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20180914_decorr [2018/09/14 13:44] – created pryke20180914_decorr [2018/09/14 15:22] (current) – pryke
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-**Data Challenge Maps II**+**Decorrelation plots for foreground models**
  
 Sept 14 2018, Clem Pryke Sept 14 2018, Clem Pryke
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 Most of the foreground models we are considering for PICO implement spatial variation of the spectral behavior at some level - this produces "decorrelation" - i.e. the sky pattern for a given foreground component changes as a function of frequency. Most of the foreground models we are considering for PICO implement spatial variation of the spectral behavior at some level - this produces "decorrelation" - i.e. the sky pattern for a given foreground component changes as a function of frequency.
 This potentially degrades the efficiency of the component separation algorithms. This potentially degrades the efficiency of the component separation algorithms.
-In this post I look at the decorrelation of the dust pattern by comparing cross-spectra to the+In this post I look at the decorrelation of the dust and sync patterns by comparing cross-spectra to the
 geometric mean of auto-spectra (the lower right panel of each plot). geometric mean of auto-spectra (the lower right panel of each plot).
-We see that only the 98 and 99 (multi-layer and Vansyngel) models are significantly decorrelated.+We see that only the 98 and 99 (multi-layer and Vansyngel) models are significantly decorrelated in dust, 
 +and none of them are significantly decorrelated in sync.
  
-{{180914_f0.png}} +I take the power spectra using anafast and the soft edge mask shown below. 
-{{180914_f1.png}} +Since foreground do not have E>>B this should be adequate. 
-{{180914_f2.png}} + 
-{{180914_f3.png}} +{{180914_fm.gif}} 
-{{180914_f6.png}} + 
-{{180914_f8.png}} +To recap the models are: 
-{{180914_f9.png}}+ 
 +  * 00=Toy Gaussian models for dust and sync with uniform amplitude over the sky at level appropriate for the BICEP/Keck patch (i.e. way too low for PICO large sky coverage). 
 +  * 91=PySM a1d1f1s1 [[https://arxiv.org/abs/1608.02841 | arxiv/1608.02841]] 
 +  * 92=PySM a2d4f1s3 
 +  * 93=PySM a2d7f1s3 
 +  * 96=Brandon's MHD model for dust and sync taken from /global/homes/b/bhensley/mhd_maps/maps_v1 on 180424 
 +  * 98=MKD multilayer dust model as described in [[https://arxiv.org/pdf/1706.04162.pdf | arxiv/1706.04162]]. Since only dust is provided this is added to PySM a2f1s3 as per models 92 and 93. 
 +  * 99=Vansyngel model as described in [[https://arxiv.org/abs/1611.02577 | arxiv/1611.02577]] with multi-frequency extension. This model provides both dust and sync (and no AME or free-free is added.) 
 + 
 +So we have 7 models for dust and 5 for sync. 
 + 
 +**Dust plots** 
 + 
 +{{180914_f0.gif}} 
 +{{180914_f1.gif}} 
 +{{180914_f2.gif}} 
 +{{180914_f3.gif}} 
 +{{180914_f6.gif}} 
 + 
 +Compare the below to fig 20 of [[https://arxiv.org/pdf/1706.04162.pdf]] 
 +{{180914_f8.gif}} 
 +{{180914_f9.gif}} 
 + 
 +**Sync plots** 
 + 
 +{{180914_f0s.gif}} 
 +{{180914_f1s.gif}} 
 +{{180914_f2s.gif}} 
 +{{180914_f6s.gif}} 
 +{{180914_f9s.gif}}
  
20180914_decorr.1536950668.txt.gz · Last modified: 2018/09/14 13:44 by pryke

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