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MOCKA -- A PLATO mock asteroseismic catalogue: Simulations for gravity-mode oscillators

T0 review · 3 major / 5 minor · reviewed 2026-08-11 · deepseek-v4-flash

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Pith's one-line read End-to-end simulations of PLATO's first southern field recover the dominant g-mode frequency in more than 95% of bright gamma Doradus and SPB stars, under both expected and degraded spacecraft noise.

desk verdict Useful, honest PLATO g-mode yield benchmark; the >95% headline is real within the simulated regimes, but those regimes were chosen at the 95% recovery contour and the amplitude inputs are the main uncertainty. read the letter →

arxiv 2412.10508 v1 pith:F32EYSG5 submitted 2024-12-13 astro-ph.SR astro-ph.EPastro-ph.GAastro-ph.IM

N. Jannsen , A. Tkachenko , P. Royer , J. De Ridder , D. Seynaeve , C. Aerts , S. Aigrain , E. Plachy
show 9 more authors
A. Bodi M. Uzundag D. M. Bowman D. J. Fritzewski L. W. IJspeert G. Li M. G. Pedersen M. Vanrespaille T. Van Reeth
This is my paper · ORCID
classification astro-ph.SRastro-ph.EPastro-ph.GAastro-ph.IM
keywords asteroseismologygravity-modepulsatorsPLATOspacephotometrygammaDoradusstarsslowlypulsatingBmockcatalogueperiod-spacingpatterns
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

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

The reading

This paper argues that PLATO's complementary-science program will be a working asteroseismic observatory for gravity-mode pulsators, not just a planet hunter. The authors build MOCKA, a simulated catalogue of intermediate- and massive-star pulsators in PLATO's first southern pointing field (LOPS2), and run realistic end-to-end pixel-level simulations of two-year observations. Their central quantitative claim is that the dominant g-mode frequency of a gamma Doradus star brighter than $G \lesssim 14$ and of an SPB star brighter than $G \lesssim 16$ is recovered in more than 95% of cases under both the expected and the degraded spacecraft-noise scenario. A sympathetic reader cares because those recovered modes are the basis of period-spacing patterns, the main tool for probing near-core rotation, chemical mixing, and angular-momentum transport in intermediate-mass stars.

What carries the argument

The load-bearing machinery is the MOCKA end-to-end simulation chain. A magnitude-limited Gaia DR3 catalogue of the LOPS2 field supplies potential targets; for each pulsation class, synthetic light curves are generated from empirically calibrated oscillation-mode models, with gamma Doradus modes built from the period-spacing pattern formalism of Li et al. (2020) and SPB modes from the 26-star Kepler sample of Pedersen et al. (2021). These signals are injected at pixel level with PlatoSim into multi-camera images that include pointing jitter, thermo-elastic distortion, readout noise, cosmic rays, realistic data gaps, and, in one batch, variable contaminating stars. Detection proceeds by iterative prewhitening with a false-alarm-calibrated SNR stopping criterion, and the recovery rate of the injected dominant mode is the metric that translates the mission noise budget into scientific yield.

What would settle it

Re-run the MOCKA pipeline with SPB and gamma Doradus mode amplitudes drawn from the full TESS+Gaia amplitude distribution of Hey & Aerts (2024) instead of the Kepler log-normal fits, and check whether the dominant-mode recovery rate stays above 95% for $G \lesssim 16$ SPB stars and $G \lesssim 14$ gamma Doradus stars under Cortado systematics; if it falls below 95%, the headline claim does not survive a realistic population shift.

Watch

Extended reading notes

Core claim

The paper's claim is that, for the first time, PLATO's ability to detect and recover oscillation modes of main-sequence g-mode pulsators is demonstrated quantitatively. Using the MOCKA catalogue, the authors report dominant-frequency recovery rates of 98.9% (Affogato, expected systematics) and 95.8% (Cortado, degraded systematics) for gamma Doradus stars, and 98.2% and 95.4% for SPB stars, within the magnitude-limited simulated regimes. They also claim that an increased spacecraft noise budget degrades g-mode recovery more than contamination by variable stars, that stellar pollution below roughly a 6% third-light ratio leaves amplitude precision acceptable while frequency precision stays almost unaffected, and that recovered frequency precisions of order $10^{-4}\,\mathrm{d}^{-1}$ lie well below the $10^{-3}\,\mathrm{d}^{-1}$ required for forward asteroseismic modelling.

Load-bearing premise

The injected pulsation amplitude distributions, especially the SPB distribution fitted to only 26 Kepler stars, match what PLATO will actually see in the LOPS2 field; the authors themselves note that the exact amplitude distribution plays a key role in how many modes can be detected.

Editorial extensions

If this is right

  • Within LOPS2, the recovery rates imply that period-spacing pattern construction will be feasible for a large fraction of bright gamma Doradus and SPB stars, including many of the 1455 pure g-mode and 1449 hybrid pulsators already identified in the field.
  • The difference between expected and degraded spacecraft noise corresponds to roughly one magnitude of brightness: reaching the same photometric precision with degraded noise requires targets about one magnitude brighter, mostly in the regime $9 < P < 13$.
  • If stellar pollution is kept below about 6% third-light, contaminating light does not dominate the noise budget; above that threshold amplitude precision degrades sharply while frequency precision remains nearly unaffected.
  • Recovered frequency precisions around or below $10^{-4}\,\mathrm{d}^{-1}$ are well inside the $10^{-3}\,\mathrm{d}^{-1}$ needed for forward asteroseismic modelling of high-order g modes, so the simulated catalogue yields seismically usable mode lists.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • If the true gamma Doradus and SPB amplitude distributions actually match the TESS/Gaia results of Hey & Aerts (2024), the paper's own high-amplitude batch suggests the detectability plateau would extend to about $P \sim 13$, so the 95% recovery claim would likely hold or improve in the bright regime but could shift in detail.
  • The SNR significance surfaces computed here for PLATO cadences could be transferred to TESS and future space photometry missions; the result that the classical SNR $=4$ threshold is too optimistic for continuous space-based data is a general caution, not a PLATO-specific one.
  • Because hybrid g-mode plus p-mode pulsators were deliberately excluded, the real LOPS2 yield may differ from MOCKA's for stars crossing both instability regions; extending the catalogue to hybrids would test whether the greater than 95% dominant-mode recovery carries over.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

3 major / 5 minor

Summary. The paper presents MOCKA, an end-to-end PlatoSim simulation catalogue for PLATO's LOPS2 field, focusing on gravity-mode pulsators (gamma Doradus and SPB stars) among eight variability classes. The authors construct a Gaia DR3-based target catalogue, inject oscillation-mode models with log-normal amplitude distributions calibrated to Kepler samples, simulate three noise scenarios (Affogato, Cortado, Doppio), reduce the light curves with a custom pipeline, and extract frequencies with an iterative prewhitening method. The headline result is that within the simulated magnitude limits (G ≲ 14 for gamma Dor and G ≲ 16 for SPB) the dominant g-mode frequency is recovered in more than 95% of cases under both expected and degraded spacecraft systematics. The paper also reports mode occurrence rates, amplitude and frequency precision, and the impact of stellar contamination.

Significance. If the central yield claim holds, this is a valuable quantitative benchmark for the PLATO-CS program: it suggests that bright gamma Dor and SPB stars in LOPS2 will yield recoverable dominant g-mode frequencies and enable period-spacing pattern studies. The study's strengths are its realistic pixel-level end-to-end simulations, the explicit three-batch comparison of spacecraft systematics and contamination, the public data products, the careful passband and apodization corrections, and the analysis of SNR stopping criteria. The main caveat is that the headline recovery fractions are conditional on assumed Kepler-based amplitude distributions and on magnitude limits that are themselves defined at the ~95% recovery contour, so the external predictive power for the real LOPS2 population is not fully established.

major comments (3)
  1. [§3.1, Appendix C, Abstract] The limiting magnitudes P = 14 and P = 16 are not independent mission constraints: Appendix C defines the detection limit as the magnitude at which more than 95% of the injected log-normal amplitudes can be recovered, and §3.1 states that each detection-magnitude threshold was set using this noise budget. The abstract then presents the >95% dominant-mode recovery within these same magnitude limits as the paper's headline result. The recovery fractions in §6.1 (98.9% and 95.8% for gamma Dor; 98.2% and 95.4% for SPB) are therefore partly a design criterion rather than an independent simulation prediction. This is not fully circular, because the criterion concerns all injected amplitudes while the headline concerns the dominant mode, but the threshold choice still removes much of the risk that the headline could fail. Please reframe the claim as conditional on the assumed input amplitude distributions and on Pmax being chosen by this 95% recovery criterion, or fix the magnitude limits a priori and let the recovery fraction be a genuine output.
  2. [§4.1.2, Fig. 15, §7] The SPB mode amplitude distribution is fitted to only 26 Kepler stars (Pedersen et al. 2021), and §7 concedes that 'the exact underlying amplitude distribution that will be observed plays a key role in how many modes can be detected.' This sensitivity is visible in the paper's own high-amplitude SPB test batch (Fig. 15), which changes the location of the detectability plateau by about a magnitude. The reported recovery rates (98.2% for Affogato and 95.4% for Cortado) are thus tied to a specific small-sample input. Please quantify the dominant-mode recovery fractions for the high-amplitude batch and/or provide a sensitivity analysis over plausible amplitude distributions, so that the abstract's numerical claim is explicitly attached to a stated input assumption rather than to a single Kepler-based sample.
  3. [§3.1] The target catalogue is restricted to presumed single stars: binaries are excluded via the Gaia reduced unit weight error cut, and the text states 'we only intend to simulate targets as if they are all single stars.' Since the abstract frames the >95% recovery as a statement about gamma Dor and SPB stars in the LOPS2 field, and massive SPB stars have a high multiplicity fraction, the yield may not apply to the full population. Please either include a binary-dilution test (e.g., injecting companions at representative flux ratios and separations) or state explicitly in the abstract and conclusions that the headline applies only to a single-star subsample. As written, the LOPS2 population-level claim goes beyond the simulated sample.
minor comments (5)
  1. [§4.1.2, §4.2.5, §5.5, Appendix C] There are several typographical and grammatical errors: 'SPB stars are are high-order' in §4.1.2, 'catagorised' in §4.2.5, 'unset' in Appendix C (should be 'onset'), and 'interferences' in §5.5 (likely 'inferences').
  2. [Table 1, §4.1.1] Table 1 lists the gamma Doradus spectral type as 'F4-F0'; this range is conventionally written F0-F4 and should be corrected for consistency with the text's 'late-A to early-F' description.
  3. [§2 and throughout] The batch name 'Cortado' is typeset as 'C ortado' in several places (e.g., Section 2 and the figure captions); please standardize the formatting of the batch names.
  4. [Fig. 17] The note that 'blue indicates the most desirable result' in Fig. 17 inverts the color convention used in most other figures; please add explicit color-bar labels to all panels and clarify the convention in the caption.
  5. [§6.1] The sentence 'We recover 98.9% and 95.8% for the gamma Dor sample and 98.2% and 95.4% for the SPB sample as per simulation batch Affogato and Cortado, respectively' is ambiguous; please state explicitly which batch corresponds to each pair of numbers.

Circularity Check

1 steps flagged · score 5.0 of 10

The >95% headline is partly by design: the simulated magnitude limits are defined at the 95% injected-amplitude recovery contour, so the predicted recovery rate is baked into the sample definition.

  1. self definitional [Sect. 3.1 (target star sky catalogue) and Appendix C (PLATO noise budget), feeding the abstract claim]
    "Each detection-magnitude threshold was set by PLATO's noise budget derived from a separate set of simulations (c.f. Appendix C). ... We define the detection limit as when more than 95% of the injected amplitudes (draw from a log-normal distribution) can be recovered. This limit is used to define the limiting simulated magnitude."

    The magnitude-limited simulation windows are not independent testbeds: Pmax was chosen by the 95% injected-amplitude recovery contour of the noise budget, so the abstract's claim of 'dominant g-mode frequency is recovered in more than 95% of the cases' inside those windows restates the selection criterion in slightly different words (dominant mode versus all amplitudes, full pipeline versus noise budget). The full simulations add systematics, masks, gaps, and contamination, so the exact numbers (98.9/95.8% for gamma Dor and 98.2/95.4% for SPB) are measured and not strictly forced; but the 95% level is a design choice, and since the dominant mode is the largest injected amplitude, a 95% all-amplitude threshold makes a >95% dominant-mode result expected rather than independently predicted.

full rationale

MOCKA is a genuinely self-contained end-to-end hare-and-hound exercise: recovery rates are computed from full pixel-level PlatoSim light curves with spacecraft systematics, masks, data gaps, and stellar contamination, and the pipeline, stopping criteria, and matching are all described in detail. There is no load-bearing self-citation chain or imported uniqueness theorem; citations to Jannsen et al. (2024) for PlatoSim are normal method citations rather than circular support. However, the central headline figure is partially circular. The paper defines the detection limit as the magnitude at which more than 95% of injected amplitudes can be recovered in the noise-budget simulations (Appendix C), then uses that limit to set the simulated magnitude ranges (P=14 for gamma Dor, P=16 for SPB), and finally reports that the dominant g-mode frequency is recovered in more than 95% of cases within those ranges. Because the dominant mode has the largest injected amplitude, a sample truncated at the 95% amplitude-recovery contour almost guarantees a similarly high dominant-mode recovery rate; the end-to-end simulations could have degraded it, and the fact that it did not is informative, but the 95% threshold is partly a construction of the sample definition rather than a free prediction. The authors' own Sect. 7 caveat that 'the exact underlying amplitude distribution that will be observed plays a key role in how many modes can be detected' further underscores that the yield depends on the injected Kepler-derived amplitude distributions, which are input assumptions rather than derived results. This is partial circularity in one headline number, not wholesale circularity of the catalogue's construction.

Assumptions & free parameters 6 free parameters · 6 assumptions · 0 invented entities

The central forecast depends on fitted amplitude distributions (SPB n=26), hand-tuned contaminant models, and a magnitude range chosen via the 95% recoverability criterion, which gives the headline number some circularity burden. No new physical entities are introduced; the MOCKA catalogue, pyspot, and SNR surfaces are software or data products, not entities.

free parameters (6)
  • Per-sample limiting magnitudes Pmax = P=14 (gamma Dor), P=16 (SPB), P=16 (beta Cep/delta Sct), P=17 (Cepheid/RR Lyr/sdBV/WD)
    Set in Sect. 3.1 from separate noise-only simulations (Appendix C) as the magnitude where more than 95% of injected mode amplitudes are recoverable. This design choice directly shapes the headline 95% dominant-mode recovery claim.
  • SPB mode amplitude distribution (log-normal) = Not quoted; fitted to 26 Kepler SPB stars (Pedersen et al. 2021)
    Injected SPB mode amplitudes are drawn from this fit; yields are sensitive to it (Sect. 6.2, Fig. 15), and the authors acknowledge the sample is small.
  • gamma Dor period-spacing gradient coefficients c1-c5 = Not quoted
    Eq. (6) fits the period-spacing gradient versus first period to the Kepler sample of Li et al. (2020); controls the synthetic g-mode patterns used in recovery tests.
  • SNR significance surface coefficients d1, d2, d3 = Table 3 (e.g., 25 s cadence: 0.13217934, -0.15429918, 5.12996448)
    Eq. (9) fitted to 10,000 white-noise simulated light curves per cadence; the resulting SNR threshold determines which extracted peaks count as detections.
  • pyspot tuning parameters = Spot size = 300 micro-hemispheres times B_em^2; decay rates lower than M19; cycle overlap U(0,0.1) P_cyc
    Chosen by trial and error (Appendix E) to produce realistic-looking spot light curves; affects contaminant variability in the Doppio batch.
  • Contaminant KDE density cut = 25-50% lowest-density points discarded
    Arbitrary cut (Sect. 5.3) to remove spurious Gaia FLAME stellar-parameter solutions; affects which contaminant variability models are assigned.
assumptions (6)
  • domain assumption The PLATO Mission Parameter Database (MPDB) 'as expected' and 'as required' configurations describe the real spacecraft noise environment.
    Sect. 5.1: detector noise, AOCS jitter, and thermo-elastic distortion are drawn from MPDB; the whole forecast inherits this assumption.
  • domain assumption Kepler and TESS pulsation-mode samples are statistically representative of the pulsator populations in the LOPS2 field.
    Sect. 4.1: gamma Dor modes use Li et al. (2020), SPB modes use Pedersen et al. (2021), delta Sct uses Bowman & Kurtz (2018); the simulation yields depend on these as ground truth.
  • domain assumption Gaia DR3 photometry, extinction estimates, and RUWE-based single-star selection yield an unbiased target catalogue.
    Sect. 3.1: stars without extinction are assumed to have zero extinction, and binaries are excluded; this biases the target-to-contaminant distribution as the authors note.
  • ad hoc to paper The simulated magnitude limits are defined by the 95% recoverability criterion rather than by mission constraints.
    Appendix C: Pmax is chosen so that more than 95% of injected amplitudes are recoverable; this embeds the headline claim in the simulation design.
  • ad hoc to paper Target stars are treated as single stars; higher-order multiplicity is ignored for yield estimates.
    Sect. 3.1: 'we only intend to simulate targets as if they are all single stars'; massive stars, and SPBs in particular, have high multiplicity fractions, so blending could affect apparent amplitudes.
  • standard math Standard periodogram, BIC, and least-squares statistics are valid for frequency extraction from PLATO-like light curves.
    Sect. 5.5: Lomb-Scargle periodogram and iterative prewhitening with BIC/SNR criteria; these are standard methods in the field.

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Cite this review

Pith. "Pith review of MOCKA -- A PLATO mock asteroseismic catalogue: Simulations for gravity-mode oscillators." pith.science (2026). https://pith.science/paper/F32EYSG5

@misc{pith2026241210508,
  author       = {Pith},
  title        = {Pith review of: MOCKA -- A PLATO mock asteroseismic catalogue: Simulations for gravity-mode oscillators},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/F32EYSG5}},
  note         = {Machine review of arXiv:2412.10508}
}
abstract

With ESA's PLATO space mission set for launch in December 2026, a new photometric legacy and a future of new scientific discoveries await. In this work we investigate PLATO's potential for observing pulsating stars across the Hertzsprung-Russell diagram as part of the PLATO Complimentary Science program (PLATO-CS). Specifically, a PLATO mock asteroseismic catalogue (MOCKA) of intermediate to massive stars is presented as a benchmark to highlight the asteroseismic yield of PLATO-CS in a quantitative way. MOCKA includes simulations of $\beta$~Cephei, slowly pulsating B (SPB), $\delta$~Scuti, $\gamma$~Doradus, RR Lyrae, Cepheid, hot subdwarf, and white dwarf stars. In particular, main-sequence gravity (g) mode pulsators are of interest as some of these stars form an important foundation for the scientific calibration of PLATO. MOCKA is based on a magnitude limited ($G\lesssim17$) \textit{Gaia} catalogue and is a product of realistic end-to-end \texttt{PlatoSim} simulations of stars for the first PLATO pointing field in the Southern hemisphere, which will be observed for a minimally 2-yr duration. We show that an abundant spectrum of frequencies is achievable across a wide range of magnitudes and co-pointing PLATO cameras. Within the magnitude limited regimes simulated ($G \lesssim 14$ for $\gamma$~Doradus stars and $G \lesssim 16$ for SPB stars) the dominant g-mode frequency is recovered in more than $95\%$ of the cases. MOCKA help us to understand the limits of the PLATO mission as well as highlight the opportunities to push astrophysics beyond current stellar models. All data products of this paper are made available to the community for further exploration. The key data products of MOCKA are the magnitude limited \textit{Gaia} catalogue of the first PLATO pointing field, together with fully reduced light curves from multi-camera observations for each pulsation class.

Figures

Figures reproduced from arXiv: 2412.10508 by the authors.

Figure 1
Figure 1. Illustration of the first PLATO pointing field called LOPS2. The platform pointing (being parallel to the pointing of the two F￾CAMs; see magenta star) is centred at the equatorial coordinate (α, δ) = (95.310 43◦ , −47.886 93◦ ), with zero rotation with respect to the Galac￾tic equator. The N-CAM overlap of nCAM ∈ {6, 12, 18, 24} is illustrated with an increasing darker shade of blue (also indicated in the white box… view at source ↗
Figure 3
Figure 3. HRD of the γ Dor and SPB (left panel), and δ Sct and βCep (right panel) stellar samples. The colour gradient indicates the stellar surface gravity, and over-plotted are MIST evolutionary tracks (Choi et al. 2016). Solid lines indicate instability strips for gravity modes in the left panel and pressure modes in the right panel. The red lines show the edges of the theoretical γ Dor instability strip from Dupret et al.… view at source ↗
Figure 4
Figure 4. Model fit to the gradient–period relation for dipole sectoral pro￾grade g modes from Li et al. (2020). Typically this diagram features the mean period, but here we correlate the first mode period in the period spacing pattern with the gradient. The colour scaling shows the value of the corresponding first period spacing [PITH_FULL_IMAGE:figures/full_fig_p006_4.png] view at source ↗
Figures from the paper (15 more)
Figure 5
Figure 5. Figure 5: Example of a simulated SPB star. The lower/left axes belong to the amplitude spectrum (blue line), where we have highlighted the mode frequencies (dotted lines), the first mode period (P0), and the first period spacing (∆P0). The upper/right axes belong to the correspo…
Figure 6
Figure 6. Figure 6: Power spectral density (PSD) diagrams showing granulation and pulsation signals caused by large convective envelopes in low-mass dwarfs. The PSD was computed for a 2-yr noise-less light curve. The bottom panel is a zoom-in on the combined model illustrating the stan￾da…
Figure 8
Figure 8. Figure 8: Gaussian KDE distribution per spectral type of the LOPS2–Gaia DR3 single stars with valid stellar bulk parameters. The normalised den￾sity is scaled from low to high with brown to purple colour, respectively. A cut in the density region, discarding the lowest 25–50%, h…
Figure 9
Figure 9. Figure 9: CaMD of different stellar classes used to assign a variable signal to stellar contaminants. The respective class is written in the title header together with the number count of the class. The upper panels show the confinement of all stars that feature solar-like varia…
Figure 10
Figure 10. Figure 10: Assembly of data gaps included prior to the frequency analy￾sis. Besides the quarterly rotational realignment of the spacecraft (blue lines), we also consider downtime due to station keeping manoeuvres (purple lines), loss of fine guidance (orange lines), and safe mod…
Figure 11
Figure 11. Figure 11: Histogram of the SNR of the highest amplitude frequency ex￾tracted from 10 000 synthetic white noise PLATO light curves. This ex￾ample shows the optimal SNR criterion (dashed lines) estimated as the FAP = 1% from time series with a duration of eight mission quarters …
Figure 12
Figure 12. Figure 12: Optimum significance surface for PLATO light curves with a cadence of δt = 25 s. The surface fit was performed with Eq. (9) to the grid points (sorted in colour after the FAP, with semi-regular grid points of {10, 8, 6, 4, 2, 1, 0.5, 0.1, 0.01}%). the cadence; ii) the…
Figure 13
Figure 13. Figure 13: Amplitude detection limit from a prewhitening strategy using the SNR stopping criterion and a high amplitude version of the Af￾fogato SPB sample (c.f. Sect. 6.2). This plot illustrates the general noise budget in the frequency domain enforced by random and systematic …
Figure 14
Figure 14. Figure 14: Limiting mode amplitude detection for the γ Dor sample (left panels) and the SPB sample (right panels). Top and bottom panel show the lowest mode amplitude detected for each star of the simulation batch Affogato and Cortado, respectively. The data points are colour-co…
Figure 15
Figure 15. Figure 15: Limiting mode amplitude detection for the SPB sample, simula￾tion batch Affogato, and using an artificially increased mode amplitude distribution. The data points are colour-coded after camera visibility. The dotted vertical line marks a clear transition (at P ∼ 12.5)…
Figure 16
Figure 16. Figure 16: Detection efficiency diagrams (E in %) for the γ Dor sample (left panels) and SPB sample (right panels). The top and middle panels show the detection efficiency as a function of the camera visibility for Affogato and Cortado, respectively. The bottom panels show the r…
Figure 17
Figure 17. Figure 17: Amplitude precision (left panels; in ppm) and frequency precision (right panels; in d−1 ) of detected pulsation modes as a function of magnitude and camera visibility for the γ Dor sample. The top and middle panels show the results for Affogato and Cortado, respective…
Figure 18
Figure 18. Figure 18: Amplitude precision vs. SPR diagrams for the γ Dor and SPB sample (left and right panels, respectively), and for the simulation batches Affogato and Cortado (upper and lower panels, respectively). The colour scaling of the γ Dor sample shows the PLATO magnitude and fo…
Figure 19
Figure 19. Figure 19: Detection efficiency residual (∆E in %) diagrams to test the impact of stellar contamination for the γ Dor sample (left panels) and SPB sample (right panels). The top panels show the results for non-variable targets from Affogato when comparing all stars vs. contamina…
Figure 20
Figure 20. Figure 20: Difference between pulsation mode detected using the BIC and the SNR prewhitening stopping criterion, ∆N = (NBIC − NSNR)/Ninput, as function of magnitude and camera visibility for the γ Dor sample (left panels) and SPB sample (right panels). The top panels show the re…

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Forward citations

Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

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  2. Observing bright pulsating white dwarfs with PLATO: A new window into the late stages of stellar evolution

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    PLATO should detect white-dwarf pulsation modes down to about 0.1 milli-magnitudes for bright targets, and the LOPS2 field contains 159 high-priority white-dwarf candidates for such measurements.

  3. The PLATO field selection process. II. Characterization of LOPS2, the first long-pointing field

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Pith tools

Reviewed August 11, 2026 · model on record in the stance chip above.