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The Spitzer IRS Debris Disk Catalog
Chris4ne H. Chen (STScI), Tushar Mi>al (Berkeley), P. Manoj (TIFR), B. Sargent (RIT),
D. M. Watson, W. J. Forrest (U Rochester), & C. M. Lisse (JHU-‐APL)
Spitzer IRS Spectrograph (IRS)
Dust Spa)al Distribu)on
• Typically well-‐fit assuming black bodies consistent with dust located in rings (Chen et al. 2006)
Dust Composi)on
• Typically includes silicates and trace species indica4ng how processed parent bodies are and therefore their origin
HD 172555: glassy silicas (Obsidian and Tek4te), steep grain size distribu4on with large quan44es of fine dust and possible fundamental and first overtone emission from SiO -‐> Hypervelocity Collision (Lisse, Chen et al. 2009)
Eta Crv: warm, water-‐ and carbon-‐rich dust in the terrestrial habitable zone -‐> Period of Late Heavy Bombardment (Lisse, Wya>, Chen et al. 2012)
Two Dust Components?
Morales et al. (2011)
IRS Observa4ons of Debris Disks
• Approximately 571 debris disks observed by Spitzer GTOs, Legacy Teams, and GOs during the cryogenic mission
• Spectral Types: typically B9 – K5, corresponding to es4mated masses 0.5-‐5.5 M¤
• Ages: evenly divided amongst logarithmic age bins: 10 Myr – 100 Myr, 100 Myr – 1 Gyr, 1 Gyr – 10 Gyr
• Distance: typically <300 pc
Spectral Energy Distribu4ons
• Stellar Photosphere Modeling – Hipparcos BV – 2MASS JHKs
• Infrared Excess Modeling – IRS – MIPS – Herschel, where
available – Submm, where
available • Consistency Checking
– Akari – WISE
Spectral Energy Distribu4on Analysis
Black Body Fi8ng • Full sample: 571 targets • Assume SED is well fit using
zero, one, or two black bodies • Calculate average probability
for each model over assumed parameter space
• Select model with lowest average probability
• Search for trends in disk proper4es (number of belts, LIR/L*, Tdust) as a func4on of stellar proper4es (M*, tage)
Silicate Emissivity Fi8ng • Subset: 120 targets • Assume SED is well fit using
spherical silicate grains (e.g. olivine, pyroxene, forsterite, ensta4te)
• Use Par4cle Swarm Op4miza4on (PSO) algorithm to search phase space for absolute minima
• Use Markov Chain Monte Carlo (MCMC) to trace out prior Probability Distribu4on Func4ons (PDFs)
• Search for trends in grain (size distribu4on, crystalline frac4on) and disk proper4es as a func4on of stellar proper4es
Black Body Models
• Assume grain temperature grid 30 K < Tgr,1 < 500 K (5 K)
• Select model with maximum probability
• Es4mate uncertainty in fihng parameters from fihng confidence levels
• Select among zero, one, and two black body models by calcula4ng the average χ2 for model phase space
Fihng Parameter Distribu4ons
Approximately 167 disks are be>er fit using a single temperature black body and 333 disks are be>er fit using two black bodies
Radia4ve Equilibrium
• Dust grains in radia4ve equilibrium are expected to have a grain temperature
• We perform a linear regression: log Tgr = α + β log L*
Tgr = (L*
16πD2σ)1p+4
where
Qabs,ν =Qabs,νo( ννo
)p
α β
Single 2.08±0.04 0.17±0.03
Hot 2.43±0.02 0.05±0.02
Cold 1.78±0.02 0.13±0.01
Silicate Feature Source Selec4on
• Integrated Flux:
• Uncertainty in Integrated Flux:
• Select targets with SNR10 and/or SNR20 = Fint/σint > 4
Dust Models
Con)nuous Disk
• Grain Size Distribu4on dn/da ~ a-‐q
• Surface Density Profile Σ ~ D-‐r
• Parameters – amin, amax, q – Din, Dout, r – Number of Olivine, Pyroxene,
Forsterite, and Ensta4te grains
Two Dust Grain • Parameters
– Temperature, T – Grain size, a – Number of Olivine,
Pyroxene, Forsterite, and Ensta4te
Mi>al et al., ApJ submi>ed
Fihng Parameter Constraints
Summary: • Con4nuous Disk Model (6) • Two Dust Grain Model (22) • Either Model (73) • More Complicated
Emissivi4es (19)
Two Step Hybrid Algorithm • Step 1: Par4cle Swarm
Op4miza4on • Step 2: Monte-‐Carlo
Markov Chain
Grain Size Distribu4on
• Large varia4on in grain size distribu4on for disks with the same age
Grain Size Distribu4on
• Collisional equilibrium predicts dn/da ~ a-‐3.5 (Dohnanyi 1969) • Collisional cascade predicts dn/da ~ a-‐4 (Pan & Schlich4ng 2012)
Minimum Grain Size The size at which the force due to radia4on pressure exceeds that of gravity (Artymowicz 1988)
Assuming M* ~ L*0.25, then we expect that amin ~ L*0.75
Linear regression indicates that the minimum grain size is less strongly dependent on L* than expected
a =3L* <Qpr (a)>16πGM*cρ
On-‐line Materials
• “The Spitzer Infrared Spectrograph Debris Disk Catalog. I. Con4nuum Analysis of Unresolved Targets” C. H. Chen, T. Mi>al, M. Kuchner, W. J. Forrest, C. M. Lisse, P. Manoj, B. A. Sargent, & D. M. Watson 2014, ApJS, 211, 25 – Spectral Energy Distribu4ons, Probability Distribu4on Func4ons, Stellar Proper4es, Photometry, Fit Parameters (ApJS)
– IRS Spectra (calibrated and photosphere subtracted, VizieR) • “The Spitzer Infrared Spectrograph Debris Disk Catalog. II.
Silicate Feature Analysis of Unresolved Targets” T. Mi>al, C. H. Chen, H. Jang-‐Condell, P. Manoj, B. A. Sarget, D. M. Watson, W. J. Forrest, C. M. Lisse 2014, ApJ, submi>ed – Probability Distribu4on Func4ons, Fit Parameters (ApJ)