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arxiv: 2310.06985 · v5 · submitted 2023-10-10 · 🌌 astro-ph.IM · astro-ph.EP· astro-ph.SR

PlatoSim: An end-to-end PLATO camera simulator for modelling high-precision space-based photometry

N. Jannsen , J. De Ridder , D. Seynaeve , S. Regibo , R. Huygen , P. Royer , C. Paproth , D. Grie{\ss}bach
show 16 more authors
R. Samadi D. R. Reese M. Pertenais E. Grolleau R. Heller S. M. Niemi J. Cabrera A. B\"orner S. Aigrain J. McCormac P. Verhoeve P. Astier N. Kutrowski B. Vandenbussche A. Tkachenko C. Aerts
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Pith reviewed 2026-05-24 06:00 UTC · model grok-4.3

classification 🌌 astro-ph.IM astro-ph.EPastro-ph.SR
keywords PLATO missionspace photometryend-to-end simulatorCCD imagingexoplanet transitsasteroseismologypayload modeling
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The pith

PlatoSim models the full chain of PLATO photometry from incoming photons to digital data units.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper presents PlatoSim as an end-to-end simulator built to generate photometric time series and CCD images that match the expected output of the PLATO space mission. It walks through the software architecture and the algorithms that translate sky photons through the multi-telescope optics, detectors, and electronics into final measurements. The work shows how this simulator has already been applied to mechanical integration, payload performance studies, pipeline development, and scientific goal assessments inside the mission consortium. If the model holds, it supplies a reliable virtual testbed for verifying that PLATO can reach the precision needed for exoplanet transit detection and asteroseismic analysis of host stars.

Core claim

PlatoSim implements a general formalism that models incoming photons from the sky through the PLATO payload optics, detectors, and electronics to final digital units, producing simulated CCD images and light curves that correspond to the mission's expected high-precision photometric observations.

What carries the argument

The step-by-step end-to-end photon modeling pipeline that encodes the multi-telescope design and converts physical processes into digital outputs.

If this is right

  • Supports ongoing mechanical integration and alignment work for the PLATO payload.
  • Enables quantitative performance studies of the full instrument suite.
  • Provides test data for developing and validating the mission's data processing pipelines.
  • Allows assessment of whether the mission design meets its exoplanet and asteroseismology science requirements.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • The same modular structure could be reused to simulate variants of the PLATO instrument or future photometry missions.
  • Post-launch comparison of simulated versus real data would quantify how well the model captures unmodeled effects such as cosmic-ray hits or thermal drifts.
  • The simulator could be coupled to optimization routines to test alternative observation strategies before launch.

Load-bearing premise

The algorithms inside PlatoSim correctly realize the physical processes of the PLATO payload without major omissions or systematic errors.

What would settle it

A side-by-side comparison of PlatoSim light curves against actual PLATO flight photometry that reveals systematic deviations exceeding the mission's required precision.

Figures

Figures reproduced from arXiv: 2310.06985 by A. B\"orner, A. Tkachenko, B. Vandenbussche, C. Aerts, C. Paproth, D. Grie{\ss}bach, D. R. Reese, D. Seynaeve, E. Grolleau, J. Cabrera, J. De Ridder, J. McCormac, M. Pertenais, N. Jannsen, N. Kutrowski, P. Astier, P. Royer, P. Verhoeve, R. Heller, R. Huygen, R. Samadi, S. Aigrain, S. M. Niemi, S. Regibo.

Figure 1
Figure 1. Figure 1: Overview of the PLATO multi-camera design. Left: Schematics of the PLATO spacecraft consisting of the payload module (with colour indication of the telescope groups) and the service module (bus). Credit: ESA/ATG medialab. Right: On-sky FOV of PLATO shown for a pointing towards the Long-duration Observation Phase (LOP) south in equatorial coordinates. The increasing darker shade of blue illustrates the incr… view at source ↗
Figure 2
Figure 2. Figure 2: Preliminary normalised N-CAM spectral response curve at be￾ginning of life (BOL) (with the red dots representing the mission re￾quirements) compared to those similar planet hunting missions such as CHEOPS (orange dotted-dashed line), TESS (green dashed line) and Kepler (blue dotted line). Each response curve is computed with cubic spline interpolation for illustrative purposes. The grey shaded areas are cu… view at source ↗
Figure 3
Figure 3. Figure 3: Schematic overview of how PlatoSim generates a CCD image in the FPA. a) Illustrative overview of the N-CAM FPA with the 4 CCDs. The blue axes indicate the focal plane with the central blue dot (in the middle of the 4 CCDs) represents the optical axis ZFP pointing in the positive direction towards the reader. The green axes illustrate the origin for nCCD = 4 as a reference and the readout register of each C… view at source ↗
Figure 4
Figure 4. Figure 4: Illustration of a synthetic PLATO PSF generated at different optical axis distances ϑ with a) Zemax OpticStudio and b) an analytic model. The top panels show the high resolution PSF for ϑ = 3 ◦ (left) and ϑ = 18◦ (right). The lower panels show the corresponding PSF after a 0.2 pixel Gaussian diffusion kernel has been applied. Each PSF is constructed at an azimuth angle of 45◦ and has a resolution of 64 sub… view at source ↗
Figure 5
Figure 5. Figure 5: Layout of the Telescope Optical Unit (TOU) together with the detectors on the right forming the Focal Plane Array (FPA). Light passes the entrance window to the left (which for the F-CAMs is a dedicated optical filter) and propagates through the refractive optical lenses (L1– L6) unto the FPA on the right. Credit: ESA. is caused after reflection of the light on the CCD surface and on both surfaces of the e… view at source ↗
Figure 7
Figure 7. Figure 7: shows a visual model comparison between PlatoSim (top left) and CosmiX (top right). The bottom panel shows a proton irradiation test performed at cold temperature on a PLATO flight model CCD (black dots from Prod’homme 7 https://gitlab.com/david.lucsanyi/cosmix 8 https://esa.gitlab.io/pyxel/ [PITH_FULL_IMAGE:figures/full_fig_p010_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: Power spectral distribution (PSD) for a high frequency jitter time series of the yaw angle produced with PlatoSim’s red noise model (top) and a dynamical OHB/TAS model (bottom). The two simulated models are sampled at 8 Hz and have a time duration of 27 h. The solid black line corresponds to a 1 min moving median filter. given time a perturbation to the pointing direction and the roll angle of the spacecra… view at source ↗
Figure 9
Figure 9. Figure 9: Illustration of the field distortion models. Left: Distortion over one quadrant of the FPA with a grid step size of 2◦ . Shown are the undistorted paraxial chief ray coordinates (black dots) and the real (dis￾torted) chief ray coordinates calculated by the Wang et al. (2008) dis￾tortion model (red diamonds), together with the CCD area (dark grey area enclosed by dark blue lines) and the effective size of t… view at source ↗
Figure 10
Figure 10. Figure 10: Illustration of the total throughput map for one full frame CCD. The dotted diagonal line shows the distance from the optical axis in degrees (ϑ) and the red dashed lines show the angular position of the stray light mask. We note that the FOV in the focal plane physically extents beyond ϑmax (to ∼ 19.6 ◦ indicated by the red dotted line) due to the effect of optical distortion cf. Sect. 6.5 and is followe… view at source ↗
Figure 11
Figure 11. Figure 11: Illustration of the automatically generated flat-field (PRNU) for a full-frame CCD image. This image represent the flat-field used to construct the subfield in [PITH_FULL_IMAGE:figures/full_fig_p015_11.png] view at source ↗
Figure 12
Figure 12. Figure 12: Illustration of the effect of CTI at post mission EOL (i.e. 6.5 yr after commissioning) using the Short model. The plot shows a centrally placed 200 × 200 pixel CCD subfields of PIC stars from the LOP south including cosmic rays simulated using a hit rate of 10 events s−1 cm−1 . The images has been clipped by a 2σ cut and then normalised for illus￾trative purposes. The readout register is located towards … view at source ↗
Figure 13
Figure 13. Figure 13: Illustration of the Archimedean spiral jitter pattern including; Left: minor residual AOCS jitter as a best case; Right: major AOCS residual jitter as a worst case. For an ideal pattern the distance D be￾tween consecutive measurements is approximately constant and dis￾tance between consecutive spiral arms is D √ 3/2. These files contain 430 scans (shown as coloured circles marking the start of each expo￾s… view at source ↗
Figure 14
Figure 14. Figure 14: On-board photometry performed with the optimal aperture al￾gorithm of Marchiori et al. (2019) for a V = 10 star. With a central barycentric pixel position and a (worst case) systematic drift of 1.3 pixel over the course of one mission quarter, the figure shows the algorithm in action with the automatic pixel-mask updates triggered every 14 days (grey-dotted lines) if a lower NSR can be achieved (which is … view at source ↗
Figure 15
Figure 15. Figure 15: Schematic of the PlatoSim software package. a) Overview of initialisation and configuration of PlatoSim prior to simulation execution. b) Overview of each simulation step as a loop over the total number of exposures. The boxes represent input files (purple), the output file (orange), software modules (blue), and the general simulation steps (green). The two flowcharts combined illustrates PlatoSim’s event… view at source ↗
Figure 16
Figure 16. Figure 16: Examples of simulated data generated in preparation of the AIT/AIV of PLATO mission. Left: Simulation of a hartmann pattern obtained at ambient temperature and far out of focus, in preparation of the camera alignment. Right: Simulation of a V = 0 star close to the optical axis of the camera (white dot) and the extended ghost it creates on the detector via parasitic reflections, ran in preparation of the t… view at source ↗
Figure 17
Figure 17. Figure 17: NSR(V) simulation study at BOL as required by the mission. a) Noise budget at the camera level with each data point coloured after the number of stellar contaminants contained within 3 pixel and ∆V < 5 of the target star. The model prediction of the noise (orange solid curve) consists of three photometric noise components: jitter noise (pink dashed line calculated using an averaged (yaw, pitch, and roll) … view at source ↗
Figure 18
Figure 18. Figure 18: Results of the Hare and Hound (injection and retrieval) exer￾cise of an Earth-sized planet transiting a V = 10 Sun-like star. With an orbital period of 365.25 d the planet transits 4 times in the 3.3 yr simulated light curve. Top: Light curves observed with a single camera (coloured per quarter) and the corresponding W¯otan trend (white/black lines). Middle: Detrended light of all 24 camera observations (… view at source ↗
read the original abstract

PLAnetary Transits and Oscillations of stars (PLATO) is the ESA M3 space mission dedicated to detect and characterise transiting exoplanets including information from the asteroseismic properties of their stellar hosts. The uninterrupted and high-precision photometry provided by space-borne instruments such as PLATO require long preparatory phases. An exhaustive list of tests are paramount to design a mission that meets the performance requirements, and as such, simulations are an indispensable tool in the mission preparation. To accommodate PLATO's need of versatile simulations prior to mission launch - that at the same time describe accurately the innovative but complex multi-telescope design - we here present the end-to-end PLATO simulator specifically developed for the purpose, namely PlatoSim. We show step-by-step the algorithms embedded into the software architecture of PlatoSim that allow the user to simulate photometric time series of CCD images and light curves in accordance to the expected observations of PLATO. In the context of the PLATO payload, a general formalism of modelling, end-to-end, incoming photons from the sky to the final measurement in digital units is discussed. We show the strong predictive power of PlatoSim through its diverse applicability and contribution to numerous working groups within the PLATO Mission Consortium. This involves the on-going mechanical integration and alignment, performance studies of the payload, the pipeline development and assessments of the scientific goals. PlatoSim is a state-of-the-art simulator that is able to produce the expected photometric observations of PLATO to a high level of accuracy. We demonstrate that PlatoSim is a key software tool for the PLATO mission in the preparatory phases until mission launch and prospectively beyond.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 0 minor

Summary. The manuscript presents PlatoSim, an end-to-end simulator for the PLATO mission's multi-telescope photometry. It outlines the step-by-step algorithms implementing a general photon-to-digital-unit formalism (sky through optics, detectors, and electronics) to generate simulated CCD images and light curves, and reports the tool's use across PLATO consortium working groups for mechanical integration, performance studies, pipeline development, and scientific assessments. The central claim is that PlatoSim is state-of-the-art and produces expected PLATO observations to a high level of accuracy.

Significance. A validated end-to-end simulator would be a valuable asset for PLATO mission preparation, enabling quantitative performance predictions and pipeline testing prior to launch. However, the manuscript supplies no quantitative validation, error budgets, or cross-checks, so the asserted high accuracy and predictive power cannot be assessed; the work's significance therefore rests on future verification of implementation fidelity.

major comments (2)
  1. [Abstract] Abstract: the assertion that PlatoSim produces 'the expected photometric observations of PLATO to a high level of accuracy' and possesses 'strong predictive power' is unsupported by any reported validation metrics, comparisons to independent ray-trace or analytic models, noise-floor tests against mission requirements, or cross-checks with other PLATO simulators.
  2. [Abstract] Abstract (and implied architecture sections): the claim that the embedded algorithms correctly realize the photon-to-digital-unit formalism without major omissions or systematics is load-bearing for the accuracy statement, yet the manuscript provides only qualitative descriptions of applicability to working groups rather than quantitative benchmarks (e.g., PSF photometry residuals, read-noise reproduction, or end-to-end photometric precision).

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive report. We agree that the abstract claims regarding accuracy and predictive power require quantitative support that is not currently present in the manuscript. We will revise the abstract and add a dedicated validation section with benchmarks. Point-by-point responses follow.

read point-by-point responses

  1. Referee: [Abstract] Abstract: the assertion that PlatoSim produces 'the expected photometric observations of PLATO to a high level of accuracy' and possesses 'strong predictive power' is unsupported by any reported validation metrics, comparisons to independent ray-trace or analytic models, noise-floor tests against mission requirements, or cross-checks with other PLATO simulators.

    Authors: We agree the current manuscript lacks the quantitative metrics requested. The abstract phrasing was intended to reflect the detailed photon-to-digital-unit implementation and the tool's adoption across consortium groups, but this does not constitute the independent benchmarks needed. We will revise the abstract to remove the unsupported accuracy and predictive-power statements and will add a new section presenting quantitative comparisons (e.g., PSF residuals, read-noise reproduction, and end-to-end photometric precision against mission requirements and other simulators) drawn from existing consortium tests. revision: yes

  2. Referee: [Abstract] Abstract (and implied architecture sections): the claim that the embedded algorithms correctly realize the photon-to-digital-unit formalism without major omissions or systematics is load-bearing for the accuracy statement, yet the manuscript provides only qualitative descriptions of applicability to working groups rather than quantitative benchmarks (e.g., PSF photometry residuals, read-noise reproduction, or end-to-end photometric precision).

    Authors: We accept that the manuscript currently offers only qualitative evidence of correct implementation via working-group usage. While the step-by-step algorithm descriptions in the architecture sections follow the formalism, they are not accompanied by the requested numerical benchmarks. We will add quantitative validation results (PSF photometry residuals, read-noise tests, and end-to-end precision) in a revised version to substantiate the implementation fidelity. revision: yes

Circularity Check

0 steps flagged

No circularity: paper describes simulator architecture without self-referential derivations or fitted predictions

full rationale

The paper presents the step-by-step algorithms and general formalism for modeling photons from sky to digital units in PlatoSim, along with its applications to PLATO working groups. No load-bearing claims reduce to self-citations, fitted inputs renamed as predictions, or definitions that presuppose the target result. The accuracy claim is asserted via the described implementation and utility, but the text supplies no equations or chains that equate outputs to inputs by construction. This is a standard tool-description paper whose central content is independent of its own outputs.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The central claim rests on the assumption that standard photon-to-digital modeling techniques can be faithfully implemented for PLATO's specific payload; no free parameters or invented entities are specified in the abstract.

axioms (1)
  • domain assumption Standard models for photon detection, optics, and CCD behavior apply to PLATO's design.
    The simulator relies on established physics of space-based photometry.

pith-pipeline@v0.9.0 · 5965 in / 1093 out tokens · 35691 ms · 2026-05-24T06:00:38.646490+00:00 · methodology

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