Open willclarkson opened 7 years ago
Can you say briefly what motivates this figure of merit? As in, which key model parameters' precision will scale with this FoM? I guess it's probably many, but it'd be good to lay out some examples. It sounds like this is probably obvious to all of you, but it may not be to your cosmologist/solar system/transient readers :-)
Thanks @drphilmarshall - what I personally have in mind is the uncertainty in age determination for each of multiple spatially-overlapping populations towards the inner Milky Way. Eventually I'd like the community to be able to make a statement like "strategy X will lead to uncertainties in the timing and duration of each star formation epoch in the bulge of Y and Z Gy respectively, and in the number of epochs of N." However I think that's a long way beyond what we can do at the moment with our current understanding of opsim and maf, the figure of merit suggested here is a step in that direction.
But that's my own scientific preference speaking... generically, any science conclusion requiring metallicity, temperature and reddening determination for stellar populations will scale with the fraction of the survey area that allows those parameters to be measured down to the turn-off.
Co-authors: examples from your favorite science areas are welcome!
I think we've got all the tools to do that. The questions I have: 1) Is the overall goal to map the bar? I'm not clear on the justification for varying the distance of the fiducial star. 2) The photometric and crowding uncertainties are going to be calculated for each observation (since they both depend on the seeing). I think right now the crowding metric uses the best seeing and assumes DM will be able to use that to de-convolve the other images. That may be too optimstic. One could be more conservative and only use observations taken in good conditions. Anyway, maybe there needs to be a 3d-part-2 on how one goes from many observations of the fiducial star in varying conditions to a final co-added uncertainty.
Thanks Peter (@yoachim) -
What I have in mind is to use model stars along the bar as a reference, yes. I'm trying to come up with a figure of merit that doesn't require a full-blown population simulation, and "fraction of fields that can be well-measured for bar-like populations" seems to be a good place to start. At least, I would expect the results of a full-blown simulation to scale with the results of the simpler suggestion I've made here.
Very interesting point, and indeed the uncertainty in a total set of observations along a particular sight-line (for photometry and astrometry) is something I would expect to be crucial for a very large fraction of the science cases... How does MAF currently compute this?
Right now, we have the Coaddm5Metric which assumes Gaussian errors and combines the depths of multiple images accordingly. Looks like the crowding metric uses the best seeing in the group of observations to compute the crowding uncertainty.
For the astrometry metrics, the depth of each image is used in the computation. The uncertainty in the proper motion is treated as computing the uncertainty of the slope in a linear fit. The proper motion is treated like fitting the amplitude of a sin-wave (where the phase and period are known). I don't think we have any astrometry metrics that take crowding into account, the centroid errors are assumed to be a function of seeing and depth with a floor set by the atmosphere.
Thanks Peter - it sounds like those of us interested in this issue should take another look at Olsen, Blum & Rigaut 2003, there may be some useful recommendations in that paper. Although at first glance the seeing:confusion interplay may seem like a second-order issue, I can imagine it becoming a main limitation for surveying crowded regions with LSST. Milky Way static science seems as good a place as any to incorporate it into the observing strategy assessment.
Hi Will,
That's a wonderful science case, and better showcase for Galactic structure and archeology than the multiple GC populations scenario I had suggested. It shares many of the same concerns, though.
Best regards, Peregrine
On Wed, Apr 26, 2017 at 11:26 AM, Will Clarkson notifications@github.com wrote:
Thanks Peter - it sounds like those of us interested in this issue should take another look at Olsen, Blum & Rigaut 2003 http://adsabs.harvard.edu/abs/2003AJ....126..452O, there may be some useful recommendations in that paper. Although at first glance the seeing:confusion interplay may seem like a second-order issue, I can imagine it becoming a main limitation for surveying crowded regions with LSST. Milky Way static science seems as good a place as any to incorporate it into the observing strategy assessment.
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Thanks @pmmcgehee - would you mind writing a couple sentences about the GC-populations case you have in mind here, so that any readers of this issue not on the lsst-milkyway-etc mailing list (and who thus missed your earlier suggestion) can see?
Will et al,
Sure thing. Here's a portion of what I posted on https://community.lsst.org/t/working-towards-crowded-field-science-requirements/1798 .
Example science case - population studies in NGC 5272 (M3):
Here is an example science case for thinking about crowded field studies. While it's neither in the bulge or the disk, it caught my interest. Others may have alternate scenarios... whatever works for discussions is fine.
The well-studied globular cluster NGC 5272 (M3), at Dec = +28, is a prime example of multiple stellar populations within a single GC (the "second parameter" problem). We would like to study the spatial and kinematic distributions of each population. Certainly, the expectations are that, with the exception of mass segregation, that these populations are well-mixed.
NGC 5272 is at a heliocentric distance of 10.4 kpc (m-M = 15.1). In the ideal case we would like to:
a) Have better than 1% photometry for stars less than 1 solar mass (stretch to the HBL).
b) Assign reasonable proper motion values to members of each population. From section 4.3.1 in the WP, the nominal PM error at r ~ 24 is 1 mas/yr, or ~48 km/s at this distance. This is large compared to the ~6 km/s velocity dispersion in M3, so we need to go brighter.
It would be interesting to see how the limits for the following vary for different photometry codes:
1) maximum field crowding or how close can we work to the core.
2) minimum stellar mass for accurate photometry.
3) minimum stellar mass for accurate astrometry.
Best regards. Peregrine
On Wed, Apr 26, 2017 at 12:54 PM, Will Clarkson notifications@github.com wrote:
Thanks @peregrine https://github.com/peregrine - would you mind writing a couple sentences about the GC-populations case you have in mind here, so that any readers of this issue not on the lsst-milkyway-etc mailing list (and who thus missed your earlier suggestion) can see?
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-- Dr. Peregrine M. McGehee Santa Clarita, CA (626) 993-4199
Thanks Will - you should include that high level text at the start of your FoM subsection. Good luck!
On Wed, Apr 26, 2017 at 4:29 PM, Peregrine M McGehee < notifications@github.com> wrote:
Will et al,
Sure thing. Here's a portion of what I posted on https://community.lsst.org/t/working-towards-crowded-field- science-requirements/1798 .
Example science case - population studies in NGC 5272 (M3):
Here is an example science case for thinking about crowded field studies. While it's neither in the bulge or the disk, it caught my interest. Others may have alternate scenarios... whatever works for discussions is fine.
The well-studied globular cluster NGC 5272 (M3), at Dec = +28, is a prime example of multiple stellar populations within a single GC (the "second parameter" problem). We would like to study the spatial and kinematic distributions of each population. Certainly, the expectations are that, with the exception of mass segregation, that these populations are well-mixed.
NGC 5272 is at a heliocentric distance of 10.4 kpc (m-M = 15.1). In the ideal case we would like to:
a) Have better than 1% photometry for stars less than 1 solar mass (stretch to the HBL).
b) Assign reasonable proper motion values to members of each population. From section 4.3.1 in the WP, the nominal PM error at r ~ 24 is 1 mas/yr, or ~48 km/s at this distance. This is large compared to the ~6 km/s velocity dispersion in M3, so we need to go brighter.
It would be interesting to see how the limits for the following vary for different photometry codes:
1) maximum field crowding or how close can we work to the core.
2) minimum stellar mass for accurate photometry.
3) minimum stellar mass for accurate astrometry.
Best regards. Peregrine
On Wed, Apr 26, 2017 at 12:54 PM, Will Clarkson notifications@github.com wrote:
Thanks @peregrine https://github.com/peregrine - would you mind writing a couple sentences about the GC-populations case you have in mind here, so that any readers of this issue not on the lsst-milkyway-etc mailing list (and who thus missed your earlier suggestion) can see?
— You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub https://github.com/LSSTScienceCollaborations/ ObservingStrategy/issues/626#issuecomment-297522583, or mute the thread https://github.com/notifications/unsubscribe-auth/ANP_2Y1F- eeaWlPKBiipkvTbMvlJeyt_ks5rz6DlgaJpZM4NIOxb .
-- Dr. Peregrine M. McGehee Santa Clarita, CA (626) 993-4199
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Hi all - when you make your pull request with the new MW static science case, can you please make sure you refer back to this issue so we can close it out? Thanks!
The science case is now specified Section 4.5 in the latest pull request (PR #643) - once @drphilmarshall approves that pull request, it will be in the main paper branch. I'm moving implementation of this science case to the "Version 2.0 Development" milestone.
Great! Thanks for the notification.
On May 26, 2017 10:00, "Will Clarkson" notifications@github.com wrote:
The science case is now specified Section 4.5 in the latest pull request (PR 643) - once @drphilmarshall https://github.com/drphilmarshall approves that pull request, it will be in the main paper branch. I'm moving implementation of this science case to the "Version 2.0 Development" milestone.
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Good plan, thanks Will. I edited the issue title to match, feel free to change it.
No, that's great, thanks!
Do you need anything more from me on Pull Request #643 (addressing Jason's comments for Chapter 4)?
Cheers
Will
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On Fri, May 26, 2017 at 3:12 PM, Phil Marshall notifications@github.com wrote:
Good plan, thanks Will. I edited the issue title to match, feel free to change it.
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@akvivas @cbritt4 @vpdebattista @caprastro @yoachim @pmmcgehee @jgizis @knutago @dnidever and all MW-interested co-authors:
Prompted partly by Jason's review of the MW chapter (see github issue #620 ), I would like to develop at least a skeleton "static science" case and figure of merit for Chapter 4, before the WP gets posted to the arXiv if possible.
I have self-assigned this "issue," but all input is of course welcome. Please let me know if you're interested to develop this, and/or if you've already got material in mind or developed!
To start things off, I've come up with the following "pseudocode" for how a science case and associated figure of merit might look. I think all the steps below are already implemented in sims_maf or maf_contrib, it'll just be a case of pulling the pieces together. This may also be a useful stepping-stone on the route to Monte Carlo population studies that we've each discussed at various points.
@yoachim - if you have time to look through this, can you let me know if there are any sims_maf tricks we should be using to accomplish the various loops here? (I'm thinking in particular of the assignment of apparent magnitude to each of the spatial slice-points)
Static-science MW figure of merit: fraction of fields well-measured for photometric metallicity and reddening estimates, for some fiducial object, in a survey covering the inner plane
Thoughts welcome!
Will