Press-Schechter Formalism: Structure Formation by Self-Similar Condensation Jean P. Walker Based on Press & Schechter’s 1974 Paper.

Slides:



Advertisements
Similar presentations
Cosmological Structure Formation A Short Course III. Structure Formation in the Non-Linear Regime Chris Power.
Advertisements

Building a Mock Universe Cosmological nbody dark matter simulations + Galaxy surveys (SDSS, UKIDSS, 2dF) Access to mock catalogues through VO Provide analysis.
DM density profiles in non-extensive theory Eelco van Kampen Institute for Astro- and Particle Physics Innsbruck University In collaboration with Manfred.
Simulating the joint evolution of quasars, galaxies and their large-scale distribution Springel et al., 2005 Presented by Eve LoCastro October 1, 2009.
Rotation of Cosmic Voids (Lee & Park 2006, ApJ in press, astro-ph/ ) Jounghun Lee & Deaseong Park (Seoul National University)
Why Environment Matters more massive halos. However, it is usually assumed in, for example, semianalytic modelling that the merger history of a dark matter.
Non-linear matter power spectrum to 1% accuracy between dynamical dark energy models Matt Francis University of Sydney Geraint Lewis (University of Sydney)
Dark Matter-Baryon segregation in the non-linear evolution of coupled Dark Energy models Roberto Mainini Università di Milano Bicocca Mainini 2005, Phys.Rev.
Theoretical Perspectives Amr El-Zant Canadian Institute for Theoretical Astrophysics.
Dark Matter and Galaxy Formation Section 4: Semi-Analytic Models of Galaxy Formation Joel R. Primack 2009, eprint arXiv: Presented by: Michael.
Primeval Starbursting Galaxies: Presentation of “Lyman-Break Galaxies” by Mauro Giavalisco Jean P. Walker Rutgers University.
Environmental dependence of halo formation times Geraint Harker.
The Underdense Universe in Simulations of Cosmic Structure Formation Jörg M. Colberg (CMU) with Tiziana Di Matteo (CMU), Ravi Sheth (UPenn), Antonaldo.
Dark Energy Interactions, Nordita, October 3, 2014 Backreaction status report Syksy Räsänen University of Helsinki Department of Physics and Helsinki Institute.
Statistics 800: Quantitative Business Analysis for Decision Making Measures of Locations and Variability.
VARIABILITY. PREVIEW PREVIEW Figure 4.1 the statistical mode for defining abnormal behavior. The distribution of behavior scores for the entire population.
Dark Energy and the Inflection Points of Cosmic Expansion in Standard and Brane Cosmologies Daniel Schmidt, Liberty University Cyclotron Institute--Texas.
CIS 2033 based on Dekking et al. A Modern Introduction to Probability and Statistics, 2007 Instructor Longin Jan Latecki Chapter 7: Expectation and variance.
The Theory/Observation connection lecture 3 the (non-linear) growth of structure Will Percival The University of Portsmouth.
Impact of Early Dark Energy on non-linear structure formation Margherita Grossi MPA, Garching Volker Springel Advisor : Volker Springel 3rd Biennial Leopoldina.
Different physical properties contribute to the density and temperature perturbation growth. In addition to the mutual gravity of the dark matter and baryons,
Black hole production in preheating Teruaki Suyama (Kyoto University) Takahiro Tanaka (Kyoto University) Bruce Bassett (ICG, University of Portsmouth)
I N T R O D U C T I O N The mechanism of galaxy formation involves the cooling and condensation of baryons inside the gravitational potential well provided.
MATTEO VIEL STRUCTURE FORMATION INAF and INFN Trieste SISSA - 28, th February/ 3 rd March 2011.
The formation of galactic disks An overview of Mo Mao & White 1998 MNRAS
Dark energy fluctuations and structure formation Rogério Rosenfeld Instituto de Física Teórica/UNESP I Workshop "Challenges of New Physics in Space" Campos.
Probing the Reheating with Astrophysical Observations Jérôme Martin Institut d’Astrophysique de Paris (IAP) 1 [In collaboration with K. Jedamzik & M. Lemoine,
Functions of Random Variables. Methods for determining the distribution of functions of Random Variables 1.Distribution function method 2.Moment generating.
Practical Statistical Analysis Objectives: Conceptually understand the following for both linear and nonlinear models: 1.Best fit to model parameters 2.Experimental.
Lecture 5: Matter Dominated Universe: CMB Anisotropies and Large Scale Structure Today, matter is assembled into structures: filaments, clusters, galaxies,
On the Property of Collapsing Primordial Cloud Core Tsuribe, T. (Osaka University) 2003/09/03-04 at Niigata Univ.
Maxime KUBRYK, IAP, Ph.D student advisors: Nikos PRANTZOS, IAP Lia ATHANASSOULA, OAMP LIA-ORIGINS, May 2012.
The Theory/Observation connection lecture 2 perturbations Will Percival The University of Portsmouth.
Part II Process Dynamics.  Process model types 1.Mathematical model 2.Fundamental and empirical model 3.Steady-state and dynamic model 4.Lumped (ODE)
Evolution of the Halo Mass Function Zarija Lukić (UIUC) Katrin Heitmann (LANL) Salman Habib (LANL) Sergei Bashinsky (LANL) Paul Ricker (UIUC) astro-ph/
IX ème Ecole de Cosmologie, Cargese, November 3, Structure formation as an alternative to dark energy Syksy Räsänen University of Geneva Syksy.
Structural and scaling properties of galaxy clusters Probing the physics of structure formation M.Arnaud, G.Pratt, E.Pointecouteau (CEA-Sap Saclay) Dark.
Statistics. A two-dimensional random variable with a uniform distribution.
Modeling the dependence of galaxy clustering on stellar mass and SEDs Lan Wang Collaborators: Guinevere Kauffmann (MPA) Cheng Li (MPA/SHAO, USTC) Gabriella.
Effects of correlation between halo merging steps J. Pan Purple Mountain Obs.
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.
Observational Test of Halo Model: an empirical approach Mehri Torki Bob Nichol.
A CDM view of the Local Group dSphs Jorge Peñarrubia In collaboration with Julio F. Navarro & Alan McConnachie Jorge Peñarrubia In collaboration with Julio.
Zheng Dept. of Astronomy, Ohio State University David Weinberg (Advisor, Ohio State) Andreas Berlind (NYU) Josh Frieman (Chicago) Jeremy Tinker (Ohio State)
Cosmology with the XMM Cluster Survey (XCS)
Selecting a mass function by way of the Bayesian Razor Darell Moodley (UKZN), Dr. Kavilan Moodley (UKZN), Dr. Carolyn Sealfon (WCU)
L 3 - Stellar Evolution I: November-December, L 3: Collapse phase – theoretical models Background image: courtesy ESO - B68 with.
Cosmology and Dark Matter III: The Formation of Galaxies Jerry Sellwood.
Holographic Dark Energy and Anthropic Principle Qing-Guo Huang Interdisciplinary Center of Theoretical Studies CAS
Semi-analytical model of galaxy formation Xi Kang Purple Mountain Observatory, CAS.
Present-Day Descendants of z=3.1 Ly  Emitting (LAE) Galaxies in the Millennium-II Halo Merger Trees Jean P. Walker Soler – Rutgers University Eric Gawiser.
Feasibility of detecting dark energy using bispectrum Yipeng Jing Shanghai Astronomical Observatory Hong Guo and YPJ, in preparation.
We created a set of volume limited samples taken from the 2dFGRS (Colless 2001) that contains about 250,000 galaxies with accurate redshifts, is relatively.
Initial conditions for N-body simulations Hans A. Winther ITA, University of Oslo.
Study of Proto-clusters by Cosmological Simulation Tamon SUWA, Asao HABE (Hokkaido Univ.) Kohji YOSHIKAWA (Tokyo Univ.)
Simulating the Production of Intra-Cluster Light Craig Rudick Department of Astronomy CERCA - 02/17/05.
Self-Consistent Theory of Halo Mergers Andrew Benson (Caltech/Oxford) Marc Kamionkowski (Caltech) Steven Hassani (Caltech/Princeton) astro-ph/ (MNRAS,
BAO Damping and Reconstruction Cheng Zhao
Spherical Collapse and the Mass Function – Chameleon Dark Energy Stephen Appleby, APCTP-TUS dark energy workshop 5 th June, 2014 M. Kopp, S.A.A, I. Achitouv,
3D Matter and Halo density fields with Standard Perturbation Theory and local bias Nina Roth BCTP Workshop Bad Honnef October 4 th 2010.
Reionization of the Universe MinGyu Kim
2dF Galaxy Redshift Survey ¼ M galaxies 2003
Outline Part II. Structure Formation: Dark Matter
Clustering and environments of dark matter halos
The influence of Dark Energy on the Large Scale Structure Formation
Solving Equations by Adding and Subtracting Solving Equations
Outline Part II. Structure Formation: Dark Matter
The impact of non-linear evolution of the cosmological matter power spectrum on the measurement of neutrino masses ROE-JSPS workshop Edinburgh.
MATH 3033 based on Dekking et al
Presentation transcript:

Press-Schechter Formalism: Structure Formation by Self-Similar Condensation Jean P. Walker Based on Press & Schechter’s 1974 Paper

Structure Formation in Simulations Images Courtesy of the Max Planck Institute of Astrophysics & Virgo Consortium (Top, Millennium-II; Right, Aquarius Project).

Basic Definitions of Dark Matter  Number Density  Characteristic Particle Mass  Deceleration Parameter: Describes the ability of the universe to inhibit condensation.  Jean’s Number: Describes the number of particles needed to begin condensation. See Eqn. (3) for an empirical formula.

Intuitions for Self-Similarity  Gravitational Collapse: “Large correlations in the gas must be interperated as changes in n(m), by treating highly correlated groups of particles as single more massive particles.” (Pg. 427)  Non-Linearity of Equations: If we expect n(m) to depend only on the statistics of the current scale, then the evolutions of n(m) will depend on the statistical properties of the non-linear differential equations. (Pg. 428)

Preparation for Derivation  Define Mass Variance inside of Volume V.  An upper bound on the variance can be found by taking the dark matter particles to be distributed uniformly, so that the variance is linear in volume.

Derivation  We define the probability of finding a fractional mass deviation between δ and δ+dδ in volume V as P(δ,V).

Derivation (Cont’d)  The turn-around scale, R 2, for R 1 is found for spherical collapse in the Appendix.  We can define the probability of having an overdensity δ collapse before R 2 as P.

Derivation (Cont’d)  The number density distribution is found by multiplying the percentage of collapsed mass with the mass density of the second scale and dividing by M.  The factor of 2 was added to take into account the underdensities around the collapsed objects (Improved explanation can be found in Bond et al. 1991).

Summary  Press-Schechter Formalism allows us to analytically recreate the linear evolution of dark matter perturbations without the need of resource exhaustive computer simulations.  Press-Schechter Formalism describes a universe where different scales collapse in a similar manner without a dependence on the scale size (Self-similar condensation).  The Formalism has been extensively used and compared to simulations to confirm its accuracy.  An improved Sheth-Tormen Formalism, which uses ellipsoidal collapse and excursion set theory, reproduces the main results of Press-Schechter while correcting the discrepancies at the high and low mass extremes of the halo mass function.