pith. machine review for the scientific record. sign in

arxiv: 2604.07703 · v1 · submitted 2026-04-09 · 🌌 astro-ph.EP

Recognition: no theorem link

A Search for Wide-orbit Planets Around M-dwarfs using Deep MIRI 15-micron Images

Yihan Li , Yifan Zhou , Rachel Bowens-Rubin , Mary Anne Limbach , Hannah Diamond-Lowe , Cassidy E. Walker , Kevin B. Stevenson , Andrew Vanderburg
show 2 more authors
Giovanni Strampelli Gregory J. Herczeg
Authors on Pith no claims yet

Pith reviewed 2026-05-10 17:33 UTC · model grok-4.3

classification 🌌 astro-ph.EP
keywords M-dwarfswide-orbit planetsJWST MIRIdirect imagingexoplanetsmid-infrared imagingarchival observationsgas giants
0
0 comments X

The pith

Archival MIRI time-series data provides sensitive probes for wide-orbit gas giant planets around M-dwarfs.

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

This paper examines deep 15-micron images from JWST's MIRI instrument obtained as time-series observations of transiting planets in ten M-dwarf systems. The authors apply reference differential imaging to subtract the stellar point spread function and achieve high contrast sensitivities at separations from 1 arcsecond outward. These sensitivities are translated into detection probabilities for planets of various masses and orbital distances, showing the ability to detect Jupiter-sized planets with temperatures around 170 K at distances beyond 35 AU in the nearest systems. Readers should care because wide-orbit planets greater than 10 AU play a key role in shaping planetary system architectures, yet their occurrence rates are not well known. The work shows how existing archival observations can be repurposed to study this population without new telescope time.

Core claim

The central discovery is that processing archival MIRI 15-micron time-series data from four programs on ten M-dwarf systems yields median 5-sigma contrasts ranging from 8.9 x 10^{-4} to 6.2 x 10^{-3} at 1 arcsecond and 1.2 to 9.1 x 10^{-4} at separations greater than or equal to 3 arcseconds. Under the assumption of solar metallicity and clear atmospheres, this corresponds to sensitivity for Jupiter-sized planets at effective temperatures of approximately 170 K beyond 35 AU for systems located at 12.5 parsecs. The paper also catalogs nearby sources and evaluates their potential as background contaminants for future observations.

What carries the argument

Reference differential imaging for precise subtraction of the stellar PSF in MIRI 15-micron time-series observations.

If this is right

  • Achieves contrast limits sufficient to detect Jupiter-sized planets at ~170 K effective temperature beyond 35 AU in systems at 12.5 pc.
  • Provides planet detection probability as a function of mass and semimajor axis for each of the ten systems.
  • Catalogs nearby sources and assesses their impact assuming they are background objects.
  • Establishes that archival MIRI time-series imaging data can serve as a powerful tool for investigating the population of wide-orbit gas giants around M-dwarfs.

Where Pith is reading between the lines

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

  • Extending this analysis to a larger number of archival MIRI datasets could yield statistical constraints on the occurrence rate of wide-orbit planets around M-dwarfs.
  • Cross-matching with data from other instruments or wavelengths could help confirm or rule out candidate companions identified in these images.
  • This approach might be combined with radial velocity or astrometric data to better characterize any detected planets.
  • Similar techniques could be applied to other stellar types to compare wide-orbit planet populations across different host star masses.

Load-bearing premise

The mapping of contrast limits to planet effective temperature and mass assumes solar metallicity and clear atmospheres without clouds or other opacity sources.

What would settle it

A direct detection of a wide-orbit planet in one of these systems at a separation and contrast consistent with the reported limits, or a null result in a much larger sample that contradicts the expected sensitivity.

Figures

Figures reproduced from arXiv: 2604.07703 by Andrew Vanderburg, Cassidy E. Walker, Giovanni Strampelli, Gregory J. Herczeg, Hannah Diamond-Lowe, Kevin B. Stevenson, Mary Anne Limbach, Rachel Bowens-Rubin, Yifan Zhou, Yihan Li.

Figure 1
Figure 1. Figure 1: Examples of cal.fits images of TRAPPIST-1 observed in two epochs. The left panel shows time-series data obtained in 2022 (GTO-1177, Observation 7), and the middle panel shows a similar observation taken in 2023 (GO-3077, Observation 1). The right panel presents the residual im￾age between these two epochs, with the target star aligned. There are two background objects on the image, denoted by arrows. 4. No… view at source ↗
Figure 2
Figure 2. Figure 2: Map of image metrics across numbers of KLIP basis and annuli parameter space for TRAPPIST-1. The lower right show the quality of parameters measured by the combination of these metrics. Each pixel’s color represents the relative quality of that parameter combination, with 1 being the best and 0 being the worst. The False Positive Fraction metric is nearly uniform across parameter space and has minimal effe… view at source ↗
Figure 3
Figure 3. Figure 3: PSF-subtracted images of two exposures target￾ing GJ 3473 and the corresponding S/N maps. The upper left image shows a clean PSF subtraction while the upper right image presents apparent residuals near the central star. The peak S/N of these residual patterns is ∼2.8 (lower right panel). North is up and east is to the left. ranging from 40 to 50 pixels (15 to 20 pixels for tar￾gets with smaller field of vi… view at source ↗
Figure 4
Figure 4. Figure 4: PSF-subtracted images of all targets. The observation subarray of each target is indicated. The first seven images are zoomed in to area of 11.0” × 11.0” for clearer view of the central regions. For the last three targets, the small size (4.4” × 4.4”) is due to the choice of the observation subarray. The location of the star PSF center is denoted by the white cross. Sources around LHS 1478, TOI-1468, and T… view at source ↗
Figure 5
Figure 5. Figure 5: Signal-to-noise ratio maps of all targets. Figure annotations follow the same convention as [PITH_FULL_IMAGE:figures/full_fig_p008_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: Survey sensitivity in 5σ contrast (upper panel) and apparent magnitude (lower panel). The contrast is in planet flux/star flux unit, while the apparent magnitude cor￾responds to sensitivity. The three bright targets HD 260655, L 98-59, and GJ 357 are observed with smaller subarrays, thus limiting the curves to ∼2”. The shaded area within 0.5” indicates the region there the throughput curve is ex￾trapolated… view at source ↗
Figure 7
Figure 7. Figure 7: Detection probability map as a function of planet mass versus semimajor axis, assuming a solar metallicity and cloud-free atmosphere model. The age assumption is 5 Gyr, except for LHS 1140 (8 Gyr), TRAPPIST-1 (7.6 Gyr), and L 98-59 (4.94 Gyr). White contours show detection probabilities of 50%, 80%, and 95%. The truncation below 4 MJup is caused by the lack of evolutionary model points at >5 Gyr (see Secti… view at source ↗
Figure 8
Figure 8. Figure 8: Detection probability maps for TRAPPIST-1, considering different ages, with solar metallicity and cloud-free atmospheres. Detectable mass limits increase with system age. The cutoff at the bottom is a artifact caused by the lack of evolutionary model points at such old age. The discontinuity in the 1 Gyr map is a result from different choice of model for below and above 2 MJup. plained by the wider PSF at … view at source ↗
Figure 9
Figure 9. Figure 9: PSF subtracted images of all targets, convolved with a Gaussian kernel to better reveal close companion sources. The central star position is denoted by the white cross. Detected sources are labeled, and their astrometry and photometry properties are achieved in [PITH_FULL_IMAGE:figures/full_fig_p012_9.png] view at source ↗
Figure 10
Figure 10. Figure 10: Comparison of observed point-source-like resid￾ual to PSF model prediction for HD 260655. The green line represents data extracted from the PSF-subtracted image, and the orange line shows the PSF model from interpolating the stpsf grid. GJ 3473 was observed on 2024 March 12, 13, 30, and October 20. The March 30 observation was ex￾cluded from PSF subtraction due to apparent residuals ( [PITH_FULL_IMAGE:fi… view at source ↗
Figure 12
Figure 12. Figure 12: PSF subtraction results for GJ 3473 using in￾dividual and combined exposures. Upper panel: PSF-sub￾tracted images from the combined March 12–13 observations (left) and the October 20 observation (right). Lower panel: Contrast curves from individual epochs, with the combined three-exposure result shown for comparison. slope in the initial regime at 5” is -0.08, shallower than the photon noise-limited expec… view at source ↗
Figure 13
Figure 13. Figure 13: Contrast versus exposure time for TRAPPIST-1 at three angular separations. Blue, orange, and green points represent the median contrast at 0.5”, 1”, and 5” separations, respectively, computed from ten randomized stacking trials. The red dashed line indicates a linear fit to the initial regime at 5”, with a slope of -0.05.Contrast improvement plateaus beyond ∼8.8 hours for 5”. Our work enables the explorat… view at source ↗
read the original abstract

Wide-orbit ($>$10 AU) gas giant planets shape the architecture of planetary systems, yet their occurrence rate remains poorly constrained. JWST has obtained the deepest mid-infrared images of nearby stars to date through substantial MIRI time-series observations of transiting planets, providing sensitive probes for wide-orbit companions. Here we leverage 15 micron observations from four programs targeting ten M-dwarf systems to search for such planets. By applying reference differential imaging for precise PSF subtraction, we achieve a median 5$\sigma$ contrast of $8.9 \times 10^{-4} - 6.2 \times 10^{-3}$ (median sensitivity in apparent magnitude of 15.8-16.8 mag) at a separation of 1" and $1.2 -9.1 \times 10^{-4}$ (17.5-19.0 mag) at separations $\gtrsim$3". The sensitivity is converted to planet detection probability for each system as a function of planet mass versus semimajor axis. Assuming solar metallicity and a clear atmosphere, we are sensitive to Jupiter-sized planets with an effective temperature of ${\sim}170$ K at separations beyond 35 AU in systems at 12.5 pc. Additionally, we catalog the nearby sources and estimate their possible impact on future observations assuming they are background sources. Our results demonstrate that archival MIRI time-series imaging data is a powerful window into the population of wide-orbit gas giants around M-dwarfs.

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

0 major / 3 minor

Summary. The paper reports a search for wide-orbit (>10 AU) gas giant planets around ten M-dwarf systems using archival JWST MIRI 15-micron time-series imaging from four programs. The authors apply reference differential imaging (RDI) for PSF subtraction to achieve median 5σ contrasts of 8.9×10^{-4} to 6.2×10^{-3} (15.8-16.8 mag) at 1 arcsec and 1.2-9.1×10^{-4} (17.5-19.0 mag) at ≳3 arcsec. These limits are converted to planet effective temperature and mass sensitivities (e.g., ~170 K Jupiter-sized planets beyond 35 AU at 12.5 pc) under solar-metallicity clear-atmosphere assumptions, with a catalog of nearby sources; the central conclusion is that such archival MIRI data provides a powerful window into wide-orbit gas giants around M-dwarfs.

Significance. If the reported contrasts and sensitivity maps hold, the work demonstrates the viability of repurposing existing JWST MIRI time-series observations for high-contrast imaging of wide-orbit companions, offering a low-cost path to constrain occurrence rates without new telescope time. The direct observational contrasts and standard post-processing approach provide concrete, falsifiable sensitivity benchmarks that can be tested against future detections or deeper surveys.

minor comments (3)
  1. [Abstract] Abstract and §3 (or equivalent data reduction section): the median contrast ranges are presented without explicit per-system values or a table; adding a supplementary table of individual 5σ limits at 1″ and 3″ would improve traceability of the quoted medians.
  2. [Results] The conversion from contrast to Teff/mass (mentioned in abstract and results) relies on solar metallicity and clear atmospheres; while not central to the viability claim, a brief sensitivity test to cloudy or sub-solar models would clarify the robustness of the ~170 K limit.
  3. [Discussion] The catalog of nearby sources and their potential impact is noted but lacks quantitative details on proper-motion checks or contamination probabilities; a short paragraph or figure panel would strengthen the claim that they do not affect the planet search.

Simulated Author's Rebuttal

0 responses · 0 unresolved

We thank the referee for their positive summary and significance assessment of our manuscript on repurposing archival JWST MIRI 15-micron time-series imaging for high-contrast searches around M-dwarfs. The recommendation for minor revision is noted. No specific major comments were provided in the report, so we have no individual points to address point-by-point. We will incorporate any minor editorial or clarification changes as needed in the revised version.

Circularity Check

0 steps flagged

No significant circularity; results are direct observational measurements

full rationale

The paper's derivation chain consists of standard data reduction (reference differential imaging for PSF subtraction on archival MIRI 15-micron time-series data) followed by direct measurement of 5σ contrast limits at various separations, conversion of those contrasts to planet effective temperature and mass limits via explicit external assumptions (solar metallicity, clear atmosphere), and cataloging of nearby sources. No equations or steps reduce by construction to fitted inputs, self-definitions, or load-bearing self-citations; the central demonstration that the data source yields useful sensitivity is an empirical outcome of the processing pipeline applied to the observations, with all modeling assumptions stated and not derived from the results themselves. This is self-contained against external benchmarks such as standard contrast curves and atmospheric models.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The paper relies on standard domain assumptions for exoplanet atmosphere models and imaging reduction techniques without introducing new free parameters or postulated entities.

axioms (1)
  • domain assumption Planet atmosphere models assume solar metallicity and clear (cloud-free) conditions to map contrast to effective temperature and mass.
    Explicitly stated in the abstract when converting sensitivity to planet properties.

pith-pipeline@v0.9.0 · 5616 in / 1294 out tokens · 78026 ms · 2026-05-10T17:33:07.351731+00:00 · methodology

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Reference graph

Works this paper leans on

55 extracted references · 54 canonical work pages

  1. [1]

    I., Follette, K

    Adams Redai, J. I., Follette, K. B., Wang, J., et al. 2023, AJ, 165, 57, doi: 10.3847/1538-3881/aca60d

    work page doi:10.3847/1538-3881/aca60d 2023

  2. [2]

    H., Espinoza, N., Diamond-Lowe, H., et al

    Allen, N. H., Espinoza, N., Diamond-Lowe, H., et al. 2025, AJ, 170, 240, doi: 10.3847/1538-3881/adfc51

    work page doi:10.3847/1538-3881/adfc51 2025

  3. [3]

    Amara, A., & Quanz, S. P. 2012, MNRAS, 427, 948, doi: 10.1111/j.1365-2966.2012.21918.x Astropy Collaboration, Robitaille, T. P., Tollerud, E. J., et al. 2013, A&A, 558, A33, doi: 10.1051/0004-6361/201322068 Astropy Collaboration, Price-Whelan, A. M., Lim, P. L., et al. 2022, ApJ, 935, 167, doi: 10.3847/1538-4357/ac7c74

    work page doi:10.1111/j.1365-2966.2012.21918.x 2012

  4. [4]

    C., Buchhave, L

    August, P. C., Buchhave, L. A., Diamond-Lowe, H., et al. 2025, A&A, 695, A171, doi: 10.1051/0004-6361/202452611 Bardalez Gagliuffi, D. C., Balmer, W. O., Pueyo, L., et al. 2025, ApJL, 988, L18, doi: 10.3847/2041-8213/ade30f

    work page doi:10.1051/0004-6361/202452611 2025

  5. [5]

    2025, ApJL, 989, L22, doi: 10.3847/2041-8213/adf53f

    Beichman, C., Sanghi, A., Mawet, D., et al. 2025, ApJL, 989, L22, doi: 10.3847/2041-8213/adf53f

    work page doi:10.3847/2041-8213/adf53f 2025

  6. [6]

    2024, Astronomy & Astrophysics, 686, A33, doi: 10.1051/0004-6361/202348771

    Boccaletti, A., Lagage, P.-O., & Baudoz, P. 2024, Astronomy & Astrophysics, 686, A33, doi: 10.1051/0004-6361/202348771

    work page doi:10.1051/0004-6361/202348771 2024

  7. [7]

    E., Lawson, K

    Bogat, E., Schlieder, J. E., Lawson, K. D., et al. 2025, https://arxiv.org/abs/2504.11659

    work page arXiv 2025

  8. [8]

    2012, A&A, 537, A67, doi: 10.1051/0004-6361/201116852

    Bonavita, M., Chauvin, G., Desidera, S., et al. 2012, A&A, 537, A67, doi: 10.1051/0004-6361/201116852

    work page doi:10.1051/0004-6361/201116852 2012

  9. [9]

    Bowens-Rubin, R., Mang, J., & Limbach, M. A. 2025, The Astrophysical Journal, 986, L26, doi: 10.3847/2041-8213/ada6b9

    work page doi:10.3847/2041-8213/ada6b9 2025

  10. [10]

    Bowler, B. P. 2016, PASP, 128, 102001, doi: 10.1088/1538-3873/128/968/102001

    work page doi:10.1088/1538-3873/128/968/102001 2016

  11. [12]

    2025,, 2.1.0 Zenodo, doi: 10.5281/zenodo.14606896

    Bradley, L., Sip˝ ocz, B., Robitaille, T., et al. 2025,, 2.1.0 Zenodo, doi: 10.5281/zenodo.14606896

    work page doi:10.5281/zenodo.14606896 2025

  12. [13]

    L., & Lee, E

    Bryan, M. L., & Lee, E. J. 2024, ApJL, 968, L25, doi: 10.3847/2041-8213/ad4993

    work page doi:10.3847/2041-8213/ad4993 2024

  13. [14]

    L., & Lee, E

    Bryan, M. L., & Lee, E. J. 2025, ApJL, 982, L7, doi: 10.3847/2041-8213/adb0bd

    work page doi:10.3847/2041-8213/adb0bd 2025

  14. [15]

    Y., de Wit, J., Broˇ z, M., et al

    Burdanov, A. Y., de Wit, J., Broˇ z, M., et al. 2024, Nature, 638, 74, doi: 10.1038/s41586-024-08480-z

    work page doi:10.1038/s41586-024-08480-z 2024

  15. [16]

    J., & Mamajek, E

    Burgasser, A. J., & Mamajek, E. E. 2017, ApJ, 845, 110, doi: 10.3847/1538-4357/aa7fea

    work page doi:10.3847/1538-4357/aa7fea 2017

  16. [17]

    2025, JWST Calibration Pipeline, 1.17.1 Zenodo, doi: 10.5281/zenodo.14597407 Calder´ on, D., Ballone, A., Cuadra, J., et al

    Bushouse, H., Eisenhamer, J., Dencheva, N., et al. 2025,, 1.17.1 Zenodo, doi: 10.5281/zenodo.14597407

    work page doi:10.5281/zenodo.14597407 2025

  17. [18]

    2023, A&A, 674, A110, doi: 10.1051/0004-6361/202346063

    Carmona, A., Delfosse, X., Bellotti, S., et al. 2023, A&A, 674, A110, doi: 10.1051/0004-6361/202346063

    work page doi:10.1051/0004-6361/202346063 2023

  18. [19]

    2022, A&A, 666, A155, doi: 10.1051/0004-6361/202244056

    Chaturvedi, P., Bluhm, P., Nagel, E., et al. 2022, A&A, 666, A155, doi: 10.1051/0004-6361/202244056

    work page doi:10.1051/0004-6361/202244056 2022

  19. [20]

    D., Rodriguez, J

    Cloutier, R., Eastman, J. D., Rodriguez, J. E., et al. 2020, AJ, 160, 3, doi: 10.3847/1538-3881/ab91c2

    work page doi:10.3847/1538-3881/ab91c2 2020

  20. [21]

    A., Irwin, J

    Dittmann, J. A., Irwin, J. M., Charbonneau, D., et al. 2017, Nature, 544, 333, doi: 10.1038/nature22055

    work page doi:10.1038/nature22055 2017

  21. [22]

    2025, Nature Astronomy, 9, 358, doi: 10.1038/s41550-024-02428-z

    Ducrot, E., Lagage, P.-O., Min, M., et al. 2025, Nature Astronomy, 9, 358, doi: 10.1038/s41550-024-02428-z

    work page doi:10.1038/s41550-024-02428-z 2025

  22. [23]

    G., & Guinan, E

    Engle, S. G., & Guinan, E. F. 2023, ApJL, 954, L50, doi: 10.3847/2041-8213/acf472 16

    work page doi:10.3847/2041-8213/acf472 2023

  23. [24]

    P., Diamond-Lowe, H., et al

    Fortune, M., Gibson, N. P., Diamond-Lowe, H., et al. 2025, A&A, 701, A25, doi: 10.1051/0004-6361/202554198

    work page doi:10.1051/0004-6361/202554198 2025

  24. [25]

    P., & Zhou, Y

    Franson, K., Bowler, B. P., & Zhou, Y. 2024, The Astrophysical Journal, 974, L11, doi: 10.3847/2041-8213/ad73da Gaia Collaboration, Prusti, T., de Bruijne, J. H. J., et al. 2016, A&A, 595, A1, doi: 10.1051/0004-6361/201629272 Gaia Collaboration, Vallenari, A., Brown, A. G. A., et al. 2023, A&A, 674, A1, doi: 10.1051/0004-6361/202243940

    work page doi:10.3847/2041-8213/ad73da 2024

  25. [26]

    Gillon, M., Triaud, A. H. M. J., Demory, B.-O., et al. 2017, Nature, 542, 456, doi: 10.1038/nature21360

    work page doi:10.1038/nature21360 2017

  26. [27]

    J., et al

    Gillon, M., Ducrot, E., Bell, T. J., et al. 2025, arXiv e-prints, arXiv:2509.02128, doi: 10.48550/arXiv.2509.02128

    work page doi:10.48550/arxiv.2509.02128 2025

  27. [28]

    P., Bell, T

    Greene, T. P., Bell, T. J., Ducrot, E., et al. 2023, Nature, 618, 39, doi: 10.1038/s41586-023-05951-7

    work page doi:10.1038/s41586-023-05951-7 2023

  28. [29]

    K., Steffes, P

    Gupta, P., Atreya, S. K., Steffes, P. G., et al. 2022, in EGU General Assembly Conference Abstracts, EGU General Assembly Conference Abstracts, EGU22–966, doi: 10.5194/egusphere-egu22-966

    work page doi:10.5194/egusphere-egu22-966 2022

  29. [30]

    R., Millman, K

    Harris, C. R., Millman, K. J., van der Walt, S. J., et al. 2020, Nature, 585, 357, doi: 10.1038/s41586-020-2649-2

    work page doi:10.1038/s41586-020-2649-2 2020

  30. [31]

    Y., & Weiss, L

    He, M. Y., & Weiss, L. M. 2023, AJ, 166, 36, doi: 10.3847/1538-3881/acdd56

    work page doi:10.3847/1538-3881/acdd56 2023

  31. [32]

    Hunter, J. D. 2007, Computing in Science & Engineering, 9, 90, doi: 10.1109/MCSE.2007.55

    work page doi:10.1109/mcse.2007.55 2007

  32. [33]

    D., et al

    Kammerer, J., Lawson, K., Perrin, M. D., et al. 2024, AJ, 168, 51, doi: 10.3847/1538-3881/ad4ffe

    work page doi:10.3847/1538-3881/ad4ffe 2024

  33. [34]

    2020, A&A, 642, A236, doi: 10.1051/0004-6361/202038967

    Kemmer, J., Stock, S., Kossakowski, D., et al. 2020, A&A, 642, A236, doi: 10.1051/0004-6361/202038967

    work page doi:10.1051/0004-6361/202038967 2020

  34. [35]

    B., Schlieder, J

    Kostov, V. B., Schlieder, J. E., Barclay, T., et al. 2019, AJ, 158, 32, doi: 10.3847/1538-3881/ab2459

    work page doi:10.3847/1538-3881/ab2459 2019

  35. [36]

    2025, Nature, doi: 10.1038/s41586-025-09150-4

    Lagrange, A.-M., et al. 2025, Nature, doi: 10.1038/s41586-025-09150-4

    work page doi:10.1038/s41586-025-09150-4 2025

  36. [37]

    Astronomy & Astrophysics623, A85 (2019)

    Linder, E. F., Mordasini, C., Molli` ere, P., et al. 2019, A&A, 623, A85, doi: 10.1051/0004-6361/201833873

    work page doi:10.1051/0004-6361/201833873 2019

  37. [38]

    J., Kunimoto, M., et al

    Luque, R., Fulton, B. J., Kunimoto, M., et al. 2022, A&A, 664, A199, doi: 10.1051/0004-6361/202243834

    work page doi:10.1051/0004-6361/202243834 2022

  38. [39]

    , year = 2024, month = sep, volume =

    Matthews, E. C., Carter, A. L., Pathak, P., et al. 2024, Nature, 633, 789, doi: 10.1038/s41586-024-07837-8

    work page doi:10.1038/s41586-024-07837-8 2024

  39. [40]

    C., Mang, J., Carter, A

    Matthews, E. C., Mang, J., Carter, A. L., et al. 2026, arXiv e-prints, arXiv:2603.08780. https://arxiv.org/abs/2603.08780 Meier Vald´ es, E. A., Demory, B.-O., Diamond-Lowe, H., et al. 2025, A&A, 698, A68, doi: 10.1051/0004-6361/202453449

    work page doi:10.1051/0004-6361/202453449 2026

  40. [41]

    2025,, 1.3.4 Zenodo, doi: 10.5281/zenodo.16175987

    Newville, M., Otten, R., Nelson, A., et al. 2025,, 1.3.4 Zenodo, doi: 10.5281/zenodo.16175987

    work page doi:10.5281/zenodo.16175987 2025

  41. [42]

    K., Winters, J

    Pass, E. K., Winters, J. G., Charbonneau, D., et al. 2023, AJ, 166, 11, doi: 10.3847/1538-3881/acd349

    work page doi:10.3847/1538-3881/acd349 2023

  42. [43]

    T., Gaudi, B

    Penny, M. T., Scott Gaudi, B., Kerins, E., et al. 2019, The Astrophysical Journal Supplement Series, 241, 3, doi: 10.3847/1538-4365/aafb69

    work page doi:10.3847/1538-4365/aafb69 2019

  43. [44]

    , keywords =

    Phillips, M. W., Tremblin, P., Baraffe, I., et al. 2020, A&A, 637, A38, doi: 10.1051/0004-6361/201937381

    work page doi:10.1051/0004-6361/201937381 2020

  44. [45]

    2024, AJ, 167, 257, doi: 10.3847/1538-3881/ad374c

    Poulsen, S., Debes, J., Cracraft, M., et al. 2024, AJ, 167, 257, doi: 10.3847/1538-3881/ad374c

    work page doi:10.3847/1538-3881/ad374c 2024

  45. [46]

    D., Lee, E

    Powell, D., Feinstein, A. D., Lee, E. K. H., et al. 2024, Nature, 626, 979, doi: 10.1038/s41586-024-07040-9

    work page doi:10.1038/s41586-024-07040-9 2024

  46. [47]

    The Astronomical Journal , author =

    Price-Whelan, A. M., Sip˝ ocz, B. M., G¨ unther, H. M., et al. 2018, AJ, 156, 123, doi: 10.3847/1538-3881/aabc4f

    work page doi:10.3847/1538-3881/aabc4f 2018

  47. [48]

    2016, ApJ, 824, 117, doi: 10.3847/0004-637X/824/2/117

    Pueyo, L. 2016, ApJ, 824, 117, doi: 10.3847/0004-637X/824/2/117

    work page doi:10.3847/0004-637x/824/2/117 2016

  48. [49]

    2024, arXiv preprint arXiv:2404.02932

    Redfield, S., Batalha, N., Benneke, B., et al. 2024, doi: 10.48550/arXiv.2404.02932

    work page doi:10.48550/arxiv.2404.02932 2024

  49. [50]

    2025, ApJL, 989, L23, doi: 10.3847/2041-8213/adf53e

    Sanghi, A., Beichman, C., Mawet, D., et al. 2025, ApJL, 989, L23, doi: 10.3847/2041-8213/adf53e

    work page doi:10.3847/2041-8213/adf53e 2025

  50. [51]

    2012, ApJL, 755, L28, doi: 10.1088/2041-8205/755/2/L28

    Soummer, R., Pueyo, L., & Larkin, J. 2012, ApJL, 755, L28, doi: 10.1088/2041-8205/755/2/L28

    work page doi:10.1088/2041-8205/755/2/l28 2012

  51. [52]

    P., Todorov, K

    Stolker, T., Quanz, S. P., Todorov, K. O., et al. 2020, A&A, 635, A182, doi: 10.1051/0004-6361/201937159

    work page doi:10.1051/0004-6361/201937159 2020

  52. [53]

    R., Challener, R

    Valentine, D., Wakeford, H. R., Challener, R. C., et al. 2024, AJ, 168, 123, doi: 10.3847/1538-3881/ad5c61

    work page doi:10.3847/1538-3881/ad5c61 2024

  53. [54]

    E., et al

    Virtanen, P., Gommers, R., Oliphant, T. E., et al. 2020, Nature Methods, 17, 261, doi: 10.1038/s41592-019-0686-2

    work page doi:10.1038/s41592-019-0686-2 2020

  54. [55]

    J., Ruffio, J.-B., De Rosa, R

    Wang, J. J., Ruffio, J.-B., De Rosa, R. J., et al. 2015,, Astrophysics Source Code Library, record ascl:1506.001 http://ascl.net/1506.001

    2015

  55. [56]

    2023, Nature, 620, 746, doi: 10.1038/s41586-023-06232-z

    Zieba, S., Kreidberg, L., Ducrot, E., et al. 2023, Nature, 620, 746, doi: 10.1038/s41586-023-06232-z 17 APPENDIX A.DETECTED BACKGROUND SOURCES We list the detected background sources in Table 3. 18 T able 3. Background Sources Astrometry And Photometry Properties Source ∆RA ∆Dec Separation Mag S/N FWHM Major FWHM Minor Mass(1 Gyr) Mass(5 Gyr) Mass(10 Gyr)...

    work page doi:10.1038/s41586-023-06232-z 2023