Hipparcos Mira Variable Stars

Hipparcos Mira Variable Stars

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Hipparcos Mira Variable Stars


ABSTRACT

From the visual and infrared light curves we are trying to find the phase changes and correlate them to Infrared shift and magutdes to see what is happing to Mira type stars as they age. Most of the radiation in the star is in the Infrared. The method being used O-C and fitting mean light curves. All mira variables pulsate undergoing rapid mass loss. In the conclusion we show that the magnitude has a positive correlation with the phase shift.

I.Introduction

Studies of Mira variables are of considerable importance in stellar astrophysics because they are pulsating stars undergoing rapid mass loss. During one cycle, which typically lasts from 200-500 days, these stars undergo significant changes in their observable properties. At some point in their lives, many if not most stars go through an unstable phase that leads to pulsation. They are evolving through the tip of the asymptotic giant branch (AGB) in the H-R diagram and are affected by two significant processes. In the interior, helium shell flashes cause large excursions in their luminosity’s and period on a timesscale of ten of thousands of years. In the outer layers, pulsation-enhanced mass loss, which reduces their envelope masses and drives their evolution to the white dwarf. The atmospheres of Mira variables are very deep and there effective diameters change markedly with wavelength because of the opacity effects. The massive
winds of Miras are believed to be driven by a combination of dust formation and shocks induced by stellar pulsation. (Willson). Understanding the nature of shocks and measuring their properties is essential to understanding the physics of pulsation and mass loss from pulsating stars.

This paper presents an analysis of visible and IR (JHKL) data for 2 Long Period Variables (LPV). The four pulsating variables chosen are classified as Miras. All Miras stars are Long period variables that exhibit a very large change in visible light because they are cool (less than or equal to 3000K), and so most of their radiation lies in the infrared. We are studying the Mira stars instead the irregular stars because to understand any star you must first start with the simplest model then expand upon that, Mira are relatively well-behaved long period variable.

II. Data Search

For this study we required stars that had already been studied intensively, so that both IR data and visual data were available for many cycles.

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Related Searches

A search of the SIMBAD database located many useful papers about mass-loss rates and infrared photometry. The American Association of Variable Star Observers (AAVSO) has a long-term program to monitor hundreds of Miras by using observations from amateur astronomers around the world. Using the AAVSO data obtained from the World Wide Web we obtained evaluated visual light curves. The Infrared data was obtained from Patricia Whitelock who works at the South African Astronomical Observatory.

III. Data Analysis

The method used for computing the analysis is fitting mean light curves. To find the mean light curve you must take the regular light curves and the period and epoch. The period is the time interval for some regular event to take place. Epoch is the phase at 0. The period and Epoch was received from General Catalogue of Variable Stars (GCVS) data, which was the most accurate data that could be found. The formula for finding the phase plus the cycle is (Julian Date – Epoch)/Period. Then you take the phase from that by just subtracting the integer from the phase plus cycle. That will superimpose all data in one phase. To get the so-called cardboard cutout, I then take all the points in each bin and get a mean point. That will produce the mean light curve. For the (J, H, K, L) light curve I took 1/10 of a cycle. For the visual light curve 1/20, because there were considerably more points.

In phasing I phased with the most defined structure, if there was no defined structure you must look at the cycle before and after. Usually the best phasing comes when you are fitting it to he rising or falling branch of the curve. Then an O-C (Observed minus Calculated) method to detect the presence of systematic changes in the periods of variable stars. The calculated portion of the O-C is equal to (E+nP). The observed is basically my job to find the amount of shift and subtract it from the calculated-C analysis begins with an assumption that he period is constant. A plot of the residuals is the O-C.

Results:

R Horologii was the most stable star I worked with; in the visible and infrared there was not many random points. The O-C curve showed that the period changes we used early in the star but for more recent data the period we used turns out to be correct. R Hor phase diagram is also shows a positive correlation.

S Pictoris is very different. The regular light curve was not too well defined, and the O-C results were in a positive correlation but not a very high positive correlation. There was a sizable gap in the Infrared data that may have influenced the results. Also in S Pic there were not that many points to phase with, so that in a lot of cycles I had only three points to work with in odd locations on the lightcurve. There were many instances were it was questionable were the phase could go. In the visual phasing of S Pic, in contrast, I had very good phasing thoughout the light curve and very few uncertainties.

After finding all of the phasing for the stars, playing with the data made me think, what if the magnitude had to do with the phase shift, I acted on my idea and plotted a correlation between the magnitude and phase shift. The correlation shows the they are related. I took three of the highest points in the magnitude. The first highest point could be a bad point, the amateur observer may have thought the star was bright, I used the assumption that if two or more people observed the magnitude at about same place that point is real. After doing that the correlation is higher. I also took the Infrared and did the same correlation graph. Again a positive correlation.

In conclusion the method of fitting mean light curves, our results were that we have made a independent discovery of the Harrington effect in a different way. We also used the infrared data to find a postive correlation. The magnitude of the light curve shows directly the phase shift of the cycle. In the future of this project, further testing of this theory and trying to see if the is a pattern that can be used to predict the next cycle phase shift and magnitude.

References

Alvarez, R and Plez, B Near-infrared narrow-band photometry of M-giant and Mira stars: models meet observations Bertre, T Le and Winters, J.M. On the relations between
infrared colors and mass loss for Mira stars Harrington, J. Patrick. Variations in the Maxima of Long Period Variabless P. De Laverny et al.: Long-term UBV (RI) monitoring of 12 Southern Hemisphere Long Period Variables

P.G. Tuthill, W.C. Danchi, D.S. Hale, J.D. Monnier and C.H. Townes NEAR AND MID-INFRARED SUBARCESECOUND STRUCTURE OF THE DUSTY SYMBIOTIC STAR R AQUARII

Tej, Anandmayee, Chandrasekhar, T. Ashok, N.M The Angular diameter of the mira variable R Leonis at 3.36 and 2.2 microns

Wood, B.E and Karovska M. Studying the pulsation of mira variables in the Ultraviolet
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