#Maf lsst astrometry registration#

(2018) whitepaper so that it can be run on the opsims. In terms of numbers to compare across different simulations: some of us have been working to implement the metrics and figure of merit specified in the Gonzalez et al. For one of our bulge metrics and investigations validating this metric with data, we have been running this separately for each filter using crowding_error=0.05 mag. Hi - apologies, I think I confused the plot title with the metric name there… I meant the crowdingMetric.crowdingM5metric. It’s not clear to me if part of that is because DECAPS is doing deblending differently than assumed in what was built into the crowding metric? Or if it’s something else? *the number of stars we estimate to measure with crowding ‘on’ seems to result in fewer stars than others report in surveys such as DECAPs. Now, that said, if you would still like the crowding error metric calculation results - we can run the crowding metric (per bandpass? all bandpasses?) over the sky, but how would you like to consolidate that from maps into numbers you can compare across different simulations?

I don’t believe we’re doing anything incorrect when applying the crowding effect cutoff, so it would be good to hear what you think. (the input stellar luminosity function seems about right and matches with model expectations … but the crowding effect seems to throw the count results off*). I will note that we have had numerous complaints that the crowding calculation must be inaccurate because the resulting stellar counts seem too low to people. Which are calculated using the NStarsMetric. We’re not calculating that explicitly, but we do use the underlying crowding formula to calculate the number of stars down to X precision (with and without crowding). Will Clarkson, for the SMWLV Observing Strategy Task Forceĭo you mean the results of this metric CrowdingMetric ? (which calculates the magnitude at which crowding error equals photometric precision, if I’ve got that right) Information on Datalab, including the link to request an account, can be found at this Community post. If you fit this description, we recommend you request a NOIRLAB-Datalab account, as the Datalab will be the preferred venue for most investigators to run MAF remotely.

While the Feb 18th hack day will focus on specifications of metrics, some groups may already be at the stage of coding their investigations in MAF.

The current list of planned SMWLV cadence investigations.

The Community announcement of the FBS 1.7 Survey Simulations.

The 2020 August cadence report to the SCOC and the related “cheat sheet” summarizing the runs.The SCOC solicitation for Cadence Notes (revised deadline April 15th, 2021).If you are planning on working towards a Cadence Note at this Hack Day, we recommend you (re-)familiarize yourself with at least the following resources:

#Maf lsst astrometry registration#

Registration is not required: if you are planning on joining us for the Hack Day, you might reply to this post or email Will Clarkson so that we have an idea how many to expect. The main objective for the Feb 18th hack day is to ensure that metrics and figures of merit for the planned cadence notes have been specified and the specifications posted in a publicly shared location, ideally at a sufficient level of detail that you can start to implement your investigations in MAF. This google doc contains the schedule and Zoom link & password. This first hack day will be somewhat informal: this community thread will be its internet home. This will consist mostly of time blocks for groups working on an SMWLV-relevant Cadence Note to work together remotely on their MAF-based investigations. Hi all - This is to let you know that we will be holding the first SMWLV Observing Strategy Hack Day this coming Thursday, Feb 18th, from 10:00am - 3:00pm EST.