We used the built-in python wrapper of PlatoSim, platonium, to run the simulations.

This combines the outputs of the picsim, varsim, and payload modules, runs the simulation for one star over one quarter (of a year) as observed by one camera, and then applies the chosen photometry pipeline.

We do not yet know precisely which data product will be produced for these targets; therefore, we adopted a mixed approach to photometry extraction.

Firstly, we simulated the use of the 25-second cadence imagettes for on-ground PSF-fitting photometry via the L1 photometry pipeline.

This is the treatment that the P1, P2, P4 and ∼3.7 per cent of the P5 sample targets will receive.

Secondly, on the same imagettes, we simulated onboard aperture photometry using the method of Marchiori et al. (2019), which constructs photometric precision-maximizing apertures composed of whole pixels that are updated periodically throughout the quarter.

This method is analogous to the expected treatment of the majority of the P5 sample stars for which bandwidth limitations preclude imagette downlinking.

In both cases, the treatment of the PSF is important.

For stars subject to PSF fitting, point spread functions with subpixel resolution are obtained via a microscanning approach (see Samadi et al. 2019 for details).

This method involves acquiring a series of imagettes of the target that are shifted by subpixel displacements following an Archimedean spiral, and combining these data using a regularized least-squares approach with a positivity constraint on the solution.

In our simulations, platonium orchestrates the spiral observations within PlatoSim at the beginning of each observing quarter, while the L1 proto-pipeline performs the PSF inversion and fitting.

For stars for which only aperture photometry is performed, knowledge of the PSF is still required – in order to define the photometric apertures.

In the nominal processing, PSFs are reconstructed for reference stars across the field of view and interpolated to estimate the PSF at a given focal-plane position.

In our simulations, however, we do not perform this reconstruction step; instead, we use the theoretical PSFs provided by PlatoSim.

We initially ran 29,184 simulations – 152 stars observed by 24 cameras over 8 quarters.

We ran simulations from mission quarters 9 to 16 in platonium to account for the expected instrumental degradation between the beginning of the mission and when the Northern field is observed.

Since we did not know in advance which or how many cameras the targets would be visible to, we ran the simulations for all 24 cameras.

Simulations for which the target was outside the field of view terminated early.

These simulations took approximately seven weeks spread across three systems, each equipped with two 32-thread Intel Xeon Silver 4514Y processors, for a total of around 200,000 CPU hours.

The execution time was dominated by the computational cost of the L1 PSF-fitting photometry proto-pipeline.

Additionally, we ran an identical set of simulations using only aperture photometry, with all contaminants removed, to quantify the mean photometric contamination level per simulation and per mask update.

These simulations took around three days using one of the above-described machines for a total of around 4,000 CPU hours.

For each mask update, we subtract the mean contamination level from the contaminant-present aperture photometry.

This produces light curves corrected for contamination in the mean signal, while retaining the noise impact of photometric contaminants.

In the real data, contamination will be addressed via the spacecraft jitter correction, which re-scales the measured flux to the level expected with only the target.

These corrections can be validated by measuring the dilution of exoplanet transits relative to the catalogued transit depths.

We did not utilize the jitter or long-term drift corrections in the present work.

The PSF-fitting photometry failed for one eighth of the targets – 19 stars hosting 50 planets.

These 19 stars all have 𝑉≥14.79 mag, and the mean and standard deviation of the failed PSF-fitting host brightnesses in V are 15.79 and 0.53 mag, respectively.

Failed extraction in the current pipeline implementation appears to be associated with a combination of low target brightness and high levels of photometric contamination.

We note, however, that PSF-fitting photometry is generally expected to outperform aperture photometry in crowded fields and for faint sources.

This has been demonstrated for Kepler – which used similarly undersampled PSFs – by Libralato et al. (2016a,b).

We therefore expect comparable improvements to be achievable.

The PSF-fitting method used in the present work was primarily developed for and tested against stars with 𝑉≤11 mag, which may contribute to the reduced performance observed for dimmer targets.