1. A NEAR-INFRARED STUDY OF THE SOUTHERN STAR FORMING REGION RCW 34 Lientjie de Villiers M.Sc. PROJECT SUPERVISOR: Prof. D.J. van der Walt

2. CONTENTS Star-formation The region RCW 34 M.Sc. Objectives Method Preliminary results Future objectives Relevance to SKA

3. From above the Jeans criterion can be derived as where the Jeans mass M J is given by the RHS of (1). STAR-FORMATION Molecular cloud Pre-stellar core Infrared protostar T Tauri  Pre-main sequence star From the Virial theorem, if  gravitational collapse of molecular cloud.

4. RCW 34 ~ 3 kpc L = 5 x 10 5 L  and R  23 R . Cometary shaped H II region. Bright point source in front of ionization front. Large IR excess  dust around exciting star. Near-IR observations  star formation at border of ionization front (Zavagno et al.) Source

5. OBJECTIVES Study stars associated with high mass star in NIR K s band (extinction less at 2.2  m) Stack images  Long integration times  obtain deep (~18 th –19 th mag) JHK s images  sub-solar – solar mass stars. Error vs magnitude graphs (reliability of data) Magnitude distribution histograms 2-Color diagram, dereddening 2-point correlation analysis of spatial clustering K s luminosity function (KLF) Initial Mass Function (IMF)

6. METHOD OBSERVATIONS & DATA REDUCTION JHKs-bands on 1.4 m IRSF. 30s exposure Reduction with the SIRIUS pipeline in IRAF (Image Reduction & Analysis facility) Stacked images  ~ 60min integration times.

7. METHOD SELECTION OF STARS Crowded field Initially: Source Extractor Problem: fixed apertures in crowded field – wrong photometry.

8. Solution 1: Aperture corrected photometry – no optimal aperture radius (graph of mag. vs. aperture radius) Solution 2: PSF photometry: In IRAF Extract stars with DAOFIND in Daophot (5  detection) Compute PSF with PSF task, using 20 stars selected by PSTSELECT Perform PSF fitting photometry using ALLSTAR

9. METHOD PHOTOMETRY Stacked all images of one night  no specific airmass  need different calibration method than standard stars Used 2MASS (2 Micron All Sky Survey) all-sky point source catalog  40 of brightest stars with coordinates corresponding with results of Daofind Get average offset between 2MASS and IRSF for each of the 40 stars & calculate standard deviation. EXTREMELY close linear correlation between 2MASS and IRSF magnitudes – confirmed by a very small standard deviation on the offsets. Calibrate by subtracting the obtained constant from magnitudes of all IRSF stars found by Daofind  Apparent magnitude.

10. PRELIMINARY RESULTS RELIABILITY OF DATA Relative error for N counts = Therefore as N , the relative error  Magnitude = thus Error on magnitude  Plot of magnitude-error vs magnitude  vs. N with inverse x-axis (minus sign).

11. PRELIMINARY RESULTS RELIABILITY OF DATA J-BAND

12. PRELIMINARY RESULTS RELIABILITY OF DATA H-BAND

13. PRELIMINARY RESULTS RELIABILITY OF DATA K s -BAND

14. 18.0 20 PRELIMINARY RESULTS APPARENT MAGNITUDE DISTRIBUTIONS Out of deep images & with the detection of stars on 5  level  Succeeded to detected very faint (low mass) stars 20.0

15. PRELIMINARY RESULTS APPARENT MAGNITUDE DISTRIBUTIONS 17.0 19.5

16. PRELIMINARY RESULTS APPARENT MAGNITUDE DISTRIBUTIONS 17.0 18.5

17. (2) PRELIMINARY RESULTS INTERSTELLAR REDDENING Difference in magnitude due to dust: m (0) = m - A (1) Reddening law (difference in intrinsic color due to reddening) E(J - H) = 0.107A v  [J - H] = [J – H] 0 + 0.107 A V Rieke & Lebofsky E(H - K) = 0.063A v  [H - K] = [H – K] 0 + 0.063 A V Slope of reddening lines: E(J-H) / E(H-K) (3)

18. PRELIMINARY RESULTS TWO-COLOR DIAGRAMS T Tauri: (J-H) = 0.58  0.11  (H-K) + 0.52  0.06 MS & Giant branches from Koorneef. T Tauri Locus (Meyer et. Al) Reddening: || to reddening vector (T Tauri due to disk) 5 A v Left – photometric err. Problem: 5  vs 15  2CD Suggestions: Maybe some stars are real: MS not infinitely narrow; Lada et al. (1993) found ~50%  20% of cluster shows NIR excess. New calibration constant for 5  detection level. Remove “bad-pixels” detected as “faint stars” Investigate errors on color terms – indication of accuracy. Two point correlation – field stars > 1-2 correlation lengths from center.

20. PRELIMINARY RESULTS TWO-COLOR DIAGRAMS Infrared excess Embedded stars – accretion disk / dust shell

21. FUTURE OBJECTIVES Investigate strange T Tauri clustering on 2CD. Determine location of T Tauri’s and IR excess stars on image (dusty regions ?). Two-point correlation. Characterize population of stars: KLS IMF

22. RELEVANCE TO SKA YSO & T Tauris still embedded  circumstellar matter radiate in IR – distinguish b.m.o. IR excess in 2CD Need to investigate star formation in IR at first to characterize population Expand to multi-wavelength Radio complements IR: Mapping Some stars with IR excess have hotspots of ~ 7000K  can get information about their rotation. With better angular- & spatial resolution of SKA  distinct between binary systems & stars currently indistinguishable  get thermal radiation of individual T Tauris.

23. THANK YOU!! Ps. 19:1 “The heavens declare the glory of God; And the firament shows His handiwork.”

25. STAR-FORMATION Virial theorem: (1)  condition for stable, gravitationally bound system. U g, K and R c into (1) with gives: (  = mean molecular weight) (5) If  gravitational collapse of molecular cloud Gravitational potential energy: (2) Kinetic energy (monatomic gas): (3) Radius i.t.o. density: (4)

26. RCW 34 Cometary shaped H II region G264.29+1.47 3.1 kpc Excited by O 9.5 Ib (O 8.5V) star (Vittone et al. & Heydari-Malayeri) L = 5 x 10 5 L  and R  23 R .

27. RCW 34 ~ 3 kpc L = 5 x 10 5 L  and R  23 R . Cometary shaped H II region. Near-IR observations  star formation at border of ionization front (Zavagno et al.) Source Molecular bar divided region into 3 regions: Dense, less dense & diffuse. Bright MSX & IRAS point source ( O 9.5 Ib) in front of ionization front  excites H II region. Large IR excess  dust around exciting star

28. RCW 34 Bright MSX (Midcourse Space Experiment) & IRAS point source in front of bright ionization front (Deharveng et al.). Near-IR observations  star formation at border of ionization front (Zavagno et al.) Source Large IR excess  dust around exciting star Molecular bar divided into 3 regions: Dense, heated  post shock Cold less dense  besides Diffuse  in front of dense parts (~10 2 per cm 3 & 30-60K)

29. METHOD TELESCOPE 1.4 m Infrared telescope at Sutherland NIR camera  SIRIUS Designed for deep & wide JHK s -bands simultaneous surveys (1.25, 1.65, 2.2  m). Images with 30s exposure time & total of 60 min integration time per night.

30. METHOD DATA REDUCTION SIRIUS pipeline 10 ditherings of telescope

31. Got “weird” stars with high error value at bright magnitudes Extracted “weird” stars’ coordinates Plot on image Bad pixels / dust  explanation PRELIMINARY RESULTS RELIABILITY OF DATA Relative error for N counts = Therefore as N , the relative error  Magnitude = thus Error on magnitude  Plot of magnitude-error vs magnitude  vs. N with inverse x-axis (minus sign).

32. PRELIMINARY RESULTS INTERSTELLAR REDDENING Difference in magnitude due to dust: m (0) = m - A (1) change in intrinsic color due to reddening: E(J – H) = 0.107A v  [J - H] = [J – H] 0 + 0.107 A V Known ratio: Rieke & Lebofsky [H - K] = [H – K] 0 + 0.063 A V

33. FUTURE OBJECTIVES Stellar clusters important in determination of IMF  equidistant & co-eval populations of stars  instantaneous sampling of IMF at different epochs in Galactic history.