| | 7 | |
| | 8 | We have set up 2 'tiger teams' to push on 2 specific top-level concerns: 1) why is processing throughput not where it should be? (WS, CZW, MEH) 2) what is the cause (and mitigation?) of the false detections found in the footprint stacks? (HAF, SC, RH). Both teams have met multiple times over the week and are making what seems to be good progress. |
| | 9 | |
| | 10 | The quick answer to (1) is "various issues" : some specific hardware problems (ipp014, ippc06), some memory overload problems (streaksremove, ppMops), some bottleneck bugs in the LAP management code, ongoing disk space issues. There are a few places that we can reduce our sensitivity to hardware problems (the distributed apache/neb interface can be made responsive to machine failures; a particular type of hang-up caused by a blocked log file can be fixed). We need to keep fixing and avoiding glitchy hardware and to finish the disk upgrades in progress. The memory overload issues can be addressed by modifying the fits table I/O functions somewhat, but there is also a problem with allowing some bad diffs to go through the system. Bill and Mark are working on those issues, while Chris works on the LAP related issues. Overall, the bottom line is that, if things go smoothly, the system can run ~50 exposures / hour (1200 / day), but keeping things at that rate is the trouble. |
| | 11 | |
| | 12 | The quick answer to (2) seems to be "faint, roughly sky-level detections". It is clear that the wide wings of the pixel distribution are not Gaussian, and these outliers are driving the faint source detections. The bulk of false positives are faint, and are not associated with specific bright defects (or real effects). But they do prefer certain parts of the camera over others. The likely bet is that these are coming from the 'streakies', the residuals of the row-by-row bias variations that remain in the images. One additional supporting piece of evidence is that the g-band has by far the largest number of these type of false positives. The psphot/SDSS test shows that the software does not tend to pick up fake things that are not coming from the data. TT2 is looking further at tests that can distinguish these faint false positives from real faint things, but hopes are not very high (IMO). |
| | 13 | |
| | 14 | We were having lots of problems with ipp014 (which had the backup of ipp013 while under refurb). Cindy replaced ipp014's raid card, with good improvement in its behavior. Cindy and Haydn also did the second round of disk swaps (and mobo swap for ipp037). We are ready for the last one 8/31. |
| | 15 | |
| | 16 | I also spent some time this week talking with John Tonry and Doug Finkbeiner about photometry. Doug has done a lot of work comparing PS1 and SDSS in MD fields, and the results generally look really good. There is one lingering effect that we are trying to understand better: at the faint end, the PS1 mags (IPP values) are fainter by a small amount than the SDSS mags of the same objects. The effect is between 0.2 and 0.5 sigmas, but it seems to be a consistent bias. There are actually a number of effects that may be present and can drive this difference in this same direction: color terms (faint stars are redder than bright stars on average), galaxy contamination (harder to distinguish at the faint end, and the SDSS numbers are model mags), Poisson vs Constant weighting in the psphot analysis, and error in the sky estimation. |
| | 17 | |
| | 18 | Finally, I am more-or-less happy with the state of the Kron mags in psphot -- they are now in good agreement with sextractor and reasonable agreement with input values for synthetic galaxies. I needed to include better downweighting of nearby objects and a more robust 1st moment measurement. I am now putting the finishing touches on the model fits using those new Kron mag measurements as inputs. |
