nov 9, 2011 KDUST workshop, IHEP, Beijing The shape of velocity power spectrum can be reconstructed from CMN

Nov 9, 2011 KDUST workshop, IHEP, Beijing CMN data

Cosmological applications Nov 9, 2011 KDUST workshop, IHEP, Beijing

Nov 9, 2011 KDUST workshop, IHEP, Beijing WMAP7 + UNION2 +CMN (6dF)

Power of CMN B 0 <0.4 (95% CL, CMB+SN) B 0 <5x10 -5 (95% CL, CMB+SN+CMN) Nov 9, 2011 KDUST workshop, IHEP, Beijing

CMN is a promising tool Immune to galaxy bias, overall amplitude, nonlinearities Highly sensitive to the scale-dependence of the growth, thus an ideal tool to constrain MG parameters and neutrino mass Complimentary to weak lensing Measure CMN from KDUST?? Nov 9, 2011 KDUST workshop, IHEP, Beijing

On Non-linear scale Environmental dependence of dark matter halos Nov 9, 2011 KDUST workshop, IHEP, Beijing

f(R) Gravity Nov 9, 2011 KDUST workshop, IHEP, Beijing Mimic GR at high z; Accelerate the expansion at low z; Recover GR locally to pass solar system test.

In GR Nov 9, 2011 KDUST workshop, IHEP, Beijing

In f(R) Nov 9, 2011 KDUST workshop, IHEP, Beijing lClC

In very dense regions Nov 9, 2011 KDUST workshop, IHEP, Beijing lClC

12 billion years ago

10 billion years ago

8 billion years ago

Now

Numerical Simulations GBZ, B.Li, K.Koyama, PRD 11 Code: Modified MLAPM f(R) model: Model parameters: Cosmological parameters: WMAP7 Nov 9, 2011 KDUST workshop, IHEP, Beijing

Equations to solve in the code Nov 9, 2011 KDUST workshop, IHEP, Beijing

Nov 9, 2011 KDUST workshop, IHEP, Beijing Get some sense…

Nov 9, 2011 KDUST workshop, IHEP, Beijing GR

Nov 9, 2011 KDUST workshop, IHEP, Beijing f(R)

Structure formation in GR KDUST workshop, IHEP, Beijing Nov 9, 2011

Structure formation in f(R) KDUST workshop, IHEP, Beijing Nov 9, 2011

Dynamical Mass KDUST workshop, IHEP, Beijing Nov 9, 2011

Dynamical Mass KDUST workshop, IHEP, Beijing Nov 9, 2011

Dynamical Mass KDUST workshop, IHEP, Beijing Spherical symmetry Nov 9, 2011

Lensing Mass KDUST workshop, IHEP, Beijing Nov 9, 2011

Lensing Mass KDUST workshop, IHEP, Beijing Nov 9, 2011

Lensing Mass KDUST workshop, IHEP, Beijing Spherical symmetry Nov 9, 2011

KDUST workshop, IHEP, Beijing Mass Difference Nov 9, 2011

KDUST workshop, IHEP, Beijing Nov 9, 2011

KDUST workshop, IHEP, Beijing In underdense environment Nov 9, 2011

KDUST workshop, IHEP, Beijing In underdense environment Nov 9, 2011

KDUST workshop, IHEP, Beijing Nov 9, 2011

KDUST workshop, IHEP, Beijing In dense environment Nov 9, 2011

KDUST workshop, IHEP, Beijing In dense environment The halos are screened so that they cannot feel the enhancement of gravity! Nov 9, 2011

How to define “Environment”? Number of neighbours in spheres of radius R Mass or density in spheres of radius R Matter density in spherical shells Average mass density of surrounding halos Distance to nearest halo with minimum mass Projected galaxy number density out to the Nth nearest neighbour with a maximum radial velocity … KDUST workshop, IHEP, Beijing Nov 9, 2011

KDUST workshop, IHEP, Beijing Haas et al., All these quantities strongly correlate with halo mass! Nov 9, 2011

To see the pure environmental effect, we need a new environment indicator which is uncorrelated with halo mass KDUST workshop, IHEP, Beijing The three-dimensional distance to the Nth nearest neighbour with a viral mass that is at least f times that of the halo under consideration, divided by the virial radius of the Nth nearest neighbour: Haas et al., Nov 9, 2011

KDUST workshop, IHEP, Beijing Small D Affected by the local environment Nov 9, 2011

KDUST workshop, IHEP, Beijing Small D Affected by the local environment Large D Affecting the local environment Nov 9, 2011

KDUST workshop, IHEP, Beijing GR analysis, Haas et al., D is a clean indicator for the local environment! Nov 9, 2011

KDUST workshop, IHEP, Beijing f(R) analysis, GBZ, Baojiu Li, Kazuya Koyama (PRL 2011) Nov 9, 2011

KDUST workshop, IHEP, Beijing Nov 9, 2011

KDUST workshop, IHEP, Beijing Similar pattern!! Nov 9, 2011

KDUST workshop, IHEP, Beijing Similar pattern!! The screening is only determined by the halo mass for the isolated halos! Nov 9, 2011

KDUST workshop, IHEP, Beijing Different pattern Nov 9, 2011

KDUST workshop, IHEP, Beijing Different pattern The screening of the clustered halos is not determined by the halo mass only! Nov 9, 2011

KDUST workshop, IHEP, Beijing Different pattern Environmental Effect!! Nov 9, 2011

KDUST workshop, IHEP, Beijing Nov 9, 2011

KDUST workshop, IHEP, Beijing Clean mass dependence! Nov 9, 2011

KDUST workshop, IHEP, Beijing Nov 9, 2011

KDUST workshop, IHEP, Beijing Large scatter shows the environmental effect!! Nov 9, 2011

KDUST workshop, IHEP, Beijing Nov 9, 2011

KDUST workshop, IHEP, Beijing Apparent environmental dependence!! Nov 9, 2011

KDUST workshop, IHEP, Beijing Nov 9, 2011

KDUST workshop, IHEP, Beijing No screening at all!! Nov 9, 2011

KDUST workshop, IHEP, Beijing Nov 9, 2011

KDUST workshop, IHEP, Beijing No screening! Nov 9, 2011

KDUST workshop, IHEP, Beijing Nov 9, 2011

KDUST workshop, IHEP, Beijing Maximum screening Core is better screened Nov 9, 2011

KDUST workshop, IHEP, Beijing Nov 9, 2011

KDUST workshop, IHEP, Beijing Screened purely by environment Nov 9, 2011

KDUST workshop, IHEP, Beijing Nov 9, 2011

KDUST workshop, IHEP, Beijing Screening on the edge shows environmental dependence! Nov 9, 2011

Observationally… KDUST workshop, IHEP, Beijing Lensing MassDynamical Mass Nov 9, 2011

Measure lensing and dynamical mass for each halo; Divide the sample using D; Compare! KDUST workshop, IHEP, Beijing Nov 9, 2011

Measure lensing and dynamical mass for each halo; Divide the sample using D; Compare! KDUST workshop, IHEP, Beijing Apply to KDUST data?! Nov 9, 2011

Summary and Outlook KDUST is powerful to constrain DE and MG by measuring SN, WL, BAO; KDUST is powerful to constrain MG by measuring CMN, lensing and dynamical mass of galaxies; KDUST can do more science, RSD, ISW, etc Nov 9, 2011 KDUST workshop, IHEP, Beijing