April 2005 ALMA Offline software test NAME: Munetake MOMOSE Questionnaire on testing experience 1. Please list briefly your background in the following areas: A. Radio Interferometry ((sub)millimeter or centimeter) I have long experience in reducing data taken with the Nobeyama Millimeter Array (NMA). I also have some experience in developing new correlator and reduction software for the NMA. B. Experience with VLA and/or PdBI data Almost no experience (except the ALMA Offline TST1). C. Astronomical Data Reduction packages: - AIPS - MIRIAD - MMA - Gildas/Clic - AIPS++ I have experience in using AIPS but not in other softwares. D. How much experience have you had with the AIPS++ software package before this test? I was a tester of AIPS++ TST1 in January 2004, which was the only occasion to try. 2. Please identify which dataset you processed during this test: B. BIMA CO(1-0) observations of NGC 4826 3. Were you able to combine the single dish and interferometric data using feather and deconvolution techniques? If not, why? Please comment on specific steps if desired (comments can be positive or negative, you may not have tried all steps): A. Feather images or image cubes provided by Offline subsystem Yes. I obtained a feather image with 'n4826_12mmom0.im' and 'n4826_mom0.im'. The cookbook is well written and I was able to understand easily what the "feathering" is. Just by following sample scripts in the cookbook, I easily obtained the feather image. Although I did not make any detailed inspection for this image, the obtained result looked reasonable. B. Feather single dish image provided and interferometer image that you created from the dataset provided. Yes. I first generated channel maps with the BIMA visibility data 'n4826_both.ms', and then obtained a feather image cube using the BIMA channel maps and 'NGC4826.12motf.chan.fits', which was provided by the developer team. I met no trouble during the imaging process. C. Deconvolve the single dish and interferometer data using the single dish image to create an input model. Yes, following the cookbook, I created a joint deconvolved image cube using 'NGC4826.12motf.chan.fits' (for a model image) and the visibility data 'n4826_both.ms'. Only a minor issue I would like to know was how to determine the masked regions when one creates the model image from sigle dish data. This is, however, a minor technical issue. Please identify any problems you had during imaging. There was almost no problem during imaging. Only thing that troubled me a little bit was that a MS file should be specified in the feathering process, which has already been mentioned in the cookbook. 4. Were you able to analyze the images adequately to determine if the results you obtained were scientifically reasonable (e.g. display the image, calculate RMS and peak, make a moment map or take a spectrum)? If not, why? Basically, yes. Although I had a trouble in making moment maps, the developer team gave me a quick suggestion. Another thing I struggled was to manipulate the image viewer. I need some time to make simple measurement such as comparing rms levels in the fixed regions among different image cubes. This is due to my little experience in aips++. 5. Please summarize the final results of your image(s): Get three image cubes as follows: NOTE: -RMS levels are measured in an emission-free channel -Peak and Total flux density are measured in the Regions of BLC=(12:56:48, 21:40:20) and TRC=(12:56:40, 21:40:40) in the 0th moment map (cutoff = 0.0 in each channel) #1 Only using BIMA data - RMS: 93.7 mJy/beam - Peak and Total Flux Density: peak: 151.3 [Jy/beam km/s], total: 1.80e5 [Jy/beam km/s pixels] #2 Feather image using BIMA & 12m maps - RMS: 92.2 mJy/beam - Peak and Total Flux Density: peak: 139.3 [Jy/beam km/s], total: 1.63e5 [Jy/beam km/s pixels] #3 Joint Deconvolved image - RMS: 96.6 mJy/beam - Peak and Total Flux Density: peak: 151.4 [Jy/beam km/s], total: 1.82e5 [Jy/beam km/s pixels] #1 and #3 are quite similar to each other; there is almost no difference in moment maps with relatively high cutoff (2 sigma level for example). Joint deconvolution (#3) recovered faint and extended emission features, though these are minor components. #2 seems to have lower peak and flux densities compared to the BIMA only image, suggesting feathering is not appropriate way to deal with data which have low S/N and moderate spatial extent. 6. Did you have adequate support during your test? If you contacted the AIPS++ groups for questions or to fix a bug, please comment on the interaction and whether it was helpful. Yes, I need help during installation and making moment images, but the support is responsive and helpful. 7. Was AIPS++ easy to install? If not, why? I had trouble in installation. I could not download the aips++ files with the script "casa". Actually, this was NOT the aips++ specific issue in my case. In Redhat 9 or MandrakeLinux 10, the default action of the ftp command seems passive mode, but file transfer does not work well in this mode in our environment. (I have not yet understood the reason). Since I could not find out the way to change the default mode of ftp, I explicitly turned off the passive mode first (by the command "passive") and then interactively downloaded all the files in a conventional manner. After downloading all the files, I was able to install aips++ by usual rpm command (rpm -ivh ...). It was very easy. 8. The Synthesis Reduction Cookbook you used for this test is the second version of a comprehensive cookbook for ALMA users. Please evaluate the organization, content, and presentation of the cookbook. It is meant to be the first documentation users will see when they want to reduce ALMA data, it provides background on the code capabilities, and extensive examples. The on-line documentation provides more details and code descriptions. With this in mind, please answer the questions below. If you have detailed comments, please attach them to the end of this questionnaire. - Was the documentation adequate for you to complete your test? Yes, but I also referred the online aips++ manual in which I can find more detailed explanation. I believe both the cookbook and online comprehensive manual (or help menu) are essential. - Do you have any suggestions for how to improve the cookbook? It could be helpful if you have a section like "basic procedure from beginning to end", in which you just introduce very basic functions/options but covering all the reduction processes. No detailed explanation of each task/function is needed. - Was the on-line documentation helpful: * User Reference Manual?: Yes. I usually check out the meaning of each option by the online document, although sample scripts in the cookbook are useful. * Supporting documentation? Yes, the README-1st document by Debra was especially useful to quickly select an appropriate parameters in deconvolution processes. 9. Roughly how much time did you take to perform the following steps: - Installing aips++: 7h (because of trouble) - Imaging: 15h - Analysis: 10h (including retry the imaging process) - Filling out this questionnaire: 4h - Evaluating and grading the scientific requirements: 1h - Total time: 37h 10.Please rate your overall testing experience: - good 11.Was the test well designed and executed by those in the ALMA offline subsystem (e.g. the subsystem scientist and the Offline subsystem group). If not, can you provide any suggestions for improving the next test? I fully agree with the deveoper's strategy in which two datasets with different nature should be tested to get a comprehensive view. In the N4826 case, I cannot find out any serious problem, although feather channel maps are not useful in this case. Improvement by adding single dish data was not so remarkable, but I believe this kind of test will also be important to allow us to make accurate imaging by the ALMA. 12.Do you have any additional comments that may help improve test of the offline software in the future? No.