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LSST’s wide array of science cases, spanning cosmology, transients, and solar system studies, requires careful optimisation of observing strategy (the choice of where, when and in what filter to observe). For transient science in particular, effective scheduling directly impacts the ability to classify sources and use them in downstream analyses such as cosmology with type Ia supernovae.
As co-editor of the cosmology chapter in Marshall et al. (ArXiv:1708.04058, 2017), a large community white paper, I helped outline key challenges and findings from early observing strategy work. Building on this, I co-led efforts within the LSST Dark Energy Science Collaboration to propose metrics and recommendations that maximise the telescope’s scientific output.
Simulation of the observing strategy of the Vera C. Rubin telescope. Each dot represents a single visit (a 40s observation) and the colour indicates which filter is used to make the observation. Choices of which piece of sky to visit when, and in which filter, have critical impact on a number of important science cases. Credit: Lynne Jones
Optimising LSST’s observing strategy has been one of the most important contributions of my career that will have long-lasting impact on all scientific outputs from LSST. As co-leader of the LSST Dark Energy Science Collaboration’s Observing Strategy Working Group, I led a diverse team of over 30 cosmologists and spearheaded efforts that significantly improved LSST’s baseline strategy. This resulted in two influential white papers: one focused on the main survey (Lochner et al., ArXiv:1812.00515, 2018) and another on the deep drilling fields (Scolnic et al., ArXiv:1812.00516, 2018), which laid the groundwork for a cosmology-optimised observing strategy.
Visualisation of the effect of different observing strategies (named in boxes) on a combined cosmology metric, which generally improves with larger sky area and increased cadence. This indicates that observing strategy can have significant impact on the high precision requirements of cosmological surveys. Credit: Lochner et al. (2022).
Four years of work, culminating in the journal article Lochner et al. (ApJS, 2022), cited over 30 times, has influenced key decisions on LSST’s survey design. By analysing simulated surveys, we identified strategies that enhance uniformity, improve cadence, and optimise filter changes, ensuring the survey meets its diverse science objectives. These efforts laid the groundwork for a widely cited (over 100 citations) review paper by Bianco et al. (ApJS, 2022). The true significance lies not in the citations but in the profound impact on the actual implemented observing strategy. Through our efforts, simulations have evolved from producing poorly sampled light curves to enabling truly transformative time domain science. In 2020 I was awarded LSST DESC builder status for my contributions (see the Awards page for more information).
With collaborators at University College London, we also led the first comprehensive study investigating the impact of observing strategy on supernova classification (Alves et al., ApJS, 2022 & 2023). Our findings revealed that "rolling cadence" strategies significantly enhance classification performance, while frequent filter changes are essential to maintaining accuracy.
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