Introduction

• DP0.3 - https://dp0-3.lsst.io/

• PCW2023 notes

• Gareth Francis' EPCC news item on Lasair - https://www.epcc.ed.ac.uk/whats-happening/articles/lasair-alert-broker

• Comms Office appointment

• First Rubin science release - https://rubinobservatory.org/news/visitors-from-distant-stars

Those with ideas for future newsletter items should contact the LSST:UK Project Managers (George Beckett and Terry Sloanlusc_pm@mlist.is.ed.ac.uk), while everyone is encouraged to subscribe to the Rubin Observatory Digest for more general news from the US observatory team.

Bob Mann

Strategies for optimal sky-subtraction in the low-surface-brightness regime

Paper submitted to MNRAS (Watkins et al.) based on work performed by LSST:UK Phase B WP 3.7

Myself (Aaron Watkins) and my collaborators completed and submitted a paper to MNRAS detailing the investigations we did into various sky-subtraction algorithms optimized for low surface brightness science. Using idealized simulated images, we investigated two algorithms commonly used in LSB-oriented surveys--a masking and modeling approach, and an approach in which average sky models are generated via median-combination of science exposures taken close on the sky and in time--as well as a third experimental algorithm meant to remove the flux of static objects prior to sky estimation via subtraction of a preliminary sky-subtracted image coadd.

In general, we find that contamination from non-sky sources will always tend to bias sky estimates to brighter levels, with the level of bias dependent on the amount of contamination from non-sky sources present during estimation of the model. This bias makes the experimental coadd-subtraction approach untenable, as the background in said coadd inevitably is negative, a result of background over-subtraction in the coadded images. This artifact is then imprinted on every image when the coadd is subtracted to remove the static sources, leading to a continual propagation of any errors made during the initial round of sky estimation. Also, when the sky is modeled using a complex fitting function or a spline interpolation of local sky estimates, the bias induced by contaminated sources can lead to local sky overestimation, which is difficult to correct for. This effect is most prominent around either extended sources (galaxies, intracluster light, tidal features) or highly clustered sources (either real star or galaxy clusters, or sources which simply cluster in projection on the sky).

That said, while a perfect sky estimation remains a future endeavor, fairly accurate sky models are still achievable via careful, deep masking of non-sky sources, and via the use of simple fitting functions (either empirical, as in the image combination method, or by using a low-order fit such as a constant or a plane) to reduce the likelihood of local sky over-estimation. The two commonly used LSB-oriented approaches tested should thus be viable for LSST given the survey's anticipated surface brightness limits. Given the survey cadence, the masking and modeling approach is the most viable for LSST. The primary causes for concern are sources of contamination not tested for in this study: scattered light, bright star reflections, satellite trails, and other artifacts with large angular size, the removal of which prior to sky estimation is a critical component of any LSB-oriented data reduction pipeline.

We have shared the results of this study with Data Management and are working to find the best path toward implementing our recommendations in the pipeline. The ultimate goal is to ensure that an LSB-friendly image coadd becomes a standard pipeline data product.

Aaron Watkins and Sugata Kaviraj

Recent LSST:UK Science Centre outputs

The LSST:UK Science Centre has recently produced the following technical reports.

Terry Sloan

Forthcoming meetings of interest

The online registration for the Rubin Project and Community Workshop 2023 remains open.

Other meetings of potential interest for the coming months include:

Members of the Consortium (not in receipt of travel funding through one of the Science Centre grants) may apply for travel support for meetings of this kind via the the LSST:UK Pool Travel Fund. Details are available at Forthcoming LSST-related Meetings .

Note that the current list of forthcoming meeting is always available on the Relevant Meetings page. You may also wish to check information held on the LSST organisation website LSST-organised events and the LSST Corporation website.

George Beckett

Announcements

If you have significant announcements that are directly relevant to LSST:UK and would like to share the announcement in a future newsletter, please contact the LSST:UK project managers.