REVIEW 5 major objections 4 minor 119 references
The SEDs of very long-period cepheids in the Milky Way, the Magellanic Clouds, M31 and M33
T0 review · 5 major / 4 minor · reviewed 2026-08-06 · deepseek-v4-flash
Pith's one-line read Among 35 very long-period Cepheids in the Magellanic Clouds, M31, and M33, only one shows a significant infrared excess — dust is unlikely to bias the Cepheid distance scale.
desk verdict A careful multi-galaxy census that confirms IR excess is rare in external-gala xy Cepheids, though the null result is less airtight than the abstract suggests. read the letter →
The pith
A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.
The reading
What carries the argument
The central tool is the spectral energy distribution assembled from literature photometry spanning ultraviolet to mid-infrared wavelengths (GALEX, Gaia, 2MASS, VMC, WISE, IRAC, MIPS, and others). Each SED is fitted with MARCS model atmospheres at a fixed adopted distance and reddening, yielding the best luminosity and effective temperature; for stars where long-wavelength flux remains unexplained, a spherical dust shell is added with the dust optical depth and inner-edge temperature as free parameters, and the Bayesian information criterion decides whether the dust model is genuinely better. The decisive step is image inspection: WISE W1/W3 and IRAC channels 1 and 4 cut-outs are used to verify that claimed excess emission actually coincides with the star, which removes the M31 and M33 candidates whose infrared flux turned out to be diffuse or blended background instead.
What would settle it
Point new mid- or far-infrared observations at the 19 Cepheids in M31 and M33 — most directly the four that currently lack data beyond the near-infrared (M31-PSO009.76, M33-013331, M33-V00021, M33-013405) — for example with JWST/MIRI imaging or spectroscopy; if several of these stars show excess emission above the best-fitting photosphere, or silicate features appear in the spectra, the conclusion that long-period Cepheids in external galaxies are dust-free would be overturned.
Extended reading notes
Core claim
On its own terms, the paper establishes that very long-period classical Cepheids in external galaxies do not commonly present an infrared excess in their spectral energy distributions. Fitting MARCS model atmospheres with the MoD radiative-transfer code to photometry from the ultraviolet to 24 micrometers, and checking candidate excesses against WISE and IRAC images to discard blended or diffuse background emission, the author finds one significant excess in the LMC (LMC-CEP-0619) and none among the seven SMC, twelve M31, and seven M33 objects; in the Milky Way, II Car shows an excess but it is unclear whether it is a classical Cepheid or a Type II Cepheid. This runs contrary to earlier Galactic work that hinted infrared excess might be more prominent in Milky Way Cepheids than in the Magellanic Clouds. The same fits locate nearly all objects inside the classical Cepheid instability strip in the Hertzsprung-Russell diagram, with masses near 10-15 solar masses, while the outliers are largely the objects already re-classified as Type II Cepheids; for Milky Way objects, changing the adopted distance or reddening can move stars in and out of the strip, so those positions carry larger uncertainty.
Load-bearing premise
The finding that no infrared excess exists in most of these stars rests on the available mid-infrared photometry being sensitive enough to reveal one — the paper itself states that the absence of proof of infrared excess is not proof of absence, and four of the M31 and M33 objects have no photometry beyond the near-infrared.
Editorial extensions
If this is right
- If the near-null holds, mid-infrared photometry of long-period Cepheids in the LMC, SMC, M31, and M33 is not contaminated by circumstellar dust, so period-luminosity relations built from those bands carry no dust-excess bias for these objects.
- The earlier hint that infrared excess is more prominent among Milky Way Cepheids than in the Magellanic Clouds is not confirmed for the longest-period stars, weakening the case that metallicity drives the fraction of dusty Cepheids.
- The HRD placement inside the classical Cepheid instability strip for most objects supports treating the >50-day variables as classical Cepheids with masses near 10-15 solar masses, while the confirmed outliers clarify which catalog entries are actually Type II Cepheids.
- For the Milky Way subsample, distance and reddening uncertainties move stars substantially in the HRD, so improved parallaxes (such as Gaia DR4) are needed before those objects can pin down luminosities or effective temperatures tightly.
Reading between the lines
- A direct test the paper leaves implicit: longer-wavelength photometry for the four M31 and M33 objects that currently stop at the near-infrared could still reveal warm dust, so the zero-detection count in those galaxies is an upper limit until such data exist.
- If the genuine excesses (LMC-CEP-0619 and II Car) turn out to come from free-free emission of ionized gas rather than dust — an option the paper itself discusses — then the interesting comparison across galaxies is not dust formation but the prevalence of circumstellar ionized gas around the most luminous Cepheids.
- Extending the same fitting pipeline to the shorter-period Cepheids in M31 and M33 (left unstudied here) would test whether the roughly 5 percent excess fraction seen in Milky Way stars is universal; a null there would make the Milky Way the anomaly rather than the rule.
Editorial analysis
A structured set of objections, weighed in public.
Referee Report
Summary. The paper constructs and fits SEDs for 55 long-period (P > 50 d) classical Cepheid candidates in the Milky Way, LMC, SMC, M31, and M33, using literature photometry and MARCS model atmospheres, optionally adding a dust shell. Distances and reddenings are adopted from the literature, and WISE/IRAC images are inspected to verify candidate infrared excesses. The principal result is that only LMC-CEP-0619 shows a confirmed IR excess, with II Car in the MW being an additional but possibly Type II Cepheid case; no IR excess is found in the SMC, M31, or M33. The paper also places the stars in the HRD and derives PL and PR classifications for the MW/Bulge objects, concluding that the impact of IR excess on the Cepheid distance scale is likely small.
Significance. If the null result is robust, the paper provides an important constraint: warm circumstellar dust around long-period Cepheids is not common in external galaxies, and the Cepheid distance scale is unlikely to be significantly biased by IR excess. The analysis is careful and homogeneous across five galaxies, and the two confirmed excesses (LMC-CEP-0619 and II Car) are supported by independent WISE/IRAC image inspection. The public release of the SED fits and the use of established fitting tools are strengths. However, the weight of the central null claim depends on the sensitivity of the available MIR data, which is never quantified; the paper itself acknowledges the relevant caveat in Sec. 4.3. As it stands, the abstract overstates the contrast with the Milky Way for the same period range.
major comments (5)
- [Sec. 4.3, Table 4] The central null claim is not accompanied by a quantified detection threshold. The paper states in Sec. 4.3 that four objects have no photometry beyond the NIR and that 'the absence of proof for infrared excess is not the proof of absence,' but this caveat applies more broadly: for the remaining M31 and M33 stars the MIR data are often single-epoch and shallow, and the SED fits show large reduced chi-squared values (Table A.2). No test is made of whether an excess like that of LMC-CEP-0619 (T_d ~ 925 K, tau_V ~ 0.08; Table 2) would be statistically preferred given the actual photometric error bars. I request an injection/recovery test or, at minimum, upper limits on tau_V for each non-detection, and a corresponding softening of the abstract and conclusion.
- [Abstract, Table 4] The claimed contrast with the Milky Way is overstated. For P > 50 d, Table 4 gives MW 0/5-1/8, LMC 1/9, SMC 0/7, and M31+M33 0/19; these rates are statistically indistinguishable from one another. The 'contrary to earlier work' phrasing in the abstract implicitly compares with the shorter-period Galactic sample (16/350 for P < 50 d) rather than with the long-period sample studied here. The abstract and summary should be rephrased to report that no strong excess is seen in the long-period external-galaxy sample, and that a comparison with MW long-period Cepheids is not yet statistically meaningful.
- [Sec. 2 / Sec. 1] The Introduction calls this 'a complete sample of long-period Cepheids,' but Sec. 2 states that known CCs in M31 and M33 with P > 50 d are not included if they are absent from the Gaia vari_cepheid table. The sample is therefore not a complete census of long-period Cepheids in those galaxies, and the null rates in Table 4 are rates for a Gaia-selected subsample. The completeness statement should be corrected and the selection function should be stated explicitly as a limitation on the external-galaxy null result.
- [Sec. 4.3, Table 2] The BIC comparison is not made on equal footing. The 'no dust' model in Table A.2 excludes clipped outliers, while the dust model appears to use a different treatment of the photometric points; for LMC-CEP-0619 the reduced chi-squared is actually larger for the dust model (54.8) than for the no-dust model (51.3), yet the dust model is preferred by BIC. Because six of the eight BIC-preferred candidates are later rejected on the basis of image inspection, the statistical selection step is not the decisive evidence. I recommend reporting BIC or likelihood values computed with identical outlier handling and identical data sets, and specifying the criterion used to call an image detection 'associated' with the central star.
- [Table A.2, Sec. 4.4] Distance errors are deliberately not propagated into the quoted luminosity errors (Table A.2 note). For MW stars with fractional distance uncertainties of 10-30% (e.g., ATO093m31 at 15.78 +/- 2.58 kpc), this affects the HRD, PL, and PR classifications in Table 3, and hence the denominator of the MW >50 d excess rate in Table 4. The alternative-distance runs in Sec. 4.4 address this partially, but the standard-model classifications in Table 3 are used without this uncertainty, so the MW comparison rate should carry a corresponding caveat.
minor comments (4)
- [Sec. 3.3] The description of how Teff errors are derived ('models within a certain range above the minimum') should specify the adopted Delta-chi-squared threshold and how the 125 K interpolation step enters the quoted uncertainties.
- [Table B.1] The W3/W4 quality cuts are given in magnitude-error terms, but the number of epochs and the pulsation phase of single-epoch MIR measurements are not documented; phase-dependent photometry could masquerade as scatter or as a false excess.
- [Figs. C.2 and C.3] The visual classification of 'not clearly associated' would be more reproducible with a quantitative measure, such as PSF-matched aperture photometry at the expected stellar position versus the local background.
- [Title / Sec. 2] The phrase 'very long-period' is not defined; since the sample starts at 50 d and includes many objects below the usual 80 d ultra-long-period threshold, 'long-period' may be more accurate.
Circularity Check
No significant circularity: the IR-excess result is derived from independent SED fitting, literature distances/reddenings, and image inspection, with the author's own PL relations used only as auxiliary classification aids.
full rationale
The central claim — that only one long-period Cepheid in the LMC and none in the SMC, M31, or M33 show a significant infrared excess — is obtained from SED fits using MARCS model atmospheres and the MoD/DUSTY radiative-transfer code, with distances and reddenings adopted from external literature and the excess assessed via BIC comparison and direct WISE/IRAC image inspection. No parameter entering the SED fitting is calibrated to the IR-excess outcome itself, and no relation derived from the same data is used to define the excess. The author's earlier period-luminosity relations (Groenewegen & Lub 2023; Groenewegen & Jurkovic 2017) appear only as auxiliary tools for classifying CC versus T2C candidates and as comparison lines in the PL/PR diagrams; they do not enter the SED fits or the IR-excess determination. The paper explicitly acknowledges the sensitivity limitation for objects without mid-infrared photometry ('the absence of proof for infrared excess is not the proof of absence'), which is an honest data-completeness caveat rather than a circular step. Self-citations to G20 and Groenewegen & Lub (2023) are legitimate continuations of prior work with external distance anchors and do not carry the load of the present null result. Therefore no circular step is exhibited, and the derivation is self-contained with respect to its central claim.
Assumptions & free parameters
free parameters (4)
- Bolometric luminosity L =
per star, e.g., 16,668 L_sun for M31-PSO009.76 (Table A.2)
- Effective temperature T_eff =
per star from a 125 K grid, e.g., 4625 K for M31-PSO009.76
- Dust temperature at inner radius T_d =
330-1858 K for the 9 dust-model candidates (Table 2)
- Dust optical depth tau_V =
0.082-1.161 for the 9 dust-model candidates (Table 2)
assumptions (6)
- domain assumption MARCS model atmospheres at log g=1.5 represent Cepheid photospheres
- domain assumption DUSTY radiative transfer with spherical symmetry describes any dust shell
- domain assumption Adopted distances from the literature are correct
- domain assumption Adopted reddening values from 3D maps are correct
- ad hoc to paper The Gaia vari_cepheid and OGLE samples are representative of long-period Cepheids in each galaxy
- domain assumption Theoretical instability strips and evolutionary tracks (De Somma 2021; Anderson 2016; MIST) are accurate
Cite this review
Pith. "Pith review of The SEDs of very long-period cepheids in the Milky Way, the Magellanic Clouds, M31 and M33." pith.science (2026). https://pith.science/paper/ETKDNMQS
@misc{pith2026250704757,
author = {Pith},
title = {Pith review of: The SEDs of very long-period cepheids in the Milky Way, the Magellanic Clouds, M31 and M33},
year = {2026},
howpublished = {\url{https://pith.science/paper/ETKDNMQS}},
note = {Machine review of arXiv:2507.04757}
}
read the original abstract
The spectral energy distributions (SEDs) of 20 Milky Way (MW), 9 Large Magellanic Cloud (LMC), 7 Small Magellanic Cloud (SMC), 12 M31, and 7 M33 (classical) Cepheids with periods longer than 50 days were constructed using photometric data from the literature and fitted with model atmospheres with the aim of identifying objects with an infrared excess. The SEDs were fitted with stellar photosphere models to derive the best-fitting luminosity and effective temperature; a dust component was added when required. The distance and reddening values were taken from the literature. WISE and IRAC images were inspected to verify whether potential excess emission was related to the central objects. Only one star with a significant infrared (IR) excess was found in the LMC and none in the SMC, M31, and M33, contrary to earlier work on the MW suggesting that IR excess may be more prominent in MW Cepheids than in the Magellanic Clouds. One additional object in the MW was found to have an IR excess, but it is unclear whether it is a classical Cepheid or a type-{\sc ii} Cepheid. The stars were plotted in a Hertzsprung--Russell diagram (HRD) and compared to evolutionary tracks for CCs and to theoretical instability strips. For the large majority of stars, the position in the HRD is consistent with the instability strip. For stars in the MW uncertainties in the distance and reddening can significantly change their position in the HRD.
Figures
Figures from the paper (1 more)
Reference graph
Works this paper leans on
-
[1]
Anders , F., Khalatyan , A., Queiroz , A. B. A., et al. 2022, , 658, A91
2022
-
[2]
I., Saio , H., Ekstr \"o m , S., Georgy , C., & Meynet , G
Anderson , R. I., Saio , H., Ekstr \"o m , S., Georgy , C., & Meynet , G. 2016, , 591, A8
2016
-
[3]
Bailer-Jones , C. A. L., Rybizki , J., Fouesneau , M., Demleitner , M., & Andrae , R. 2021, , 161, 147
2021
-
[4]
Beichmann , C. A. 1985, Infrared Astronomical Satellite (IRAS) catalogs and atlases. Explanatory supplement
1985
-
[5]
Berdnikov , L. N. 2008, VizieR Online Data Catalog, 2285
2008
-
[6]
N., Kniazev , A
Berdnikov , L. N., Kniazev , A. Y., Sefako , R., et al. 2015, VizieR Online Data Catalog, J/PAZh/41/27
2015
-
[7]
2017, , 230, 24
Bianchi , L., Shiao , B., & Thilker , D. 2017, , 230, 24
2017
-
[8]
C., Stanek , K
Bird , J. C., Stanek , K. Z., & Prieto , J. L. 2009, , 695, 874
2009
Show all 119 references
-
[9]
& Kiss , L
B \'o di , A. & Kiss , L. L. 2019, , 872, 60
2019
-
[10]
2016, , 587, A117
Breitfelder , J., M \'e rand , A., Kervella , P., et al. 2016, , 587, A117
2016
-
[11]
G., Macri , L
Breuval , L., Riess , A. G., Macri , L. M., et al. 2023, , 951, 118
2023
-
[12]
C., Magnier , E
Chambers , K. C., Magnier , E. A., Metcalfe , N., et al. 2016, arXiv e-prints, arXiv:1612.05560
2016 arXiv
-
[13]
2020, , 249, 18
Chen , X., Wang , S., Deng , L., et al. 2020, , 249, 18
2020
-
[14]
2016, , 823, 102
Choi , J., Dotter , A., Conroy , C., et al. 2016, , 823, 102
2016
-
[15]
H., Scowcroft , V., & Wuyts , S
Chown , A. H., Scowcroft , V., & Wuyts , S. 2021, , 500, 817
2021
-
[16]
L., Clementini , G., Girardi , L., et al
Cioni , M.-R. L., Clementini , G., Girardi , L., et al. 2011, , 527, A116
2011
-
[17]
& Anderson , R
Cruz Reyes , M. & Anderson , R. I. 2023, , 672, A85
2023
-
[18]
Cutri , R. M. & et al. 2014, VizieR Online Data Catalog, 2328, 0
2014
-
[19]
M., Skrutskie , M
Cutri , R. M., Skrutskie , M. F., van Dyk , S., et al. 2003, VizieR Online Data Catalog, II/246
2003
-
[20]
M., Skrutskie , M
Cutri , R. M., Skrutskie , M. F., van Dyk , S., et al. 2012, VizieR Online Data Catalog, II/281
2012
-
[21]
J., Williams , B
Dalcanton , J. J., Williams , B. F., Lang , D., et al. 2012, , 200, 18
2012
-
[22]
2021, , 508, 1473
De Somma , G., Marconi , M., Cassisi , S., et al. 2021, , 508, 1473
2021
-
[23]
2005, VizieR Online Data Catalog, B/denis
Denis , C. 2005, VizieR Online Data Catalog, B/denis
2005
-
[24]
2016, , 222, 8
Dotter , A. 2016, , 222, 8
2016
-
[25]
E., Gonzales-Solares , E., Greimel , R., et al
Drew , J. E., Gonzales-Solares , E., Greimel , R., et al. 2016, VizieR Online Data Catalog, II/341
2016
-
[26]
E., Gonzalez-Solares , E., Greimel , R., et al
Drew , J. E., Gonzalez-Solares , E., Greimel , R., et al. 2014, , 440, 2036
2014
-
[27]
P., Price , S
Egan , M. P., Price , S. D., Kraemer , K. E., et al. 2003, VizieR Online Data Catalog, V/114
2003
-
[28]
Eggen , O. J. 1977, , 34, 33
1977
-
[29]
Gaia Collaboration , Prusti , T., de Bruijne , J. H. J., et al. 2016, , 595, A1
2016
-
[30]
, Brown, A.G.A
Gaia Collaboration , Vallenari, A. , Brown, A.G.A. , Prusti, T. , & et al. 2022, A&A
2022
-
[31]
2012, , 538, A24
Gallenne , A., Kervella , P., & M \'e rand , A. 2012, , 538, A24
2012
-
[32]
2017, , 608, A18
Gallenne , A., Kervella , P., M \'e rand , A., et al. 2017, , 608, A18
2017
-
[33]
2013, , 558, A140
Gallenne , A., M \'e rand , A., Kervella , P., et al. 2013, , 558, A140
2013
-
[34]
B., et al
Graczyk , D., Pietrzy \'n ski , G., Thompson , I. B., et al. 2020, , 904, 13
2020
-
[35]
2022, , 657, L12
GRAVITY Collaboration , Abuter , R., Aimar , N., et al. 2022, , 657, L12
2022
-
[36]
2021, , 647, A59
GRAVITY Collaboration , Abuter , R., Amorim , A., et al. 2021, , 647, A59
2021
-
[37]
J., Sarajedini , A., Olsen , K
Grocholski , A. J., Sarajedini , A., Olsen , K. A. G., Tiede , G. P., & Mancone , C. L. 2007, , 134, 680
2007
-
[38]
Groenewegen , M. A. T. 2012, , 543, A36
2012
-
[39]
Groenewegen , M. A. T. 2020 a , , 635, A33, (G20)
2020
-
[40]
Groenewegen , M. A. T. 2020 b , , 640, A113
2020
-
[41]
Groenewegen , M. A. T. & Jurkovic , M. I. 2017, , 604, A29
2017
-
[42]
Groenewegen , M. A. T. & Lub , J. 2023, , 676, A136
2023
-
[43]
2008, , 486, 951
Gustafsson , B., Edvardsson , B., Eriksson , K., et al. 2008, , 486, 951
2008
-
[44]
Gutermuth , R. A. & Heyer , M. 2015, , 149, 64
2015
-
[45]
A., Levine , S., Terrell , D., & Welch , D
Henden , A. A., Levine , S., Terrell , D., & Welch , D. L. 2015, in American Astronomical Society Meeting Abstracts, Vol. 225, American Astronomical Society Meeting Abstracts \#225, 336.16
2015
-
[46]
2020, VizieR Online Data Catalog, VIII/106
Herschel PSC Working Group , Marton , G., Calzoletti , L., et al. 2020, VizieR Online Data Catalog, VIII/106
2020
-
[47]
2025 a , , 694, L15
Hocd \'e , V., Kami \'n ski , T., Lewis , M., et al. 2025 a , , 694, L15
2025
-
[48]
2025 b , , 694, A101
Hocd \'e , V., Matter , A., Nardetto , N., et al. 2025 b , , 694, A101
2025
-
[49]
2020 a , , 633, A47
Hocd \'e , V., Nardetto , N., Lagadec , E., et al. 2020 a , , 633, A47
2020
-
[50]
2020 b , , 641, A74
Hocd \'e , V., Nardetto , N., z Borgniet , S., et al. 2020 b , , 641, A74
2020
-
[51]
2010, , 514, A1
Ishihara , D., Onaka , T., Kataza , H., et al. 2010, , 514, A1
2010
-
[52]
2010, , 62, 273
Ita , Y., Onaka , T., Tanab \'e , T., et al. 2010, , 62, 273
2010
-
[53]
1999, DUSTY: Radiation transport in a dusty environment , Astrophysics Source Code Library
Ivezi \'c , Z ., Nenkova , M., & Elitzur , M. 1999, DUSTY: Radiation transport in a dusty environment , Astrophysics Source Code Library
1999
-
[54]
T., & Mirtorabi , M
Javadi , A., van Loon , J. T., & Mirtorabi , M. T. 2011, , 411, 263
2011
-
[55]
R., Van Winckel , H., & Nie , J
Kamath , D., Wood , P. R., Van Winckel , H., & Nie , J. D. 2016, , 586, L5
2016
-
[56]
2012, , 144, 179
Kato , D., Ita , Y., Onaka , T., et al. 2012, , 144, 179
2012
-
[57]
2006, , 448, 623
Kervella , P., M \'e rand , A., Perrin , G., & Coud \'e du Foresto , V. 2006, , 448, 623
2006
-
[58]
2017, , 228, 5
Khan , R. 2017, , 228, 5
2017
-
[59]
Z., Kochanek , C
Khan , R., Stanek , K. Z., Kochanek , C. S., & Sonneborn , G. 2015, , 219, 42
2015
-
[60]
M., Graziani , R., et al
Kourkchi , E., Courtois , H. M., Graziani , R., et al. 2020, , 159, 67
2020
-
[61]
L., Babusiaux , C., & Cox , N
Lallement , R., Vergely , J. L., Babusiaux , C., & Cox , N. L. J. 2022, , 661, A147
2022
-
[62]
Laney , C. D. & Stobie , R. S. 1992, , 93, 93
1992
-
[63]
G., Busch , M
Li , S., Riess , A. G., Busch , M. P., et al. 2021, , 920, 84
2021
-
[64]
2025, arXiv e-prints, arXiv:2504.18779
Li , Y., Jiang , B., & Ren , Y. 2025, arXiv e-prints, arXiv:2504.18779
2025 arXiv
-
[65]
2021, , 649, A4
Lindegren , L., Bastian , U., Biermann , M., et al. 2021, , 649, A4
2021
-
[66]
2018, , 479, 111
Ma , B., Shang , Z., Hu , Y., et al. 2018, , 479, 111
2018
-
[67]
Madore , B. F. 1975, , 29, 219
1975
-
[68]
Madore , B. F. 1982, , 253, 575
1982
-
[69]
2018, , 618, A21
Manick , R., Van Winckel , H., Kamath , D., Sekaran , S., & Kolenberg , K. 2018, , 618, A21
2018
-
[70]
Marocco , F., Eisenhardt , P. R. M., Fowler , J. W., et al. 2021, , 253, 8
2021
-
[71]
Martin , W. L. & Warren , P. R. 1979, South African Astronomical Observatory Circular, 1, 98
1979
-
[72]
F., & Smart , B
Massey , P., Neugent , K. F., & Smart , B. M. 2016, , 152, 62
2016
-
[73]
G., Banerji , M., Gonzalez , E., et al
McMahon , R. G., Banerji , M., Gonzalez , E., et al. 2013, The Messenger, 154, 35
2013
-
[74]
2006, , 453, 155
M \'e rand , A., Kervella , P., Coud \'e du Foresto , V., et al. 2006, , 453, 155
2006
-
[75]
W., Emerson , J
Minniti , D., Lucas , P. W., Emerson , J. P., et al. 2010, , 15, 433
2010
-
[76]
Monson , A. J. & Pierce , M. J. 2011, , 193, 12
2011
-
[77]
S., Riess , A
Murakami , Y. S., Riess , A. G., Stahl , B. E., et al. 2023, , 2023, 046
2023
-
[78]
2022, Universe, 8, 335
Musella , I. 2022, Universe, 8, 335
2022
-
[79]
2021, , 501, 866
Musella , I., Marconi , M., Molinaro , R., et al. 2021, , 501, 866
2021
-
[80]
2016, , 593, A45
Nardetto , N., M \'e rand , A., Mourard , D., et al. 2016, , 593, A45
2016
-
[81]
F., Massey , P., Georgy , C., et al
Neugent , K. F., Massey , P., Georgy , C., et al. 2020, , 889, 44
2020
-
[82]
L., Olsen , K., Choi , Y., et al
Nidever , D. L., Olsen , K., Choi , Y., et al. 2021, , 161, 74
2021
-
[83]
2011, , 192, 3
Paxton , B., Bildsten , L., Dotter , A., et al. 2011, , 192, 3
2011
-
[84]
2013, , 208, 4
Paxton , B., Cantiello , M., Arras , P., et al. 2013, , 208, 4
2013
-
[85]
2015, , 220, 15
Paxton , B., Marchant , P., Schwab , J., et al. 2015, , 220, 15
2015
-
[86]
Pel , J. W. 1976, , 24, 413
1976
-
[87]
& Macri , L
Pellerin , A. & Macri , L. M. 2011, , 193, 26
2011
-
[88]
2024, , 110, 123518
Perivolaropoulos , L. 2024, , 110, 123518
2024
-
[89]
2021, , 71, 205
Pietrukowicz , P., Soszy \'n ski , I., & Udalski , A. 2021, , 71, 205
2021
-
[90]
2019, , 567, 200
Pietrzy \'n ski , G., Graczyk , D., Gallenne , A., et al. 2019, , 567, 200
2019
-
[91]
Queiroz , A. B. A., Anders , F., Santiago , B. X., et al. 2018, , 476, 2556
2018
-
[92]
G., Casertano , S., Yuan , W., et al
Riess , A. G., Casertano , S., Yuan , W., et al. 2021, , 908, L6
2021
-
[93]
G., Casertano , S., Yuan , W., Macri , L
Riess , A. G., Casertano , S., Yuan , W., Macri , L. M., & Scolnic , D. 2019, , 876, 85
2019
-
[94]
G., Yuan , W., Macri , L
Riess , A. G., Yuan , W., Macri , L. M., et al. 2022, , 934, L7
2022
-
[95]
2022, , 512, 563
Ripepi , V., Chemin , L., Molinaro , R., et al. 2022, , 512, 563
2022
-
[96]
L., Moretti , M
Ripepi , V., Cioni , M.-R. L., Moretti , M. I., et al. 2017, , 472, 808
2017
-
[97]
2023, , 674, A17
Ripepi , V., Clementini , G., Molinaro , R., et al. 2023, , 674, A17
2023
-
[98]
I., et al
Ripepi , V., Marconi , M., Moretti , M. I., et al. 2016, , 224, 21
2016
-
[99]
1978, Ann
Schwarz, G. 1978, Ann. Stat., 6, 461
1978
-
[100]
M., Skowron , J., Udalski , A., et al
Skowron , D. M., Skowron , J., Udalski , A., et al. 2021, , 252, 23
2021
-
[101]
K., et al
Soszy \'n ski , I., Udalski , A., Szyma \'n ski , M. K., et al. 2019, , 69, 87
2019
-
[102]
K., et al
Soszy \'n ski , I., Udalski , A., Szyma \'n ski , M. K., et al. 2020, , 70, 101
2020
-
[103]
K., et al
Soszy \'n ski , I., Udalski , A., Szyma \'n ski , M. K., et al. 2017, , 67, 103
2017
-
[104]
2009, VizieR Online Data Catalog, II/293
Spitzer Science , C. 2009, VizieR Online Data Catalog, II/293
2009
-
[105]
1977, Mitt
Szabados , L. 1977, Mitt. Sternw. Ungarisch. Akad. Wiss, 70
1977
-
[106]
1980, Communications of the Konkoly Obs
Szabados , L. 1980, Communications of the Konkoly Obs. Hungary, 76, 1
1980
-
[107]
1981, Communications of the Konkoly Obs
Szabados , L. 1981, Communications of the Konkoly Obs. Hungary, 77, 1
1981
-
[108]
1991, Communications of the Konkoly Obs
Szabados , L. 1991, Communications of the Konkoly Obs. Hungary, 96, 123
1991
-
[109]
2019, PhD thesis, L'Universit\'e PSL, l'Observatoire de Paris
Trahin, B. 2019, PhD thesis, L'Universit\'e PSL, l'Observatoire de Paris
2019
-
[110]
2021, , 656, A102
Trahin , B., Breuval , L., Kervella , P., et al. 2021, , 656, A102
2021
-
[111]
2018, , 68, 315
Udalski , A., Soszy \'n ski , I., Pietrukowicz , P., et al. 2018, , 68, 315
2018
-
[112]
K., Udalski , A., et al
Ulaczyk , K., Szyma \'n ski , M. K., Udalski , A., et al. 2012, , 62, 247
2012
-
[113]
K., Udalski , A., et al
Ulaczyk , K., Szyma \'n ski , M. K., Udalski , A., et al. 2013, , 63, 159
2013
-
[114]
& Wood , P
Vassiliadis , E. & Wood , P. R. 1994, , 92, 125
1994
-
[115]
L., Lallement , R., & Cox , N
Vergely , J. L., Lallement , R., & Cox , N. L. J. 2022, , 664, A174
2022
-
[116]
F., Durbin , M
Williams , B. F., Durbin , M. J., Dalcanton , J. J., et al. 2021, , 253, 53
2021
-
[117]
F., Lang , D., Dalcanton , J
Williams , B. F., Lang , D., Dalcanton , J. J., et al. 2014, , 215, 9
2014
-
[118]
, " * write output.state after.block = add.period write newline
ENTRY address archiveprefix author booktitle chapter edition editor howpublished institution eprint journal key month note number organization pages publisher school series title type volume year label extra.label sort.label short.list INTEGERS output.state before.all mid.sent...
-
[119]
write newline
" write newline "" before.all 'output.state := FUNCTION n.dashify 't := "" t empty not t #1 #1 substring "-" = t #1 #2 substring "--" = not "--" * t #2 global.max substring 't := t #1 #1 substring "-" = "-" * t #2 global.max substring 't := while if t #1 #1 substring * t #2 gl...
Reviewed August 6, 2026 · model on record in the stance chip above.
Discussion (0). Sign in to comment.