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Geometrical Distances of Extragalactic Binaries through Spectroastrometry

T0 review · 2 major / 6 minor · reviewed 2026-08-11 · deepseek-v4-flash

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Pith's one-line read This paper demonstrates a purely geometric method to measure distances to extragalactic binary stars by jointly fitting spectroastrometric phase curves, radial velocities, and eclipsing light curves, recovering the distance to a typical…

desk verdict A coherent joint SA+RV+LC framework for extragalactic binary distances; the ~6% precision forecast is real but rests on a closed-loop simulation, so accuracy under real stellar physics is not yet demonstrated. read the letter →

arxiv 2412.08889 v1 pith:37DU6GNH submitted 2024-12-12 astro-ph.CO astro-ph.GAastro-ph.IMastro-ph.SR

Yu-Yang Songsheng , Jian-Min Wang , Yuan Cao , XueFei Chen , JianPing Xiong , Zhi-Xiang Zhang , Rong-Gen Cai This is my paper · ORCID
classification astro-ph.COastro-ph.GAastro-ph.IMastro-ph.SR
keywords spectroastrometrygeometricdistanceeclipsingbinariesLargeMagellanicCloudHubbletensionopticalinterferometryBayesianparameterestimationladder
topics The Hubble Tension
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

The paper aims to turn an eclipsing binary in a nearby galaxy into a self-contained geometric distance probe. It combines three observables: spectroastrometry, which measures how the binary's photocenter shifts across an absorption line; radial velocities, which set the physical velocity scale; and eclipse light curves, which fix stellar radii and the flux ratio. Fitting a parameterized binary model to simulated data, the paper finds that a typical Large Magellanic Cloud binary (2 au separation, 300 day period) yields its distance to about 6.5% when interferometric phases are measured to 0.1 degrees at spectral resolution 10,000. Across a range of data qualities and binary parameters, individual systems stay better than 10%. If real binaries behave like the model, this gives an empirical-calibration-free rung for extragalactic distances, relevant to the Hubble tension.

What carries the argument

The load-bearing observable is the spectroastrometric differential phase curve, Δφ(λ): the wavelength-resolved shift of the binary photocenter, measured as interferometric phase differences between a line wavelength and a continuum reference. Because the two stars' absorption lines are Doppler-shifted in opposite directions, the photocenter traces an S-shaped curve whose amplitude encodes the binary's angular semimajor axis a/D. The model couples this to the Keplerian orbit (Thiele-Innes projection), Gaussian rotation-plus-thermal line profiles, uniform-disk eclipses, and a Gaussian likelihood; the posterior is explored with diffusive nested sampling. The distance emerges from matching the angular orbit from spectroastrometry to the physical orbit from radial velocities.

What would settle it

Observe an eclipsing binary whose distance is already known independently (for example a Galactic system with a parallax or a cluster member with a geometric cluster distance), run the spectroastrometry-plus-radial-velocity-plus-light-curve pipeline on it, and compare the recovered distance with the known value; a discrepancy larger than the reported ~6% statistical error would show the model assumptions are biased. Alternatively, detect a spectroastrometric phase curve with clear asymmetry from wind emission and show that the symmetric model fit shifts the inferred distance.

Watch

Extended reading notes

Core claim

The central claim is that the distance D to an extragalactic binary can be measured geometrically because the spectroastrometric differential phase curve carries the angular scale of the orbit, while radial velocities carry the same orbit in physical units, and the light curve pins down the component radii and luminosity ratio. In the model, the angular photocenter offset across a line is ε(λ), and the observed differential phase is Δφ(λ) = −(2π/λ) B·[ε(λ) − ε(λ_r)], so the measured phase amplitude is proportional to angular separation a/D. The joint likelihood then constrains D, a, inclination, mass ratio, flux ratio, and stellar parameters; for the fiducial LMC binary the recovered distance is log D = 3.$940^{{+0.064}}$_{−0.065}, i.e. about 6.5% at 1σ. The paper emphasizes this is purely geometric: it uses only Keplerian dynamics and the comparison of angular and physical scales, with no empirical period-luminosity or surface brightness-color calibration.

Load-bearing premise

The load-bearing premise is that a real binary's surface brightness and line profiles follow the same uniform-disk, Gaussian-line model used to generate and fit the mock data; if limb darkening, wind emission, or line asymmetries shift the photocenter differently than the model assumes, the recovered distance carries a systematic error that this paper does not quantify.

Editorial extensions

If this is right

  • A single LMC eclipsing binary observed at 0.1-degree phase precision and R = 10,000 yields a ~6.5% geometric distance; averaging several systems would shrink the statistical error roughly as 1/√N.
  • The method is independent of Cepheid period-luminosity and surface brightness-color calibrations, offering a cross-check on the distance ladder where the Hubble tension is debated.
  • Because distance precision is set mainly by interferometric phase and line-flux errors and by spectral resolution, improvements in long-baseline optical interferometry translate directly into sharper extragalactic distances.
  • The same joint spectroastrometry-plus-radial-velocity-plus-light-curve pipeline can be applied to binaries in other nearby galaxies, not just the LMC, whenever their eclipses and lines are observable.
  • Repeated monitoring of one binary over many orbits, or measuring multiple binaries, turns individual ~6% measurements into a galaxy distance with substantially higher precision.

Reading between the lines

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

  • Beyond the paper's stated results: if the statistical floor holds, the dominant obstacle to sub-percent galaxy distances shifts from calibration to stellar astrophysics—limb darkening, line asymmetries, and wind contamination—so tests on nearby binaries of known distance become the natural next step.
  • Because D and the flux ratio ℓ are only weakly correlated in the fiducial fit, spectroastrometry itself can supply much of the angular information; this suggests the method could extend to non-eclipsing binaries if ℓ is constrained by spectral energy distribution fitting instead of eclipses.
  • The paper's sensitivity scaling implies that observational campaigns should prioritize phase precision and spectral resolution over radial-velocity or light-curve cadence, since the latter have little effect on the distance error.
  • A straightforward validation strategy, implied but not detailed in the paper, is to run the same pipeline on Galactic binaries with independent distances to measure the real-world systematic floor before committing to LMC targets.
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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

2 major / 6 minor

Summary. The paper proposes a purely geometric method for measuring distances to extragalactic eclipsing binaries by jointly fitting spectroastrometry (SA), radial velocities (RV), and light curves (LC). A parameterized binary model is constructed with Keplerian orbits projected via Thiele-Innes elements, uniform-disk stellar surfaces with Gaussian absorption lines, and analytic eclipse light-curve formulae. The authors simulate mock SA/RV/LC data for a fiducial LMC-like binary (a=2 au, P=300 d, i=87.13 deg, D=50 kpc) and fit them with a Bayesian nested-sampling algorithm, recovering the input distance with roughly 6.5% uncertainty. They then systematically vary data-quality parameters and binary parameters to map the dependence of the distance uncertainty, and they discuss the feasibility of the method with VLTI/GRAVITY+. The central claim is that, within a specified range of data quality and input parameters, individual binary systems can yield distance measurements better than 10%.

Significance. If the claimed precision is realized on real systems, this method would provide a calibration-free geometric distance anchor for the LMC and other nearby galaxies, complementing the existing SBCR-based eclipsing-binary distances and offering a new probe of the Hubble tension. The paper's strengths are the internally consistent derivation of the differential-phase observable (Eqs. 1-9), a transparent Bayesian recovery test in the fiducial case, and a broad parameter study that identifies the key sensitivities. The main limitation is that the mock data are generated from exactly the same parameterized model that is used in the likelihood, so the reported precision is statistical under an assumed model; the magnitude of model-mismatch systematics is asserted but not quantified. This gap is the principal obstacle between the demonstration and the claimed real-world capability.

major comments (2)
  1. [§3.1, §4.1] The headline result of ~6.5% distance precision is obtained from a closed-loop simulation: the mock SA, RV, and LC data in §3.1 are generated with the same uniform-disk surface-brightness model (Eq. 17), Gaussian thermal-plus-rotation line profiles (Eqs. 18-19), and analytic eclipse formulae (Eq. 21) that the likelihood (Eq. 24) assumes. This tests internal consistency, but it does not test fidelity to real binaries. The discussion of systematic errors in §4.1 quotes a ~6% difference between uniform-disk and limb-darkened angular diameters and argues this translates to <0.6% in distance because the stellar diameter is only ~10% of the orbital separation. That argument applies to the angular diameter, not to the differential-phase curve (Eq. 9), which is sensitive to the line-weighted photocenter and its variation across the line; limb darkening, line asymmetry, and wind emission can bias the measured differential phases without changing the total stellar diameter by 6%. No injection test with a different generative model is performed. Because the paper's central claim is that real LMC binaries can be measured to ~6% precision, this gap is load-bearing; please add a mismatched-model recovery test or provide a quantitative propagation of model uncertainties to D.
  2. [§4.1 and Fig. 6] The paper argues that the distance measurement is not highly reliant on the line-profile model because the projected rotational velocities, rotation-axis angles, and thermal broadenings are poorly constrained in the fiducial fit (Fig. 6). This inference is not valid: the posterior shows that these parameters are degenerate within the assumed Gaussian profile family, but a different line-profile model (e.g., non-Gaussian or asymmetric, as from winds) could shift the photocenter curve and bias D even while the parameters of the Gaussian model remain unconstrained. The breadth of the posteriors within one model family does not bound the bias from model mismatch. Please either demonstrate insensitivity to the line-profile family directly, or temper the claim that line-profile systematics are negligible.
minor comments (6)
  1. [§2.1, Eq. (12)] In the sentence after Eq. (12), "αx and αx point to the direction" should read "αx and αy point to the direction."
  2. [§2.5, Eq. (24) text] The phrase "ecplipsing light curve" in the description of Fc,i is a typo and should be "eclipsing light curve."
  3. [§3.2, Eq. (25)] The symbol σℓ is used both for the line-flux measurement error in Fig. 7 and for the uncertainty of the luminosity ratio ℓ in the text around Eq. (25); please disambiguate these two quantities.
  4. [§3.1 and §4.3] The term "UV plane" (Fig. 2 right panel and §3.1) should be "u–v plane" to avoid confusion with ultraviolet; the same applies to the abstract and Fig. 2 caption.
  5. [§4.3] The word "bightest" should be "brightest" in the paragraph following Eq. (27).
  6. [§1] The name "Paczynski" should be written "Paczyński" throughout, including the reference list.

Circularity Check

0 steps flagged · score 0.0 of 10

No circularity: distance is a free parameter recovered from mock observables, and the unquantified model-mismatch systematics are an external-validity concern, not a circular step.

full rationale

The central claim is a parameter-recovery forecast. Mock SA, RV, and LC data are generated with a fixed input distance (50 kpc, Table 1) and then fitted with a likelihood in which D is a free parameter with a log-uniform prior; the posterior recovers the input within 1 sigma. D enters the forward model through Eq. 12 as the conversion from physical orbital scale a to angular separation, and the differential phase in Eq. 9 depends on that angular scale, while a is independently constrained by the RV equations (Eqs. 14-16). No equation fixes D to its input value, and no fitted parameter is renamed as a prediction. The use of the same parameterized model for simulation and likelihood is a closed-loop self-consistency test, not a derivation that assumes its conclusion. The paper explicitly acknowledges that real binaries violate the uniform-disk and Gaussian-line assumptions and states in Section 4.1 that systematic errors are outlined rather than accurately quantified; this is a limitation in external validity, and the proposed calibration against nearby binaries is a test, not a circular justification. The only self-citation (Wang et al. 2020) appears in background context and is not load-bearing. Therefore no circular step is identified.

Assumptions & free parameters 6 free parameters · 5 assumptions · 0 invented entities

The central forecast depends on a set of chosen noise levels (phase, line flux, RV, LC) and a fiducial binary configuration; these are inputs, not fitted constants, but they directly set the quoted precision. The model assumptions are standard for simulation forecasts, yet the closed-loop nature of using the same generative and fitting model is the most important assumption, because it removes all systematic error from the uncertainty budget.

free parameters (6)
  • Differential phase noise sigma_phi = 0.1 deg
    Central to the headline precision; sigma_D scales roughly linearly with sigma_phi (Fig. 7, first row). Chosen as an optimistic but plausible GRAVITY+ noise level.
  • Spectral resolution R = 10,000
    Fiducial assumption; sigma_D decreases with R from about 11% at R=5,000 to about 2.8% at R=20,000.
  • Line flux noise sigma_ell = 1% per spectral channel
    Contributes to sigma_D through Eq. 25; sigma_D rises from 4.2% to 15.3% as sigma_ell goes from 0.5% to 5%.
  • Radial velocity noise sigma_v = 2 km/s
    Fiducial choice; distance uncertainty has weak dependence on sigma_v.
  • Light curve noise sigma_c = 0.2%
    Fiducial choice; sigma_D shows little dependence on sigma_c and LC cadence.
  • Fiducial binary parameters (a, e, i, q, ell, r1, r2) = a=2 au, P=300 d, e=0.3, i=87.13 deg, q=1.5, ell=3, r1=0.1, r2=0.08
    The 6.5% number is specific to this system; Fig. 8 shows sigma_D ranges from 4.3% to 9.3% as dimensionless input parameters vary.
assumptions (5)
  • standard math Binary orbits follow Kepler's equations with Thiele-Innes sky projection (Eqs. 10-15).
    Textbook orbital mechanics; used to generate positions and radial velocities.
  • domain assumption Stellar surfaces are uniform disks in both the mock data and the fitted model (Eq. 17), with eclipses computed from geometric overlap (Eqs. 20-21).
    No limb darkening in the simulation. Section 4.1 estimates a real star's limb-darkened diameter differs from uniform by about 6%, leading to below 0.6% distance error, but this is not included in the mock data or likelihood.
  • domain assumption Absorption lines have Gaussian thermal profiles with rigid rotation (Eqs. 18-19) and the same profile model is used for generation and fitting.
    Line profile parameters are only weakly constrained (Fig. 6); the paper acknowledges stellar winds and asymmetric lines in massive stars as complications (Section 4.1).
  • domain assumption All measurements are independent and Gaussian, with the product likelihood of Eq. 24.
    Idealized noise model; real interferometric phases have correlated and non-Gaussian errors.
  • ad hoc to paper The fiducial model is exactly the true model for the simulated binaries (closed-loop recovery).
    The mock data are generated from the same parameterization used in the fit, so no systematic model mismatch enters the 6% uncertainty. This is the central simplifying assumption that makes the forecast a statistical limit rather than a field measurement.

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Cite this review

Pith. "Pith review of Geometrical Distances of Extragalactic Binaries through Spectroastrometry." pith.science (2026). https://pith.science/paper/37DU6GNH

@misc{pith2026241208889,
  author       = {Pith},
  title        = {Pith review of: Geometrical Distances of Extragalactic Binaries through Spectroastrometry},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/37DU6GNH}},
  note         = {Machine review of arXiv:2412.08889}
}
read the original abstract

The growing ``Hubble tension'' has prompted the need for precise measurements of cosmological distances. This paper demonstrates a purely geometric approach for determining the distance to extragalactic binaries through a joint analysis of spectroastrometry (SA), radial velocity (RV), and light curve (LC) observations. A parameterized model for the binary system is outlined, and simulated SA, RV, and LC data are computed to infer the probability distribution of model parameters based on the mock data. The impact of data quality and binary parameters on distance uncertainties is comprehensively analyzed, showcasing the method's potential for high-precision distance measurements. For a typical eclipsing binary in the Large Magellanic Cloud (LMC), the distance uncertainty is approximately 6% under reasonable observational conditions. Within a specific range of data quality and input parameters, the distance measurement precision of individual binary star systems is generally better than 10%. As a geometric method based on the simplest dynamics, it is independent of empirical calibration and the systematics caused by model selections can be tested using nearby binaries with known distances. By measuring multiple binary star systems or monitoring one binary system repeatedly, geometric distance measurements of nearby galaxies can be achieved, providing valuable insights into the Hubble tension and advancing our understanding of the universe's structure and evolution.

Figures

Figures reproduced from arXiv: 2412.08889 by the authors.

Figure 1
Figure 1. The orbit of the binary and its projection onto the celestial plane. The focal point O of the elliptical orbit is chosen as the coordinate origin. The orbital plane and the celestial plane intersect at line AD with an angle i, where A and D represent the ascending and descending nodes respectively. In the celestial plane, OX points north, and OY points east. Ω represents the azimuthal angle of ascending node A relat… view at source ↗
Figure 2
Figure 2. The left panel shows the projected orbits of both stars in the binary system. The blue and red circles mark the sizes and the initial positions of the primary and secondary stars respectively. The right panel shows the six projected baselines we used for the simulation in the UV plane. We keep the projected baselines fixed for simplicity. In practice, they will vary as the earth rotates. differential phase curve, RV… view at source ↗
Figure 3
Figure 3. Profiles of the absorption line used for SA observation at different orbital phases. Black dots are measured values of line flux with 1σ error bars and black lines are best-fitted profiles. The continuum flux is normalized to 1 and the center of the line is moved to 0 A for clarity. ˚ EW2) are very sensitive to σℓ and R, and they can change the angular position of the photocenter by altering the weights from each st… view at source ↗
Figures from the paper (6 more)
Figure 4
Figure 4. Figure 4: The differential phase measured by each baseline at different orbital phases and their best-fitted curves. The data points’ colors correspond to the baselines’ colors in the right panel of [PITH_FULL_IMAGE:figures/full_fig_p009_4.png]
Figure 5
Figure 5. Figure 5: The upper panel shows the measured RV of each star and their best-fitted curves. The lower panel shows the measured LC and its best-fitted curve. Flux drops when the eclipse happens. are sufficiently separated and the orbital velocity falls below the width of an indivi…
Figure 6
Figure 6. Figure 6: Posterior distributions of model parameters obtained by fitting the binary star model to the mock data. The median values with error bars at 1σ level of all parameters are given on the tops of panels. Contours in two-dimensional distribution are at 1σ, 1.5σ, and 2σ, re…
Figure 7
Figure 7. Figure 7: Dependence of measurement uncertainties on data quality for some parameters. In each row, we depict the relationship between the uncertainties of a parameter and the quality of various datasets. The red point denotes the uncertainties of the parameters derived from the…
Figure 8
Figure 8. Figure 8: Dependence of measurement uncertainties of some model parameters on their input values. The symbols are the same with [PITH_FULL_IMAGE:figures/full_fig_p013_8.png]
Figure 9
Figure 9. Figure 9: Properties of selected eclipsing binaries in LMC. In the left panel, we plot the colors and absolute G band magnitudes of 163 selected targets in LMC. The black stars are those with radial velocity curves, composed of two red giants. The red circles are the remaining t…

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Works this paper leans on

45 extracted references · 11 canonical work pages

  1. [1]

    , " * write output.state after.block = add.period write newline

    ENTRY address archivePrefix author booktitle chapter doi edition editor eprint howpublished institution journal key month number organization pages publisher school series title misctitle type volume year version url label extra.label sort.label short.list INTEGERS output.state before.all mid.sentence after.sentence after.block FUNCTION init.state.consts ...

  2. [2]

    write newline

    " write newline "" before.all 'output.state := FUNCTION format.url url empty "" new.block "" url * "" * if FUNCTION format.eprint eprint empty "" archivePrefix empty "" archivePrefix "arXiv" = new.block " " eprint * " " * new.block " " eprint * " " * if if if FUNCTION format.doi doi empty "" " " doi * " " * if FUNCTION format.pid doi empty eprint empty ur...

  3. [3]

    V*Md yDCE vJ G( 9 NHPߞ* [bY pXzbO0y M3ж?O :/G

    thebibliography [1] 20pt to REFERENCES 6pt =0pt -12pt 10pt plus 3pt =0pt =0pt =1pt plus 1pt =0pt =0pt -12pt =13pt plus 1pt =20pt =13pt plus 1pt \@M =10000 =-1.0em =0pt =0pt 0pt =0pt =1.0em @enumiv\@empty 10000 10000 `\.\@m \@noitemerr \@latex@warning Empty `thebibliography' environment \@ifnextchar \@reference \@latexerr Missing key on reference command E...

    arXiv 2021

  4. [4]

    J., Partay, L

    Brewer, B. J., Partay, L. B., & Csanyi, G. 2011, STATISTICS AND COMPUTING, 21, 649, 10.1007/s11222-010-9198-8

    doi:10.1007/s11222-010-9198-8 2011

  5. [5]

    H., & Lebofsky , M

    Campins , H., Rieke , G. H., & Lebofsky , M. J. 1985, , 90, 896, 10.1086/113799

    work page doi:10.1086/113799 1985

  6. [6]

    2021, Classical and Quantum Gravity, 38, 153001, 10.1088/1361-6382/ac086d

    Di Valentino , E., Mena , O., Pan , S., et al. 2021, Classical and Quantum Gravity, 38, 153001, 10.1088/1361-6382/ac086d

    doi:10.1088/1361-6382/ac086d 2021

  7. [7]

    2016, VizieR Online Data Catalog: JMDC : JMMC Measured Stellar Diameters Catalogue (Duvert, 2016) , VizieR On-line Data Catalog: II/345

    Duvert , G. 2016, VizieR Online Data Catalog: JMDC : JMMC Measured Stellar Diameters Catalogue (Duvert, 2016) , VizieR On-line Data Catalog: II/345. Originally published in: JMMC center (2016)

    work page 2016

  8. [8]

    2007, , 476, 73, 10.1051/0004-6361:20078187

    Fouqu \'e , P., Arriagada , P., Storm , J., et al. 2007, , 476, 73, 10.1051/0004-6361:20078187

    doi:10.1051/0004-6361:20078187 2007

Show all 45 references
  1. [9]

    L., & Madore , B

    Freedman , W. L., & Madore , B. F. 1990, , 365, 186, 10.1086/169469

    1990 doi

  2. [10]

    2010, , 48, 673, 10.1146/annurev-astro-082708-101829

    ---. 2010, , 48, 673, 10.1146/annurev-astro-082708-101829

    2010 doi

  3. [11]

    Gaia Collaboration , Brown , A. G. A., Vallenari , A., et al. 2021, , 649, A1, 10.1051/0004-6361/202039657

    2021 doi

  4. [12]

    2023, , 672, A119, 10.1051/0004-6361/202245712

    Gallenne , A., M \'e rand , A., Kervella , P., et al. 2023, , 672, A119, 10.1051/0004-6361/202245712

    2023 doi

  5. [13]

    2018, , 616, A68, 10.1051/0004-6361/201833341

    Gallenne , A., Pietrzy \'n ski , G., Graczyk , D., et al. 2018, , 616, A68, 10.1051/0004-6361/201833341

    2018 doi

  6. [14]

    B., et al

    Graczyk , D., Pietrzy \'n ski , G., Thompson , I. B., et al. 2018, , 860, 1, 10.3847/1538-4357/aac2bf

    2018 doi

  7. [15]

    2017, , 602, A94, 10.1051/0004-6361/201730838

    GRAVITY Collaboration , Abuter , R., Accardo , M., et al. 2017, , 602, A94, 10.1051/0004-6361/201730838

    2017 doi

  8. [16]

    2021, , 654, A85, 10.1051/0004-6361/202141426

    GRAVITY Collaboration , Amorim , A., Baub \"o ck , M., et al. 2021, , 654, A85, 10.1051/0004-6361/202141426

    2021 doi

  9. [17]

    2022, The Messenger, 189, 17, 10.18727/0722-6691/5285

    Gravity+ Collaboration , Abuter , R., Alarcon , P., et al. 2022, The Messenger, 189, 17, 10.18727/0722-6691/5285

    2022 doi

  10. [18]

    Heintz , W. D. 1978, Double stars (D. Reidel Publishing Company, Dordrecht, Holland), 31--35

    1978

  11. [19]

    F., Watson , D., Kishimoto , M., & Hjorth , J

    H \"o nig , S. F., Watson , D., Kishimoto , M., & Hjorth , J. 2014, , 515, 528, 10.1038/nature13914

    2014 doi

  12. [20]

    O zdarcan , O., & C ak rl , \

    Hoyman , B., Bulut , S., \"O zdarcan , O., & C ak rl , \"O . 2020, , 496, 550, 10.1093/mnras/staa1476

    2020 doi

  13. [21]

    V., Pandey , S., Subramaniam , A., & Sagar , R

    Jadhav , V. V., Pandey , S., Subramaniam , A., & Sagar , R. 2021, Journal of Astrophysics and Astronomy, 42, 89, 10.1007/s12036-021-09746-y

    2021 doi

  14. [22]

    2023, , 669, A91, 10.1051/0004-6361/202244601

    Jim \'e nez-Arranz , \'O ., Romero-G \'o mez , M., Luri , X., et al. 2023, , 669, A91, 10.1051/0004-6361/202244601

    2023 doi

  15. [23]

    2003, , 400, 795, 10.1051/0004-6361:20030072

    Lachaume , R. 2003, , 400, 795, 10.1051/0004-6361:20030072

    2003 doi

  16. [24]

    2002, , 580, L171, 10.1086/345520

    Mandel , K., & Agol , E. 2002, , 580, L171, 10.1086/345520

    2002 doi

  17. [25]

    2001, , 51, 81, 10.48550/arXiv.astro-ph/0104182

    Paczynski , B. 2001, , 51, 81, 10.48550/arXiv.astro-ph/0104182

    2001 doi arXiv

  18. [26]

    2013, , 495, 76, 10.1038/nature11878

    Pietrzy \'n ski , G., Graczyk , D., Gieren , W., et al. 2013, , 495, 76, 10.1038/nature11878

    2013 doi

  19. [27]

    2019, , 567, 200, 10.1038/s41586-019-0999-4

    Pietrzy \'n ski , G., Graczyk , D., Gallenne , A., et al. 2019, , 567, 200, 10.1038/s41586-019-0999-4

    2019 doi

  20. [28]

    2020 a , , 641, A6, 10.1051/0004-6361/201833910

    Planck Collaboration , Aghanim , N., Akrami , Y., et al. 2020 a , , 641, A6, 10.1051/0004-6361/201833910

    2020 doi

  21. [29]

    2020 b , , 641, A1, 10.1051/0004-6361/201833880

    ---. 2020 b , , 641, A1, 10.1051/0004-6361/201833880

    2020 doi

  22. [30]

    G., Meilland , A., & H \"o nig , S

    Rakshit , S., Petrov , R. G., Meilland , A., & H \"o nig , S. F. 2015, , 447, 2420, 10.1093/mnras/stu2613

    2015 doi

  23. [31]

    J., Pesce , D

    Reid , M. J., Pesce , D. W., & Riess , A. G. 2019, , 886, L27, 10.3847/2041-8213/ab552d

    2019 doi

  24. [32]

    2005, , 635, L37, 10.1086/499161

    Ribas , I., Jordi , C., Vilardell , F., et al. 2005, , 635, L37, 10.1086/499161

    2005 doi

  25. [33]

    G., Casertano , S., Yuan , W., et al

    Riess , A. G., Casertano , S., Yuan , W., et al. 2021, , 908, L6, 10.3847/2041-8213/abdbaf

    2021 doi

  26. [34]

    G., Yuan , W., Macri , L

    Riess , A. G., Yuan , W., Macri , L. M., et al. 2022, , 934, L7, 10.3847/2041-8213/ac5c5b

    2022 doi

  27. [35]

    2004, , 608, 42, 10.1086/386540

    Sakai , S., Ferrarese , L., Kennicutt , Robert C., J., & Saha , A. 2004, , 608, 42, 10.1086/386540

    2004 doi

  28. [36]

    2022, , 662, A120, 10.1051/0004-6361/202142133

    Salsi , A., Nardetto , N., Plez , B., & Mourard , D. 2022, , 662, A120, 10.1051/0004-6361/202142133

    2022 doi

  29. [37]

    M., Hines , B

    Shao , M., Colavita , M. M., Hines , B. E., et al. 1988, , 193, 357

    1988

  30. [38]

    2017, , 55, 213, 10.1146/annurev-astro-082214-122339

    Sharma , S. 2017, , 55, 213, 10.1146/annurev-astro-082214-122339

    2017 doi

  31. [39]

    F., Cutri , R

    Skrutskie , M. F., Cutri , R. M., Stiening , R., et al. 2006, , 131, 1163, 10.1086/498708

    2006 doi

  32. [40]

    2019, , 886, 111, 10.3847/1538-4357/ab4b57

    Taormina , M., Pietrzy \'n ski , G., Pilecki , B., et al. 2019, , 886, 111, 10.3847/1538-4357/ab4b57

    2019 doi

  33. [41]

    A., Frinchaboy , P

    Thompson , B. A., Frinchaboy , P. M., Spoo , T., & Donor , J. 2021, , 161, 160, 10.3847/1538-3881/abde4c

    2021 doi

  34. [42]

    K., & Szyma \'n ski , G

    Udalski , A., Szyma \'n ski , M. K., & Szyma \'n ski , G. 2015, , 65, 1, 10.48550/arXiv.1504.05966

    2015 doi arXiv

  35. [43]

    L., & Guinan , E

    Vilardell , F., Ribas , I., Jordi , C., Fitzpatrick , E. L., & Guinan , E. F. 2010, , 509, A70, 10.1051/0004-6361/200913299

    2010 doi

  36. [44]

    2017, , 844, 72, 10.3847/1538-4357/aa79f1

    Waisberg , I., Dexter , J., Pfuhl , O., et al. 2017, , 844, 72, 10.3847/1538-4357/aa79f1

    2017 doi

  37. [45]

    2020, Nature Astronomy, 4, 517, 10.1038/s41550-019-0979-5

    Wang , J.-M., Songsheng , Y.-Y., Li , Y.-R., Du , P., & Zhang , Z.-X. 2020, Nature Astronomy, 4, 517, 10.1038/s41550-019-0979-5

    2020 doi

Pith tools

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