LSST TVS SC Subgroup: Supernovae
Topic: LSST Supernovae
The LSST data set will contain millions of supernovae.
We're preparing to do science with them.
Membership
Join the TVS Science Collaboration and this Supernovae subgroup via the main TVS Webpage. Note that your application should include your science interests and proposed contributions to the current TVS-Supernovae activities described below. All members are expected to read and abide by the TVS Code of Conduct, the TVS Charter, and the TVS Publication Policy. Those documents describe the priviledges and responsibilities of TVS membership. Members may sign the Code of Conduct and Charter using this web form. The Supernovae subgroup contact and lists of currently active members can be found at the bottom of this page. We look forward to having you join us!
Science: LSST Supernovae
In 2019, a poll regarding the science interests and activities of the LSST TVS-SC Supernovae subgroup was done. As expected, the respondents mainly self-identified as observers (with ~20% reporting interest in theory), researching supernova progenitors, explosion mechanisms, and late-stage stellar evolution. As also expected, studies of event rates, host galaxies, and follow-up spectroscopy were the most frequently reported analysis methods for the research goals. A full write-up of the results for the 2019 can be found here.
In the 2021 a kickstarter program founded by Las Cumbres Observatory for the activities of the SN subgroup started, so the same poll submitted in 2019 has been repeated in the 2021 to analyse possible changes in the science interests of the group. The results appear in accordance with the poll in 2019 for both the self-identification of the members of the group (with ~20% reporting interest in theory, the majority reports interest in obsevations). As also expected, studies of progenitor system, host galaxies, and follow-up spectroscopy were the most frequently. The slides with the plan for the kickstarter program and the results of the poll can be found here.
Supernova Progenitor Systems
Which kinds of stars make which kinds of supernovae?
How long do stars live, and what happens during the latest stages of evolution before they explode?
What are the roles of binary companions for stars that become supernovae?
Do characteristics of the local environment or host galaxy affect supernovae?
Supernova Explosion Mechanisms
How does stellar mass and metallicity affect the nucleosynthetic processes in theromnuclear supernovae?
Are supernovae spherically symmetric and, when they're not, why not?
Deflagrations, detonations, ingition(s): how does burning proceed?
Can external factors such as stellar collisions trigger supernova explosions?
Supernovae as Standardizable Candles
How can we improve Type Ia peak-brightness standardization?
How can core collapse supernovae be improved as standard candles?
How can the LSST survey strategy and/or follow-up resources be optimized for improving standardization?
(See also the efforts of the Dark Energy Science Collaboration's Supernova Working Group.)
Resources to learn more about ...
... LSST and supernova science:
(1) LSST: From Science Drivers to Reference Design and Anticipated Data Products, Ivezic et al. (2019)
(2) The LSST Science Book, Version 2.0 Chapter 11 (Supernovae)
(3) Science-Driven Optimization of the LSST Observing Strategy, Chapters 6.3 (Supernovae as Transients) and 9.5 (Supernova Cosmology and Physics)
... LSST data products and observing strategy:
(1) The LSST Data Products Definitions Document Includes alert packet contents, catalog table columns, and image types.
(2) This slide deck for a talk on "The LSST Data Management Systems: Infrastructures for Enabling Multi-Messenger Astrophysics".
(3) Recorded talks for scientists about LSST, including observing strategy, data products, the science platform, photometric pipelines, the alert stream, and commissioning.
(4) A Report from the LSST Science Advisory Committee: Recommendations for Operations Simulator Experiments Based on Submitted Cadence Optimization White Papers.
(5) The LSST Community Forum has a science topic thread Data Q&A where anyone can ask questions of the LSST Data Management team and recieve a timely, verified answer.
Active Projects of the SN Subgroup
(1) Photometric classiciation: optimization for SN classification algorithm: the project aims to optimize a Neural Network model to perform the SN photometric classification LSST TVS task force.
(2) Alert Brokers: simulation of SN CC alerts for analysis of brokers’ performance: generate ZTF alerts from simulated light curves to test Fink and ALeRCE brokers and compare the results.
Old Projects of the SN Subgroup
(1) Survey Cadence: proposing and evaluating strategies for the LSST survey with respect to supernova science, e.g., via the deep-drilling fields and mini-survey proposals planning LSST TVS task force.
(2) Alert Brokers: preparing to identify targets of interest released via the LSST Alert Stream, e.g., with the LSST TVS task force to characterize the functionality needed from a community broker interface.
(3) Light Curve Collections: building and maintaining a collection of observed and model supernova light curves is necessary for our analyses of proposed LSST survey strategies and for developing classification algorithms that will be used in brokers. Check out the GitHub repo LSST-TVSSC/ContributedLCVs and the data set used for the Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC).
Roadmap
The Roadmap sets a plan for the objectives of the SN group to identify and focus our preparations in the lead-up to LSST operations (e.g., tool development, precursor observations).
Active Members
Subgroup Contact: Fabio Ragosta, INAF- Astronomical Observatory of Rome (fabio.ragosta@inaf.it)