P. Ade2, P. Ashton1, F.E. Angile3, S. Benton4, M. Devlin3, B. Dober 3, Y. Fukui 5, N., Galitzki3, N. Gandilo4, J. Klein3, A. Korotkov6, Z. Li7 ,L. Moncelsi8, T. Matthews1, F. Nakamura8, C. B. Netterfield4, G. Novak1, E. Pascale2, F. Poidevin9,10,P. Martin10, G. Savini11, D.Scott12, F. Santos1, J. Shariff4, J. D. Soler13, N. Thomas14, C. Tucker2, G. Tucker6, D. Ward-Thompson15

1CIERA and Northwestern University, 2Cardiff University, 3University of Pennsylvania, 4University of Toronto, 5Nagoya University, 6Brown University, 7University of Virginia, 8California Institute of Technology, 8NAOJ, 9Inst. de Astrofisica de Canarias, 10CITA, 11University College London, 12University of British Columbia, 13CNRS-IAS, 14NASA Goddard, 15University of Central Lancashire

Laura Fissel1

First Results from BLASTPol 2012: Submillimeter Polarimetry of Vela C

Magnetic fields may play an important role in the dynamics and evolution of molecular clouds. In order to constrain the role of magnetic fields in star formation, we require detailed observations of magnetic fields for a large sample of molecular clouds.

Detailed Maps of Magnetic Field Morphology with BLASTPolBLASTPol Magnetic Field Map of the Vela C GMC

Background: BLASTPol 500 μm intensity smoothed to 2.5’ (0.5 pc) resolution. Drapery Image: Line Integral (LIC, Cabral & Leedom (1993)) showing the inferred magnetic field orientation projected on the plane of the sky.

Polarized dust emission can be used to trace magnetic field morphology. Dust grains tend to align perpendicular to the local magnetic field, possibly due radiative alignment torques (Cho & Lazarian 2005), and thus we observe polarized dust emission that is perpendicular to the cloud local average field direction. However ground based polarimeters are generally limited to small (<0.1 deg2) maps, while Planck’s limited resolution gives it only a few independent polarization measurements across most molecular clouds.

Here we present the most detailed sub-mm polarization map ever made of a Giant Molecular Cloud. Our goals are to:(1) Find an empirical model for our polarization data. This

model can then be compared to numerical simulations of star formation.

(2) Examine whether our measured magnetic field orientations might be preferentially sampling less dense regions where the dust grain alignment efficiency is high.

Large area detailed portraits of cloud magnetic field morphology are now becoming available (Planck for very near clouds, BLASTPol for more distant clouds). To use these maps to constrain magnetic field strength we need statistical measures of polarization data that can be also be applied to simulated observations from 3-D numerical models of magnetized clouds.Here we have shown that our polarization fraction (p) data is well fit by a power-law model of two variables: the column density (N) and the local field angular dispersion on 0.5 pc scales (S). Our best fit model is p(N,S) = p0 N-0.4 S-0.6 . We see little evidence for a correlation between N and S. In future work we will look for these trends in simulated observations. We also considered the implications of the extreme case that all of the decrease in p with N is due to reduced polarization efficiency. We appear to trace the average field direction for moderate columns (AV~10) well, though we may not be sensitive to field direction changes in deeply embedded dust for highly extincted sightlines (AV ~50).

Motivation

Polarization trends Observed:

If all of the decrease in polarization with increasing column density is caused by varying grain properties (less efficient alignment with respect to the magnetic field, rounder grains) then our magnetic field measurements preferentially sample regions where the polarization efficiency is high.

χ

AV/2

Line of Sight (z)

ρ

ε=ε0

BLASTPol team with the telescope, prior to the 16 day Dec 2012 Antarctic flight. BLASTPol utilizes a 1.8 m primary mirror and maps polarized emission at 250, 350 and 500 μm.

The BLASTPol polarimeter operates at an altitude of ~38km, so it can have wide frequency bands covering the spectral peak of 10-20 K dust. This makes BLASTPol extremely sensitive and able to map large areas of the sky quickly.

References:Cabral & Leedom, 1993, 263Yamaguchi et al.,1999, ApJ 696, 567Cho & Lazarian, 2005, ApJ, 631,361Lazarian, 2007, QJSTR, 106, 225

2-D histogram of N vs S. Color: median p for each bin.

p/p(N,S)p(N,S)

Histogram of p (red) , our power-law model p(N,S) (blue) and p with the dependence on N and S removed (yellow). Our two power-law model is able to reproduce most of the variation in polarization fraction seen in our map.

Decrease of p with increasing S: is likely caused by changes in the average magnetic field direction within the beam. This leads to cancellation of polarization components. A decrease of p with S was also seen in Planck Intermediate XX, albeit for more diffuse sightlines.

Decrease of p with increasing N: Possibly due to reduced effectiveness of radiative alignment torques for sightlines where much of the dust is highly shielded (Whittet et al., 2008), or because the magnetic field is more tangled towards high dust column sightlines (Falceta-Goncalves et al., 2008).

Lack of correlation between N and S: Implies that sharp changes in the magnetic field orientation do not tend to occur near high column density features. This is in contrast to what was found by Falceta-Goncalves et al. (2008), when they examined simulated polarization observations of an MHD cloud model. A correlation might be expected if the magnetic field direction has been significantly bent by gravitational motions of gas near dense filaments.

Note: For this exercise we assume that all of the decrease with p vs N is due to grain physics (not due to field tangling). This can be considered a worst case scenario.

We parameterize the polarization efficiency ε as a function of the depth into the cloud χ (total extinction to the nearest cloud surface).

In this model ε(χ) is constant up to a critical cloud depth (χcrit) and falls as a power-law of slope η for χ > χcrit.

Resolution=2.5’ (0.5pc)

> 4400 Nyquist sampled polarization measurements

Vela C: An early stage GMCd = 700 pcM = 5 x 104 Msun, (Yamaguchi et al. 1999)

25 pc

Compact HII region RCW 36

Pola

rizati

on F

racti

on p

Column Density N (cm-2)1022 1023

Angu

lar D

ispe

rsio

n on

0.5

pc

scal

es S

(°)

10

1

p decreases as S and N increase

ε=ε0

ε=ε0(χ/χcrit)η

zχcrit

The polarization efficiency model can be used to predict p vs AV:

Model fit

Model Predictions:- AV=10 sightline:

- Inner half of dust (χ=2.5-5) contributes 40% of the total polarized fluxWell traced by BLASTPol

- Highest column sightlines (AV = 50):- Inner half of dust (χ=12.5-25)

contributes only 15% to the total polarized fluxInner half not well traced

Falceta-Goncalves et al., 2008, ApJ, 679,537Whittet et al. 2008, ApJ, 674, 304Hill et al., 2011,A&A, 533, A94 Planck Collab.,2014, A&A, 576,105Galitzki et al. 2014, SPIE, 9145

BLASTPol:The Balloon-borne Large Aperture Sub-mm Telescope for Polarimetry

Modeling the BLASTPol Vela C Polarization Data

Conclusions

We look for correlations between:

S: Dispersion in the local magnetic field angle (on 0.5 pc scales)Large where there are sharp changes in the average B-field direction

N: Hydrogen column density(derived from Herschel Data)

p: fraction of 500 μm emission that is polarized

Can BLASTPol Trace Magnetic Fields in Deeply Embedded Dust?

Best fit model:p0 = 0.037, Avcrit=3.3,η=-1.43

AV > AVcrit p=p0 (AV /AVcrit )η+1

AV < AVcrit p=p0 (constant)

Contours: I500

Outlines: Vela C sub-regions defined by Hill et al., 2011

Best fit power-law model: p(N,S) = p0 N-0.4±0.1 S-0.6±0.02