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University of Chicago 2007 July 30 SOFIA-POL 2007 The Infrared - Millimeter Polarization Spectrum John Vaillancourt California Institute of Technology.

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Presentation on theme: "University of Chicago 2007 July 30 SOFIA-POL 2007 The Infrared - Millimeter Polarization Spectrum John Vaillancourt California Institute of Technology."— Presentation transcript:

1 University of Chicago 2007 July 30 SOFIA-POL 2007 The Infrared - Millimeter Polarization Spectrum John Vaillancourt California Institute of Technology

2 University of Chicago 2007 July 30 SOFIA-POL 2007 Observing Goals for FIR Polarization Spectra Characterize spectrum of different environments –Dense cloud cores –Cloud envelopes –Isolated cores / protostars T-tauri stars, Bok globules, other Class I - IV objects –Diffuse clouds - Different morphologies of IR Cirrus clouds Test models of alignment efficiency –Radiative torques increase alignment efficiency :  correlation between percent polarization and 1.location of embedded stars (direct) 2.location of dense clumpy material (inverse) 3.dust temperature and/or spectral index (in p.o.s & along l.o.s.) a)spectrum falls with (direct) b)spectrum rises with  (inverse) B-field orientation changes with depth into cloud, or is unresolved

3 University of Chicago 2007 July 30 SOFIA-POL 2007 Magnetic field vs. Wavelength 60  m, 100  m, 350  m, 850  m W3 W51 Schleuning et al. 2000 (350  m grayscale/contours) Dotson et al. 2000 Dotson et al. 2007 Chrysostomou 2002

4 University of Chicago 2007 July 30 SOFIA-POL 2007 OMC-1: 450/350  m polarization spectrum E-vectors Orion Molecular Cloud: 3  polarization vectors from SHARP/SHARC-II Red = 350  m, Blue = 450  m, Purple = 850 (SCUBA) 10 arcsec beam B-vectors

5 University of Chicago 2007 July 30 SOFIA-POL 2007 OMC-1: 450/350  m position angle variation Diamonds mark positions of BNKL, Trapezium, and KHW (north to south) Median angle difference  (450) -  (350) ~ -8 degrees (i.e. CW rotation with ) P > 3 

6 University of Chicago 2007 July 30 SOFIA-POL 2007 Observing Goals for FIR Polarization Spectra Characterize spectrum of different environments –Dense cloud cores –Cloud envelopes –Isolated cores / protostars T-tauri stars, Bok globules, other Class I - IV objects –Diffuse clouds - Different morphologies of IR Cirrus clouds Test models of alignment efficiency –Radiative torques increase alignment efficiency :  correlation between percent polarization and 1.location of embedded stars (direct) 2.location of dense clumpy material (inverse) 3.dust temperature and/or spectral index (in p.o.s & along l.o.s.) a)spectrum falls with (direct) b)spectrum rises with  (inverse) B-field orientation changes with depth into cloud, or is unresolved

7 University of Chicago 2007 July 30 SOFIA-POL 2007 Measured Polarization Spectra Cloud Envelopes Vaillancourt 2002, 2007 Matthews et al. 2002 P drops with increasing opacity in cores P ~ [1 - ( 0 /   ] In cloud envelopes, polarization minimum ~ 350  m Cloud Cores Schleuning 1998 Orion - KHW Orion - KL Normalized Polarization

8 University of Chicago 2007 July 30 SOFIA-POL 2007 Observing Goals for FIR Polarization Spectra Characterize spectrum of different environments –Dense cloud cores –Cloud envelopes –Isolated cores / protostars T-tauri stars, Bok globules, other Class I - IV objects –Diffuse clouds - Different morphologies of IR Cirrus clouds Test models of alignment efficiency –Radiative torques increase alignment efficiency :  correlation between percent polarization and 1.location of embedded stars (direct) 2.location of dense clumpy material (inverse) 3.dust temperature and/or spectral index (in p.o.s & along l.o.s.) a)spectrum falls with (direct) b)spectrum rises with  (inverse) B-field orientation changes with depth into cloud, or is unresolved

9 University of Chicago 2007 July 30 SOFIA-POL 2007 The Diffuse ISM: Infrared Cirrus Clouds - All grains exposed to same radiation field Finkbeiner, Davis, & Schlegel (FDS99) - - high latitude dust –T = 9.5 K,  = 1.7 (silicate) –T = 16 K,  = 2.7 (graphite) If silicate is polarized and graphite unpolarized:  T C > T Si, p C < p Si  Polarization rises with wavelength IRAS 100  m N. Gal. Pole (FDS99) T A > T B, p A < p B

10 University of Chicago 2007 July 30 SOFIA-POL 2007 Improving the Polarization Spectrum: Wavelength SHARP @ CSO 350 & 450  m, 620  m SCUBA-2 @ JCMT 450 & 850  m Bolocam @ CSO - 1100  m HAWC @ SOFIA 53, 88, 155, 215  m

11 University of Chicago 2007 July 30 SOFIA-POL 2007 Improving the Polarization Spectrum: Sensitivity  p ~ 1% in 5 hrs  Improved sensitivity allows observations of more diffuse clouds InstrumentWavelength (  m) Beam size (arcsec) Sensitivity (MJy/sr) No. of IR filaments HAWC8894002 1551510049 215216053 SHARP450103003 SCUBA-2*850152*60* BOLOCAM1100300.275 * Photometry only Consider filaments from Jackson, Werner, & Gautier 2003

12 University of Chicago 2007 July 30 SOFIA-POL 2007 Observing Goals for FIR Polarization Spectra Characterize spectrum of different environments –Dense cloud cores –Cloud envelopes –Isolated cores / protostars T-tauri stars, Bok globules, other Class I - IV objects –Diffuse clouds - Different morphologies of IR Cirrus clouds Test models of alignment efficiency –Radiative torques increase alignment efficiency :  correlation between percent polarization and 1.location of embedded stars (direct) 2.location of dense clumpy material (inverse) 3.dust temperature and/or spectral index (in p.o.s & along l.o.s.) a)spectrum falls with (direct) b)spectrum rises with  (inverse) B-field orientation changes with depth into cloud, or is unresolved

13 University of Chicago 2007 July 30 SOFIA-POL 2007 A) Near embedded stars - warm dust, “aligned” via radiative torques B) Cooler dust away from stars; optically opaque clumps C) Cold surface layers exposed to the interstellar radiation field (ISRF) T A > T B > T C p A  p C > p B Model of Molecular Clouds ISRF Falling P-spectrum T A >T B, p A >p B,  A ~  B Rising P-spectrum T B >T C, p B <p C,  B ~  C or T B ~T C, p B  C

14 University of Chicago 2007 July 30 SOFIA-POL 2007 Observing Goals for FIR Polarization Spectra Characterize spectrum of different environments –Dense cloud cores –Cloud envelopes –Isolated cores / protostars T-tauri stars, Bok globules, other Class I - IV objects –Diffuse clouds - Different morphologies of IR Cirrus clouds Test models of alignment efficiency –Radiative torques increase alignment efficiency :  correlation between percent polarization and 1.location of embedded stars (direct) 2.location of dense clumpy material (inverse) 3.dust temperature and/or spectral index (in p.o.s & along l.o.s.) a)spectrum falls with (direct) b)spectrum rises with  (inverse) B-field orientation changes with depth into cloud, or is unresolved

15 University of Chicago 2007 July 30 SOFIA-POL 2007 Embedded Stars

16 University of Chicago 2007 July 30 SOFIA-POL 2007 Observing Goals for FIR Polarization Spectra Characterize spectrum of different environments –Dense cloud cores –Cloud envelopes –Isolated cores / protostars T-tauri stars, Bok globules, other Class I - IV objects –Diffuse clouds - Different morphologies of IR Cirrus clouds Test models of alignment efficiency –Radiative torques increase alignment efficiency :  correlation between percent polarization and 1.location of embedded stars (direct) 2.location of dense clumpy material (inverse) 3.dust temperature and/or spectral index (in p.o.s & along l.o.s.) a)spectrum falls with (direct) b)spectrum rises with  (inverse) B-field orientation changes with depth into cloud, or is unresolved

17 T A > T B, p A > p B Expected Polarization Spectra (Hildebrand et al. 1999) Dust emission from a single grain species at a single temperature yields a flat spectrum in the FIR/SMM Dust emission from multiple grain species at multiple temperatures T A > T B, p A < p B

18 Polarization (%), Flux (Jy/beam) Temperature (K) T 2, Warm Component 28 K 52 K Testing the Mixture Model Spectral Energy Distributions T 1, Cold Component OMC-1 BNKL M42 KHW (Vaillancourt 2002)

19 University of Chicago 2007 July 30 SOFIA-POL 2007 OMC-1: 450/350  m polarization spectrum E-vectors Orion A Molecular Cloud (OMC-1): 3  polarization vectors from SHARP/SHARC-II Red = 350  m, Blue = 450  m B-vectors 10 arcsec beam

20 University of Chicago 2007 July 30 SOFIA-POL 2007 OMC-1: 450/350  m polarization spectrum Diamonds mark positions of BNKL, Trapezium, and KHW (north to south) flip in ratio around BNKL also observed at P(100)/P(350) [Vaillancourt 2002] Median P(450) / P(350) ratio ~ 1.4 P > 3 

21 University of Chicago 2007 July 30 SOFIA-POL 2007 Observing Goals for FIR Polarization Spectra Characterize spectrum of different environments –Dense cloud cores –Cloud envelopes –Isolated cores / protostars T-tauri stars, Bok globules, other Class I - IV objects –Diffuse clouds - Different morphologies of IR Cirrus clouds Test models of alignment efficiency –Radiative torques increase alignment efficiency :  correlation between percent polarization and 1.location of embedded stars (direct) 2.location of dense clumpy material (inverse) 3.dust temperature and/or spectral index (in p.o.s & along l.o.s.) a)spectrum falls with (direct) b)spectrum rises with  (inverse) B-field orientation changes with depth into cloud, or is unresolved

22 University of Chicago 2007 July 30 SOFIA-POL 2007 Microwave Polarization WMAP 3-year polarization results (Page et al. 2006) K-band: 23 GHz ~ 13 mm W-band: 94 GHz ~ 3.2 mm Infer CMB based on spectral dependence of known components  want to know dust pol’n at long wavelengths 3mm 10mm Bennett et al. 2003

23 Cloud Cores Schleuning 1998 Orion - KHW Orion - KL Normalized Polarization Polarization (%), Flux (Jy/beam) 28 K 52 K Testing the Mixture Model OMC-1 BNKL M42 Trapezium KHW p cold /p hot For 2 components: P tot F tot = p 1 F 1 + p 2 F 2

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