Galactic Dust D Fixsen University of Maryland / Goddard Space Flight Center.

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Presentation transcript:

Galactic Dust D Fixsen University of Maryland / Goddard Space Flight Center

1) How good do we need to model the dust? 2) How do we model the dust? 3) How do we know it is good enough? In order to measure r~.001 B modes!

Interstellar Dust Pixel-by-pixel dust characterization need to get to few*.001 of dust

A)Build a model based on the physics of dust How do we model the dust? A)Build a model based on the physics of dust Problem: Physics is complicated B)Build a parametric mathematical spectral model Problems: Different parameterizations lead to different results. Need many frequencies (more than parameters) C)Build a parametric mathematical spatial model Problems: Low l’s are hard Variation in distance Real physical scales What are the spatial variations in B modes D)Combination of A, B & C Problem: The model is complex

Dust is small (<1 um? ) Dust is cold (<30 K? ) Dust is thin (~10-5 ? ) Spherical dust r<<l Model an2Bn(T)

Temperature Distribution Radiation Field – temperature proportional to radiation^(1/6) Particle Size – bigger particles cooler Chemistry – dependence on optical/UV vs IR emissivity Stochastic Variation – dependence on time since UV photon Dust must have a temperature distribution

Dash = n2Bn(T) uniform distribution T = [0,20 K] Dot = nbBn(T) modified black body b=1.69 T = 18.03 K

FIRAS frequencies and weights -> T = 18.03 K, b=1.69 Match is within 0.2% over the range .07-1.8 THz 4% at 3 THz where FIRAS uncertainties are large With PLANCK frequencies and weights -> T=16.35 K, b=1.85, error of 20% at 30 GHz

Principle Component Analysis allows data to show the way Eigen Values > Eigen spectrum Eigen Vectors > What is important

Eigen Value Spectrum

Take out known signals Uniform Black Body spectrum (1 DOF) CMB dipole (3 DOF) Zodiacal emission (2 DOF) C+ & N+ emission (12126 DOF) CIB ??? CMB anisotropy? CIB anisotropy?

Average of dimmest 10% of sky Dash = uniform n2Bn(T) T=2.8-17.4 K Dot = nbBn(T) b=.65 T=24.75 Dash-Dot CIB (Fixsen etal 1998)

Prime Eigen Vector Dot = n2Bn(T) T=19.84 K

Second Eigen Vector Dot = n2dBn(T)/dT T=19.84 K Dash = n2dBn(T)/dT T=17.48 K

Third Eigen Vector Dot = n2d2Bn(T)/dT2 T=19.84 K

Residual Prime Eigen Vector (60% sky) Dot = n2Bn(T) T=23.36 K

FIRAS data has too much noise Include PLANCK data Subtract CIB (which also removes offsets) Subtract dipole (already done) Subtract Zodi Exclude brightest 40% of sky Convolve with FIRAS Beam

Tilted by n-2 Dot =CO lines Dash =Sum Warm Dust n2Bn(20 K) Synchrotron n-.7 Cold Dust n2Bn(5 K)

Summary Dust is complicated, even along line of sight Complications matter at level r<0.01 Available data show complications, but can't unravel them To KNOW we got it, extra frequencies, extra pixels and extra S/N are needed. Extra frequencies to analyze dust available .5-3 THz