The DM monthly status report covering October activities has been posted to Docushare, Collection-1645. For your convenience, the High-level Summary is pasted below. Direct link to full report (pdf): http://ls.st/kqa.
High-level Summary
Community interaction, meetings and workshops
Leanne Guy, the DM Subsystem Scientist, has been named as a co-liaison to DESC, the Dark Energy Science Collaboration. She will focus on overall coordination of DESC-Project interactions.
A productive workshop on the LSST Science Platform was held at NCSA during the week of October 22. In addition to many useful technical topics, discussion focused on the the Final Design Review of the Science Platform which will take place in spring 2019. LDM-652, the charge for the review, was drafted over the course of this month, with the expectation that it will be baselined during November.
Members of the Alert Production team met with staff from the Minor Planet Center to develop detailed plans for closer integration of LSST moving objects processing with the MPC. A change request to update the baseline to incorporate these plans is expected before the end of the calendar year.
Representatives from the Data Release Production team presented progress on, and plans for, atmospheric characterization at the DESC Photometric Calibration Workshop in Paris, France at the start of the month.
Technical Progress
DMTN-094, describing the design of the authentication and authorization system for the Science Platform, was published.
Discussion in the DM System Science Team over the last several months has focused on the development of the user-facing Science Data Model. In support of this, the DM Architecture team has developed Felis, a mechanism for describing the contents of scientific databases in a language and implementation-independent way.
The SQuaRE team adopted a new technology stack, based on InfluxDB, Chronograf and Kapacitor, as the basis of the performance metric storage and visualization system. This replaces the bespoke in-house system previously in use.
Work on prototyping LSST data processing in the “cloud” continued with the successful deployment and testing of the Qserv database system, demonstrating reasonable levels of performance.
The Data Access team deployed a version of the Canadian Astronomical Data Centre (CADC) Table Access Protocol (TAP) service on the NCSA Kubernetes cluster. This was demonstrated at the Science Platform workshop, and is expected to form the basis for LSST TAP services. In support of this, the SUIT team upgraded Firefly data model capabilities to fully support TAP services and other VO standards. In addition, the user interface for building three-color images was improved.
Scientific and Algorithmic Progress
The Alert Production Pipeline code is now included in our core “lsst_distrib” software distribution, and will be part of the upcoming “v17” release of the LSST Science Pipelines.
It is now possible to build and use coadded images corrected for differential chromatic refraction (DCR) as part of the Alert Production system
A new star/galaxy classification system has been completed and integrated with the LSST Pipelines.
The Pipelines group rolled out a new mechanism for exposing algorithmic code written in C++ to Python. This is both more robust, and results in smaller compiled code, than the previous system.
Data Transport and Networks
Data was successfully transferred from the Auxiliary Telescope test stand in Tucson to the LSST Data Facility at NCSA and ingested it into a preliminary data backbone (based on the Generation 2 Butler). Data was also successfully transferred from Qserv database nodes at the Data Facility to Google for scale testing and possible burst processing into the Google Cloud.
Spectrum First Light (Contract #3 Deliverable #3) was accomplished 2018-09-30. Preparations continue for a 100 gigabit/second networking demonstration in conjunction with Supercomputing 2018 on November 14, 2018. 200 GB of DECam pre-cursor image data will be sent from La Serena to NCSA and a 1 PB “simulated” data release (binary data) in the opposite direction.