(simulating the dynamics of the…) gas in interacting galaxies
DESCRIPTION
(simulating the dynamics of the…) Gas in Interacting Galaxies. John E. Hibbard North American ALMA Science Center (NAASC/NRAO) Josh Barnes Institute for Astronomy U. Hawai’i. “Gas & Stars in Galaxies: A Multi-wavelength 3D perspective” ESO, Garching, June 10-13 2008. - PowerPoint PPT PresentationTRANSCRIPT
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John E. HibbardNorth American ALMA
Science Center (NAASC/NRAO)
Josh BarnesInstitute for Astronomy
U. Hawai’i
(simulating the dynamics of the…)
Gas in Interacting Galaxies
“Gas & Stars in Galaxies: A Multi-wavelength 3D perspective” ESO, Garching, June 10-13 2008
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Peculiar Galaxies: dynamically unrelaxed (non-equilibrium) forms
Toomre Sequence of On-going Mergers (Toomre 1977) from Arp Atlas of Peculiar Galaxies (Arp 1966)
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5%-10% of population in local universe
In UGC, ~600 out of 9000 galaxies (~7%) with morphological descriptions including: disrupted, distorted, disturbed, interacting, eruptive, peculiar, bridge, loop, plume, tail, jet, streamer, connected (note, some are multiple systems, but not all need be interacting)
Total fraction that went through a peculiar phase = %peculiar * T/tpeculiar
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Morphologies (& Kinematics!) can be explained by galaxy-galaxy
interactions
Seminal Paper (1369 citations): Toomre & Toomre 1972
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Neutral Hydrogen in Galaxies
B/W=optical image of NGC 6946 from Digital Sky Survey
Blue=Westerbork Synthesis Radio Telescope 21 cm image of Neutral Hydrogen (Boomsma 2007 PhD Thesis)
Neutral Hydrogen is the raw fuel for all star formation
Hydrogen usually much more extended than stars
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Dynamically cold & extended HI responds strongly to the tidal
forces M81/M82/NGC3077VLA 12-pointing mosaic
Yun et al. 1994
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HI contours on DSS: van der Hulst, 1977, PhD. Thesis
HI kinematics strongly affirmed interaction hypothesis
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Spectral Line Maps are inherently 3-dimensional
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For illustrations, You must choose between many 2-dimensional projections
1-D Slices along velocity axis = line profiles
2-D Slices along velocity axis = channel maps
Slices along spatial dimension = position velocity profiles
Integration along the velocity axis = moment maps
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“Channel Maps”spatial distribution of line flux at each successive
velocity setting
QuickTime™ and aYUV420 codec decompressor
are needed to see this picture.
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Emission from channel maps contoured upon an optical image
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Moment Maps
Zeroth MomentIntegrated flux
First Momentmean velocity
Second Momentvelocity dispersion
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Position-Velocity Profiles
Slice or Sum the line emission over one of the two spatial dimensions, and plot against the remaining spatial dimension and velocity
Susceptible to projection effects
+250 km/s-250 km/s
-250 km/s
+250 km/s
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Rotating datacubes gives complete picture of data, noise, and remaining systematic
effects
QuickTime™ and aYUV420 codec decompressor
are needed to see this picture.
QuickTime™ and aYUV420 codec decompressor
are needed to see this picture.
Karma “xray” package & Oosterloo “cube2mpeg”
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Rotations emphasize kinematic continuity and help separate out projection effects
3-D rendering program “xray” in the Karma visualization package & “cube2mpeg”http://www.atnf.csiro.au/computing/software/visualisation/http://www.atnf.csiro.au/computing/software/karma/Gooch, R.E., 1996, "Karma: a Visualisation Test-Bed", in Astronomical Data Analysis Software and Systems V, ASP Conf. Series vol. 101, ed. G.H. Jacoby & J. Barnes, ASP, San Francisco, p.80-83, ISSN 1080-7926
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Rotations emphasize kinematic continuity and help separate out projection effects
QuickTime™ and aYUV420 codec decompressor
are needed to see this picture.
3-D rendering program “xray” in the Karma visualization package & “cube2mpeg”
http://www.atnf.csiro.au/computing/software/visualisation/
http://www.atnf.csiro.au/computing/software/karma/
Gooch, R.E., 1996, "Karma: a Visualisation Test-Bed", in Astronomical Data Analysis Software and Systems V, ASP Conf. Series vol. 101, ed. G.H. Jacoby & J. Barnes, ASP, San Francisco, p.80-83, ISSN 1080-7926
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3rd dimension allows us to construct more accurate numerical models
“Identikit” Mk 0
Hibbard 1995
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A few dozen model “matches” to interacting galaxies have been published
Only a handful “match” spatially resolved kinematics
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Models of binary interactions have a large
parameter space
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Model Matching: the Hard Way
Build two model galaxies (B+D+H; Barnes 1988; Barnes & Hernquist 1996)
Select 1 encounter geometry; run
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Model Matching: the Hard Way
Run model Match Build another & run Compare; decide how
to change params Etc… Takes ~50 trials to get
decent fit to simple forms (N7252 Hibbard & Mihos 1995; N4676 Hibbard & Barnes 1997)
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Identikit Mk 0.5: 9x18x2=324 simulations
in one
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Identikit Mk 1: simulate all disk geometries
Populate live halo with swarm of test particles on circular orbits
Display only test particles with initial angular momentum closely aligned with desired disks
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Test: generate 36 random BDH simulation & match
generate 36 random BDH self-consistent N-body simulations
Read into Identikit & Match
Subjectively grade fit: good, fair, poor
Check fit vs. actual parameters
Barnes & Hibbard 2008 submitted
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Identikit interactive modeling tool
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Identikit interactive modeling tool
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Red=“good” fits
Black=“fair” fits
Cyan=“poor” fits
Disk orientation parameters
Viewing Angles
Disk orientation All fits: 25deg Good fits: 10deg
Viewing angles All fits: 25deg Good fits: 8deg
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Red=“good” fits
Black=“fair” fits
Cyan=“poor” fits
Time since pericenter
Pericentric Separation
Time since pericenter
All fits: 14% Good fits: 9%
Pericentric separation
All fits: 25% Good fits: 15%
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Red=“good” fits
Black=“fair” fits
Cyan=“poor” fits
Linear Scale Factor
Velocity Scale Factor
Linear scale factor All fits: 16% Good fits: 10%
Velocity scale factor*
All fits: 15% Good fits: 5%
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Identikit interactive modeling tool
Can match models fairly well Models judged as good fits are better
able to recover true parameters Perhaps more importantly, models that
do not recover true parameters are judged as fair/poor fits (no false positives)
Caveat: simulated “real” systems had the same radial mass profile as Identikit models
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Tools like Identikit 1 can greatly speed model matching process
Hibbard, 1993-1997: Identikit 0 for N7252, N4676, N4038 ~50 simulations per system, ~2mo
each Barnes, 2008: Identikit 1:
matched 36 systems in ~1 mo
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Why bother matching?
So you know some angles and scale factors, so what?
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QuickTime™ and aYUV420 codec decompressor
are needed to see this picture.
Time Evolution
System made first pass ~220 Myr ago; will merge in ~40 Myr
1 million particlesimulation of best fitting parameters
http://www.ifa.hawaii.edu/~barnes/pressrel/antfacts/
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QuickTime™ and aYUV420 codec decompressor
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3-dimensional structure of The Antennae
http://www.ifa.hawaii.edu/~barnes/pressrel/antfacts/
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Why is base of northern tail devoid of HI, while southern tail is gas rich?
- Gas in northern tail has direct view of young SSCs with ionizing radiation- Gas in southern tail does not
Simulation confirms that 3-D geometry is suitable for this interpretation
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Next Generations telescopes require novel visualization
approaches 2009: EVLA widar correlator
2:1 bandwidth ratios16k-4M channels!
2012: ALMA10 bands4096 channels per IFHundreds of atomic & molecular transitions in the
mm-submm IN THE SAME DATA CUBES
Both: All spectral mode, all the time
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Imaging Chemistry in Galaxies
IC 342 — Owens Valley Millimeter Array
PC Axis 1:
Density-weightedmean column density
PC Axis 2:
Shock tracers vs PDR molecules
Gas density: CO, N2H+, HCNC2H: PDR
Methanol, HCNO: shocks
Meier & Turner 2005
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Detected interstellar molecules
H2 HD H3+ H2D+ CH CH+ C2 CH2 C2H *C3
CH3 C2H2 C3H(lin) c-C3H *CH4 C4
c-C3H2 H2CCC(lin) C4H *C5 *C2H4 C5HH2C4(lin) *HC4H CH3C2H C6H *HC6H H2C6
*C7H CH3C4H C8H *C6H6
OH CO CO+ H2O HCO HCO+HOC+ C2O CO2 H3O+ HOCO+ H2COC3O CH2CO HCOOH H2COH+ CH3OH CH2CHOCH2CHOH CH2CHCHO HC2CHO C5O CH3CHO c-C2H4O CH3OCHO CH2OHCHO CH3COOH CH3OCH3 CH3CH2OH CH3CH2CHO(CH3)2CO HOCH2CH2OH C2H5OCH3 (CH2OH)2CONH CN N2 NH2 HCN HNC N2H+ NH3 HCNH+ H2CN HCCN C3NCH2CN CH2NH HC2CN HC2NC NH2CN C3NHCH3CN CH3NC HC3NH+ *HC4N C5N CH3NH2
CH2CHCN HC5N CH3C3N CH3CH2CN HC7N CH3C5N? HC9N HC11NNO HNO N2O HNCO NH2CHO SH CS SO SO+ NS SiH*SiC SiN SiO SiS HCl *NaCl*AlCl *KCl HF *AlF *CP PNH2S C2S SO2 OCS HCS+ c-SiC2
*SiCN *SiNC *NaCN *MgCN *MgNC *AlNCH2CS HNCS C3S c-SiC3 *SiH4 *SiC4
CH3SH C5S FeO
DEMIRM
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END
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Young star clusters
Why is base of northern tail devoid of HI, while southern tail is gas rich?
- gas in northern tail has direct view of young SSCs with ionizing radiation
- Gas in southern tail does notSimulation confirms that 3-D geometry is suitable for this interpretation