Making a virtual Universe Adrian Jenkins - ICC, Durham University.

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Transcript of Making a virtual Universe Adrian Jenkins - ICC, Durham University.

Making a virtual Universe

Adrian Jenkins - ICC, Durham University

Outline

Introduction: Modelling a galaxy population

Example of an application Hubble volume simulation

Future projects: Millennium simulation

Introduction

• Galaxy formation

• Modelling galaxy populations

Galaxy Formation

Cosmological model(, , h) dark matter

Formation and evolution of galaxies

Primordial fluctuations

/(M, t)

N-body/gasdynamics simulations

Semi-analytics (+N-body simulation)

Dark matter halos

Halo Merger History

John Helly

White & Rees ‘78White & Rees ‘78

Fall & Efstathiou ‘80

Semi-a

nalyt

ic m

odel

of g

alax

y fo

rmat

ion

Halo Merger History

John Helly

Cooling onto a disk

Halos merge

Galaxies merge; if major merger, spheroid forms with starburst

New disk may form by further cooling

Galaxies in a Virgo N-body simulation

Observable properties of galaxies in each N-body halo computed using the SA model:

colour B-V; size ~ Mb

Galaxies trace filaments Red galaxies in clusters

Benson, Frenk, Baugh, Cole & Lacey ‘01

Z = 0

3000 Mpc/h

ΛCDM Hubble Volume Simulation

A virtual universe: Hubble volume simulations

2dF redshift survey

2dF vs mocks from Hubble vol simulation

The 2dF galaxy power spectrum

Galaxy power spectrum in redshift space, convolved with survey window, inclunding non-linear effects

Future Plans

Millennium simulation: 10 billion particles

Data sizes:

Each output -- 300 Gbytes

To make merger histories need 50 outputs -- 15 Tbytes

Post-processing will allow some reduction but not bya large factor

Final product: a Virtual universe

Galaxy population in 500 Mpc/h volume – complete to L* + 5 at all redshifts and wavelenghtsIncluding spectrophotometric, structural and chemicaland clustering properties of all the galaxies.

Conclusions

The construction of virtual universes to aid the analysis of real data is becoming increasinglycommon.

The required sizes of these kinds of datasets is becoming very large.

The size of the collaborations that generate and utilisethese kinds of data is growing larger.

Future Collaborations

EC Framework 6 network - Virgo institutions + Paris, Padova, Warsaw, Talin, Harvard,

Michigan, McMaster, Victoria

DEISA - linking IBM SP4s in Europe including HPCx Virgo/EPCC/RZG