ROTSE: THE SEARCH FOR SHORT PERIOD VARIABLE STARS

Transcription

1 ROTSE: THE SEARCH FOR SHORT PERIOD VARIABLE STARS COURTNEY FAGG SOUTHERN METHODIST UNIVERSITY Dallas, TX Abstract We present a search for stars that demonstrate rapidly changing visible light curves. The data we have used for this search has been procured from the ROTSE-I and III telescopes archival data of multiple nights in April These thirteen fields cover eight degrees of the night sky, and are observed for at least two continuous hours in one night. By using general statistical properties of the light curves, we were able to narrow our search to obtain clearly-varying light curves. The analysis has shown to be most effective for light curve variations with periods less than 0.3 days that possess magnitudes greater than 0.1 mag., and mean magnitude values varying from 10 mag. to 15 mag. Our search has produced 20 variable star candidates, whose classification will be based solely on their light curve characteristics. We have observed phenomena such as YY δ Scuti and ZZ W UMa stars in our data collection. The presence of these short period variable stars prove the effectiveness of our method of searching. I. Introduction Stars with varying magnitudes (known as variable stars) have interested astronomers for hundreds of years, beginning with the first supernovae with pulsating light variations that were observed and documented. Since then, thousands of variable stars have been 1

2 discovered and classified based on their peculiarities in variation. The observation of these interstellar phenomena have allowed astronomers, both amateur and professional, to learn more about the night sky, as well as the night sky not visible to the unaided eye. Variable stars are grouped into two major categories: intrinsic, whose stars' luminosity varies by pulsating and/or shrinking in size due to physical characteristics, and extrinsic, whose stars appear to vary in magnitude due to an eclipsing companion. Long period variable stars have been studied for many years because of their apparent brightness changes that can be easily observed using a telescope, depending on the magnitudes of variation. The period of these stars can last from weeks up to several years. Most recently discovered have been the short period variable stars, whose periods can last from less than an hour to a few days. These types of variables are more commonly observed today because of their high-energy outputs and unusual light curves. Two examples of these types of variables are the RR Lyraes (period: 0.2 day T 1.0 day) and δ Scutis (period: T > 0.3 day), which are radial pulsators. Eclipsing binary systems containing stars relatively close or touching each other also exhibit short period behavior, and their light curves are generally characterized by a span of higher magnitude with a small dip of lower magnitude. Binary systems of the W UMa type contain stars that are presumably so close in proximity that the surfaces are in contact with one another [1]. The second law of thermodynamics states that the entropy of an isolated system, which is not in equilibrium, will increase until equilibrium is attained. By nature, heat 2

3 transfers from the body of higher temperature to the body of lower temperature, therefore the heat, and thus, luminosity, is transferred from the more massive star to the less massive one until equal temperatures are acquired. According to this law, it would be expected to see a light curve that is similar to binary systems containing separated stars, though with time, the dips in magnitude would become similar in size, corresponding to the equalization of the stars temperature and luminosity. Binary systems with stars whose surfaces do not touch however, such as Algol systems, do not experience this transfer of heat and mass, and therefore should exhibit light curves that show consistent dips in magnitude. Many telescopes, including the Robotic Optical Transient Search Experiment telescopes (ROTSE-I and III) observe these short period variables. The ROTSE telescopes have provided the data used in this report. II. Detector and Data The ROTSE telescopes generate images taken when photons emanating from a light source are focused to an image on an array of cells and sends an electric signal based on the intensity of the source. These signals are usually only a pixel wide, but, for bright stars, can be spilled over to multiple cells, creating an undesirably bright and distorted image. Many different signals can be obtained over the span of one night, and with the use of the operating system Linux and Interface Description Language (IDL), these collected data inputs can be placed together based on magnitude of light intensity versus time, creating a light curve. These small but powerful telescopes are distributed around 3

4 the world for international use. Today, two phases of ROTSE telescopes have been utilized: ROTSE-I and III, with II as an abortive intermediary step between the two. The telescopes were originally created to study the optical light emitted by gamma ray bursts (GRB) in deep space, but now they are used to study optical light from numerous types of sources, including variable stars. III. Selection The data stored in the University of Michigan s IDL library can be extracted through a special directory search called find_burst. Data is classified according to quantifying search cuts inputted by the user based on Δ magnitude (deltamag), maximum σ (maxsig), and χ 2 (chisquared). Δ m = m max - m min (1) σ max = (m max - m min ) / (ε max 2 - ε min 2 ) ½ (2) χ 2 = Σ (Δ m / σ max ) ½ (3) 4

5 These cuts indicate the level of error present in each light curve, and some levels of error proved to be more useful than others. The initial cuts used in the search were: Deltamag Maxsig Chisquared TABLE 1 Cuts in find_burst used in initial image search. The images shown in Figures 1-5, along with the data displayed in Table 2 display the light curve data from the best-yielding cuts, including deltamag 0.1, maxsig 5.0, chisquared 1.0; deltamag 0.1, maxsig 0.0, chisquared 3.0; and deltamag 0.1, maxsig 0.0, chisquared 0.5. The remaining cuts yielded a couple of these desirable images, however the majority of the images exhibited light curve characteristics that have high levels of error, are incomplete, and/or unclear. 5

6 Cuts using deltamag 0.1 yielded the most results: i.e. Δ m = 0.1, σ max = 5.0, χ 2 = 1.0 yielded 121 pages of light curves, both desirable and undesirable. The last cut, Δ m = 0.1, σ max = 5.0, χ 2 = 1.0, yielded 1436 pages of light curves. Any data showing incomplete or indistinguishable curves were disregarded. Δ m = 0.5, σ max = 0.0, χ 2 = 3.0, Δ m = 0.5, σ max = 2.0, χ 2 = 3.0, Δ m = 1.0, σ max = 2.0, χ 2 = 5.0, and Δ m = 1.0, σ max = 5.0, χ 2 = 0.0 yielded the least satisfactory results, ranging from 3 37 pages of undesirable light curves. It had become clear that cuts using deltamag 0.1 would yield the largest number of light curves, with a maxsig of 3.0 showing the largest number of desirable light curves. IV. Catalog of Objects The twenty objects that were chosen based on their clarity and advantageous light curves were compared to existing objects catalogued in the SIMBAD astronautical database according to their right ascension and declination. The matches in the catalogue had proven to be either a pulsating variable, eclipsing binary, radio source, quasar, or unidentified. Table 2, shown on the next page, lists the variables with clear light curves that have close matches with objects already catalogued in SIMBAD. 6

7 Object # Object Name Right Ascension (hr. min. sec.) Declination (deg. min. sec.) Period (Day) Magnitude Range 657 V* HH UMa MASS J TYC V* MT UMa V* MU UMa V* MQ UMa FIRST J V* BS UMa V* MO UMa V* MP UMa MASS J TABLE 2 List of identified variables in the collected 2000 April stare data. The nearest matches in SIMBAD are given. 7

8 Table 3 shows the list of variables with light curves that have either no close or direct matches with objects already catalogued in SIMBAD. Object # Object Name Right Ascension (hr. min. sec.) Declination (deg. min. sec.) Period (Day) Magnitude Range 2316 FIRST J _ _ SDSS J _ FIRST J GB6 B FIRST J _ TABLE 3 List of variables that are not directly identified in SIMBAD. Those with object names are of catalogued objects that are located closest to the variables coordinates. 8

9 According to ROTSE-I 2000 April stare data. According to SIMBAD astronomical database. V. Results Pulsating Variables FIG. 1 - Seven single-night light curves for pulsating variables from the 2000 April stare data. Each of these has previously been identified as variable through the SIMBAD astronautical database. Errors are statistical + systematic. 9

10 Eclipsing Binaries FIG. 2 - Three single-night light curves for candidate pulsating variables from the 2000 April stare data. Each of these have previously been identified as variable through the SIMBAD astronautical database. Errors are statistical + systematic. Radio Sources FIG. 3 - Four single-night light curves for candidate radio sources from the 2000 April 10

11 stare data. Two of these, objects 1266 and 3121, have previously been identified as radio sources through the SIMBAD astronomical database. Objects 2316 and 3786 have close matches to radio sources in the database. Errors are statistical + systematic. Quasar FIG. 4 - Single-night light curve for a candidate quasar from the 2000 April stare data. This has previously been identified as variable through the SIMBAD astronautical database. Errors are statistical + systematic. Yet to be Identified FIG. 5 - Four single-night light curves for candidate pulsating variables from the

12 April stare data. None of these have been previously identified as variable. Errors are statistical + systematic. V. Conclusion VI. References [1] Sterken, C., & Jaschek, C. Light Curves of Variable Stars: A Pictorial Atlas. Cambridge University Press, [2] Levy, David H. Observing Variable Stars: A Guide for the Beginner. Cambridge University Press,