1. Nicola Da Rio Department of Astronomy, University of Florida The pre-main sequence population of the Orion Nebula Cluster. Optical studies The pre-main sequence population of the Orion Nebula Cluster. Optical studies M. Robberto (STScI) – R. Jeffries (Keele) – J. Tan - L. Hillenbrand (Caltech) – D. Soderblom (STScI) – C. Manara (ESO) – G. Scandariato (INAF Catania) – M. Reggiani (ETH) – F. Palla (INAF Arcetri) – K. Stassun (Vanderbild) – L. Ricci (Caltech) M. Robberto (STScI) – R. Jeffries (Keele) – J. Tan - L. Hillenbrand (Caltech) – D. Soderblom (STScI) – C. Manara (ESO) – G. Scandariato (INAF Catania) – M. Reggiani (ETH) – F. Palla (INAF Arcetri) – K. Stassun (Vanderbild) – L. Ricci (Caltech) The Orion Nebula Cluster as a Paradigm of Star Formation Space Telescope Science Institute, October 13-16 2013

2. “Complete” census of the PMS population in the Orion Nebula Cluster. (Da Rio et al, 2009, 2010, 2012) Individual spectral types and A V for >1800 sources. 40’x40’ – 3pc x 3pc 2.2 ESO-MPG/WFI UBVI+H  +620nm (2005) I + 770nm + 753nm (2010) Survey started as part of the HST Orion Treasury Program Ongoing updates are being carried out.

3. 1)Collection of spectral types from Hillenbrand (1997) 2)>200 new spectral types from 620nm narrow band photometry (Da Rio et al 2010)

4. 1)Collection of spectral types from Hillenbrand (1997) 2)>200 new spectral types from 620nm narrow band photometry (Da Rio et al 2010) 3)>500 new spectral types from 770nm narrow band photometry (Da Rio et al 2012) T eff AVAVAVAV

5. 1)Collection of spectral types from Hillenbrand (1997) 2)>200 new spectral types from 620nm narrow band photometry (Da Rio et al 2010) 3)>500 new spectral types from 770nm narrow band photometry (Da Rio et al 2012)

6. what are the intrinsic (photospheric) colors of young PMS stars? do the intrinsic colors depend on age? Intrinsic optical colors in Orion differ from MS dwarfsdiffer from MS dwarfs are not reproduced by current atmosphere modelsare not reproduced by current atmosphere models MS 2Myr isoch Av = 2 Inaccurate calibration of colors and temperature scale systematic offsets in A V, masses, ages (see also Naylor et al works)

7. Colors are shifted to the blue due to accretion hot spots on the stellar surface Disentangling accretion and extinction for individual stars: 1)Simulation of an accretion spectrum, considering optically thick + thin emission. 2)Computation of the shifts in the colors adding L acc to a star of given temperature 3)Solution for L acc and A V from multi- band photometry and known spectral type. Better estimate of AV Not a good indicator for the determination of Lacc

8. Dramatic lack of brown dwarfs in Orion -compared to canonical IMFs -compared to other young stellar clusters Chabrier system Chabrier stellar Kroupa

9. Andersen et al. (2011) NICMOS photometry no deficiency of BDs Brown dwarfs segregated Previous works on BDs / substellar IMF in Orion also included under-luminous sources, likely background contaminants. (e.g. Slesnick et al 2004, Riddick et al 2007) contamination

10. Rob Jeffries’ talk Isochronal ages show a spread of ~0.4 dex around 2.5Myr (model dependent!) This spread is not produced by uncertainties (Reggiani+2012) Several pieces of evidence (Disk-age correlation Jeffries et al 2011, and mass accretion – age biases, Da Rio et al submitted ) point to a 0.2 dex real age spread Bayesian estimate of allowed combinations of age spread, uncertainties and diversity of protostellar accretion to reproduce the observed HRD

11. Meyer (1997) Robberto et al. (2010)

12. Meyer (1997) Extinction map (Scandariato et al. 2011)

13. Available T eff and A V + near-infrared photometry 1)Calibration of intrinsic colors and consequences on the IMF (Scandariato et al 2012) Meyer (1997) 2)CTTS NIR locus (Scandariato et al, in prep)

14. The knowledge of the (in)accuracies severely impacts ours understanding of Orion see Reggiani et al. (2011) Meyer (1997) Hillenbrand (2013) RMS=1.75 subtypes Are we overestimating the accuracy of the stellar parameters? How many sources have VERY wrong assigned stellar parameters (see Manara et al 2013) RMS=2.25 subtypes

15. -Spatially variable extinction -Inhomogeneous detection limits May cause Do cause selection effects when looking for correlations Meyer (1997)

16. ACS NICMOS WFPC2 Robberto et al (2013) 104 orbits Full coverage ACS BVIZ H  WFPC2 UBI H  Partial coverege NICMOS JH

17. Ricci et al (2009) catalog of proplyds Robberto et al (2009) evidence for a circumbinary proplyd and.. Manara et al. (2012) – accretion rates from WFPC2 U and Ha excess Reggiani et al (2011) – role of stellar parameter uncertainties in age spread Andersen et al (2011) – substellar IMF Press release, credits NASA/ESA and L. Ricci (ESO)

18. The HST photometry is deep enough to reach down to planetary masses. The NIR surveys probe into the embedded populations. Lack of memberships or spectral types is limiting. FIELD 0.5M  0.08M  0.02M  0.5M  0.08M  0.02M  ACSNICMOS

19. Meyer (1997) The HST photometry is deep enough to reach down to planetary masses. The NIR surveys probe into the embedded populations. Lack of memberships or spectral types is limiting. Green: spectral types from Da Rio+ (2010) Red: spectral types from Da Rio+ (2012) Black: ACS photometry Robberto et al (2013) FIELD

20. Meyer (1997) 1)Spectral types collected by dozens of works 2)Multi band and multi-epoch photometry Pan-Starrs 3)Membership estimators and other (circum)stellar properties: Proper motions (Parenago 1954, Jones & Walker 1998, McNamara 1976, Tian et al. 1996) X-ray emission (Getman+2005) Disk excess (Megeath+2012, Morales-Caleron+2011) Accretion tracers (Rebull, Manara, Da Rio, Robberto, …) Stellar variability and rotation (Rodriguez-Ledesma+2009, Herbst+2002, Jeffries+) Radial velocity (Furesz+2008, Tobin+2009,.. ) A universal (inspected and reasoned) catalog of all stellar information in the ONC? Black: ACS photometry Increase the sample Detect and correct for problems Improve estimates of stellar properties

21. Meyer (1997) Black: ACS photometry Identical observational setup as in Da Rio et al (2012) Is NGC1980 a foreground older cluster (Alves & Bouy 2012) How does average age and age spread vary along the filament?

22. Meyer (1997) Black: ACS photometry APOGEE fiber spectrograph at the SDSS High resolution NIR spectra of 2700 candidate members down to H=12.5 (0.5M  ) Radial velocities with 0.3-0.5 km s -1 accuracy of nearly all known members Larger coverage than previous works Less limited by extinction Tobin 2009

23. We have obtained the “full” census of the ONC stellar population. Unpublished updates are and will be present. The accuracy of derived stellar parameters is un part unclear. Beware of spatially non uniform incompleteness. IMF is deficient of brown dwarfs. Future extension of the sample to the lowest masses is needed to settle the debate. The full potential of the Orion HST Treasury program has not been yet used. We need deep surveys to get memberships and spectral types in the substellar range. A universal catalog of stellar properties in Orion could enable a number of new studies Coming soon: extension of census along the Orion A filament and RV

24. Huff & Stahler (2006) Do we see radial variations of average age in Orion? The signal, if real, must be corrected for uncertainties and selection effects

25. Luminosity spread leads to isochronal ages spanning from 10 Myr  (log t)=0.4 dex But several uncertainties in the estimated stellar parameter broaden the age distribution

26. Reggiani et al (2011) : modeling of the sources of apparent spread: unable to reproduce the observed spread. Jeffries et al. (2007) : projected radii compatible with spread of R (factor 2-3) Jeffries et al. (2011) : no disk frequency – age correlation:  log t < 0.2 Littlefair et al (2011): stellar rotation spins down with increasing isochronal age The real age spread has a width of ~<0.2 dex (half of the total one) Protostellar accretion diversity may play a role The associated uncertainty is uncertain... Uncertainties in the stellar parameter do not dominate the broadening. The spread in stellar radii (at same T eff ) is real. The spread in radii cannot represent an age spread The population cannot be coeval either

27. 1) Detailed spectral analysis of faint PMS stars accretion rates, spectral types, luminosity lithium abundance surface gravity VLT/X-Shooter spectra of 2 OPMS (Manara et al, in prep.): 2) Measurement of mass accretion rates in protostars calibration of MIR lines as accretion diagnostics. What is the range of accretion rates? What is the fraction of bursts? 3) Population synthesis analysis including episodic accretion. Can we reproduce the observed HRD assuming: No mass-dependence of average age No mass-dependence of age spreads Sergison et al (in prep) + = ? intermediate masses low mass stars

28. Selection of the members based on proper motions  2 – like analysis of cluster age probability distributions the measured age spread is <1Myr just accounting for binaries Kudryavtseva et al (2012): instantaneous starburst of the massive clusters Wd1 and NGC3603

29. Gullbring et al. (2000)Sicilia-Aguilar et al. (2006)Muzerolle et al. (2003) Mass accretion produces flux excesses: UV continuum (shock) Recombination lines (infall) Optical veiling (heated photosphere)

30. Manara et al. (2012) -Accretion rates derived for >700 ONC members, from both H  excess and U-band excess. -Complete down to the H- burning limit; 2/3 of the ONC members show evidence of on-going accretion -The accretion rate decreases more slowly for intermediate mass stars.

31. Manara et al (2012) -Accretion rates derived for >700 ONC members, from both H  excess and U- band excess. -Complete down to the H-burning limit; 2/3 of the ONC members show evidence of on-going accretion -The accretion rate decreases more slowly for intermediate mass stars.

32. Hosokawa, Offner, Krumholz (2011) ? No Spread Apparent spread

33. 1.The mass accretion rate depends on the stellar parameters. 2.The stellar parameters of young stars are always very uncertain. Mass and age are function of L, R is also function of L, R What is the bias in the estimated dependence of accretion on mass and age?

34. 1.Simulate PMS populations of different ages and age spreads 2.Assign values of mass accretion rate, with different mass and age dependences 3.Introduce uncertainties, scattering the stellar parameters 4.Rederive the mass accretion rate, as it would be measured  (log t) real =0.2  t>=2.5 Myr

35. 1.Simulate PMS populations of different ages and age spreads 2.Assign values of mass accretion rate, with different mass and age dependences 3.Introduce uncertainties, scattering the stellar parameters 4.Rederive the mass accretion rate, as it would be measured  (log t) real =0.2  t>=2.5 Myr

36. 1.Simulate PMS populations of different ages and age spreads 2.Assign values of mass accretion rate, with different mass and age dependences 3.Introduce uncertainties, scattering the stellar parameters 4.Rederive the mass accretion rate, as it would be measured  (log t) apparent =0.4  t>=2.5 Myr

37. 1.Simulate PMS populations of different ages and age spreads 2.Assign values of mass accretion rate, with different mass and age dependences 3.Introduce uncertainties, scattering the stellar parameters 4.Rederive the mass accretion rate, as it would be measured  (log t) apparent =0.4  t>=2.5 Myr

38. Case A: both L acc and L star altered Case B: only L star altered Case C: episodic accretion  (log t) real =0.2  (log t) apparent =0.4

39. Smaller real age spread  (log t) real =0.1  (log t) apparent =0.4 Larger real age spread  (log t) real =0.3  (log t) apparent =0.4

40. Luminosity spread introduces a fake dependence of mass accretion with isochronal age

41. T eff uncertainty differential A V Apparent mass-age correlation

42. 1.Simulate PMS populations of different ages and age spreads 2.Assign mass accretion rates, and transform them into observable quantities (e.g., Ha excess) 3.Assign a detection limit, and a photometric error distribution 4.Isolate sources which are: a.Detected and with dM/dt measured b.Detected but excess is smaller than the photometric error c.Undetected 5.Fit the a) sample Slopes flatten towards  ~1

43. The bias in h is dictated mostly by: the real age spread the total apparent age spread 1)The decay of mass accretion rate must be much faster than previously assumed >(~age -3 ) 2)The real age spread must be >  (log t)=0.2 dex Fast clearing of inner circumstellar disks Slow star formation dM/dt~t -4

44. Total apparent age spread Observational uncertainties Disk fraction Accretion rate vs age bias  log t = 0.4 dex 0.15 dex 0.2 dex Episodic accretion- induced spread? Slow star formation. Episodic accretion seems to play a marginal role. Uncertainties remain large. contributions add in quadrature Constraints not well constrained

45. A IDL-based software to simplify the analysis of stellar photometric data with respect to models. 1)Interpolation of evolutionary models 2)Synthetic photometry 3)Data / models quick look and selection 4)Interpolation of stellar parameters / SED fitting on multi-band photometry General and versatile Usable NASA APRA grant, P.I. M.Robberto

64. Da Rio & Robberto 2012, AJ 144,176

65. http://www.rssd.esa.int/Faculty/Staff/dario/TADA/