Intro
The steps in processing the data
Map positions raw data
    Plot: sampled map positions for each field (.ps) (.pdf).
    Plot: where all 28 fields fit into the final combined map (.ps) (.pdf).

Removing Tsys.

The individual maps by field
    The  average maps for each field (.gif)

Mosaicing the 28 fields together

Intro: (top)

    Data was taken oct12-dec12. The a2125 and a2415  data was then included in the final combined map.

 

mapname	map center ra, dec
Field_A	00:14:36 36:00:00
Field_B	00:14:36 33:30:00
Field_C	00:15:00 30:00:00
Field_D	00:06:18 26:07:30
Field_E	00:14:18 23:07:30
Field_F	00:33:00 35:22:30
Field_G	01:29:30 36:00:00
Field_H	01:29:30 34:00:00
Field_I	01:49:00 35:18:00
Field_J	01:48:00 32:00:00
Field_K	01:47:00 28:30:00
Field_L	01:46:00 24:30:00
Field_M	01:25:00 23:00::0

---

The steps in processing the data  (top)

• see a2125 steps in making the maps.
• Mosaic these fields together with the a2415 and a2125 fields (28 fields total).
  

---

Map positions   (top)

• Pages 1-3 shows the az,za positions for each field
• Page 4 has the ra/dec sampled positions for each field (labels are not very helpful).

• each field is plotted in a different color.
• an index (0..27) is plotted on top of each field for identification
• The list at the bottom of the plot, maps index number of field name, and average ra, dec for each field
  

Removing Tsys (top)

• Create a model of the za dependence of Tsys using the x102 data (tsysX102M). Normalize this so tsysX102M(za=10) is 1.
• For each map (ra,dec strips processed together):
• fit for the scale factor TsysData(za)=tsysX102M(za)*scale
• TsysRemoved= TsysData(za) - tsysX102M(za)*scale  .. this is done separately for pola, polb.
• If the actual Tsys changes over time ,this should help correct for that.
• If the cal Values change (without remeasuring them), then the 0 of tsysRemoved should be ok, but the scaleFactor of tsysRemoved will still be off (since we didn't scale it by the change in the cal values).
  

• Plot (TsysA/TsysB -1) before fitting or corrections (.ps)    (.pdf)
  
• The data has been converted from correlator counts to kelvins using the cals (after cal fitting).
  
• Top: TsysA/TsysB-1 vs za
• 2nd: TsysA/TsysB -1  vs az
• bottom:TsysA/TsysB -1 by field
  
• dashed green lines separate fields.
• Cal scale factors by field (.ps)  (.pdf)
  
• These values are computed from the cals on every strip. they convert from correlator counts to Kelvins.
  
• black (polA) ,red(polB) after cal fitting
• green(polA), blue(polB) before cal fitting
• Cal fitting takes adjacent cals (with no attenuation changes) and does a linear fit to the measured scaling factor ( throwing out outliers). The fit is then used to convert correlator counts to kelvins rather than the individual measurements.
  
• If there are no outliers than the blue,green overlay the black, red traces.
  

• Global fitting of all the data:
• Plot Tsys vs za and then fit for all data at once (.ps)  (.pdf)
  
• Show fit residuals by field (.ps)   (.pdf)
  
• Fitting Tsys by Field.
•  Remove tsys by field (rascans, decscans separate). plot Residuals for each field (.ps)   (.pdf)
  
• Each page is a separate field.
  
• top: polA, bottom PolB
• Black points are the rascans, red points are the dec strips
• When the images are made, Tsys is removed from the ra and dec scans simultaneously
  
• We left them separate here to see if the ra, or dec scans had any outliers.
• Tsys residuals by field (rascans and decscans together)(.ps)  (.pdf)
  
• Same as above plots but the scaling fit is done with ra and dec strips together. This is how the images are made.
• Black is polA, red is polB.
  
• The scale factor and errors are included in the title for each plot.

---

The individual maps.  (top)

1. grid the ra driven and dec driven maps separately to the same grid.
• Grid spacing was 3 arcminutes.
• The gridding function used a gaussian with a fwhm of 5.5 (it was repeated with a gaussian of 11 aminutes).
• The gridding function extended out to about 30 arcminutes.
• A sin projection was used to project onto the  2-d grid.
2. basketweave the two  maps. Create an average map and a difference map after basketweaving.
• The basket weaving will try an remove offsets in strips.

---

Mosaicing the fields.  (top)

1. take each pair of overlapping maps.
   
2. Interpolate the first map of each  pair to the grid position of the second  (within the overlap region).
3. compute  mapRaDif=(map2 - interpolated Map1) in the overlap region
4. Fit a linear polynomial to the differences as a function of the ra position
5. Correct the two maps by subtracting half the difference from map2 and adding half the difference to map 1
6. Repeat steps 1 5 with the corrected fields, using the dec overlap of the pairwise maps.
7. 21feb11: changed so that 1-6 only corrects 20% of the difference. It then iterates 1-6 5 times. This gets rid of jumps caused by the correction.
   

• the units are Janskies (multiply by 10 to get kelvins).
  
• Pages 1-6. Overlap in ra direction with  map1-map2Interpolated plotted  vs ra.
• The red line is the fit  vs ra.
• Page 2, frame 2 Field12 - Field11A vs ra has a  large offset and slope
  
• Pages 6-13. Overlap in dec direction with map1 - map2Interpolated plotted vs dec.
• Each set is the start of iteration i (i=1 to 5). the last one is when everything is done. The set shows how the correction progresses with a correction factor of 20% per iteration.
• Pairwise difference overlap region:Iteration 1 start (.ps) (.pdf)
  
• Pairwise difference overlap region:Iteration 2 start (.ps) (.pdf)
  
• Pairwise difference overlap region:Iteration 3 start (.ps) (.pdf)
  
• Pairwise difference overlap region:Iteration 4 start (.ps) (.pdf)
  
• Pairwise difference overlap region:Iteration 5 start (.ps) (.pdf)
  
• Pairwise difference overlap region:Iteration 5 end (.ps) (.pdf)
  

The final mosaiced maps (.gif):

• The  x,y positions are just grid points along the ra,dec direction.
  
• This used a 5.5 arcmin gridding function. The final resolution is about 14 arcminutes.
Processing: combinemaps.pro

Notes on the fields.  (top)

• Field K. PolB data is zero. Looks like the interim correlator sbc3 dropped out.
• I copied polA into Polb so the software wouldn't complain.
• Field L. Need to re observe topmost (highest dec) 8 strips.
• You can see a horizontal line in two strips (each starting at the same side of the map.
  
• The cals for two of the strips look like they were sitting on a source. Can't use interpolation since the adjacent strips were not taken at the same time.
• 
  

Instabilities in polA.

    Spectral ripples were seen in polA during various nights. This type of problem has plagued polA 430gr for multiple years (more info..). It doesn't look like this caused a problem in the total power measurements. I thinkt he ripple problem was finally identified. it was the filter in front of the dewar. It had a loose connection in inside the filter. There was also a problem with one of the elbow connectors. The teflon insert was not always seating properly... so we would get different results after taking things apart, and reassembling..