Sort of Introduction

Idiosyncratic Definitions

We have files containing detections (the positives). They have been verified against Sloane. If they were in Sloane, they are true positives or matched. If they are not, they are false positives or unmatched. With detections come with features. Features can be numeric (ra, dec...), alphanumeric (skycell, filter...).

I don't see anything else for the moment.

Wikipages

The main wikipages are:

• Database related questions: ​http://svn.pan-starrs.ifa.hawaii.edu/trac/ipp/wiki/ZoologyDatabase
• Investigations: ​http://svn.pan-starrs.ifa.hawaii.edu/trac/ipp/wiki/ZoologyInvestigations

#4: 2011-08-25

Attendees: Heather, Roy, Serge, Jim

• Serge had troubles creating the new database (A-004, A-005) but everything's fine now.
• Serge wrote documentation about the database at: ​http://svn.pan-starrs.ifa.hawaii.edu/trac/ipp/wiki/ZoologyDatabase
• Heather plotted many histograms shown in ​http://svn.pan-starrs.ifa.hawaii.edu/trac/ipp/wiki/ZoologyInvestigations
• Roy updated ​http://svn.pan-starrs.ifa.hawaii.edu/trac/ipp/wiki/ZoologyInvestigations
• During the 54 seconds meeting, Jim dropped by and told us about what he did with MD04 checks against CFHT

Actions

• A-008 (Heather): Once A-005 is done, check flux_sig/flux ratio for true positive (true positive = matched)
• A-009 (See details): Answer Gene's questions:
  • 1) (Serge/Heather for plots) What fraction of the detections have flux / flux_sig < 5 (the nominal cutoff) or < 3 (a possible agressive cutoff)?;
  • 2) (Serge/Roy/Heather) What is the spatial distribution of these detections?
  • 3) (Who?) What does the histogram of pixel value / sqrt(pixel variance) look like in areas / cells with large numbers of these detections? Should be a Gaussian with a width of 1, but if there is excess noise from the camera in some areas, the width will be > 1 (we underestimate the variance).
• A-010 (Roy): Is the false detections filter dependent?
• A-011 (Roy/Heather for plots): Classify "matched": statistics similar to the unmatched (flags, flags2, flux_sig/flux ratio histogram, anything else)
• A-012 (Roy): DS9 region files for "matched" detections with bad flags (see Heather for details)

Pending Actions

• A-004 (Serge): Done Create the database again on ipp001 (neverland is almost full).
• A-005 (Serge): Done Ingest the full detections on ipp001 (in an another table)
• A-006 (Roy): Done Update ​http://svn.pan-starrs.ifa.hawaii.edu/trac/ipp/wiki/ZoologyInvestigations with the flux_sig/flux ratio explanation
• A-007 (Heather): Done Make histograms of flux_sig/flux ratio.

#3: 2011-08-24

Attendees: Heather, Roy, Serge, (Bill invited himself because we were noisy and gave info about processing)

• Serge created the database (see action A-002)
• Heather showed that using appropriate flags to cut the "detection candidates" reduced the size of the set by 8 (56000 out of 400000). See action A-003. She reported her discoveries in ​http://svn.pan-starrs.ifa.hawaii.edu/trac/ipp/wiki/ZoologyInvestigations
• In the 56000 that remain, a lot have a large flux_sig/flux ratio

Pending Actions

• A-002 (Serge): Done Create a database with: all values taken from the footprint-<filter>-not-matched-psphot.fits files. Add columns filter, stack_id, skycell_id. See /data/ipp009.0/heather/heather.blog.txt .
• A-003 (All): Done Identify false positives which have been correctly set as "having a problem" (see flags meaning at ​http://svn.pan-starrs.ifa.hawaii.edu/trac/ipp/wiki/cmf_columns )

Actions

• A-004 (Serge): Create the database again on ipp001 (neverland is almost full)
• A-005 (Serge): Ingest the full detections on ipp001 (in an another table)
• A-006 (Roy): Update ​http://svn.pan-starrs.ifa.hawaii.edu/trac/ipp/wiki/ZoologyInvestigations with the flux_sig/flux ratio explanation
• A-007 (Heather): Make histograms of flux_sig/flux ratio.
• A-008 (Who?): Once A-005 is done, check flux_sig/flux ratio for true positive
• A-009 (Who?): Answer Gene's questions:
  • 1) What fraction of the detections have flux / flux_sig < 5 (the nominal cutoff) or < 3 (a possible agressive cutoff)?;
  • 2) What is the spatial distribution of these detections?
  • 3) What does the histogram of pixel value / sqrt(pixel variance) look like in areas / cells with large numbers of these detections? Should be a Gaussian with a width of 1, but if there is excess noise from the camera in some areas, the width will be > 1 (we underestimate the variance).
• A-010 (heather): Is it filter dependent?

#2: 2011-08-23

Attendees: Heather, Roy, Serge

Heather wrote some doc here: ​http://svn.pan-starrs.ifa.hawaii.edu/trac/ipp/wiki/ZoologyHints

Pending Actions

• A-001 (Heather): Done Provide FITS files where false positives can be displayed and underlined using ds9.

Actions

• A-002 (Serge): Create a database with: all values taken from the footprint-<filter>-not-matched-psphot.fits files. Add columns filter, stack_id, skycell_id. See /data/ipp009.0/heather/heather.blog.txt .
• A-003 (All): Identify false positives which have been correctly set as "having a problem" (see flags meaning at ​http://svn.pan-starrs.ifa.hawaii.edu/trac/ipp/wiki/cmf_columns )

#1: 2011-08-22

Attendees: Heather, Roy, Serge

Heather talked about the problem. She already has wikipages showing some of them:

• ​http://svn.pan-starrs.ifa.hawaii.edu/trac/ipp/wiki/MaskFeatures.pattern.20090722
• ​http://svn.pan-starrs.ifa.hawaii.edu/trac/ipp/wiki/MaskFeatures090712

Actions

• A-001 (Heather): Provide FITS files where false positives can be displayed and underlined using ds9.

Previous Actions

• None

Next meeting: as soon as A-001 has been completed.