Modeling the 3-point correlation function Felipe Marin Department of Astronomy & Astrophysics University of Chicago arXiv:0705.0255 Felipe Marin Department.

Slides:



Advertisements
Similar presentations
Building a Mock Universe Cosmological nbody dark matter simulations + Galaxy surveys (SDSS, UKIDSS, 2dF) Access to mock catalogues through VO Provide analysis.
Advertisements

Andrey Kravtsov Kavli Institute for Cosmological Physics (KICP) The University of Chicago Simulating galaxy formation at high redshifts.
Hierarchical Clustering Leopoldo Infante Pontificia Universidad Católica de Chile Reunión Latinoamericana de Astronomía Córdoba, septiembre 2001.
Important slides (Cosmological group at KASI)
Galaxy Clustering Topology in the Sloan Digital Sky Survey Yun-Young Choi Kyunghee University.
Galaxy alignment within cosmic structures Weipeng Lin Shanghai Astronomical Observatory, CAS, China
Galaxy and Mass Power Spectra Shaun Cole ICC, University of Durham Main Contributors: Ariel Sanchez (Cordoba) Steve Wilkins (Cambridge) Imperial College.
Non-linear matter power spectrum to 1% accuracy between dynamical dark energy models Matt Francis University of Sydney Geraint Lewis (University of Sydney)
Nikolaos Nikoloudakis Friday lunch talk 12/6/09 Supported by a Marie Curie Early Stage Training Fellowship.
July 7, 2008SLAC Annual Program ReviewPage 1 Weak Lensing of The Faint Source Correlation Function Eric Morganson KIPAC.
Large Scale Structure of the Universe at high redshifts Large Scale Structure of the Universe at high redshifts M.Demianski, A.Doroshkevich and S.Gottloeber.
Merger Histories of LCDM Galaxies: Disk Survivability and the Deposition of Cold Gas via Mergers Kyle Stewart AAS Dissertation Talk 213 th AAS Meeting.
Dark Matter and Galaxy Formation (Section 3: Galaxy Data vs. Simulations) Joel R. Primack 2009, eprint arXiv: Presented by: Michael Solway.
Angular clustering and halo occupation properties of COSMOS galaxies Cristiano Porciani.
Luminosity & color of galaxies in clusters sarah m. hansen university of chicago with erin s. sheldon (nyu) risa h. wechsler (stanford)
Lens Galaxy Environments Neal Dalal (IAS), Casey R. Watson (Ohio State) astro-ph/ Who cares? 2.What to do 3.Results 4.Problems! 5.The future.
Clustering of QSOs and X-ray AGN at z=1 Alison Coil Hubble Fellow University of Arizona October 2007 Collaborators: Jeff Newman, Joe Hennawi, Marc Davis,
Cosmological constraints from models of galaxy clustering Abstract Given a dark matter distribution, the halo occupation distribution (HOD) provides a.
박창범 ( 고등과학원 ) & 김주한 ( 경희대학교 ), J. R. Gott (Princeton, USA), J. Dubinski (CITA, Canada) 한국계산과학공학회 창립학술대회 Cosmological N-Body Simulation of Cosmic.
The Statistical Properties of Large Scale Structure Alexander Szalay Department of Physics and Astronomy The Johns Hopkins University.
Reporter: Haijun Tian Alex Szalay, Mark Neyrinck, Tamas Budavari arXiv:
Cosmological Tests using Redshift Space Clustering in BOSS DR11 (Y. -S. Song, C. G. Sabiu, T. Okumura, M. Oh, E. V. Linder) following Cosmological Constraints.
Robust cosmological constraints from SDSS-III/BOSS galaxy clustering Chia-Hsun Chuang (Albert) IFT- CSIC/UAM, Spain.
, Tuorla Observatory 1 Galaxy groups in ΛCDM simulations and SDSS DR5 P. Nurmi, P. Heinämäki, S. Niemi, J. Holopainen Tuorla Observatory E. Saar,
What can we learn from galaxy clustering? David Weinberg, Ohio State University Berlind & Weinberg 2002, ApJ, 575, 587 Zheng, Tinker, Weinberg, & Berlind.
Constraining the Dark Side of the Universe J AIYUL Y OO D EPARTMENT OF A STRONOMY, T HE O HIO S TATE U NIVERSITY Berkeley Cosmology Group, U. C. Berkeley,
Intrinsic ellipticity correlation of luminous red galaxies and misalignment with their host dark matter halos The 8 th Sino – German workshop Teppei O.
The Black-Hole – Halo Mass Relation and High Redshift Quasars Stuart Wyithe Avi Loeb (The University of Melbourne) (Harvard University) Fan et al. (2001)
Cosmological studies with Weak Lensing Peak statistics Zuhui Fan Dept. of Astronomy, Peking University.
Clustering in the Sloan Digital Sky Survey Bob Nichol (ICG, Portsmouth) Many SDSS Colleagues.
The clustering of galaxies detected by neutral hydrogen emission Sean Passmoor Prof. Catherine Cress Image courtesy of NRAO/AUI and Fabian Walter, Max.
Cosmological Constraints from the maxBCG Cluster Sample Eduardo Rozo October 12, 2006 In collaboration with: Risa Wechsler, Benjamin Koester, Timothy McKay,
PHY306 1 Modern cosmology 3: The Growth of Structure Growth of structure in an expanding universe The Jeans length Dark matter Large scale structure simulations.
Using Baryon Acoustic Oscillations to test Dark Energy Will Percival The University of Portsmouth (including work as part of 2dFGRS and SDSS collaborations)
Disentangling dynamic and geometric distortions Federico Marulli Dipartimento di Astronomia, Università di Bologna Marulli, Bianchi, Branchini, Guzzo,
Baryonic signature in the large-scale clustering of SDSS quasars Kazuhiro Yahata Dept. of Phys., University of Tokyo. Issha Kayo, Yasushi Suto, Matsubara.
Large-scale Structure Simulations A.E. Evrard, R Stanek, B Nord (Michigan) E. Gaztanaga, P Fosalba, M. Manera (Barcelona) A. Kravtsov (Chicago) P.M Ricker.
The Co-evolution of Galaxies and Dark Matter Halos Charlie Conroy (Princeton University) with Andrey Kravtsov, Risa Wechsler, Martin White, & Shirley Ho.
Anisotropic Clustering of Galaxies in High-z Universe as a Probe of Dark Energy Taka Matsubara (Nagoya Univ.) “Decrypting the Universe: Large Surveys for.
23 Sep The Feasibility of Constraining Dark Energy Using LAMOST Redshift Survey L.Sun Peking Univ./ CPPM.
The Pursuit of primordial non-Gaussianity in the galaxy bispectrum and galaxy-galaxy, galaxy CMB weak lensing Donghui Jeong Texas Cosmology Center and.
Cosmic shear and intrinsic alignments Rachel Mandelbaum April 2, 2007 Collaborators: Christopher Hirata (IAS), Mustapha Ishak (UT Dallas), Uros Seljak.
Probing cosmic structure formation in the wavelet representation Li-Zhi Fang University of Arizona IPAM, November 10, 2004.
Environmental Effect on Mock Galaxy Quantities Juhan Kim, Yun-Young Choi, & Changbom Park Korea Institute for Advanced Study 2007/02/21.
6dF Workshop April Sydney Cosmological Parameters from 6dF and 2MRS Anaïs Rassat (University College London) 6dF workshop, AAO/Sydney,
Observational Test of Halo Model: an empirical approach Mehri Torki Bob Nichol.
Zheng Dept. of Astronomy, Ohio State University David Weinberg (Advisor, Ohio State) Andreas Berlind (NYU) Josh Frieman (Chicago) Jeremy Tinker (Ohio State)
Zheng I N S T I T U T E for ADVANCED STUDY Cosmology and Structure Formation KIAS Sep. 21, 2006.
The Feasibility of Constraining Dark Energy Using LAMOST Redshift Survey L.Sun.
Xiaohu Yang (SJTU/SHAO) With: H. Wang, H.J. Mo, Y.P. Jing, F.C van den Bosch, W.P. Lin, D. Tweed… , KIAS Exploring the Local Universe with re-
Probing Cosmology with Weak Lensing Effects Zuhui Fan Dept. of Astronomy, Peking University.
Evolution of galaxies and dark matter halos Yipeng Jing Shanghai Astronomical Observatory Main Collaborators: Chunyan Jiang ( 姜春艳), Cheng Li (李成), Donghai.
1 Baryon Acoustic Oscillations Prospects of Measuring Dark Energy Equation of State with LAMOST Xuelei Chen ( 陳學雷 ) National Astronomical Observatory of.
Semi-analytical model of galaxy formation Xi Kang Purple Mountain Observatory, CAS.
The Evolution of Intracluster Light Craig Rudick Department of Astronomy Case Western Reserve University.
Taka Matsubara (Nagoya Univ.)
Feasibility of detecting dark energy using bispectrum Yipeng Jing Shanghai Astronomical Observatory Hong Guo and YPJ, in preparation.
KASI Galaxy Evolution Journal Club A Massive Protocluster of Galaxies at a Redshift of z ~ P. L. Capak et al. 2011, Nature, in press (arXive: )
Interpreting the relationship between galaxy luminosity, color, and environment. Andreas Berlind (NYU, CCPP) SPH predictions: Michael Blanton (NYU) David.
ZCOSMOS galaxy clustering: status and perspectives Sylvain de la Torre Marseille - June, 11th Clustering working group: Ummi Abbas, Sylvain de la Torre,
MEASUREING BIAS FROM UNBIASED OBSERVABLE SEOKCHEON LEE (KIAS) The 50 th Workshop on Gravitation and Numerical INJE Univ.
Simulating the Production of Intra-Cluster Light Craig Rudick Department of Astronomy CERCA - 02/17/05.
Inh Jee University of Texas at Austin Eiichiro Komatsu & Karl Gebhardt
Dark Matter Halos A.Klypin. 2 Major codes: GADET Springel, SDM White PKDGRAV - GASOLINE Quinn, Steidel, Wadsley, Governato, Moore ART Kravtsov, Klypin,
3D Matter and Halo density fields with Standard Perturbation Theory and local bias Nina Roth BCTP Workshop Bad Honnef October 4 th 2010.
Clustering and environments of dark matter halos
An Analytic Approach to Assess Galaxy Projection Along A Line of Sight
Core of Coma Cluster (optical)
Voids size distribution in the 2dFGRS
A Prescription for High-Redshift star formation
Presentation transcript:

Modeling the 3-point correlation function Felipe Marin Department of Astronomy & Astrophysics University of Chicago arXiv: Felipe Marin Department of Astronomy & Astrophysics University of Chicago arXiv:

06/01/2007Great Lakes Cosmology Workshop 8 Collaborators: Josh Frieman (KICP-Chicago & Fermilab) Josh Frieman (KICP-Chicago & Fermilab) Bob Nichol (ICG, Portsmouth) Bob Nichol (ICG, Portsmouth) Risa Wechsler (KICP-Chicago, now Stanford) Risa Wechsler (KICP-Chicago, now Stanford)

06/01/2007Great Lakes Cosmology Workshop 8 Correlation functions on LSS  Galaxy surveys show us that the (luminous) matter does not distribute very smoothly in the Universe  From cosmological N-body simulations, we can see that is also not the case for the dark matter  How do we get a more quantitative insight?  Can we infer DM clustering using galaxies?  Galaxy surveys show us that the (luminous) matter does not distribute very smoothly in the Universe  From cosmological N-body simulations, we can see that is also not the case for the dark matter  How do we get a more quantitative insight?  Can we infer DM clustering using galaxies? A. Kravtsov M. Tegmark

06/01/2007Great Lakes Cosmology Workshop 8 N-point statistics  One way to achieve this is using spatial N-point correlation functions: measure how more likely is to have certain configurations of N-points in a particular field than in a random distribution.  For instance, we can describe the probability that two objects (galaxies, dark matter particles, DM halos, etc.) are found at a distance r:  One way to achieve this is using spatial N-point correlation functions: measure how more likely is to have certain configurations of N-points in a particular field than in a random distribution.  For instance, we can describe the probability that two objects (galaxies, dark matter particles, DM halos, etc.) are found at a distance r:  This defines the two-point correlation function. Along with its Fourier counterpart, the Power Spectrum, have been measured in simulations and galaxy surveys, CMB,etc.

06/01/2007Great Lakes Cosmology Workshop 8 The need for a more complete description  It is possible that two distributions have the same 2-point statistics, but they look completely different!  2-point statistics just describe completely only Gaussian Fields.  They do not take into account non-spherical morphologies  It is possible that two distributions have the same 2-point statistics, but they look completely different!  2-point statistics just describe completely only Gaussian Fields.  They do not take into account non-spherical morphologies Sefusatti & Scoccimarro 2005

06/01/2007Great Lakes Cosmology Workshop 8 The three-point correlation function  The next order correlation is the three-point correlation function (3PCF): The probability to find 3 objects in a certain triangle configuration: 1 3  2  The value of the 3PCF depends on the overall scale of the triangle, as well as on its shape.  Useful to define the reduced 3PCF:  The value of the 3PCF depends on the overall scale of the triangle, as well as on its shape.  Useful to define the reduced 3PCF: u r r

06/01/2007Great Lakes Cosmology Workshop 8 N-body simulations & mock galaxy catalogs  We want to measure & compare the 3PCF of dark matter and galaxies in real & redshift space.  We use high-resolution N-body simulations run using ART code (Kravtsov et al. ’97,’04) with concordance LCDM parameters. Can detect dark matter halos of galactic size  Two boxes: L120 with 120 Mpc/h on the side & L200 with 200 Mpc/h on the side  Redshift space: long-distance observer approximation: peculiar velocities distortions  We want to measure & compare the 3PCF of dark matter and galaxies in real & redshift space.  We use high-resolution N-body simulations run using ART code (Kravtsov et al. ’97,’04) with concordance LCDM parameters. Can detect dark matter halos of galactic size  Two boxes: L120 with 120 Mpc/h on the side & L200 with 200 Mpc/h on the side  Redshift space: long-distance observer approximation: peculiar velocities distortions Kravtsov et al 04

06/01/2007Great Lakes Cosmology Workshop 8 From DM to galaxies  Kravtsov et al (2004), Conroy, Wechsler & Kravtsov (2006) : V max, of a DM halo is a good indicator of the stellar mass and henceforth, of the luminosity of a galaxy.  In order to get luminosities, for both L120 & L200 boxes, the r-band SDSS luminosity function is matched to the cumulative velocity function at the redshift of observation n(>V max,now )  Colors are assigned using the observed relation between local density and SDSS color (Wechsler et al. 2004, Tasitsiomi et al 2004).  Kravtsov et al (2004), Conroy, Wechsler & Kravtsov (2006) : V max, of a DM halo is a good indicator of the stellar mass and henceforth, of the luminosity of a galaxy.  In order to get luminosities, for both L120 & L200 boxes, the r-band SDSS luminosity function is matched to the cumulative velocity function at the redshift of observation n(>V max,now )  Colors are assigned using the observed relation between local density and SDSS color (Wechsler et al. 2004, Tasitsiomi et al 2004). Conroy,Wechsler & Kravtsov 06

06/01/2007Great Lakes Cosmology Workshop 8 Results: DM vs halos Equilateral triangles  Reduced 3PCF for DM particles & halos  Jack-knife error bars  Halos strongly biased w.r.t. DM particles  Strong scale dependence in real space, strong redshift evolution on small scales  Features of Q very washed out in redshift space  Reduced 3PCF for DM particles & halos  Jack-knife error bars  Halos strongly biased w.r.t. DM particles  Strong scale dependence in real space, strong redshift evolution on small scales  Features of Q very washed out in redshift space MWFN 2007

06/01/2007Great Lakes Cosmology Workshop 8 Why real-space Q so different from redshift-space Q?  Big effect in observation, in Galaxy biasing

06/01/2007Great Lakes Cosmology Workshop 8 Results: DM vs. halos Shape dependence  We measured Q(r,u=2,  ), for  = degrees  Blue line: Biased dark matter Q… see later…  The amplitude of Q(  ) is higher at elongated configurations: U-shape.  We measured Q(r,u=2,  ), for  = degrees  Blue line: Biased dark matter Q… see later…  The amplitude of Q(  ) is higher at elongated configurations: U-shape. MWFN 2007

06/01/2007Great Lakes Cosmology Workshop 8 Luminosities & Colors  Kayo et al. (2004): little or no dependence of Q for SDSS galaxies in color and luminosity, for equilateral triangles  Our results agree in general: need more volume?  Kayo et al. (2004): little or no dependence of Q for SDSS galaxies in color and luminosity, for equilateral triangles  Our results agree in general: need more volume? MWFN 2007

06/01/2007Great Lakes Cosmology Workshop 8 Comparison w/SDSS results.  We compare the 3PCF of our boxes to the recent measurements of the SDSS 3PCF by Nichol et al (2006)  There’s a good agreement within the errors in general with our L120 box results using V max,now  Here we use a much lower resolution than in our previous results: then features of Q(  ) are severely attenuated.  We compare results with bigger resolution: errors do not get much higher.  We compare the 3PCF of our boxes to the recent measurements of the SDSS 3PCF by Nichol et al (2006)  There’s a good agreement within the errors in general with our L120 box results using V max,now  Here we use a much lower resolution than in our previous results: then features of Q(  ) are severely attenuated.  We compare results with bigger resolution: errors do not get much higher.

06/01/2007Great Lakes Cosmology Workshop 8 Galaxy Biasing with 3PCF  The different 3PCF from Dark Matter and galaxies reflect differences in spatial distributions: galaxy bias  Higher-order statistics can provide constrains.  On large scales, where rms overdensities are small compared to unity, we can adopt a local bias model. This will affect the values of the correlation functions as well:  The different 3PCF from Dark Matter and galaxies reflect differences in spatial distributions: galaxy bias  Higher-order statistics can provide constrains.  On large scales, where rms overdensities are small compared to unity, we can adopt a local bias model. This will affect the values of the correlation functions as well:

06/01/2007Great Lakes Cosmology Workshop 8 Galaxy Biasing: results  Adopting c 1 =b 1 and c 2 =b 2 /b 1, using the JK error covariance matrix we get constrains in these parameters from the 3PCF, 2PCF & overdensities.  The three methods have a good agreement in real space, giving c 1 ~1.2 & c 2 ~ -0.2  In redshift space the agreement is not as good, but constrains from 3PCF are consistent with 2dF results: c 1 ~0.9& c 2 ~ -0.3  Adopting c 1 =b 1 and c 2 =b 2 /b 1, using the JK error covariance matrix we get constrains in these parameters from the 3PCF, 2PCF & overdensities.  The three methods have a good agreement in real space, giving c 1 ~1.2 & c 2 ~ -0.2  In redshift space the agreement is not as good, but constrains from 3PCF are consistent with 2dF results: c 1 ~0.9& c 2 ~ -0.3

06/01/2007Great Lakes Cosmology Workshop 8 Summary  The 3PCF for both galaxies and dark matter has a strong dependence on scale and shape.  The redshift space 3PCF is strongly attenuated w.r.t. the real space 3PCF.  The galaxy reduced 3PCF shows little dependence on luminosity & color.  Our model predictions are in good agreement with the last SDSS measurements  On scales of order 10 Mpc/h, a local bias scheme is in reasonable agreement with galaxy and DM distributions.  The 3PCF for both galaxies and dark matter has a strong dependence on scale and shape.  The redshift space 3PCF is strongly attenuated w.r.t. the real space 3PCF.  The galaxy reduced 3PCF shows little dependence on luminosity & color.  Our model predictions are in good agreement with the last SDSS measurements  On scales of order 10 Mpc/h, a local bias scheme is in reasonable agreement with galaxy and DM distributions.