Estimation of Classical Cepheid's Physical Parameters from NIR Light Curves

G\'abor B. Kov\'acs; Lajos G. Bal\'azs

REVIEW 4 major objections 6 minor 51 references

Estimation of Classical Cepheid's Physical Parameters from NIR Light Curves

T0 review · 4 major / 6 minor · reviewed 2026-08-11 · deepseek-v4-flash

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

Pith's one-line read A principal-component analysis of 131 classical Cepheids in J, H, and K finds that stellar mass, not metallicity, dominates near-infrared light-curve shapes, so NIR photometry alone cannot deliver abundances.

desk verdict A workmanlike PCA/clustering tutorial on NIR Cepheid light curves whose headline interpretation overreaches the data. read the letter →

arxiv 2412.06386 v1 pith:2F63HZWG submitted 2024-12-09 astro-ph.SR astro-ph.GAastro-ph.IM

Lajos G. Balázs , Gábor B. Kovács This is my paper · ORCID

classification astro-ph.SRastro-ph.GAastro-ph.IM

keywords classicalCepheidsnear-infraredlightcurvesprincipalcomponentanalysisunsupervisedclassificationstellarmassmetallicityperiod-luminosityrelationmethods:statistical

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 asks what physical information can be recovered from near-infrared light curves of classical Cepheids, where extinction is ten times smaller than in the visual but shape sensitivity is low. It analyzes 131 Cepheids from a published JHK sample by representing each light curve as a 20-dimensional vector of phase-sampled brightness values and applying principal component analysis in each color separately. The analysis finds six significant eigenvalues, so the 20-dimensional space can be reduced to six dimensions, and the first two principal components absorb about 80 percent of the variance. Those two components correlate very strongly with period and absolute magnitude, and significantly with amplitude, but only marginally with metallicity, leading the authors to conclude that stellar mass is the key physical variable shaping the near-infrared light curves and that JHK photometry alone is insufficient for abundance determination. The wider claim is that this PCA-plus-clustering procedure can be automated and pipelined for unsupervised classification of large, biased survey samples.

What carries the argument

The central machinery is a principal component analysis of each light curve as a 20-dimensional vector of phase-sampled, amplitude-normalized brightness values in a given passband. The correlation matrix of these vectors yields eigenvectors that act as orthogonal template light curves, and keeping the six significant eigenvalues reduces the space from 20 to 6 dimensions, with squared Euclidean (chi-square) distances between light curves defined in that subspace. Clustering by partitioning around medoids, using the silhouette criterion to choose the group count, returns seven light-curve classes in each of J, H, and K. Physical interpretation then comes from Spearman rank correlations between PC scores and period, absolute magnitude, amplitude, and [Fe/H], together with the derived scaling $P \propto M^{2.1}$ obtained by combining a period-radius with a period-mass-radius relation; linear discriminant analysis identifies amplitude as the strongest discriminator between classes and metallicity as the weakest.

What would settle it

If masses were measured directly for a subset of these Cepheids, from binary orbits or asteroseismology, the mass-dominance claim predicts that PC1 and PC2 scores would fall on a one-dimensional sequence ordered by mass; observing two stars with the same mass but different [Fe/H] that have markedly different PC1 and PC2 values, or residual scatter not explained by mass, would falsify it. A complementary test is to generate synthetic JHK light curves from pulsation models at fixed mass while varying metallicity: if the light-curve shape changes noticeably with [Fe/H], then near-infrared curves do carry metallicity information that this particular PCA did not recover.

Watch

Extended reading notes

Core claim

The paper's central claim is that near-infrared (J, H, K) light-curve shapes of classical Cepheids are dominated by a single hidden physical variable, stellar mass, and that the metallicity information coded in them is too weak to estimate [Fe/H] reliably. On its own terms, the evidence is a principal component analysis of 131 amplitude-normalized, phase-sampled light curves: six eigenvalues are significant, the first two principal components describe roughly 80 percent of the variance, and Spearman rank correlations of PC1 and PC2 with period and absolute magnitude are significant at the $p < 10^{-4}$ level in all three colors, while analogous correlations with [Fe/H] are marginal. Combining a published period-radius relation with a published period-mass-radius relation yields the scaling $P \propto M^{2.1}$, which the authors use to argue that period, luminosity, and amplitude all trace the same mass variable. The paper also shows that linear discriminant analysis separates the seven light-curve clusters mainly by amplitude, with metallicity contributing the least, and that DCEP and DCEPS subtypes can be separated from PCs alone using Bayes' theorem.

Load-bearing premise

The conclusion that one hidden variable, stellar mass, shapes the near-infrared light curves rests on published period-radius and period-mass-radius relations, and on the assumption that the correlations of the principal components with period, luminosity, and amplitude are all symptoms of that single variable rather than separate effects.

Editorial extensions

If this is right

NIR-only survey pipelines can compress each light curve to six principal-component scores and recover period and luminosity information with high significance, without spectroscopy.
Metallicity estimates from JHK light-curve shapes will be unreliable, so abundance studies in dusty, high-extinction regions still require spectroscopic observations or other indicators.
The seven light-curve groups and their medoid templates provide ready-made shape classifiers that can be applied to newly observed Cepheids in an unsupervised way.
The DCEP versus DCEPS separation, obtained by applying linear discriminant analysis and Bayes' theorem to the PC scores, gives a photometry-only route to subtype classification.
Jointly treating the J, H, and K bands as a single vectorized representation is suggested by the authors as a possible way to increase the metallicity sensitivity of the method.

Reading between the lines

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

If the derived $P \propto M^{2.1}$ scaling were replaced by the canonical period-density scaling (which gives a different mass exponent), the interpretation that PC1 and PC2 trace mass alone would need revision, although the PC correlations themselves would stand.
The same PCA-plus-medoid pipeline could be applied to RR Lyrae stars or Type II Cepheids, where metallicity is known to affect light-curve shape, to test whether the metallicity blindness found here is a general property of near-infrared bands or specific to this classical Cepheid sample.
Because the sample is drawn from the northern Galactic disk and is small, the seven-group structure and the mass-dominance result are sample-dependent; a kinematically or chemically diverse sample could reveal additional independent shape parameters.
The authors' hint that vectorizing all three bands together might improve metallicity detection is directly testable: repeating the PCA on concatenated J+H+K phase vectors should produce a significant metallicity axis if that information is present in the data.

Share X Bluesky LinkedIn Reddit HN

Editorial analysis

A structured set of objections, weighed in public.

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

Desk Editor's Note

read the letter

Punchline: the paper is a solid but modest demonstration of PCA plus PAM clustering on near-infrared Cepheid light curves. The headline claim about mass is not earned by the analysis; it's an inference from literature relations that the data don't directly test.

What the paper does well: applying PCA to J,H,K light curves separately, reducing 20 phase points to 6 PCs, using jackknife to check the cluster count, and inspecting correlations with period, absolute magnitude, amplitude, and metallicity. This is a clear worked example of an unsupervised pipeline for survey data. The authors honestly cite the earlier PCA work of Kanbur et al. (2002) and Deb & Singh (2009), and they explicitly note in Section 5.1 that the mass-shape connection is not a new insight.

Soft spots: the central physical conclusion is overinterpreted. The first two PCs correlate tightly with period and absolute magnitude, which are strongly correlated with each other, so the PCA is effectively finding a univariate sequence. Calling it 'mass' is a causal assumption layered on top of the correlations. Section 5.6 actually concedes the hidden variable 'is not necessarily identical' to mass, which undercuts the abstract and highlights. There's also a small arithmetic slip in the exponent (P ~ M^1.88, not M^2.1), though that's not the main issue. The metallicity claim is similarly too absolute: J-band PC1, PC2, PC3 all show significant Spearman correlations with [Fe/H], so 'insufficient' needs effect sizes or cross-validation rather than a blanket statement based on p-values alone. The DCEP/DCEPS classifier is built from only four DCEPS stars, trained and evaluated on the same set with no holdout, so the separation shown in Figure 18 is optimistic.

None of this is fatal to the methodological demonstration. With effect sizes, a proper significance test for the number of PCs, a cross-validated classifier, and a more measured abstract, the paper would be a useful reference for people building automated classifiers for NIR variability surveys. As it stands, the analysis is workmanlike but the claims outrun the support.

Referee Report

4 major / 6 minor

Summary. The paper presents an unsupervised statistical pipeline for Classical Cepheid near-infrared light curves. Using 131 fundamental-mode Cepheids from Monson and Pierce (2011), the authors phase each J, H, and K light curve, resample it onto 20 phase points, and represent every curve as a vector in a 20-dimensional space. They apply principal component analysis, retain the first six eigenvectors, cluster the objects with partitioning around medoids, and compare the resulting PC scores with period, absolute magnitude, amplitude, and metallicity using Spearman correlations and Kruskal-Wallis tests. They also use linear discriminant analysis to separate DCEP and DCEPS types and assign posterior classification probabilities. The headline claims are that NIR JHK light curves are insufficient for metallicity determination and that stellar mass is the key physical parameter shaping the light curves.

Significance. If the central claims are correct, the pipeline has practical value for automatic classification and dimensionality reduction of large, dust-obscured Cepheid samples from NIR surveys, where spectroscopy is unavailable. The paper has genuine strengths: the PCA is unsupervised, the physical parameters are taken from external catalogs, the clustering step is checked with jackknife resampling, and the R routines are listed explicitly, which aids reproducibility. The metallicity claim is falsifiable and of interest to survey calibrations. However, the headline conclusion that mass is the key factor shaping the light curves rests on a causal interpretation of correlations that the paper itself later qualifies, and the DCEP/DCEPS classifier is presented without validation. The manuscript's methodological core is defensible, but the load-bearing interpretive steps need additional support.

major comments (4)

[Section 5.1] The derivation of the mass scaling is not consistent with the equations as written. Substituting log R = 1.068 + 0.767 log P (Gieren et al. 1989) into log P = 1.86 log R - 0.8 log M - 1.7 (Bono et al. 2001) gives log P ≈ -0.67 + 1.88 log M, so P ∝ M^1.88, not P ∝ M^2.1; the value 2.1 is recovered only if the intercepts are dropped. More importantly, the resulting P-M relation is a period-mass relation, not a relation between mass and light-curve shape. Period, absolute magnitude, and amplitude are strongly inter-correlated (Figures 9, 11, 13), so the PC1/PC2 correlations in Tables 3-5 do not single out mass as the unique hidden variable. Section 5.6 later concedes that the hidden statistical variable is not necessarily identical to mass. To support the abstract's claim that mass is the key factor, the authors need either a direct test, such as partial correlations controlling for period, or a comparison with independent mass estimates, or they should soften the claim.
[Section 4, Figure 2, Table 1] The selection of six significant eigenvalues is asserted without a formal significance test. The cumulative proportions in Table 1 show that six PCs explain roughly 86-91 percent of the variance, and Figure 2 shows an inflection, but there is no null model, no confidence intervals, no parallel analysis, and no broken-stick or cross-validated criterion. The statement in Section 7 that 'six eigenvalues differed significantly from the purely random case' is therefore unsupported. This matters because the distance in Equation (4) and all subsequent clustering and correlation analyses depend on the number of retained PCs. The authors should justify the truncation with an explicit statistical criterion or demonstrate that the conclusions are robust to retaining 5 or 7 PCs.
[Section 5.4, Table 6] The claim that NIR light curves are insufficient for metallicity determination is stronger than the reported statistics support. Table 6 gives only p-values, and several are significant at conventional levels: J PC1 p = 0.001, J PC3 p = 0.008, H PC3 p = 0.004, K PC2 p = 0.003. A p-value indicates whether a correlation is detectably nonzero, not whether it is astrophysically useful. To support the conclusion that the metallicity signal is negligible, the authors should report Spearman rank correlation coefficients, the scatter of the PC-metallicity relations, and ideally a cross-validated estimate of how well [Fe/H] can be predicted from the PCs. Without these, the blanket statement that JHK curves are 'insufficient for determination of stellar metallicity' is not quantitatively established.
[Section 5.7, Figures 17-18] The DCEP/DCEPS classifier is trained and evaluated on the same 131 stars, with only four DCEPS objects. The LDA direction and the likelihoods in Figures 17 and 18 are computed from the full sample, so the clean separation is expected regardless of whether the classification generalizes. The final sentence of Section 5.7 claims that the posterior probabilities can be used for classifying newly observed Cepheids, but no holdout validation is provided. A leave-one-out cross-validation or a split-sample analysis is necessary, together with a confusion matrix or misclassification rate, before this claim can be accepted. This issue also affects the paper's broader claim that the method can be used in automatic classification pipelines.

minor comments (6)

[Section 4] Equation (1) defines a chi-square-like distance using variances sigma_i^2, but the paper does not explain how sigma_i is estimated after the spline interpolation and phase resampling; please specify the procedure.
[Section 4] The text says the light curves are normalized in amplitude, but the normalization is not described precisely. If amplitude is divided out before PCA, the amplitude correlations in Table 5 and Figure 12 are correlations between normalized shape and amplitude, which should be stated explicitly.
[Table 2] The jackknife distribution for the K band is not strongly peaked at 7: it gives 64 of 131 samples at 7 groups and 39 at 10 groups. The statement that the optimal number of partitions is 7 'in each color' should be tempered by reporting this bimodality.
[Abstract and Section 5.4] The abstract says metallicity effects are 'only marginal' in H and K, while Section 5.4 reports significant J-band correlations; the wording should be harmonized so that the J-band sensitivity is not understated.
[Section 7] There is a typo in 'multivariate satisical study' that should be corrected.
[Section 5.5] The test name 'Kruscal-Wallis' should be 'Kruskal-Wallis', and the software should be cited consistently with the other R packages.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the PCA-based correlations are genuine comparisons against externally cataloged physical parameters, and the mass attribution is an interpretive inference rather than a reduction of the derivation to its inputs.

full rationale

The core derivation chain is self-contained. The 20-dimensional light-curve vectors are obtained by spline interpolation of Monson & Pierce (2011) photometry; PCA is unsupervised and makes no use of the physical parameters. Periods, absolute magnitudes, amplitudes, and metallicities are taken from external catalogs (Berdnikov et al., Groenewegen, Gaia DR2, etc.), so the Spearman correlations in Tables 3-6 are genuine comparisons of PCA scores to independently measured quantities. The 'mass is the key factor' claim is an interpretive step in Sections 5.1-5.3: it combines the external Gieren et al. (1989) period-radius relation with the external Bono et al. (2001) period-mass-radius relation and then identifies the common hidden variable as mass. Those relations are not defined in terms of the light curves or the PCs, so the inference is not circular, although it is underdetermined and even hedged in Section 5.6 where the authors state the hidden statistical variable 'is not necessarily identical' to mass. The only self-citation (Kovács et al. 2023) supports a background statement about metallicity influencing flux transport and is not load-bearing; removing it would not alter the analysis. The DCEP/DCEPS discrimination in Section 5.7 is presented as a demonstration without holdout evaluation, which is an overfitting concern rather than a circularity. The arithmetic slip in deriving P ∝ M^2.1 (the quoted relations give ~M^1.88) is a correctness risk, not a circularity. No equation or fitted parameter is redefined as a prediction, and no load-bearing claim reduces to a self-citation.

Assumptions & free parameters 5 free parameters · 4 assumptions · 0 invented entities

The paper introduces no new physical entities. Its free parameters are analytical choices: the number of retained PCs, the phase sampling resolution, the spline smoothing default, the amplitude normalization, and the cluster count. The axioms are standard astronomical assumptions about periodicity, published period-mass relations, and the reliability of external metallicity catalogs. None of these are ad hoc inventions, but the mass-dominance interpretation depends heavily on the literature relations.

free parameters (5)

Number of principal components retained = 6
Chosen to explain about 90% of total variance; no formal significance test is provided (Section 4, Table 1).
Number of phase sampling points = 20
Fixed sampling of spline-fitted light curves; arbitrary but affects the PCA representation (Section 4).
Spline smoothing parameter = R default (smooth.spline)
The default smoothing is used without stated tuning; this affects the 20 phase-point values that define the parameter space (Section 4).
Amplitude normalization = normalized to unit amplitude
All light curves are normalized in amplitude before PCA, yet the original amplitude is later used as a physical parameter; the paper notes this is non-trivial in Section 7.
Number of clusters = 7
Determined by pamk() with the silhouette method; the jackknife in Table 2 shows that in K color the value 10 occurs almost as often as 7, so the choice is not strongly stable.

assumptions (4)

domain assumption Classical Cepheid light curves are strictly periodic and can be represented by 20 phase points after spline interpolation.
Invoked in Section 4 before PCA; ignores possible period changes, additional modes, or short-timescale stochastic variation.
domain assumption The period-radius and period-mass relations of Gieren et al. (1989) and Bono et al. (2001) hold for this sample and justify interpreting the PC correlations as a mass effect.
Used in Section 5.1 to derive P ∝ M^2.1; this literature chain is the only evidence connecting the observed correlations to mass.
domain assumption Correlations between PCs and physical parameters are meaningful despite the light curves being amplitude-normalized before PCA.
The paper flags this as non-trivial in Section 7 but does not prove that amplitude information survives the normalization in a way that makes the amplitude correlations interpretable.
domain assumption Metallicity values from Groenewegen (2018) are accurate enough for the correlation analysis.
Metallicities are taken as external data without propagating their uncertainties into the Spearman correlations (Section 4).

how reviews work

0 comments

Cite this review

Pith. "Pith review of Estimation of Classical Cepheid's Physical Parameters from NIR Light Curves." pith.science (2026). https://pith.science/paper/2F63HZWG

@misc{pith2026241206386,
  author       = {Pith},
  title        = {Pith review of: Estimation of Classical Cepheid's Physical Parameters from NIR Light Curves},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/2F63HZWG}},
  note         = {Machine review of arXiv:2412.06386}
}

read the original abstract

Recent space-borne and ground-based observations provide photometric measurements as time series. The effect of interstellar dust extinction in the near-infrared range is only 10% of that measured in the V band. However, the sensitivity of the light curve shape to the physical parameters in the near-infrared is much lower. So, interpreting these types of data sets requires new approaches like the different large-scale surveys, which create similar problems with big data. Using a selected data set, we provide a method for applying routines implemented in R to extract most information of measurements to determine physical parameters, which can also be used in automatic classification schemes and pipeline processing. We made a multivariate classification of 131 Cepheid light curves (LC) in J, H, and K colors, where all the LCs were represented in 20D parameter space in these colors separately. Performing a Principal Component Analysis (PCA), we got an orthogonal coordinate system and squared Euclidean distances between LCs, with 6 significant eigenvalues, reducing the 20-dimension to 6. We also estimated the optimal number of partitions of similar objects and found it to be equal to 7 in each color; their dependence on the period, absolute magnitude, amplitude, and metallicity are also discussed. We computed the Spearman rank correlations, showing that periods and absolute magnitudes correlate with the first three PCs significantly. The first two PC are also found to have a relationship with the amplitude, but the metallicity effects are only marginal. The method shown can be generalized and implemented in unsupervised classification schemes and analysis of mixed and biased samples. The analysis of our Classical Cepheid near-infrared LC sample showed that the J, H, K curves are insufficient for determination of stellar metallicity, with mass being the key factor shaping them.

Figures

Figures reproduced from arXiv: 2412.06386 by the authors.

**Figure 1.** Typical light curves of a Cepheid (𝜂 Aql) in different photometric bands; the data are taken from (Wisniewski and Johnson, 1968) . Unfortunately, the theoretical side of the problem based on recent pulsation codes that treat the nonlinear dynamics of classical radial pulsators cannot directly provide the observable photometric light curves, only the bolometric one. However, static atmosphere models could be applied… view at source ↗

**Figure 2.** Eigenvalues resulted in the PCA in descending order. The first two eigenvalues are followed by a rapid value decrease with an inflection at about 5. The first 6 eigenvalues are kept for further study. Color PC1 PC2 PC3 PC4 PC5 PC6 J 0.432 0.792 0.844 0.874 0.898 0.914 H 0.482 0.816 0.852 0.872 0.890 0.907 K 0.463 0.748 0.787 0.817 0.841 0.864 [PITH_FULL_IMAGE:figures/full_fig_p006_2.png] view at source ↗

**Figure 3.** Elements of the eigenvectors (loadings) displayed as the function of the phase. They can be considered as templates for reproducing the observed LCs in the J color as linear combinations. 0.0 0.5 1.0 1.5 2.0 0.6 0.2 −0.2 −0.6 phase loading PC1 0.0 0.5 1.0 1.5 2.0 0.6 0.2 −0.2 −0.6 phase loading PC2 0.0 0.5 1.0 1.5 2.0 0.6 0.2 −0.2 −0.6 phase loading PC3 0.0 0.5 1.0 1.5 2.0 0.6 0.2 −0.2 −0.6 phase loading PC4 0.0 0.5… view at source ↗

Figures from the paper (11 more)

**Figure 4.** Figure 4: The same as [PITH_FULL_IMAGE:figures/full_fig_p006_4.png]

**Figure 5.** Figure 5: The same as [PITH_FULL_IMAGE:figures/full_fig_p007_5.png]

**Figure 6.** Figure 6: Typical LCs (medoids) in the J color. The frequency of medoids is given in the bar chart at the bottom right. Note that the clustering algorithm somewhat arbitrarily gives the serial number of a medoid, and it does not necessarily have any further physical meaning. (Th…

**Figure 9.** Figure 9: Dependence of the LC PC1 and PC2 principal components on the period in J,H, and K colors. These two PCs have the largest contribution to shaping the LCs. See the drastic change in the distribution of PC1 values over the period of 10 days, in particular in the H and K c…

**Figure 10.** Figure 10: Dependence of the LC PC1 and PC2 principal components on the absolute magnitudes in J,H, and K colors. Note the drastic change of the point pattern at about -6 Mag. in H and K colors. 0.0 0.5 1.0 1.5 2.0 −3 −5 −7 −9 log10(P) MJ (mag) 0.0 0.5 1.0 1.5 2.0 −3 −5 −7 −9 lo…

**Figure 11.** Figure 11: Period - absolute magnitude relationships in J,H, and K colors. The close linear correlation between these two quantities is fundamental in setting up the cosmological distance scale [PITH_FULL_IMAGE:figures/full_fig_p010_11.png]

**Figure 12.** Figure 12: Dependence of the LC PC1 and PC2 principal components on the Amplitude in J,H and K colors. 0.4 0.8 1.2 1.6 0.2 0.3 0.4 0.5 0.6 log10(P) Jamp 0.4 0.8 1.2 1.6 0.2 0.3 0.4 0.5 0.6 log10(P) Hamp 0.4 0.8 1.2 1.6 0.2 0.3 0.4 0.5 0.6 log10(P) Kamp [PITH_FULL_IMAGE:figures/…

**Figure 14.** Figure 14: Dependence of the LC PC1 and PC2 principal components on Fe/H in J,H and K colors. general distributions of the point patterns in [PITH_FULL_IMAGE:figures/full_fig_p011_14.png]

**Figure 15.** Figure 15: Colored display of the cross-correlations of LCs’ physical parameters with the significant discriminant functions in J,H,K colors obtained in the linear discriminant analysis (LDA). The size and tone of the circles indicate the strength of correlations. The blue color…

**Figure 16.** Figure 16: Scatterplot of PC1 and PC2 principal components in J,H and K colors. DCEPS stars are at the lower left edge of the DCEP distribution. means in J,H,K colors. Seemingly, in their DCEP, DCEPS’ group means have the most significant difference in PC1 and PC2 coordinates […

**Figure 17.** Figure 17: Probability density of DCEP and DCEPS stars along the best discriminating direction yielded by LDA in the PCs’ parameter space. 𝑃 (𝑇 𝑦𝑝𝑒|𝑃 𝐶) = 𝑃 (𝑃 𝐶|𝑇 𝑦𝑝𝑒)𝑃 (𝑇 𝑦𝑝𝑒) 𝑃 (𝑃 𝐶) (5) 6. Conclusions The parameters determining a star’s static or dynamic behavior are to be e…

Discussion (0). Continue with ORCID to comment.

Reference graph

Works this paper leans on

51 extracted references · 34 canonical work pages

[1]

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 global.max substring 't := if while FUNCTION word.in bbl.in ":" * " " * FUNCTION f...
[2]

, year 1988

author Andreasen , G.K. , year 1988 . title Precise Fourier decomposition parameters for classical Cepheids. journal volume 196 , pages 159--172

work page 1988
[3]

, author Poretti , E

author Antonello , E. , author Poretti , E. , author Reduzzi , L. , year 1990 . title The separation of s-Cepheids from classical Cepheids and a new definition of the class. journal volume 236 , pages 138

work page 1990
[4]

, author Dambis , A.K

author Berdnikov , L.N. , author Dambis , A.K. , author Vozyakova , O.V. , year 2000 a. title Galactic Cepheids. Catalogue of light-curve parameters and distances . journal volume 143 , pages 211--213 . :10.1051/aas:2000177

doi:10.1051/aas:2000177 2000
[5]

, author Dambis , A.K

author Berdnikov , L.N. , author Dambis , A.K. , author Vozyakova , O.V. , year 2000 b. title VizieR Online Data Catalog: Galactic Cepheids BVRI photometry (Berdnikov+, 2000) . journal VizieR Online Data Catalog , pages J/A+AS/143/211

work page 2000
[6]

, author Brett , J.M

author Bessell , M.S. , author Brett , J.M. , year 1988 . title JHKLM Photometry: Standard Systems, Passbands, and Intrinsic Colors . journal volume 100 , pages 1134 . :10.1086/132281

doi:10.1086/132281 1988
[7]

Multiwavelength light curve analysis of Cepheid variables

author Bhardwaj , A. , author Kanbur , S.M. , author Marconi , M. , author Singh , H.P. , author Rejkuba , M. , author Ngeow , C.C. , year 2018 . title Multiwavelength light curve analysis of Cepheid variables . journal arXiv e-prints , pages arXiv:1806.06533 http://arxiv.org/abs/1806.06533 arXiv:1806.06533

work page Pith review arXiv 2018
[8]

On the Variation of Fourier Parameters for Galactic and LMC Cepheids at Optical, Near-Infrared and Mid-Infrared Wavelengths

author Bhardwaj , A. , author Kanbur , S.M. , author Singh , H.P. , author Macri , L.M. , author Ngeow , C.C. , year 2015 . title On the variation of Fourier parameters for Galactic and LMC Cepheids at optical, near-infrared and mid-infrared wavelengths . journal volume 447 , pages 3342--3360 . :10.1093/mnras/stu2678, http://arxiv.org/abs/1412.4891 arXiv:...

work page Pith review arXiv 2015

Show all 51 references

[9]

, author Kanbur , S.M

author Bhardwaj , A. , author Kanbur , S.M. , author Singh , H.P. , author Macri , L.M. , author Ngeow , C.C. , year 2017 . title VizieR Online Data Catalog: Galactic and LMC Cepheids Fourier parameters (Bhardwaj+, 2015) . journal VizieR Online Data Catalog , pages J/MNRAS/447/3342

2017
[10]

, author Marconi , M

author Bhardwaj , A. , author Marconi , M. , author Rejkuba , M. , author de Grijs , R. , author Singh , H.P. , author Braga , V.F. , author Kanbur , S. , author Ngeow , C.C. , author Ripepi , V. , author Bono , G. , author De Somma , G. , author Dall'Ora , M. , year 2023 . ti...

2023 arXiv
[11]

, author Gieren , W.P

author Bono , G. , author Gieren , W.P. , author Marconi , M. , author Fouqu \'e , P. , author Caputo , F. , year 2001 . title Improving the Mass Determination of Galactic Cepheids . journal volume 563 , pages 319--324 . :10.1086/323834, http://arxiv.org/abs/astro-ph/0108271 a...

2001 arXiv
[12]

, author de Grijs , R

author Chen , X. , author de Grijs , R. , author Deng , L. , year 2017 . title New open cluster Cepheids in the VVV survey tightly constrain near-infrared period-luminosity relations . journal volume 464 , pages 1119--1126 . :10.1093/mnras/stw2390

2017 doi
[13]

, year 1980

author Cox , A.N. , year 1980 . title The masses of Cepheids . journal volume 18 , pages 15--41 . :10.1146/annurev.aa.18.090180.000311

1980
[14]

, author Singh , H.P

author Deb , S. , author Singh , H.P. , year 2009 . title Light curve analysis of variable stars using Fourier decomposition and principal component analysis . journal volume 507 , pages 1729--1737 . :10.1051/0004-6361/200912851, http://arxiv.org/abs/0903.3500 arXiv:0903.3500

2009 arXiv
[15]

, year 1964

author Deeming , T.J. , year 1964 . title Stellar spectral classification, I. journal volume 127 , pages 493 . :10.1093/mnras/127.6.493

1964 doi
[16]

, year 1926

author Eddington , A.S. , year 1926 . title The Internal Constitution of the Stars . publisher Cambridge University Press

1926
[17]

, author Babu , G.J

author Feigelson , E.D. , author Babu , G.J. , year 2012 . title Modern statistical methods for astronomy : with R applications . publisher Cambridge University Press

2012
[18]

, author Lemasle , B

author Genovali , K. , author Lemasle , B. , author da Silva , R. , author Bono , G. , author Fabrizio , M. , author Bergemann , M. , author Buonanno , R. , author Ferraro , I. , author Francois , P. , author Iannicola , G. , author Inno , L. , author Laney , C.D. , author Kud...

2015
[19]

, author Barnes , Thomas G., I

author Gieren , W.P. , author Barnes , Thomas G., I. , author Moffett , T.J. , year 1989 . title The Period-Radius Relation for Classical Cepheids from the Visual Surface Brightness Technique . journal volume 342 , pages 467 . :10.1086/167606

1989 doi
[20]

, year 2018

author Groenewegen , M.A.T. , year 2018 . title VizieR Online Data Catalog: Cepheid period-luminosity-metallicity relation (Groenewegen, 2018) . journal VizieR Online Data Catalog , pages J/A+A/619/A8

2018
[21]

, year 1926

author Hertzsprung , E. , year 1926 . title On the relation between period and form of the light-curve of variable stars of the Cephei type . journal Bulletin of the Astronomical Institutes of the Netherlands volume 3 , pages 115

1926
[22]

, year 1925

author Hubble , E.P. , year 1925 . title Cepheids in spiral nebulae . journal The Observatory volume 48 , pages 139--142

1925
[23]

, year 1929

author Hubble , E.P. , year 1929 . title A Relation between Distance and Radial Velocity among Extra-Galactic Nebulae . journal Contributions from the Mount Wilson Observatory volume 3 , pages 23--28

1929
[24]

, author Matsunaga , N

author Inno , L. , author Matsunaga , N. , author Romaniello , M. , author Bono , G. , author Monson , A. , author Ferraro , I. , author Iannicola , G. , author Persson , E. , author Buonanno , R. , author Freedman , W. , author Gieren , W. , author Groenewegen , M.A.T. , auth...

2015 arXiv
[25]

, author Urbaneja , M.A

author Inno , L. , author Urbaneja , M.A. , author Matsunaga , N. , author Bono , G. , author Nonino , M. , author Debattista , V.P. , author Sormani , M.C. , author Bergemann , M. , author da Silva , R. , author Lemasle , B. , author Romaniello , M. , author Rix , H.W. , year...

2019 arXiv
[26]

, author Connolly , A.J

author Ivezic , Z. , author Connolly , A.J. , author VanderPlas , J.T. , author Gray , A. , year 2014 . title Statistics, Data Mining, and Machine Learning in Astronomy . publisher Princeton University Press

2014
[27]

, author Iono , D

author Kanbur , S.M. , author Iono , D. , author Tanvir , N.R. , author Hendry , M.A. , year 2002 . title On the use of Principal Component Analysis in analysing Cepheid light curves . journal volume 329 , pages 126--134 . :10.1046/j.1365-8711.2002.04948.x, http://arxiv.org/ab...

2002
[28]

, author Rousseeuw, P.J

author Kaufman, L. , author Rousseeuw, P.J. , year 1990 . title Finding Groups in Data: An Introduction to Cluster Analysis. publisher John Wiley

1990
[29]

, author Szabados , L

author Klagyivik , P. , author Szabados , L. , author Szing , A. , author Leccia , S. , author Mowlavi , N. , year 2013 . title Determination of the iron content of Cepheids from the shape of their light curves . journal volume 434 , pages 2418--2425 . :10.1093/mnras/stt1176, ...

2013 arXiv
[30]

, author Nuspl , J

author Kov \'a cs , G.B. , author Nuspl , J. , author Szab \'o , R. , year 2023 . title Calibration of the convective parameters in stellar pulsation hydrocodes . journal volume 521 , pages 4878--4895 . :10.1093/mnras/stad884, http://arxiv.org/abs/2303.12049 arXiv:2303.12049

2023 arXiv
[31]

, author Wallis, W.A

author Kruskal, W.H. , author Wallis, W.A. , year 1952 . title Use of ranks in one-criterion variance analysis . journal Journal of the American Statistical Association volume 47 , pages 583--621 . https://www.tandfonline.com/doi/abs/10.1080/01621459.1952.10483441, :10.1080/01...

1952
[32]

, year 1966

author Lanczos , C. , year 1966 . title Discours on Fourier Series . publisher Oliver and Boyd

1966
[33]

, author Pickering , E.C

author Leavitt , H.S. , author Pickering , E.C. , year 1912 . title Periods of 25 Variable Stars in the Small Magellanic Cloud. journal Harvard College Observatory Circular volume 173 , pages 1--3

1912
[34]

, year 2019

author Luck , R.E. , year 2019 . title VizieR Online Data Catalog: Cepheid abund.: multiphase results & spatial gradients (Luck, 2018) . journal VizieR Online Data Catalog , pages J/AJ/156/171

2019
[35]

, author Brown , A.G.A

author Luri , X. , author Brown , A.G.A. , author Sarro , L.M. , author Arenou , F. , author Bailer-Jones , C.A.L. , author Castro-Ginard , A. , author de Bruijne , J. , author Prusti , T. , author Babusiaux , C. , author Delgado , H.E. , year 2018 . title Gaia Data Release 2....

2018 arXiv
[36]

, year 1967

author MacQueen, J. , year 1967 . title Some methods for classification and analysis of multivariate observations , in: booktitle Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, Volume 1: Statistics , publisher University of California P...

1967
[37]

, author Taniguchi , D

author Matsunaga , N. , author Taniguchi , D. , author Elgueta , S.S. , author Tsujimoto , T. , author Baba , J. , author McWilliam , A. , author Otsubo , S. , author Sarugaku , Y. , author Takeuchi , T. , author Katoh , H. , author Hamano , S. , author Ikeda , Y. , author Kaw...

2023 arXiv
[38]

, author Pierce , M.J

author Monson , A.J. , author Pierce , M.J. , year 2011 . title Near-infrared (JHK) Photometry of 131 Northern Galactic Classical Cepheids . journal volume 193 , pages 12 . :10.1088/0067-0049/193/1/12

2011 doi
[39]

, author Gieren , W

author Nardetto , N. , author Gieren , W. , author Storm , J. , author Hocd \'e , V. , author Pietrzy \'n ski , G. , author Kervella , P. , author M \'e rand , A. , author Gallenne , A. , author Graczyk , D. , author Pilecki , B. , author Poretti , E. , author Rainer , M. , au...

2023 arXiv
[40]

, author Kanbur , S.M

author Ngeow , C. , author Kanbur , S.M. , year 2006 a. title VizieR Online Data Catalog: Fourier parameters for Cepheid variables (Ngeow+, 2006) . journal VizieR Online Data Catalog , pages J/MNRAS/369/723

2006
[41]

, author Kanbur , S.M

author Ngeow , C. , author Kanbur , S.M. , year 2006 b. title VizieR Online Data Catalog: Fourier parameters for Cepheid variables (Ngeow+, 2006) . journal VizieR Online Data Catalog , pages J/MNRAS/369/723

2006
[42]

, author Bhardwaj , A

author Ngeow , C.C. , author Bhardwaj , A. , author Macri , L.M. , author Kanbur , S.M. , year 2018 . title Large Magellanic Cloud Near-Infrared Synoptic Survey (LMCNISS): Overview and Science Highlights for Classical and Type-II Cepheids , in: editor Jensen , J. (Ed.), bookti...

2018
[43]

, author Kanbur , S

author Ngeow , C.C. , author Kanbur , S. , year 2004 . title Reconstructing Cepheid Light Curve with Fourier Techniques II: Catalogue of the Fourier Parameters for OGLE LMC Fundamental Mode Cepheids . journal arXiv e-prints , pages astro--ph/0408452 http://arxiv.org/abs/astro-...

2004
[44]

, author Kanbur , S.M

author Ngeow , C.C. , author Kanbur , S.M. , author Nikolaev , S. , author Tanvir , N.R. , author Hendry , M.A. , year 2003 . title Reconstructing a Cepheid Light Curve with Fourier Techniques. I. The Fourier Expansion and Interrelations . journal volume 586 , pages 959--982 ....

2003 arXiv
[45]

title R: A Language and Environment for Statistical Computing

author R Core Team , year 2021 . title R: A Language and Environment for Statistical Computing . organization R Foundation for Statistical Computing . address Vienna, Austria . https://www.R-project.org/

2021
[46]

, author Lee , A.S

author Simon , N.R. , author Lee , A.S. , year 1981 . title The structural properties of cepheid light curves. journal volume 248 , pages 291--297 . :10.1086/159153

1981 doi
[47]

, author Das , S

author Singh , H.P. , author Das , S. , author Bhardwaj , A. , author Kanbur , S. , author Marconi , M. , year 2019 . title Light Curve Parameters of Cepheid and RR Lyrae Variables at Multiple Wavelengths - Models vs. Observations . journal arXiv e-prints , pages arXiv:1904.08...

2019 arXiv
[48]

, author Hoare , M.G

author Stead , J.J. , author Hoare , M.G. , year 2009 . title The slope of the near-infrared extinction law . journal volume 400 , pages 731--742 . :10.1111/j.1365-2966.2009.15530.x, http://arxiv.org/abs/0908.1601 arXiv:0908.1601

2009
[49]

, author Chen , B

author Sun , M. , author Chen , B. , author Guo , H. , author Zhao , H. , author Yang , M. , author Cui , W. , year 2023 . title SPar: Estimating Stellar Parameters from Multiband Photometries with Empirical Stellar Libraries . journal volume 166 , pages 126 . :10.3847/1538-38...

2023 arXiv
[50]

, author Hendry , M.A

author Tanvir , N.R. , author Hendry , M.A. , author Watkins , A. , author Kanbur , S.M. , author Berdnikov , L.N. , author Ngeow , C.C. , year 2005 . title Determination of Cepheid parameters by light-curve template fitting . journal volume 363 , pages 749--762 . :10.1111/j.1...

2005
[51]

, author Johnson , H.L

author Wisniewski , W.Z. , author Johnson , H.L. , year 1968 . title UBVRIJKL Light Curves of Classical Cepheids . journal Communications of the Lunar and Planetary Laboratory volume 7 , pages 57--78

1968

Pith tools

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

[1] [1]

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 global.max substring 't := if while FUNCTION word.in bbl.in ":" * " " * FUNCTION f...

[2] [2]

, year 1988

author Andreasen , G.K. , year 1988 . title Precise Fourier decomposition parameters for classical Cepheids. journal volume 196 , pages 159--172

work page 1988

[3] [3]

, author Poretti , E

author Antonello , E. , author Poretti , E. , author Reduzzi , L. , year 1990 . title The separation of s-Cepheids from classical Cepheids and a new definition of the class. journal volume 236 , pages 138

work page 1990

[4] [4]

, author Dambis , A.K

author Berdnikov , L.N. , author Dambis , A.K. , author Vozyakova , O.V. , year 2000 a. title Galactic Cepheids. Catalogue of light-curve parameters and distances . journal volume 143 , pages 211--213 . :10.1051/aas:2000177

doi:10.1051/aas:2000177 2000

[5] [5]

, author Dambis , A.K

author Berdnikov , L.N. , author Dambis , A.K. , author Vozyakova , O.V. , year 2000 b. title VizieR Online Data Catalog: Galactic Cepheids BVRI photometry (Berdnikov+, 2000) . journal VizieR Online Data Catalog , pages J/A+AS/143/211

work page 2000

[6] [6]

, author Brett , J.M

author Bessell , M.S. , author Brett , J.M. , year 1988 . title JHKLM Photometry: Standard Systems, Passbands, and Intrinsic Colors . journal volume 100 , pages 1134 . :10.1086/132281

doi:10.1086/132281 1988

[7] [7]

Multiwavelength light curve analysis of Cepheid variables

author Bhardwaj , A. , author Kanbur , S.M. , author Marconi , M. , author Singh , H.P. , author Rejkuba , M. , author Ngeow , C.C. , year 2018 . title Multiwavelength light curve analysis of Cepheid variables . journal arXiv e-prints , pages arXiv:1806.06533 http://arxiv.org/abs/1806.06533 arXiv:1806.06533

work page Pith review arXiv 2018

[8] [8]

On the Variation of Fourier Parameters for Galactic and LMC Cepheids at Optical, Near-Infrared and Mid-Infrared Wavelengths

author Bhardwaj , A. , author Kanbur , S.M. , author Singh , H.P. , author Macri , L.M. , author Ngeow , C.C. , year 2015 . title On the variation of Fourier parameters for Galactic and LMC Cepheids at optical, near-infrared and mid-infrared wavelengths . journal volume 447 , pages 3342--3360 . :10.1093/mnras/stu2678, http://arxiv.org/abs/1412.4891 arXiv:...

work page Pith review arXiv 2015