Transients and Variable Stars

Transit Method

The transit method has been responsible for many of the exoplanets confirmed to date.
The major question for Rubin will be about the conditions being met for the photometry within the observations.
Looking at the usual requirements of exoplanet detection using the transit method, that is, cadence and SNR of
flux presents a substantial challenge.

Radial Velocity Method

The radial velocity method requires high-resolution spectroscopy.
The cadence can be infrequent, but regular over long observation periods.
However, there is no direct access to spectroscopy within Rubin.
Thus, the question may be, can Rubin observations be used jointly with radial velocity?

Astrometry Method

The Rubin/LSST mission is all about astrometry.
The cadence is similar to good radial velocity observations, but exoplanet research has a big question.
Can Rubin's parallax and proper motion measurements produce enough SNR to resolve candidate exoplanets?

Resources ...

... LSST and Transiting Exoplanet science:
(1) Rubin Observatory LSST Transients and Variable Stars Roadmap, Hambleton et al. (2023)
(2) LSST Science Collaborations Observing Strategy White Paper: "Science-driven Optimization of the LSST Observing Strategy" Marshall et al. (2017)
(3) Transiting Planets with LSST. III. Detection Rate per Year of Operation, Jacklin et al. (2017)
(4) Understanding exoplanets and other variable sources in sparsely-sampled time domain surveys, Lund (2017)

... 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 receive a timely, verified answer.

Proposed Projects of the Transiting Planets Subgroup

(1) Machine learning: understand the tools and techniques used by the GAIA team to train for exoplanet signals.
(2) Commingling: during DP0.2 and DR1, develop techniques to leverage and/or inject GAIA (or other) data into the LSST database to supplement currently missing astrometry data..
(3) Pipeline: clarify the astrometry data delivered in each operational release.
(4) Conversion: re-develop tools tested during DP0.2 and DR1 to perform in the later operational releases.
(5) Joint fitting: identify candidates and collect radial velocity data from spectrographic sources to develop low uncertainty ephemeris for candidate exoplanets.