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A size-dependent low-angular-momentum bias can reproduce the observed encounter rates of kilometer-scale interstellar objects such as 3I/ATLAS.

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A size-dependent low-angular-momentum anisotropy, fitted to the observed detection rates, can reproduce the encounter rate of large interstellar objects such as 3I/ATLAS.

T0 review reviewed 2026-08-04 challenge →

load-bearing objection A readable proof-of-concept that maps ISO encounter-rate enhancements onto low-angular-momentum biases, but the size-dependent weighting is fitted, so the k(R) curve is not a dynamical prediction. the 3 major comments →

arxiv 2509.06300 v1 pith:Y7Y6E266 submitted 2025-09-08 astro-ph.EP astro-ph.GAastro-ph.IMastro-ph.SR

Dynamical Constraints on a Population of Massive Interstellar Objects

Oem Trivedi , Abraham Loeb This is my paper
classification astro-ph.EP astro-ph.GAastro-ph.IMastro-ph.SR
keywords interstellar objects3I/ATLASencounter rateEddington inversionLiouville mappinggravitational focusingangular momentum anisotropysize distribution
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

Large interstellar objects are being detected far more often than a simple Maxwellian velocity distribution would predict. This paper builds a dynamical framework to test whether that excess can be explained without invoking exotic origins. It shows that an encounter-rate model normalized to 3I/ATLAS demands flux enhancements that grow steeply with object size, and then uses Liouville's theorem to map an interstellar Maxwellian distribution inward, showing that a size-dependent bias toward low-angular-momentum orbits can reproduce the observed rise in detection rate. The central result is a monotonic enhancement slope k(R) that reaches about 4 at R=10 km. The catch is that the calculation assumes such a bias exists; the paper does not identify a natural mechanism that would produce it, which leaves the artificial-origin hypothesis in play.

Core claim

The paper's central claim: observed detection rates of kilometer-scale ISOs can be matched by gravitational dynamics alone, provided the incoming population is anisotropic in angular momentum. A brightness-limited cross section plus a power-law size distribution gives a cumulative rate Γ1(R) ∝ R^{-(q-2)}; normalized to 3I/ATLAS, objects at R~10 km require an enhancement of (R/0.6)^{q-2} over a Maxwellian background. Liouville mapping in (E,J) space propagates an interstellar Maxwellian inward, and a weighting g_R(J) suppressing high-angular-momentum orbits more strongly for larger objects yields a local density slope k(R) rising monotonically from 0 at R=0.6 km to about 4 at R=10 km. The aut

What carries the argument

The central object is the Liouville mapping in the space of specific energy E and specific angular momentum J. An isotropic Maxwellian at the interstellar boundary (r_out ~ 10^5 AU) is propagated inward using conservation of E and J, with radial velocity v_r = sqrt(2(E+GM/r) - J^2/r^2) fixing the accessible region. Size dependence enters through a weighting g_R(J) = (1 - J/J_0(R))^{a(R/R_0-1)} for J ≤ J_0(R), with cutoff J_0(R) = J_{0,base} (R/R_0)^{-s}; larger R suppresses high-J orbits more. The machinery converts a chosen angular-momentum anisotropy into a local radial density slope k(R) comparable to the required encounter-rate enhancement.

Load-bearing premise

The load-bearing premise is the assumed size-dependent angular-momentum weighting: larger interstellar objects are taken to preferentially arrive on low-angular-momentum orbits, in a functional form chosen to reproduce the observed detection rates, and the paper identifies no astrophysical mechanism that would produce such a bias. If the true population is isotropic in angular momentum, the Liouville mapping does not yield the observed size-dependent rates.

What would settle it

Observation: for a sample of ISOs with measured incoming velocities, compare the angular-momentum distribution of objects with R > 10 km against those near R = 0.6 km; a monotonic rise in k(R) requires a measurable deficit of high-J orbits among the larger objects, so an isotropic J distribution would falsify the model. Calculation: propagate an isotropic Maxwellian through the same Liouville mapping; it yields k(R)=0, so any observed monotonic rise beyond errors rules out the no-bias case.

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

If this is right

  • Detections of ISOs with radii of tens of kilometers require encounter-rate enhancements of orders of magnitude over a Maxwellian background, and the required enhancement grows steeply with the size-distribution slope q.
  • Steep radial density profiles ρ(r) ∝ r^{-k} imply phase-space distributions concentrated on radial, low-angular-momentum orbits, so gravitational focusing can in principle supply the inward bias.
  • A Liouville mapping from the interstellar boundary inward, conserving E and J, produces a smooth monotonic k(R) rising from 0 at R=0.6 km to about 4 at R=10 km, matching the size-dependent detection rate.
  • R ≳ 10 km ISOs are dynamically consistent with strong gravitational focusing only under specific velocity-space biases whose natural astrophysical origin is unknown.
  • The framework sharpens the natural-versus-artificial distinction: the required anisotropy can be tuned to fit observations, but with no known astrophysical source the artificial-origin scenario remains viable.

Where Pith is reading between the lines

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

  • Editorial extension: if the angular-momentum bias g_R(J) is real, future surveys that measure incoming velocities should find a measurable deficit of high-J orbits among objects larger than a few kilometers; the absence of such a deficit would falsify the model.
  • Editorial extension: the same Liouville machinery could be run independently on each size bin as the sample grows, testing whether the fitted anisotropy amplitude a stays constant or drifts; drift would mean the bias is absorbing uncertainty in the size-distribution slope q rather than a physical effect.
  • Editorial extension: because the paper identifies no natural production mechanism for the low-J bias, the cleanest discriminator between natural and artificial origins is ejection modeling — if planetary ejection produces size-independent angular momentum, the bias must be imposed after ejection, pointing to Galactic environmental effects or engineered orbits.
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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

3 major / 5 minor

Summary. The manuscript combines three analytical tools to interpret the observed encounter of large interstellar objects, with 3I/ATLAS as the motivating example. Section 2 derives a cumulative encounter-rate scaling Γ1(R) ∝ R^{-(q-2)} from a brightness-limited detection cross section and a power-law size distribution, normalizing to Γ1(0.6)=0.2 yr^-1 from Loeb (2025). Section 3 uses Eddington inversion to show that a power-law density profile ρ(r) ∝ r^{-k} corresponds to f(E) ∝ E^{k-3/2}. Section 4 constructs a Liouville mapping in (E,J) that propagates an interstellar Maxwellian inward, introducing a size-dependent angular-momentum weighting g_R(J) whose parameters are adjusted to match the required rate enhancement. The resulting curve k(R) rises monotonically from 0 at R=0.6 km to about 4 at R=10 km. The authors conclude that low-angular-momentum anisotropies can reproduce the observed size-dependent detection rates, while acknowledging that no known astrophysical mechanism produces such anisotropies.

Significance. The paper is clearly written and contains useful analytic material: the encounter-rate scaling in Section 2, the Eddington inversion result in Section 3, and the Liouville mapping framework in Section 4 are presented transparently, and the authors explicitly flag the absence of a natural mechanism for the required anisotropy. If the k(R) curve were a genuine prediction from fixed boundary conditions, the paper would significantly sharpen the natural-versus-artificial ISO debate. However, as presented, the central curve is constructed by fitting the R-dependence of the boundary weighting to the target enhancement, so the paper provides an illustrative existence proof rather than a dynamical constraint. That distinction is load-bearing for the title and abstract claims, and the current manuscript does not deliver the promised dynamical constraints.

major comments (3)
  1. [Sec. 4, Eqs. (32)-(36), Fig. 3] The size-dependence of k(R) is inserted by hand through the boundary weighting g_R(J). Both J0(R)=J0,base(R/R0)^{-s} and α(R,a)=a(R/R0-1) explicitly depend on R, and the text states that a is 'adjusted to be in agreement with the required enhancement implied by the cumulative detection rates.' Since a sufficiently flexible boundary distribution can reproduce essentially any k(R), the monotonic rise to k(10)≈4 is a property of the chosen parameterization, not a consequence of Liouville's theorem. The paper itself concedes that no known astrophysical mechanism generates such a size-dependent low-J bias. The central conclusion should be reframed as an existence proof, and the numerical values of a, J0,base, and s must be reported so that Fig. 3 is reproducible and falsifiable.
  2. [Sec. 4, Eqs. (34)-(36)] The connection between the fitted slope k(R) and the Section 2 enhancement factor is not demonstrated. Equation (36) defines k(R) as the local logarithmic slope of ρ(r;R,a) at r_max=4 AU, but no equation or algorithm is given that links this slope to Γ2/Γ1 in Eq. (18). The statement that a is calibrated to match the cumulative detection rates therefore cannot be checked. Please provide the explicit mapping, including the fitting window and the comparison between the model-predicted and target rate enhancements, or the code used to generate Fig. 3.
  3. [Sec. 2, Eq. (15)] The absolute rate normalization is fixed by a single-object estimate Γ1(0.6)=0.2 yr^-1 from Loeb (2025). This is an important assumption, not a measured population-averaged rate. Although the ratio in Eq. (18) is partly insensitive to the normalization, Fig. 1 and any quantitative interpretation of the required enhancement depend on it. A sensitivity study over plausible ranges of the 3I/ATLAS rate and the size-distribution slope q would strengthen the empirical basis of the claims.
minor comments (5)
  1. [Sec. 2, Eq. (13)] The formula for ⟨v⟩ is garbled in the typeset text. Please check the prefactor and the parentheses; the standard shifted-Maxwellian mean speed should be written explicitly.
  2. [Sec. 4, Eq. (34)] The upper limit of the J integral is written as Jmax(E,r), but earlier Jmax is defined as r_out v∞ at the outer boundary. The kinematic bound at radius r is Jcap(E,r) from Eq. (31). Please clarify the notation and use the correct minimum of the two limits.
  3. [Throughout] Several typos remain: 'We this plug' in Section 3, 'anf' in the acknowledgments, and inconsistent spacing in equations. A careful proofread is needed.
  4. [Sec. 3, Fig. 2] The comparison of f(v=30 km/s,r) from Eddington inversion with a Maxwellian f(v) at v=30 km/s is illustrative, but the shifted-Maxwellian background is not normalized to the same total density. State explicitly that the comparison is only relative and that no absolute normalization is implied.
  5. [Sec. 4, Eq. (32)] For R=R0, α=0 and g_R(J) is flat; for R>R0, α>0 and J0 decreases. This parameterization essentially guarantees a monotonic increase in low-J bias with R. The paper should state this structural property explicitly rather than presenting the monotonicity as a dynamical discovery.

Circularity Check

2 steps flagged

The size-dependent weighting g_R(J) (Eqs. 32-33) is fitted to the required enhancement (Eq. 18), so the monotonic k(R) is an input to the Liouville map, not a dynamical prediction.

specific steps
  1. fitted input called prediction [Sec 4, Eqs (32)-(36), paragraph 'We then adjust the anisotropy amplitude a...']
    "The family of functions we employed has the form g_R(J)∝(1−J/J0(R))^{α(R,a)} for J≤J0(R), ... J0(R)=J0,base(R/R0)^{−s}, while the exponent is taken as α(R,a)=a(R/R0−1), where a is a tunable anisotropy amplitude calibrated to match the observational constraints. ... We then adjust the anisotropy amplitude a to be in agreement with the required enhancement implied by the cumulative detection rates and once a is fixed, the function k(R) follows uniquely from the dynamics."

    The only size-dependent ingredient in the Liouville map is this g_R(J). Its cutoff J0(R) shrinks and its exponent α(R,a) grows with R, so larger objects are assigned stronger low-angular-momentum biases by ansatz. The parameter a is then explicitly 'calibrated' and 'adjusted to be in agreement with the required enhancement implied by the cumulative detection rates'—i.e., the enhancement factor Γ2/Γ1=(R/0.6)^{q-2} of Eq. (18). Eq. (36) then extracts k(R) from ρ(r;R,a), which is itself built from the fitted g_R. A flat or size-independent g_R would give k(R)=0; the monotonic rise to k(10)≈4 is therefore inherited from the fitted forms, not generated by Liouville's theorem.

  2. self definitional [Sec 4, Fig. 3 discussion and Sec 5 Conclusions]
    "within a physically consistent Liouville mapping in E,J space, one can in fact generate the necessary enhancement in the encounter rate with increasing object size purely by favoring low-angular momentum orbits."

    This central conclusion is true by construction: the 'favoring' is inserted as the R-dependent g_R(J) of Eqs. (32)-(33), and the amplitude is tuned so that k(R) matches the required enhancement. Liouville's theorem conserves phase-space density along unbound orbits; it does not restrict the boundary weighting. Because α(R,a)=a(R/R0−1) grows with R and J0(R)=J0,base(R/R0)^{−s} shrinks with R, the monotonic rise of k(R) is built into the function family itself. The paper concedes 'there is still no known astrophysical mechanism that would actually generate such a distribution,' confirming that the size-dependent bias is an unconstrained input, not a derived outcome. Thus the result is an existence proof for an arbitrary fitted weighting, not a dynamical constraint on the real ISO population.

full rationale

The paper has independent, non-circular parts: the encounter-rate scaling in Sec 2 and the Eddington inversion in Sec 3 are standard calculations, and the Liouville mapping of a given boundary distribution is a legitimate dynamical propagation. However, the paper's headline result—that low-angular-momentum anisotropies can reproduce the observed size-dependent detection rates—reduces by construction to the fitted function g_R(J). Both the cutoff scale J0(R) and the exponent α(R,a) carry explicit R-dependence chosen so that larger objects are more strongly biased toward low J, and a is explicitly 'adjusted to be in agreement with the required enhancement implied by the cumulative detection rates.' Hence the monotonic k(R) curve in Fig. 3 is the output of a parameterized fit, not a prediction from dynamics. The normalization Γ1(0.6)=0.2 yr^{-1} taken from Loeb (2025) is a self-citation, but it is anchored to the observed 3I/ATLAS encounter and only sets the zero point of k(R); it is not the source of the circularity. The absence of reported values for J0,base, s, and a additionally makes Fig. 3 impossible to reproduce or falsify, but that is a reproducibility concern rather than circularity. Overall the central claim is circular in the 'fitted input called prediction' sense, though the surrounding framework contains independent material; score 7.

Axiom & Free-Parameter Ledger

4 free parameters · 7 axioms · 0 invented entities

The central curve in Figure 3 is produced by the fitted weighting function g_R(J). The physical content lies in the Liouville propagation, but the constraints come from the inputs.

free parameters (4)
  • anisotropy amplitude a = not reported
    Tuned to match the required enhancement implied by the cumulative detection rates (Sec 4).
  • angular momentum cutoff J_0,base = not reported
    Sets the scale of the suppression in g_R(J); value not given.
  • size-slope exponent s = not reported
    Controls how J_0(R) shrinks with object radius; value not given.
  • size distribution slope q = not fitted; range explored
    Assumed power law in dN/dR; the enhancement factor scales as R^{-(q-2)}.
axioms (7)
  • standard math Liouville's theorem conserves phase-space density along collisionless orbits
    Used in Sec 4 to map the distribution from r_out to r_max.
  • domain assumption ISO trajectories follow two-body Keplerian motion in the Sun's potential GM/r
    Inherited from the potential in Eq (19) and used for E and J conservation.
  • domain assumption The velocity distribution at infinity is an isotropic Maxwellian
    Eq (28) and the text 'we adopt an isotropic Maxwellian'.
  • domain assumption The size distribution is a power law dN/dR proportional to R^{-q}
    Eq (7).
  • domain assumption Detection cross-section scales as R via brightness-limited r_max proportional to R^{1/2}
    Eqs (5)-(6).
  • standard math Eddington inversion formula applies to the assumed density profile
    Eq (20) from Binney & Tremaine, though the authors later state it presumes a bound isotropic population, making it illustrative.
  • ad hoc to paper The weighting function has the form g_R(J) with the chosen R-dependence
    Eq (32)-(33), chosen specifically to make the model match observations.

reviewed 2026-08-04 · how reviews work

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Cite this review

Pith. "Pith review of Dynamical Constraints on a Population of Massive Interstellar Objects." pith.science (2026). https://pith.science/paper/Y7Y6E266

@misc{pith2026250906300,
  author       = {Pith},
  title        = {Pith review of: Dynamical Constraints on a Population of Massive Interstellar Objects},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/Y7Y6E266}},
  note         = {Machine review of arXiv:2509.06300}
}
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read the original abstract

We investigate dynamical constraints on the population of large interstellar objects (ISOs) by combining encounter rate analysis, Eddington inversion, and Liouville mapping. Encounter rate scaling demonstrates that detections of kilometer-scale ISOs require flux enhancements beyond natural Maxwellian expectations. Using Eddington inversion, we show how steep density profiles imply phase-space biases consistent with strong gravitational focusing and we then develop a Liouville mapping formalism that propagates the interstellar velocity distribution inward under conservation of energy and angular momentum, revealing that low-angular momentum anisotropies can reproduce the observed size dependent detection rates. These results provide a self consistent dynamical framework for interpreting the observed population of ISOs and for assessing whether the required anisotropies arise from natural or artificial origins. The main results are framed in the context of the parameters for 3I/ATLAS, but the implications are general and go on to sharpen the distinction between natural dynamical mechanisms and potential artificial origins for ISOs.

Figures

Figures reproduced from arXiv: 2509.06300 by Abraham Loeb, Oem Trivedi.

Figure 1
Figure 1. Figure 1: Cumulative encounter rate enhancement factor as a function of minimum ISO radius R for different power-law slopes q, showing the steep increase in required enhancement for larger objects. The adopted parameters reflect representative values for 3I/ATLAS. distribution and the average velocity derived from the velocity distribution. To determine the proportionality constant k, we use the re￾sult from Loeb (2… view at source ↗
Figure 2
Figure 2. Figure 2: Comparison of Eddington-inverted phase-space densities for k = 3, 3.5, 4 with a shifted Maxwellian background. different power-law density profiles alongside the value expected from a shifted Maxwellian background f(v) ∝ v 2 exp − v 2 2σ2 ! . (28) Adopting for Sun’s velocity relative to the Local Standard of Rest v = 30 km/s and σ = 25 km/s yields f(v) ∼ 167.56 (km/s)−1 . Note that this is just the backgro… view at source ↗
Figure 3
Figure 3. Figure 3: k(R) as a function of ISO radius R, taking into account Liouville mapping formalism k(R) shows a smooth, monotonic rise from zero at R = 0.6 km to k(10) ≈ 4 at R = 10 km. We can extend it to R = 23km for the very large size mentioned in Lisse et al. (2025), but the trend remains the same. Physically, this curve quantifies how a bias toward low angular momentum trajectories, consistent with Liouville’s theo… view at source ↗

discussion (0)

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Reference graph

Works this paper leans on

24 extracted references · 17 canonical work pages · 1 internal anchor

  1. [1]

    & Loeb, A

    Bialy, S. & Loeb, A. 2018, The Astrophysical Journal Letters, 868, L1

    work page 2018

  2. [2]

    & Tremaine, S

    Binney, J. & Tremaine, S. 2011, Galactic dynamics (Princeton university press)

    work page 2011

  3. [3]

    W., Drlica-Wagner, A., et al

    Blum, B., Digel, S. W., Drlica-Wagner, A., et al. 2022, arXiv preprint arXiv:2203.07220 De La Fuente Marcos, R., Alarcon, M., Licandro, J., et al. 2025, Astronomy & Astrophysics, 700, L9

    Pith/arXiv arXiv 2022

  4. [4]

    Interstellar Objects in the Solar System: 1. Isotropic Kinematics from the Gaia Early Data Release 3

    Eubanks, T. M., Hein, A. M., Lingam, M., et al. 2021, arXiv preprint arXiv:2103.03289

    work page internal anchor Pith review Pith/arXiv arXiv 2021

  5. [5]

    Forbes, J. C. & Loeb, A. 2019, The Astrophysical Journal Letters, 875, L23

    work page 2019

  6. [6]

    2020, Nature Astronomy, 4, 53

    Guzik, P., Drahus, M., Rusek, K., et al. 2020, Nature Astronomy, 4, 53

    work page 2020

  7. [7]

    2025, arXiv preprint arXiv:2507.12213

    Hibberd, A., Crowl, A., & Loeb, A. 2025, arXiv preprint arXiv:2507.12213

    arXiv 2025

  8. [8]

    J., Dorsey, R

    Hopkins, M. J., Dorsey, R. C., Forbes, J. C., et al. 2025b, arXiv preprint arXiv:2507.05318

    Pith/arXiv arXiv

  9. [9]

    2025, The Astro- physical Journal Letters, 990, L2

    Jewitt, D., Hui, M.-T., Mutchler, M., Kim, Y ., & Agarwal, J. 2025, The Astro- physical Journal Letters, 990, L2

    work page 2025

  10. [10]

    2020, Monthly Notices of the Royal Astronomical Society, 499, 1250

    Kohandel, M., Pallottini, A., Ferrara, A., et al. 2020, Monthly Notices of the Royal Astronomical Society, 499, 1250

    work page 2020

  11. [11]

    2018, Journal of Cosmology and Astroparti- cle Physics, 2018, 040

    Lacroix, T., Stref, M., & Lavalle, J. 2018, Journal of Cosmology and Astroparti- cle Physics, 2018, 040

    work page 2018

  12. [12]

    1959, in Astrophysik IV: Sternsysteme/Astrophysics IV: Stellar Systems (Springer), 21–99 Article number, page 5 of 6 A&A proofs:manuscript no

    Lindblad, B. 1959, in Astrophysik IV: Sternsysteme/Astrophysics IV: Stellar Systems (Springer), 21–99 Article number, page 5 of 6 A&A proofs:manuscript no. aanda

    work page 1959

  13. [13]

    2025, arXiv preprint arXiv:2508.15469

    Lisse, C., Bach, Y ., Bryan, S., et al. 2025, arXiv preprint arXiv:2508.15469

    Pith/arXiv arXiv 2025

  14. [14]

    2022, Astrobiology, 22, 1392

    Loeb, A. 2022, Astrobiology, 22, 1392

    work page 2022

  15. [15]

    2025, Research Notes of the AAS, 9, 178

    Loeb, A. 2025, Research Notes of the AAS, 9, 178

    work page 2025

  16. [16]

    2025, arXiv preprint arXiv:2507.21402

    Loeb, A., Hibberd, A., & Crowl, A. 2025, arXiv preprint arXiv:2507.21402

    arXiv 2025

  17. [17]

    J., Weryk, R., Micheli, M., et al

    Meech, K. J., Weryk, R., Micheli, M., et al. 2017, Nature, 552, 378

    2017

  18. [18]

    1988, Celestial mechanics, 45, 19

    Miller, R. 1988, Celestial mechanics, 45, 19

    work page 1988

  19. [19]

    J., Adams, F

    Napier, K. J., Adams, F. C., & Batygin, K. 2021, The Planetary Science Journal, 2, 53 Peñarrubia, J. 2023, Monthly Notices of the Royal Astronomical Society, 519, 1955

    work page 2021

  20. [20]

    F., Thomas, S

    Sebag, J., Claver, C. F., Thomas, S. J., et al. 2020, in Ground-based and Airborne Telescopes VIII, V ol. 11445, SPIE, 396–415

    work page 2020

  21. [21]

    Z., Micheli, M., Farnocchia, D., et al

    Seligman, D. Z., Micheli, M., Farnocchia, D., et al. 2025, The Astrophysical Journal Letters, 989, L36

    work page 2025

  22. [22]

    & Loeb, A

    Siraj, A. & Loeb, A. 2019a, arXiv preprint arXiv:1904.07224

    Pith/arXiv arXiv 1904

  23. [23]

    & Loeb, A

    Siraj, A. & Loeb, A. 2022, New Astronomy, 92, 101730 Suárez, D. O., Rubio, L. B., Vögler, A., & Del Toro Iniesta, J. 2010, Astronomy & Astrophysics, 518, A2

    work page 2022

  24. [24]

    J., Barr, J., Callahan, S., et al

    Thomas, S. J., Barr, J., Callahan, S., et al. 2020, in Ground-based and Airborne Telescopes VIII, V ol. 11445, SPIE, 68–82 Article number, page 6 of 6

    work page 2020

This paper was first reviewed by deepseek-v4-flash on August 4, 2026.