Pith. sign in

REVIEW 4 minor 141 references

The paper argues that the 2019 M87* black hole image is not a single observation but the product of many defensible choices, and that the strongest evidence is the stability of the ring across those choices.

Reviewed by Pith at T0; open to challenge. T0 means a machine referee read the full paper against a public rubric. the ladder, T0–T4 →

Challenge this review Re-run · record.json Download PDF Read on arXiv ↗

The EHT's iconic black hole image is one of countless plausible renderings; the collaboration's most valuable evidence is the limited variability across choices, not the single image.

T0 review reviewed 2026-08-02 challenge →

load-bearing objection A careful, credit-worthy HPS paper that reframes the EHT's evidence as the demonstrated variability across plausible imaging choices, though 'limited variability' remains more asserted than quantified.

arxiv 2607.14928 v1 pith:HF56EUF3 submitted 2026-07-16 physics.hist-ph astro-ph.HEastro-ph.IMgr-qc

Coloring Black Holes: Epistemic and Aesthetic Choices in Astronomical Imaging

Rodrigo Ochigame , Emilie Skulberg , Jeroen van Dongen This is my paper
classification physics.hist-ph astro-ph.HEastro-ph.IMgr-qc MSC 00A3085-03
keywords Event Horizon Telescopeblack hole imagingM87*VLBIimage reconstructionscientific evidenceepistemic choicesmodel-laden data
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved

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 tries to establish that the famous 2019 image of the M87* black hole shadow was not dictated by the data. Because the telescope data are extremely noisy and sparse, researchers had to make a choice at every processing stage—how to calibrate, which imaging algorithm to use, how to weight the regularization terms, what colors to display, and even whether to crop the frame. The published picture was actually the pixel-by-pixel average of three images made with different pipelines, shown in a custom orange color map chosen partly for its cultural associations. By re-running the collaboration's open-source imaging software with different options, the authors show that many plausible renderings exist, yet a ring-and-shadow structure persists across a broad set of them. Their central claim is that the most valuable scientific evidence is not the single advertised image but the demonstration of limited variability across those defensible choices.

Core claim

The paper's central claim is that the EHT's M87* result is an ill-posed inverse problem: the visibility data underdetermine the image, so countless images fit the measurements equally well. At each stage—calibration pipeline, CLEAN versus regularized-maximum-likelihood reconstruction, regularizer weights chosen by a coarse parameter survey on synthetic 'ground truth' images, and final color and cropping decisions—researchers had to select among reasonable alternatives. The final publicized image was the simple average of three 'fiducial' images from three different pipelines, displayed with a color map chosen for perceptual and aesthetic reasons. By systematically varying algorithms, paramet

What carries the argument

The central mechanism is the variability survey: re-executing the EHT's open-source imaging workflow—calibration, CLEAN- and regularized-maximum-likelihood reconstruction, parameter grids, and color mapping—under alternative choices, and treating the spread of resulting images as the object of analysis. The key conceptual tool is the likelihood–posterior distinction: many images fit the observed visibilities equally well, so priors and regularizers decide among them; the paper then takes the ensemble of plausible outputs, rather than any single output, as the epistemic unit.

Load-bearing premise

The demonstration of 'countless plausible ways' assumes that the public open-source software, archived data, and the parameter survey the authors ran faithfully reproduce the full space of choices the EHT actually faced; if the collaboration's internal versions allowed different options, the variability could be over- or under-stated.

What would settle it

Run the public 2017 M87* data through the EHT's own imaging pipelines with a denser parameter sweep—including regularizer weights between the powers of ten the collaboration tested—and check whether any plausible combination removes the ring or changes its diameter by more than the reported uncertainty; if so, the limited-variability claim collapses. Alternatively, if the EHT were to release fully unprocessed correlator data and a unique image emerged from independent re-analysis, the underdetermination claim would be undercut.

Watch this falsifier. Get emailed when new claim-graph text bears on it.

If this is right

  • The single published image should not be treated as standalone evidence; the evidence is the range of plausible images and the structural stability across them.
  • Presenting an average of three pipeline images as 'the photo' conflates processing with observation; public communication should report the variability explicitly.
  • The EHT's selection of parameters using synthetic 'ground truth' means the images are only as trustworthy as the assumption that those simulations adequately represent the source regime.
  • For future targets such as Sagittarius A* or next-generation arrays, the collaboration could make the full set of plausible reconstructions the public result rather than a single image.

Where Pith is reading between the lines

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

  • A quantitative extension: define the evidence as the distribution of ring diameters and brightness asymmetries across the tested parameter combinations; if that distribution is wider than the EHT's reported uncertainties, the 'limited variability' conclusion would need qualification.
  • A natural test: apply the same re-sampling to the larger public data releases from 2022 and to the later machine-learning-based reconstruction; if the sharper machine-learning image falls outside the original variability envelope, that would show the envelope depends on the reconstruction family chosen.
  • The same logic transfers to other inverse problems without ground truth, such as medical or planetary image reconstruction, where the defensible output may be a set of equally plausible reconstructions rather than a single 'best' image.
Share X Bluesky LinkedIn Reddit HN

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

0 major / 4 minor

Summary. The paper reconstructs the full pipeline that produced the Event Horizon Telescope Collaboration's 2019 image of M87*, from observing campaign through correlation, calibration, algorithm design, blind and fiducial imaging, and finally averaging, coloring, and public presentation. Drawing on EHT papers, technical reports, open-source code, and the authors' own re-runs of the imaging software, it argues that at every stage the data underdetermine the image: many plausible choices of algorithms, parameters, regularizers, and color maps were available, and the published image is the average of three independently produced pipeline images. The paper's central normative claim, stated in the Conclusion (§8), is that the most valuable scientific evidence from the EHT is not the single advertised image but the demonstration of limited variability across the specific choices the collaboration actually made. The authors explicitly acknowledge that untried choices could yield greater variability.

Significance. If the central claim holds, the paper provides a historically well-grounded and epistemically substantive case study of model-data symbiosis in computational imaging, going beyond earlier philosophical discussions by actually running the open-source tools and exhibiting alternative images. The interactive parameter demonstration and animation (archived on Zenodo) are concrete, reproducible contributions; the authors also carefully document the EHT's own language ('blind', 'fiducial', 'ground truth') and contrast it with practices at LHC and LIGO. The paper is appropriately cautious: it does not argue that the image is not a photograph or observation, and it flags the circular-Gaussian-prior concern and the possibility of greater variability outside the surveyed space. This should be a valuable contribution to history and philosophy of astronomy and of data-intensive science.

minor comments (4)
  1. [§8, Conclusion] The central phrase 'limited variability' is used as an unquantified, qualitative assessment. Since the authors state they precomputed images for all 37,500 combinations of the eht-imaging parameter survey, a brief quantitative summary (e.g., distribution of ring diameters, fraction of Top Set images retaining a ring, or inter-image pixel variance) would make the claim more transparent and would preempt the skeptical reading that 'limited' is doing unearned work. If such metrics are not easily reported, the conclusion could be hedged to 'limited variability within the surveyed combinations'.
  2. [§4 and §6] The potential circularity of the circular Gaussian prior is acknowledged in §4, but the paper does not report what happens to the reconstructed images when that regularizer is removed or its FWHM is pushed outside the EHT survey range. Since the interactive demonstration appears to include the Gaussian prior as one of its seven parameters, a short sensitivity statement (e.g., 'the ring persists when the Gaussian prior is disabled' or 'the ring disappears') would materially strengthen the robustness discussion and address the shared-assumption concern.
  3. [Figure 11 caption] The caption says the demonstration 'samples seven parameters, totaling 37,500 possible combinations,' but it does not list how many values are sampled for each parameter. Adding this breakdown (e.g., 5 values for each regularizer weight, 4 values for total flux, etc.) would let readers verify the total and understand the coarseness of the grid.
  4. [§7, Averaging] The statement that the published image is 'simply the pixel-by-pixel average of the results from the three pipelines' is load-bearing for the paper's narrative but is not tied to a specific EHT Paper IV section. A citation to the relevant part of EHT (2019e) would make the historical claim easier to check.

Circularity Check

0 steps flagged

No material circularity; the central claim is an interpretive synthesis of external evidence, with only peripheral author self-citations.

full rationale

The paper is a historical-epistemological analysis, not a derivation that fits parameters and then re-predicts them. Its central conclusion—"the most valuable scientific evidence produced by the EHT comes not from the single image it ultimately advertised, but from the demonstration of the limited variability that emerged from the specific choices made"—is a normative reinterpretation of the EHT's own Top Set stability, not a quantity fitted from data and renamed as a prediction. The key premise of "countless plausible ways of rendering the data" is grounded in external sources: the EHT's own statement that "there are an infinite number of possible images that explain the data" (Bouman et al., quoted in Section 1), the public EHT data products, and the authors' independent recomputation with open-source software ("we studied the source code and tested different options for algorithms, parameters, and colors"). The paper explicitly flags, rather than commits, the main potential circularity in the EHT's imaging: the circular Gaussian prior was "partly justified" by CLEAN results, yet "one could argue that this regularizer makes a heavy-handed assumption about the shape of the image." It also acknowledges the reach of its own "limited variability" claim: "This leaves open the possibility that different choices, not tried or reported, could lead to greater variability." Author self-citations (Skulberg 2021; Skulberg & Elder 2025; Skulberg, Sparre, and Veel 2023) appear only as peripheral support for historical context—e.g., institutional frustrations, the concept of "directness," and uses of "synthetic" in visualization—and are not load-bearing for the paper's main argument. No fitted input is called a prediction, no uniqueness theorem is imported from the authors' prior work, and no ansatz is smuggled in via self-citation. The central claim is therefore independent of the authors' own assumptions in the relevant sense, and the minor self-citations do not raise the circularity score above 1.

Axiom & Free-Parameter Ledger

0 free parameters · 3 axioms · 0 invented entities

This is an interpretive-historical paper, so there are no fitted parameters or invented physical entities. The central claim rests on the fidelity of the re-implementation and the reliability of the EHT record.

axioms (3)
  • domain assumption The EHT's open-source software and public data faithfully represent the actual 2017-2019 processing choices.
    Invoked in Section 1 where the authors state they studied the source code and tested options; the central demonstration of variability depends on this.
  • domain assumption The EHT's published accounts, technical reports, and public statements accurately report the collaboration's internal processes and deliberations.
    The paper's close readings in Sections 3-7 rely on EHT papers and communications; cited internal history (Galison 2019) is treated as accurate.
  • standard math The van Cittert–Zernike theorem holds for the EHT observing conditions (incoherent source, far-field, thin screen).
    Section 2 introduces the theorem as the basis of VLBI; not proven in the paper, but standard accepted physics.

reviewed 2026-08-02 · how reviews work

0 comments
Cite this review

Pith. "Pith review of Coloring Black Holes: Epistemic and Aesthetic Choices in Astronomical Imaging." pith.science (2026). https://pith.science/paper/HF56EUF3

@misc{pith2026260714928,
  author       = {Pith},
  title        = {Pith review of: Coloring Black Holes: Epistemic and Aesthetic Choices in Astronomical Imaging},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/HF56EUF3}},
  note         = {Machine review of arXiv:2607.14928}
}
Share X Bluesky LinkedIn Reddit HN
read the original abstract

In 2019, the first image of a black hole's shadow based on observation was released by the Event Horizon Telescope Collaboration (EHT). This paper shows that despite the EHT's emphasis on a single image as its final result, there were countless plausible ways of rendering the data, among which researchers could not easily choose. To obtain a single image from the extremely noisy and sparse data, it was necessary to select one of multiple plausible approaches, or to average the results from different approaches, at each stage of data processing. We examine the epistemic and aesthetic choices involved at various stages, and explore what the images would have looked like if the EHT had made different choices. We suggest that the most valuable evidence produced by the EHT comes not from the single image it ultimately advertised as its central result, but from the demonstration of the limited variability that emerged from the specific choices made.

Figures

Figures reproduced from arXiv: 2607.14928 by Emilie Skulberg, Jeroen van Dongen, Rodrigo Ochigame.

Figure 1
Figure 1. Figure 1: The first image of the shadow of a black hole (M87*) on the basis of observation. Credit: Event Horizon Telescope Collaboration. treatment, imaging, and image presentation. This paper unpacks this process and analyzes the steps in the making of [PITH_FULL_IMAGE:figures/full_fig_p002_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Diagram of different stages of data processing in the making of the EHT image of M87*. It serves as a visual index of the sections in this paper. The stages are numbered and labeled with the corresponding sections, and color-coded using the “vibrant” scheme by Paul Tol, which is designed for accessibility to viewers with color vision deficiency. not always happen sequentially. Some of it happened simultane… view at source ↗
Figure 3
Figure 3. Figure 3: Diagram of a VLBI array. Incoherent signals from an extended astronomical radio source are measured at (in this diagram) three sites, and their times of arrival are accurately recorded. Using the distance between them, one can establish the correlations between the signals at the various sites. By using the van Cittert–Zernike theorem from the optics of extended sources, these measurements allow a reconstr… view at source ↗
Figure 4
Figure 4. Figure 4: Eight stations of the EHT 2017 campaign over six geographic locations as viewed from the equatorial plane. Source: EHT (2019b, 3). inferences involved in constructing an image from extremely noisy and sparse VLBI data. For the EHT’s 2017 observation campaign that produced the image of M87*, photons from radio wave fronts (1.3 mm wavelength) were observed during long sessions on April 5, 6, 10, and 11, 2017… view at source ↗
Figure 5
Figure 5. Figure 5: Correlator at the MIT Haystack Observatory, 2018. Photo: Emilie Skulberg. as input, this stage is essential to make raw data into possible signals from which noise can be filtered. The correlation stage involves not only specialized software but also, in some cases, specialized hardware. From the earliest days of radio astronomy, the correlation of interfer￾ometric signals typically relied on computers (kn… view at source ↗
Figure 6
Figure 6. Figure 6: Preview of an animated demonstration of the CLEAN algorithm, based on the EHT’s script for the Difmap software. The animation shows the “dirty” or “residual” image (left) and the “clean” image (right) of M87* at successive steps of the algorithm, spanning 1,300 iterations. This still frame shows an early step, after 100 iterations, and illustrates how the algorithm represents the sky as a collection of poi… view at source ↗
Figure 7
Figure 7. Figure 7: Example of image reconstructions in an Imaging Challenge. In this data set, the original “truth image” (above, shown in two color maps) was a black hole simulation by Hotaka Shiokawa; see Shiokawa (2013). The smaller images below are image reconstructions. Columns of image reconstructions in two color maps were shown, with the creators and methods listed below. For example, the first column from the left w… view at source ↗
Figure 8
Figure 8. Figure 8: The top image of a snowman is the “truth image” in two color maps, and the reconstruc￾tions of the image are below (as in [PITH_FULL_IMAGE:figures/full_fig_p019_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: Members of the EHT Imaging Group during a “blind comparison” during the first imaging workshop, which took place from October 10 to 13, 2017. Courtesy of Chi-kwan Chan. the aim of improving reliability and avoiding bias. The EHT’s use of “blindness”—hiding target images during the Imaging Challenges, and each team’s results from the others—fell closer to LIGO’s sense of concealed knowledge than to the LHC’… view at source ↗
Figure 10
Figure 10. Figure 10: Geometric shapes used as “truth images,” alongside reconstructions by different algo￾rithms. Source: EHT (2019e, 16). were no previous trusted images of black holes. In the absence of conventional “ground truth” data, the EHT tested its algorithms and parameters on synthetic data. First, the researchers generated a set of synthetic images, including geometric shapes and GRMHD simulations. Then, they produ… view at source ↗
Figure 11
Figure 11. Figure 11: Preview of an interactive demonstration of parameter choices for an RML algorithm, based on the software package eht-imaging. Following the EHT’s “parameter survey,” it samples seven parameters, totaling 37,500 possible combinations. We computed the images for all combi￾nations in advance; the demonstration displays these precomputed results rather than running the algorithm live. The interactive version,… view at source ↗
Figure 12
Figure 12. Figure 12: Reconstructions of M87* by three different algorithms for each of the observing days in April 2017. Source: EHT (2019e, 21). terplay of observational and simulated data at many stages, the resulting images would not be possible—though, as we will see, not all uses of simulations are equally consequential.67 In April 2023, four years after the original M87* publication, four EHT researchers pub￾lished a ne… view at source ↗
Figure 13
Figure 13. Figure 13: New reconstructions of M87* made using the machine-learning-based PRIMO algorithm in 2023 (center and right), compared with the EHT’s image from 2019 (left). Source: Medeiros et al. (2023b, 2). holes if it was generated by a model trained on simulations that already assume black holes? The PRIMO authors sought to address such worries in various ways. They presented their algorithm as complementary to, and… view at source ↗
Figure 14
Figure 14. Figure 14: Anton Pannekoek’s “mean subjective image”: as a photograph of the Milky Way offered too much resolution, which loses vital information, Pannekoek made a naturalistic drawing of a region of the northern Milky Way (left), of which he then made an isophotic map (center). After doing the same for drawings made by other observers, he then averaged over these isophotic maps, to finally produce the “mean subject… view at source ↗
Figure 15
Figure 15. Figure 15: The M87* image in alternative color maps. These images were generated by recoloring the final published image using color maps from the EHT’s software. The blue (top right) and grayscale (bottom left) color maps were among the 196 options that were custom-made for the EHT by a group led by Chi-kwan Chan and Lia Medeiros. The “viridis” map (top left) is the default option in the matplotlib software package… view at source ↗
Figure 16
Figure 16. Figure 16: Heat map of temperature fluctuations in the cosmic microwave background, based on nine years of Wilkinson Microwave Anisotropy Probe data (2012). It uses the rainbow color map. Credit: NASA. • Rainbow. The rainbow color map varies hue instead of brightness or luminosity. It is widely used for scientific visualization in many fields, from oceanography to neurobi￾ology.81 In cosmology, the rainbow color map… view at source ↗

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

141 extracted references

  1. [1]

    Ades, Rachel , date =

  2. [2]

    Akiyama, Kazunori and Tazaki, Fumie and Moriyama, Kotaro and Cho, Ilje and Ikeda, Shiro and Sasada, Mahito and Okino, Hiroki and Honma, Mareki , year =

  3. [3]

    PBS NewsHour , url =

    Akpan, Nsikan , date =. PBS NewsHour , url =

  4. [4]

    Nature Astronomy , volume =

    Arras, Philipp and Frank, Philipp and Haim, Philipp and Knollm. Nature Astronomy , volume =. 2022 , title =

    2022

  5. [5]

    2023 , title =

    Baneke, David , editor =. 2023 , title =

    2023

  6. [6]

    Science, Technology, & Human Values , volume =

    Baneke, David , year =. Science, Technology, & Human Values , volume =

  7. [7]

    1973 , title =

    Bardeen, James M , editor =. 1973 , title =

    1973

  8. [8]

    and Fish, Vincent L

    Blackburn, Lindy and Chan, Chi-kwan and Crew, Geoffrey B. and Fish, Vincent L. and Issaoun, Sara and Johnson, Michael D. and Wielgus, Maciek and Akiyama, Kazunori and Barrett, John and Bouman, Katherine L. , year =. The Astrophysical Journal , volume =

  9. [9]

    Nature Astronomy , volume =

    Blum, Alexander and Lalli, Roberto and Renn, J. Nature Astronomy , volume =. 2018 , title =

    2018

  10. [10]

    Philosophy of Science , volume =

    Bokulich, Alisa , year =. Philosophy of Science , volume =

  11. [11]

    Synthese , volume =

    Bokulich, Alisa , year =. Synthese , volume =

  12. [12]

    2020 , title =

    Bonolis, Luisa and Leon, Juan-Andres , editor =. 2020 , title =

    2020

  13. [13]

    and Johnson, Michael D

    Bouman, Katherine L. and Johnson, Michael D. and Zoran, Daniel and Fish, Vincent L. and Doeleman, Sheperd S. and Freeman, William T. , year =

  14. [14]

    , year =

    Bouman, Katherine L. , year =

  15. [15]

    , year =

    Bowker, Geoffrey C. , year =

  16. [16]

    Philosophy of Science , volume =

    Boyd, Nora Mills , year =. Philosophy of Science , volume =

  17. [17]

    and Gold, Roman and Karami, Mansour and Preciado-L

    Broderick, Avery E. and Gold, Roman and Karami, Mansour and Preciado-L. The Astrophysical Journal , volume =. 2020 , title =

    2020

  18. [18]

    Osiris , volume =

    Capshew, James H and Rader, Karen A , year =. Osiris , volume =

  19. [19]

    and Thyagarajan, Nithyanandan , year =

    Carilli, Chris L. and Thyagarajan, Nithyanandan , year =. The Astrophysical Journal , volume =

  20. [20]

    Les trous noirs, maelstr

    Carter, Brandon and Luminet, Jean-Pierre , year =. Les trous noirs, maelstr. La Recherche , volume =

  21. [21]

    Nature , volume =

    Castelvecchi, Davide , year =. Nature , volume =

  22. [22]

    and Bouman, Katherine L

    Chael, Andrew A. and Bouman, Katherine L. and Johnson, Michael D. and Narayan, Ramesh and Doeleman, Sheperd S. and Wardle, John F. C. and Blackburn, Lindy L. and Akiyama, Kazunori and Wielgus, Maciek and Chan, Chi-kwan and Farah, Joseph R. and Palumbo, Daniel and Pesce, Dominic , year =

  23. [23]

    Chael, Andrew Alan , year =

  24. [24]

    Chan, Chi-kwan and Medeiros, Lia , year =

  25. [25]

    Chang, Hasok , year =

  26. [26]

    Charbonneau, Rebecca , year =

  27. [27]

    Science , doi =

    Clery, Daniel , date =. Science , doi =

  28. [28]

    Collins, Harry , year =

  29. [29]

    The Astrophysical Journal , volume =

    Cunningham, Christopher Thomas and Bardeen, James M , year =. The Astrophysical Journal , volume =

  30. [30]

    2011 , title =

    Daston, Lorraine and Lunbeck, Elizabeth , editor =. 2011 , title =

    2011

  31. [31]

    Daston, Lorraine and Galison, Peter , year =

  32. [32]

    and Callanan, Maureen A

    DeJesus, Jasmine M. and Callanan, Maureen A. and Solis, Graciela and Gelman, Susan A. , year =. Proceedings of the National Academy of Sciences , volume =

  33. [33]

    and Tingay, S

    Deller, Adam T. and Tingay, S. J. and Bailes, M. and West, C. , year =. Publications of the Astronomical Society of the Pacific , volume =

  34. [34]

    Social Studies of Science , volume =

    de Swart, Jaco and Mol, Annemarie , year =. Social Studies of Science , volume =

  35. [35]

    Philosophy of Physics , volume =

    Doboszewski, Juliusz and Elder, Jamee , year =. Philosophy of Physics , volume =

  36. [36]

    Philosophy of Science , volume =

    Doboszewski, Juliusz and Elder, Jamee , year =. Philosophy of Science , volume =

  37. [37]

    L'image scientifique: De la visualisation

    Dondero, Maria Giulia , year =. L'image scientifique: De la visualisation. Nouveaux Actes S

  38. [38]

    Les images anachroniques de l'histoire de l'univers , journal =

    Dondero, Maria Giulia , year =. Les images anachroniques de l'histoire de l'univers , journal =

  39. [39]

    Dondero, Maria Giulia and Fontanille, Jacques , year =

  40. [40]

    Dondero, Maria Giulia , year =. S. Signata. Annales des s

  41. [41]

    Nuncius , volume =

    Doran, Connemara , year =. Nuncius , volume =

  42. [42]

    Dumit, Joseph , year =

  43. [43]

    , year =

    Edwards, Paul N. , year =

  44. [44]

    Studies in History and Philosophy of Science Part A , volume =

    Elder, Jamee , year =. Studies in History and Philosophy of Science Part A , volume =

  45. [45]

    Enander, Jonas , year =

  46. [46]

    2019 , title =

    The Astrophysical Journal Letters , volume =. 2019 , title =

    2019

  47. [47]

    2022 , title =

    The Astrophysical Journal Letters , volume =. 2022 , title =

    2022

  48. [48]

    The Astrophysical Journal Letters , volume =

    Falcke, Heino and Melia, Fulvio and Agol, Eric , year =. The Astrophysical Journal Letters , volume =

  49. [49]

    Fiala, Mark , year =. 2005

    2005

  50. [50]

    Physics in Perspective , volume =

    Franklin, Allan David , year =. Physics in Perspective , volume =

  51. [51]

    Synthese , volume =

    Frigg, Roman and Reiss, Julian , year =. Synthese , volume =

  52. [52]

    1988 , title =

    Galison, Peter and Assmus, Alexi , editor =. 1988 , title =

    1988

  53. [53]

    Galison, Peter , date =

  54. [54]

    Galison, Peter , year =

  55. [55]

    MoMA Magazine , url =

    Galison, Peter , date =. MoMA Magazine , url =

  56. [56]

    Galison, Peter and Doboszewski, Juliusz and Elder, Jamee and Martens, Niels C. M. and Ashtekar, Abhay and Enander, Jonas and Gueguen, Marie and Kessler, Elizabeth A. and Lalli, Roberto and Lesourd, Martin and Marcoci, Alexandru and. Galaxies , volume =. 2023 , title =

    2023

  57. [57]

    Antikythera: Journal for the Philosophy of Planetary Computation , doi =

    Galison, Peter , date =. Antikythera: Journal for the Philosophy of Planetary Computation , doi =

  58. [58]

    Gamwell, Lynn , year =

  59. [59]

    BBC News , url =

    Ghosh, Pallab , date =. BBC News , url =

  60. [60]

    Goddi, Ciriaco and Crew, Geoff and Impellizzeri, Violette and Marti-Vidal, Ivan and Matthews, Lynn D. and Messias, Hugo and Rottmann, Helge and Alef, Walter and Blackburn, Lindy and Bronzwaer, Thomas and Chan, Chi-kwan and Davelaar, Jordy and Deane, Roger and Dexter, Jason and Doeleman, Shep and Falcke, Heino and Fish, Vincent L. and Fraga-Encinas, Raquel...

  61. [61]

    Physical Review D , volume =

    Godfrey, Brendan B , year =. Physical Review D , volume =

  62. [62]

    South Atlantic Quarterly , volume =

    Goodyear-Kaʻ. South Atlantic Quarterly , volume =. 2017 , title =

    2017

  63. [63]

    and Holz, Daniel E

    Gralla, Samuel E. and Holz, Daniel E. and Wald, Robert M. , year =. Physical Review D , volume =

  64. [64]

    , year =

    Gralla, Samuel E. , year =. Physical Review D , volume =

  65. [65]

    Philosophy of Science , volume =

    Gueguen, Marie , year =. Philosophy of Science , volume =

  66. [66]

    2021 , title =

    Helmreich, Stefan , editor =. 2021 , title =

    2021

  67. [67]

    Native American and Indigenous Studies , volume =

    Hobart, Hiʻilei , year =. Native American and Indigenous Studies , volume =

  68. [68]

    Hoddeson, Lillian and Kolb, Adrienne W and Westfall, Catherine , year =

  69. [69]

    Astronomy and Astrophysics Supplement Series , volume =

    H. Astronomy and Astrophysics Supplement Series , volume =. 1974 , title =

    1974

  70. [70]

    Humphreys, Paul , year =

  71. [71]

    and Kettenis, Mark and Small, Des and Liuzzo, Elisabetta and Rygl, Kazi and Mart

    Janssen, Michael and Goddi, Ciriaco and van Bemmel, Ilse M. and Kettenis, Mark and Small, Des and Liuzzo, Elisabetta and Rygl, Kazi and Mart. Astronomy & Astrophysics , volume =. 2019 , title =

    2019

  72. [72]

    Kennefick, Daniel , year =

  73. [73]

    , year =

    Kessler, Elizabeth A. , year =

  74. [74]

    , editor =

    Kessler, Elizabeth A. , editor =. 2011 , title =

    2011

  75. [75]

    , year =

    Kessler, Elizabeth A. , year =. Technology and Culture , volume =

  76. [76]

    De wetenschap heeft bij mij nooit eerste prioriteit

    Keulen, Jean-Paul , year =. De wetenschap heeft bij mij nooit eerste prioriteit. Interview met. Nederlands Tijdschrift voor Natuurkunde , volume =

  77. [77]

    Annual Review of Nuclear and Particle Science , volume =

    Klein, Joshua R and Roodman, Aaron , year =. Annual Review of Nuclear and Particle Science , volume =

  78. [78]

    2023 , title =

    Koay, Jun Yi and Romero-Ca. 2023 , title =

    2023

  79. [79]

    Journal of

    Kragh, Helge , year =. Journal of

  80. [80]

    2023 , title =

    Kragh, Helge , editor =. 2023 , title =

    2023

Showing first 80 references.

This paper was first reviewed by deepseek-v4-flash on August 2, 2026.