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Combining GBT and VLA data

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The integration of GBT and VLA data into CASA presents several challenges. Currently, GBT spectra, despite being fully reduced and calibrated, cannot be loaded into CASA due to a lack of compatible file conversion. Bob Garwood from NRAO is actively working on a program to convert SDFITS files into a format readable by CASA. Until this conversion is completed, testing with new gridding functions and addressing current issues such as checkerboard patterns in the data will be limited. Ongoing flux measurements highlight discrepancies, emphasizing the need for a reliable combination method.

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Combining GBT and VLA data

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  1. Combining GBT and VLA data

  2. CASA Issues • GBT spectra (fully reduced, calibrated spectra) currently unable to load into CASA • NRAO’s Bob Garwood working on program to convert SDFITS file into scantable that CASA can read • Bob is working the program into his schedule, so no definitive time on when it will be completed • CASA has new spherical Bessel function for gridding (imaging) GBT data • waiting for above to be complete before testing can commence • CASA’s current task ‘imregrid’ is producing checkerboard pattern in GBT data • likely due to large GBT pixels (3.5’/side) being re-gridded to match teeny tiny VLA pixels (~7”/side), causing an artificial “edge-effect” • Helpdesk ticket submitted and NRAO is working on correcting problem

  3. Flux measurements • GBT flux: • converted K to Jy/bm using: • GBT flux produced = 10.91 Jy/bm compared to 1.085 Jy/bm from VLA CLEAN channel (see Feather notes) – Does this make sense???

  4. Weighting Function for Feather

  5. FFT of GBT and VLA center pixel profile

  6. Feathered image • The LT GBT + VLA data look like this:

  7. Combined in Image Domain • GBT + VLA data look like this for M81/M82 group using AIPS:

  8. Other data combination methods • Image domain • Using GBT as model for CLEAN:

  9. Other data combination methods • Combining in uv-plane??? • Convolving VLA data with GBT beam – then combine – then run CLEAN (multi-scale??) on combined data

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