2005Unpublished venueOpen access

Determination of Cepheid parameters by light-curve template fitting

N. R. Tanvir, M. A. Hendry, A. Watkins, S. M. Kanbur, L. N. Berdnikov, C. C. Ngeow

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Abstract

Determining the parameters (periods, mean magnitudes etc.) of periodic variable stars is a frequently met problem in astronomy. Here we describe techniques to characterise the light-curves of regular variables by applying principal component analysis (PCA) to a training set of high quality data, and to fit the resulting light-curve templates to sparse and noisy photometry. The PCA approach allows us to efficiently represent the multi-band light-curve shapes of each variable, and hence quantitatively describe the average behaviour of the sample as a smoothly varying function of period, and also the range of variation around this average. In this paper we focus particularly on the utility of such methods for analysing HST Cepheid photometry, and present simulations which illustrate the advantages of our PCA template-fitting approach. These are: accurate parameter determination, including light-curve shape information; simultaneous fitting to multiple passbands; quantitative error analysis; objective rejection of variables with non Cepheid-like lightcurves or those with potential period aliases. We also use PCA to confirm that Cepheid light-curve shapes are systematically different (at the same period) between the Milky Way (MW) and the Large and Small Magellanic Clouds (LMC, SMC), and consider whether light-curve shape might therefore be used to estimate the mean metallicities of Cepheid samples, thus allowing metallicity corrections to be applied to derived distance estimates. Key words: Cepheids, variable stars – general 1

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What this paper is about

Determining the parameters (periods, mean magnitudes etc.) of periodic variable stars is a frequently met problem in astronomy. Here we describe techniques to characterise the light-curves of regular variables by applying principal component analysis (PCA) to a training set of high quality data, and to fit the resulting light-curve templates to sparse and noisy photometry. The PCA approach allows us to efficiently represent the multi-band light-curve shapes of each variable, and hence quantitatively describe the average behaviour of the sample as a smoothly varying function of period, and also the range of variation around this average. In this paper we focus particularly on the utility of such methods for analysing HST Cepheid photometry, and present simulations which illustrate the advantages of our PCA template-fitting approach. These are: accurate parameter determination, including light-curve shape information; simultaneous fitting to multiple passbands; quantitative error analysis; objective rejection of variables with non Cepheid-like lightcurves or those with potential period aliases. We also use PCA to confirm that Cepheid light-curve shapes are systematically different (at the same period) between the Milky Way (MW) and the Large and Small Magellanic Clouds (LMC, SMC), and consider whether light-curve shape might therefore be used to estimate the mean metallicities of Cepheid samples, thus allowing metallicity corrections to be applied to derived distance estimates. Key words: Cepheids, variable stars – general 1

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Available abstract

Determining the parameters (periods, mean magnitudes etc.) of periodic variable stars is a frequently met problem in astronomy. Here we describe techniques to characterise the light-curves of regular variables by applying principal component analysis (PCA) to a training set of high quality data, and to fit the resulting light-curve templates to sparse and noisy photometry. The PCA approach allows us to efficiently represent the multi-band light-curve shapes of each variable, and hence quantitatively describe the average behaviour of the sample as a smoothly varying function of period, and also the range of variation around this average. In this paper we focus particularly on the utility of such methods for analysing HST Cepheid photometry, and present simulations which illustrate the advantages of our PCA template-fitting approach. These are: accurate parameter determination, including light-curve shape information; simultaneous fitting to multiple passbands; quantitative error analysis; objective rejection of variables with non Cepheid-like lightcurves or those with potential period aliases. We also use PCA to confirm that Cepheid light-curve shapes are systematically different (at the same period) between the Milky Way (MW) and the Large and Small Magellanic Clouds (LMC, SMC), and consider whether light-curve shape might therefore be used to estimate the mean metallicities of Cepheid samples, thus allowing metallicity corrections to be applied to derived distance estimates. Key words: Cepheids, variable stars – general 1

Key concepts: Cepheid variable, Physics, Light curve, Astrophysics, Astronomy, Curve fitting, Statistics, Stars

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