Patrik Jonsson, UCSC In collaboration with TJ Cox, Joel Primack, Jennifer Lotz, Sandy Faber…
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Patrik Jonsson, UCSCIn collaboration with
TJ Cox, Joel Primack, Jennifer Lotz, Sandy Faber…
Simulations of dust in interacting galaxies
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Purpose
• Make realistic “simulated observations” of merger simulations:– Broadband images– Spectral Energy Distributions
• Requires radiative transfer to take dust effects into account
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Monte-Carlo method“Photons” are emitted and scattered/absorbed stochastically
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Outputs
• Data cube for each camera, typically 300x300 pixels x 500 wavelengths– Can be integrated to give images in broadband filters– Or look at spectral characteristics
• Absorbed energy in grid cells– Determines FIR luminosity reradiated by dust– Devriendt FIR template SED is added to integrated spectra
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To Date:
• 20 merger scenarios completed
• 50 snapshots/scenario
• 11 viewpoints/snapshot
• 10 filters/viewpoint
=
• Many images… 100,000 images, 10,000 SEDs
Total of 1TB data
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Sbc vs. G-series galaxiesG3G3b-u1 Sbc201a-u4
G-series has less gas and hence less star formation and less dust.
(urz color)
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With dust
Without dust (urz color)
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Integrated energy
UV/vis brightness practically constant
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Magnitudes & Colors
Rapid change of attenuation andcolor at coalescence
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All simulations
Looks good…
Mostly different orbital configurations
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CMD
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Also Looks Pretty good
Comparing to Heckman et al (98)Explored correlations between quantities for starbursts
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Real
Selection effect
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But this is not so good… correlation is in the wrong direction!
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The effect of mass
Dust direction
Mass direction
3 different Sbcs with different massesFiducial
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The effect of IMF
Slope -2.35 Slope -3.3
Attenuation peaks at 60% instead of 80%
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The effect of orbit
Fiducial (prograde-prograde) Retrograde-retrograde
RR is about 50% brighter, but only in IR
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The effect of dust model
Milky-Way-type dust SMC-type dust
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Future
• Morphological analysis (Jennifer)
• SCUBA source comparison (Chapman)
• Improve SAM burst recipe
• …– What are we going to do with all the data?
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The End
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All viewpoints (long…)
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3 steps
For every GADGET snapshot:
• SED calculation
• Adaptive grid construction
• Radiative transfer
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Adaptive grid
200kpc size with max resolution 2pc, equivalent to a 1e5^3 uniform grid but with only 100k cells.
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Adaptive Grid construction
• Start with uniform grid (10^3)
• Recursively subdivide cells into 2^3 subcells, until– Maxlevel is reached– Cell size < min(r_i)*fudge
• Recursively unify cells as long as– (Sigma gas/<gas> < gas tolerance AND– Sigma L/<L> < L tolerance) OR– “cell is uniform enough that < 1 ray will be affected by unification”
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SED calculation
• Convolve SFR history with stellar model– Disk stars uniform SFR for 8 Gyr– Bulge stars instantaneous burst 8 Gyr old
• Single metallicity for SEDs
• Formed stars expand– 1km/s velocity dispersion
• End up with SED (500 points) for each particle
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MC input parameters
• M_dust/M_gas– Effectively determines metallicity of gas at the start of the
simulation
• M_dust/M_metals– From metals produced during the simulation
• Dust model (Draine 03 MW)– Dust opacity, albedo and scattering characteristics
And the info from the grid, of course, luminosity and density of gas & metals in the cells
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Radiative transfer stage
• Run entire SED at once without scattering
• Run with scattering for a single wavelength– 10^6 rays per wavelength, 11 view points– Repeat for 20 wavelengths between 20nm and 5um– And for lines (H alpha and H beta)
• Interpolate SED to full resolution
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IRX-Beta correlation