X-ray to Radio Mapping of 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 spectrum including information about structure Direct and quantitative comparison The Physics of Galaxy Formation and Evolution

GCD+: Galactic Chemo-Dynamics Code GCD+: Galactic Chemo-Dynamics Code (Kawata & Gibson 03) 3D vector/parallel tree N-body/SPH code taking into account the complex dynamical and 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 Virtual Cosmos Virtual Cosmos Cosmological Simulations by GCD+  Virtual Cosmos offers physical condition and chemical conposition of gas and stellar components at various redshift and environments Synthesized spectrum from gas and stars + absorption by IGM and ISM including dust + re-emission from dust

2. Brief Introduction of GCD+ 3D vector/parallel tree N-body/SPH code DM and Stars DM and Stars Tree N-body code Gas Radiative Cooling Star Formation SNe Feedback Metal Enrichment H,He,C,N,O,Ne,Mg,Si, and Fe Gas Smoothed Particle Hydrodynamics (SPH) + Radiative Cooling (MAPPINGSIII: Sutherland & Dopita) depends on metallicity + Star Formation SFR ∝ ρ 1.5 (ρ g ＞ 2 x g/cm 3 ) IMF: Salpeter type + SNe Feedback SNeII and SNeIa + Metal Enrichment SNe II, SNeIa, and intermediate mass stars H,He,C,N,O,Ne,Mg,Si, and Fe

3. 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 ΛCDM ( standard ΛCDM (Ω 0 =0.3, λ 0 =0.7, h=0.7, Ω b =0.019h -1, σ 8 =0.9

Multi-Resolution Cosmological Simulation Multi-Resolution Cosmological Simulation (  grafic2: Bertschinger 01) Highest Resolution Region: m DM =2x10 5 M , ε DM =0.14 kpc, m gas =3x10 4 M , ε gas =0.08 kpc face-on 5kpc = 0.83” Mvir = 6x10 9 M  Vmax = 65 km/s snap z = 5.45 J band image edge-on

Good agreement with HDF and 2df galaxies = reliable cosmological simulation High-z (z>5) galaxies which should be detectable by JWST predicted size of these galaxies < diffraction limit? Comparison of apparent size and magnitude relation with observations

gas stars derive both X-ray/Optical properties withminimum assumption ４. Analysis Synthetic R-band image + X-ray contours

Distribution of gas particles (ρ,T,Z O,Mg,Si,Fe… ) X-ray properties fake X-ray Spectrum using XSPEC vmekal plasma model + XMM EPN response function Lx,Tx,(Fe/H)x,(O/H)x… Fit the spectrum using XSPEC vmekal model  Lx,Tx,(Fe/H)x,(O/H)x… Synthetic X-ray Spectrum with XMM response function

Distribution of star particles (age,Z O,Mg,Si,Fe… ) Optical properties X-ray Spectrum with XMM response function  Luminosities and colours (M B, V  K) Population Synthesis Population Synthesis SSPs: Kodama & Arimoto97 Synthetic Optical/NIR Spectrum

Current 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/optical XMM, Chandra Grand+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,optical Parkes(HIPPASS), ATCA, Southern optical telescopes Tomorrow Sec. 5 Sec. 6 Previous Slides Near future…

5.1. Introduction Coma R B-R 5. An X-ray/Optical Study of Elliptical Galaxy Formation in  CDM Universe Cluster & group Xue & Wu (00) 110 Any successful galaxy formation scenario must explain both observed X-ray and optical properties. Using self-consistent numerical simulations, we are attempting to construct such models for elliptical galaxies. Elliptical Galaxies optical: stellar properties X-ray: gas properties

5.2. Cosmological Simulation Model High Resolution Region: m DM =4x10 8 M , ε DM =4.3kpc, m g =5.9x10 7 M , ε DM =2.3kpc Target galaxy Target galaxy Largest galaxy in the simulation volume Mvir =2x10 13 M   NGC4472 (Virgo elliptical) 3 Different Models model A: adiabatic model model B: cooling + weak feedback model C: cooling + strong feedback

5.3.1 Lx  Tx relation 5.3. Results model A model C model B 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 Lx and higher Tx Inclusion of cooling leads to lower Lx and higher Tx  consistent with observed Lx and Tx for NGC4472 (models B & C) Adiabatic model (model A) Adiabatic model (model A) incompatible with data  higher Lx and lower Tx model A: adiabatic model (no cooling = no star formation) model B: with cooling and minimum SNe feedback model C: with cooling and 100 times stronger feedback model A: adiabatic model (no cooling = no star formation) model B: with cooling and minimum SNe feedback model C: with cooling and 100 times stronger feedback consistent with simulations of Pearce et al. (00), Muanwong et al. (01)

Semi-cosmological galaxy formation model advantage: less computational costs = can achieve higher resolution disadvantage: 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

Optical properties Colour  Magnitute relation model C model B Coma ellipticals (Bower et al. 1992) Problem!: An excessive popuation of young stars result due to cooling flow. Colours are too blue Problem!: An excessive popuation of young stars result due to cooling flow. Colours are too 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=0.5gas particles eccentricity Traditional interpretation: sign of rapid collapse (Eggen et al. 62)

Phase Space properties disrupted satellitestars with low [Fe/H] and high e field stars Simulation Observation Observed low [Fe/H]/high-e stars concentration can be explained by the recent accretion of high-e orbit satellite. = alternative explanation from “rapid collapse” scenario Identical phase space distribution

7. Conclusion Quantitative comparison between GCD+ VO for VC and VO in multi-wavelength regime should be exciting for 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 (plan) Public GCD+ VO for VC Public 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, spectrum luminosity 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 description of modeling.  unified format for such description and classification of modeling would be also important. Interface allow to chose whose which model e.g., GCD+ no feedback model or with strong feedback model simulator who knows differences between the codes If all (cosmological) simulators follow this sort of idea, what is the benefit? for simulator 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…

Optical properties Colour  Magnitute relation model C model B 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/or Extra heating source (AGN?) to suppress star formation, but then the Lx  Tx relation and Lx-(Fe/H)x must be checked again. Problem!: An excessive popuation of young stars result due to cooling flow. Colours are too blue Problem!: An excessive popuation of young stars result due to cooling flow. Colours are too blue, regardless of feedback.