X-ray to Radio Mapping of X-ray to Radio Mapping of the Virtual Cosmos by GCD+the Virtual Cosmos by GCD+

Daisuke Kawata, Chris B. Brook, Tim W. Connors, and Brad K. Gibson

Centre for Astrophysics and Supercomputing,Swinburne University of Technology

1. Introduction

The Virtual Observatory offers multi-wavelength (X-ray to radio) observational data

Numerical Simulations of Galaxy Formation can follow chemo-dynamical evolution of gas and stellar components of galaxies

Synthesized multi-wavelength spectrumincluding information about structure

Direct and quantitative comparison

The Physics of Galaxy Formation and Evolution

GCD+: Galactic Chemo-Dynamics CodeGCD+: Galactic Chemo-Dynamics Code (Kawata & Gibson 03)

3D vector/parallel tree N-body/SPH code3D vector/parallel tree N-body/SPH codetaking into account the complex dynamical and taking into account the complex dynamical and

chemical evolutions in forming galaxy self-consistently chemical evolutions in forming galaxy self-consistently

DM, Gas, Star formation, SNe Feedback, and Metal Enrichment

plasma model, population synthesis, K-correction, etc.

Self-consistent X-ray to radio mapping of Self-consistent X-ray to radio mapping of Virtual CosmosVirtual Cosmos

Cosmological Simulations by GCD+ Virtual Virtual CosmosCosmosoffers physical condition and chemical conposition of offers physical condition and chemical conposition of

gas and stellar components at various redshift and environmentsgas and stellar components at various redshift and environments

Synthesized spectrum from gas and starsSynthesized spectrum from gas and stars + absorption by IGM and ISM including + absorption by IGM and ISM including dustdust + re-emission from dust + re-emission from dust

2. Brief Introduction of GCD+2. Brief Introduction of GCD+ 3D vector/parallel tree N-body/SPH code3D vector/parallel tree N-body/SPH code

DM and StarsDM and Stars ••• Tree N-body code

GasGas Smoothed Particle Hydrodynamics (SPH)••• + Radiative CoolingRadiative Cooling (MAPPINGSIII: Sutherland & Dopita) depends on metallicity + Star FormationStar Formation SFR ∝ ρ1.5 (ρg ＞ 2 x10-25 g/cm3) IMF: Salpeter type + SNe FeedbackSNe Feedback SNeII and SNeIa + Metal EnrichmentMetal Enrichment SNe II, SNeIa, and intermediate mass stars H,He,C,N,O,Ne,Mg,Si, and FeH,He,C,N,O,Ne,Mg,Si, and Fe

3. Cosmological Simulation Model3. Cosmological Simulation Model

DM density map

I band image

follows the evolution of large scale structures as well as the galaxy formation process, including gas dynamics and star formation

standard standard ΛCDM (ΛCDM (Ω0=0.3, λ0=0.7, h=0.7, Ωb=0.019h-1, σ8=0.9

Multi-Resolution Cosmological Simulation Multi-Resolution Cosmological Simulation (grafic2: Bertschinger 01)

Highest Resolution Region: mDM=2x105 M, εDM=0.14 kpc, mgas=3x104 M , εgas=0.08 kpc

face-on

5kpc = 0.83”

Mvir = 6x109 M Vmax = 65 km/

s

snap shot @ z = 5.45

J band imageedge-on

Good agreement with HDF and 2df galaxies= reliable cosmologicalsimulation

High-z (z>5) galaxies whichshould be detectable byJWST

predicted size of these galaxies < diffraction limit?

Comparison of apparent size and magnitude relation with observations

gas

stars

derive both X-ray/Optical properties withderive both X-ray/Optical properties withminimum assumptionminimum assumption

４４ . Analysis. Analysis

Synthetic R-band image + X-ray contours

Distribution of gas particles (ρ,T,ZO,Mg,Si,Fe…)

X-ray propertiesX-ray properties

fake X-ray Spectrum using XSPEC vmekal plasma model

+ XMM EPN response function

Fit the spectrum using XSPEC vmekal model Lx,Tx,(Fe/H)x,(O/H)x…Lx,Tx,(Fe/H)x,(O/H)x…

Synthetic X-ray Spectrum with XMM response function

Distribution of star particles (age,ZO,Mg,Si,Fe…)

Optical propertiesOptical properties

X-ray Spectrum with XMM response function

Luminosities and colours (MLuminosities and colours (MBB, V, VK)K)

Population SynthesisPopulation SynthesisSSPs: Kodama & Arimoto97

Synthetic Optical/NIR Spectrum

Current StatusCurrent Status

Properties of high-z galaxies Kawata, Gibson w/Windhorst (ASU)

Wavelength Telescope

Dynamics of high-z galaxies Kawata, Gibson

optical

Radio (redshifted 21cm)

HST, JWST

SKA, LOFAR

Formation of elliptical galaxies Kawata, Gibson

X-ray/opticalXMM, ChandraGrand+Space

optical telescopes

Formation of Milky Way Brook, Kawata, Gibson w/Flynn (Tuorla)

optical(astrometry)

Hipparcos,(RAVE), GAIA

SMC and Magellanics Stream Connors, Kawata, Gibson

radio,opticalParkes(HIPPASS),ATCA, Southern

optical telescopes

TomorroTomorroww

Sec. 5Sec. 5

Sec. 6Sec. 6

Previous Previous SlidesSlides

Near Near future…future…

5.1. Introduction5.1. IntroductionComa

R

B-R

5. An X-ray/Optical Study of Elliptical Galaxy Formationin CDM Universe

Cluster & groupXue & Wu (00)

1 10

Any successful galaxy formationscenario must explain both observed X-ray and optical properties.Using self-consistent Using self-consistent numericalnumericalsimulations, we are simulations, we are attemptingattemptingto construct such models forto construct such models forelliptical galaxies.elliptical galaxies.

Elliptical Galaxies optical: stellar properties X-ray: gas properties

5.2. Cosmological Simulation Model5.2. Cosmological Simulation Model

High Resolution Region: mDM=4x108M, εDM=4.3kpc, mg=5.9x107 M , εDM=2.3kpc

Target galaxy Target galaxy Largest galaxy in the simulation volume Mvir=2x1013M NGC4472 (Virgo elliptical)

3 Different Models3 Different Models model Amodel A: adiabatic model : adiabatic model model Bmodel B: cooling + weak : cooling + weak feedbackfeedback model Cmodel C: cooling + strong : cooling + strong feedbackfeedback

5.3.1 Lx5.3.1 LxTx relationTx relation

5.3. Results5.3. Results

model model AA

model model CC

model model BB

ellipticals (Matsushita et al. 00)

adiabatic simulation of clusters (Muanwong et al. 01)

extrapolation of cluster relation (Edge et al. 91)Inclusion of cooling leads to lower Inclusion of cooling leads to lower

Lx and higher TxLx and higher Tx consistent with observed Lx and Tx for NGC4472 (models B & C)

Adiabatic model (Adiabatic model (model Amodel A) ) incompatible with data higher Lx and lower Tx

model Amodel A: adiabatic model (no cooling = no star formation): adiabatic model (no cooling = no star formation) model Bmodel B: with cooling and minimum SNe feedback : with cooling and minimum SNe feedback model Cmodel C: with cooling and 100 times stronger feedback: with cooling and 100 times stronger feedback

consistent with simulations of Pearceconsistent with simulations of Pearceet al. (00), Muanwong et al. (01) et al. (00), Muanwong et al. (01)

Semi-cosmological galaxy formation model

advantage: less computational costs = can achieve higher resolutiondisadvantage: not exactly follow the cosmological evolution, e.g., might underestimate later accretion of the gas and satellite dwarf galaxies update to full cosmological simulation in near future

5.3.3. Optical properties 5.3.3. Optical properties Colour ColourMagnitute relationMagnitute relation

model model CC

model model BB

Coma ellipticals (Bower et al. 1992)

Problem!:Problem!: An excessive An excessive popuation of young stars popuation of young stars result due to cooling flow. result due to cooling flow. Colours areColours are too bluetoo blue, regardless of feedback.

Double check in both X-ray and optical properties

gives stronger constraints on the theoretical models

6. Self-consistent modeling of Milky Way formation Brook, Kawata, Gibson, Flynn

GAIA (also RAVE by UK Schmidt) Astrometry, radial velocities, and chemical composition for more than 1 billion stars within 10 kpc

Chemo-dynamical modeling of formation and evolution of Milky Way templates of Milky Way like galaxies with different formation histories, such as major and minor merger history, to extract useful information from such huge data set. what observational signatures tell what formation history.

The detailed formation history of Milky Way

Galactic Halo Stars in Phase Space: A Hint of Satellite Accretion? Brook, Kawata, Gibson, & Flynn (2003, ApJL in press)

Solar neighbourhood stars Chiba & Beers (00)

disrupted satellite which is identified at z=0.5

gas particles

eccentricity

Traditional interpretation: sign of rapid collapse (Eggen et al. 62)

Phase Space properties

disrupted satellite stars with low [Fe/H] and high efield stars

Simulation Observation

Observed low [Fe/H]/high-e stars concentration can be explained bythe recent accretion of high-e orbit satellite.

= alternative explanation from “rapid collapse” scenario

Identical phase space distribution

7. Conclusion7. Conclusion

Quantitative comparison between GCD+ VO for VCQuantitative comparison between GCD+ VO for VC and VO in multi-wavelength regime and VO in multi-wavelength regime

should be exciting forshould be exciting for studies of galaxy formation and evolution studies of galaxy formation and evolution

GCD+GCD+ can provide observable values from numerical simulations. = equivalent data to what the Virtual Observatory offers.

The Virtual Observatory for Virtual Cosmos

Ultimate Goal

The Virtual Observatory is great for our science!

Contribution to the Theory Virtual Observatory Contribution to the Theory Virtual Observatory (plan)(plan)

Public GCD+ VO for VCPublic GCD+ VO for VC, using the same interface as VC

store: the raw data physical and chemical data for DM, gas, star

particles

analysis code synthesized image and spectrum

Image, spectrumluminosity function

similar interface to VO

black box (= reducing process in observation)

user

requests

looks great and all cosmological simulators can follow this with minimum amount of effort (probably), however…

Problem: There is no perfect theoretical model.i.e. we can create lots of different virtual cosmos

Therefore, the VO for VC should be provided with the descriptionof modeling. unified format for such description and classification of modeling would be also important.

Interface allow to chose whose which modele.g., GCD+ no feedback model or with strong feedback

modelIf all (cosmological) simulators follow this sort of idea, what is the benefit? for simulator who knows differences between the codessimulator who knows differences between the codes easy to compare with the results from other code reduce the bugs for observer or other theoretician helpful to understand their observation and/or analytic model confused by lots of different model? show the idea how to chose the model (whose one is the best, in which case?) or enquiry to prepare this, regular meeting and comparisons among the simulator are necessarily…

5.3.3. Optical properties 5.3.3. Optical properties Colour ColourMagnitute relationMagnitute relation

model model CC

model model BB

ignore young stars(age<8 Gyr)

Coma ellipticals (Bower et al. 1992)

If the contribution of these young stars is ignored, the observed colour is recovered.

Young stars formed in later cooling might have a bottom-heavy IMF? (Fabian et al. 1987; Mathews & Brighenti 1999) and/orExtra heating source (AGN?) to suppress star formation, but then the LxTx relation and Lx-(Fe/H)x must be checked again.

Problem!:Problem!: An excessive An excessive popuation of young stars popuation of young stars result due to cooling flow. result due to cooling flow. Colours areColours are too bluetoo blue, regardless of feedback.