Christophe Pinte. Multi-technique observations and modelling of protoplanetary disks. University of Exeter

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1 Multi-technique observations and modelling of protoplanetary disks Christophe Pinte University of Exeter Christophe Pinte Multi-technique modelling 1/12

2 Collaborators F. Ménard, G. Duchêne, J.C. Augereau, J. Olofsson, C. Ceccarelli, G. Duvert (LAOG, Grenoble) D.L. Padgett, K. Stapelfeldt (IPAC & JPL/Caltech) G. Schneider (Steward Observatory) P. Woitke, W.F. Thi, I. Tilling (ROE, Edinburgh) I. Kamp (KAI, Groningen) J. Cernicharo (DAMIR/CSIC, Madrid) the GASPS team Christophe Pinte Multi-technique modelling 2/12

3 Protoplanetary disks Gas and dust disks are the birthplace of planets? Goal :characterizing the first steps of planet formation Understanding disk structure as well as dust grain and gas properties to test their evolution processes. For instance: grain growth and settling gas dissipation formation of a large variety of planetary systems Christophe Pinte Multi-technique modelling 3/12

4 A variety of observations Each approach probes a different part of the disk Disk modelling must consider as many observations as possible at once HST/Nicmos HST/WFPC2 HST/WFPC2 1.6 µm 0.8 µm 0.6 µm Multi-λ modelling Not so frequent...but necessary! VLTI Spitzer 5-30 µm SMA 1.3mm Christophe Pinte Multi-technique modelling 4/12

5 A variety of observations Each approach probes a different part of the disk Disk modelling must consider as many observations as possible at once OI H 2 O CO rotational lines CII Multi-λ modelling Not so frequent...but necessary! The same is true for the gas phase Christophe Pinte Multi-technique modelling 4/12

6 Multi-λ modelling of IM Lupi Pinte et al, RT modelling with MCFOST (Pinte et al 2006) A single model with mild stratification remarkably reproduces all observations: H(1 mm) H(1 µm) 1 WFPC2 E 0.6 µm N Fν (Jy) 0.1 SMA 1.3mm p=2 λ.fλ (W.m 2 ) λ (µm) M disk, grain growth and settling Nicmos 1.6 µm Obs Models R ext, i, H 0, grain sizes & composition Fν (Jy) p=0 ATCA 3.3mm p=2 p= Baseline (kλ) p=1 p=1 Surface density Σ(r) r p Christophe Pinte Multi-technique modelling 5/12

7 IM Lup : quantitative constraints Pinte et al, 2008 Bayesian probabilities SED models Some parameters fixed from data (a max, M dust, R out ) + Fitting 6 parameters Bayesian approach to estimate model parameters Probability Probability cos(i) r in (AU) surface density h 0 (AU) flaring stratification Christophe Pinte Multi-technique modelling 6/12

8 IM Lup : quantitative constraints Pinte et al, 2008 Bayesian probabilities SED + mm visibilities models Some parameters fixed from data (a max, M dust, R out ) + Fitting 6 parameters Bayesian approach to estimate model parameters Probability Probability cos(i) r in (AU) surface density h 0 (AU) flaring stratification Christophe Pinte Multi-technique modelling 6/12

9 IM Lup : quantitative constraints Pinte et al, 2008 Bayesian probabilities SED + mm visibilities + scattered light images models Some parameters fixed from data (a max, M dust, R out ) + Fitting 6 parameters Bayesian approach to estimate model parameters Probability Probability cos(i) r in (AU) surface density h 0 (AU) flaring stratification Christophe Pinte Multi-technique modelling 6/12

10 IM Lup : quantitative constraints Pinte et al, 2008 Bayesian probabilities SED + mm visibilities + scattered light images models Some parameters fixed from data (a max, M dust, R out ) + Fitting 6 parameters Bayesian approach to estimate model parameters Probability Probability cos(i) r in (AU) surface density h 0 (AU) flaring stratification Christophe Pinte Multi-technique modelling 6/12

11 Simultaneous modelling of gas & dust Detailed model of the dust disk of IRAS Glauser et al, 2008 Radiative transfer + chemistry 1 Temperature structure, UV flux from MCFOST 2 CO abundance from chemistry model (coll. with C. Ceccarelli) 3 Level populations and emission maps with MCFOST central mass (0.3-M ) age turbulence (-0.3km.s 1 ) Flux (Jy) Obs Model v (km.s 1 ) v (km.s 1 ) Scattered light (HST) & 12 CO(3-2) (SMA) Christophe Pinte Multi-technique modelling 7/12

12 GASPS and the DENT grid of models Gas in Protoplanetary Systems (GASPS) key program Systematic survey of gas and dust in disks (PI: W. Dent) 250 disks, 0.3 to 30 Myrs, spectral types: M4 to B2 PACS: OI, CII, CO and H 2 O + continuum The DENT model grid (see poster B47 by P. Woitke) coupling MCFOST & ProDiMo (Woitke et al 2009) SEDs + NLTE line fluxes (+physical & chemical structure) for disks models dependence of continuum & line observation on star, disk and dust properties Christophe Pinte Multi-technique modelling 8/12

13 Signatures of dust settling Far-IR is the regime where signatures of dust settling are maximum probed by Herschel Spitzer Herschel IRAM Color-magnitude diagrams distinction between settled and non settled disks independent of the geometry, dust properties,...if T eff and M disk known Christophe Pinte Multi-technique modelling 9/12

14 Signatures of dust settling Far-IR is the regime where signatures of dust settling are maximum probed by Herschel Color-magnitude diagrams distinction between settled and non settled disks independent of the geometry, dust properties,...if T eff and M disk known [210 µm] - [24 µm] Spitzer Herschel IRAM [24 µm] Christophe Pinte Multi-technique modelling 9/12

15 Constraining the gas disk Herschel/PACS should detect lines even for low luminosity T Tauri stars GASPS sensitivity limit First results of the DENT grid Most lines scale with stellar parameters: L star and UV excess Line ratios eliminate the main scalings information about disk mass and shape Christophe Pinte Multi-technique modelling 10/12

16 H 2 O lines with HIFI Cernicharo et al, 2009 Dust settling dramatically changes the conditions for water vapor in disk H 2 O lines powerful tool But dangerous strongly depends on collisional coefficients Christophe Pinte Multi-technique modelling 11/12

17 Concluding remarks A variety of datasets = finer disk models Dust evolution and spatial differentiation are frequent in disks around T Tauri stars By combining line and continuum data, more detailed information about the disks Testing the physics of dust grains towards planet formation Grain growth Separate dust populations dust and gas evolution? Simultaneous studies of the gas & dust phases are promising in the context of Herschel and ALMA Christophe Pinte Multi-technique modelling 12/12