Presentation is loading. Please wait.

Presentation is loading. Please wait.

Jeff Byron Variable Stars South and Northern Sydney Astronomical Society.

Similar presentations


Presentation on theme: "Jeff Byron Variable Stars South and Northern Sydney Astronomical Society."— Presentation transcript:

1 Jeff Byron Variable Stars South and Northern Sydney Astronomical Society

2  A plot of ToM against cycle number should be a straight line within the limits allowed by ToM error values, (unless there is variation in the period). But scale values make it impractical to graphically verify this!

3  However, a plot of O-C against cycle number should also be a straight line within the limits allowed by ToM error values and this can be graphically verified.

4  For an observation to match a set of Light Elements, that straight line should be the horizontal axis.

5  However, a plot of O-C against cycle number should also be a straight line within the limits allowed by ToM error values and this can be graphically verified.  For an observation to match a set of Light Elements, that straight line should be the horizontal axis.  It is NOT sufficient that O-C is less than O-C error.

6

7

8  Use the most recent observation with low ToM uncertainty.

9  Analyst process data should be recorded to make measurement repeatable.  Data points excluded  Process used  Limits used  Combinations averaged

10  Unfortunately, Peranso is very cumbersome for recording this data.

11  Asymmetries in a light curve cause KvW (& other) processes to return "ToM" values which are dependant on the phase range analysed.

12

13  Recorded Error values depend upon:  Actual accuracy of photometry.  Phase duration & “density” of observations.  Process Used (Polynomial, Kwee & van Woerden, etc)  Incorrect reporting by software (e.g. Peranso)

14  Recorded Error values depend upon:  Actual accuracy of photometry.  Phase duration & “density” of observations.  Process Used (Polynomial, Kwee & van Woerden, etc)  Incorrect reporting by software (e.g. Peranso)  If the last of these effects dominates, there is no point in using Weighted Regression.

15

16

17

18

19  Publically available data (e.g. ASAS) can extend the time frame over which measurements are made.  This has the effect of adding precision to the light elements – provided there has been no changes in period in the intervening time. (This is an important proviso!)

20  Download text file from web site.  Check RA & Dec match for each data set.  Select data – “A” grade only.  (To speed the last 2 processes, the author developed a computer program to handle them.)  Plot phase-folded ASAS (HJD, mag) values along with VSS observers’ data, using VSS data generated period.

21 Incorporation of ASAS Data - Procedure DI Cen: Plot Period = 3.5495541

22 Incorporation of ASAS Data - Procedure Adjust period to achieve best possible correlation between ASAS and VSS data “by eye”. DI Cen: Plot Period = 3.549563

23  In some cases, no period gives a good correlation between ASAS and VSS data.  In such cases, cannot use ASAS data to refine Light Elements.

24 Incorporation of ASAS Data - Procedure CT Phi Plot Period = 1.260826

25 Incorporation of ASAS Data - Procedure CT Phi Plot Period = 1.260838

26 Incorporation of ASAS Data - Procedure CT Phi Plot Period = 1.260844

27 Incorporation of ASAS Data - Procedure CT Phi Plot Period = 1.260850

28 Incorporation of ASAS Data - Procedure CT Phi Plot Period = 1.260855

29 Incorporation of ASAS Data - Procedure CT Phi Plot Period = 1.260860

30 Incorporation of ASAS Data - Procedure CT Phi Plot Period = 1.260865

31 Incorporation of ASAS Data - Procedure CT Phi Plot Period = 1.260870

32 Where correlation between ASAS and VSS data appears reasonable “by eye”:  Select median date of ASAS observations.  Using this date and corresponding phase as reference, phase fold all ASAS data.  Generate a table and graph of “pseudo HJD” and magnitude as though all observations were in one cycle.

33

34  After deleting “outlier” points, use software tool of choice to determine Time-of-Minimum and associated error value. (Bob Nelson’s “Tracing Paper” often suitable in presence of large scatter of data points.)  Add this (ToM, error) value to Excel “Linest” and weighted regression procedures to obtain provisional improved light elements.

35

36 Incorporation of ASAS Data - Procedure Sanity Check DI Cen: Plot Period = 3.5495668 (Weighted Regression value including ASAS.)

37

38  Currently still a “work in progress”.  Includes “standard” KvW.  Uses “least squares” fitting for polynomial and Mikulasek model fitting.  Rather than relying on errors reported by the KvW or Least Squares routines, uses statistical re-sampling (Jackknife).  Generates a table of values for a range of observation intervals included in the process.

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54  Minima Timing of Eclipsing Binaries Brat, L; Mikulasek, Z; & Pejcha,O (2012) http://var2.astro.cz/library/1350745528_ebfit.pdf  A method for computing accurately the epoch of minimum of an eclipsing variable Kwee, K. K. & van Woerden, H. Bulletin of the Astronomical Institutes of the Netherlands, Vol. 12, p.327 1956BAN....12..327K  A FORTRAN Subroutine for Determining Times of Minimum Light Mallama, A. D. International Amateur-Professional Photoelectric Photometry Communication, No. 7, p.14 1982IAPPP...7...14M  Southern Eclipsing Binaries Programme - Basic Analysis Procedures Richards, T. http://www.variablestarssouth.org/analysis-procedure-i/finish/136-seb-programme/662-seb- analysis-procedure

55  Margaret Streamer and other VSS Observers and Analysts for information and comments during development of "Revised Light Elements of 78 Southern Eclipsing Binary Systems“

56  My wife Julie – without whose help I would never have had the time to develop this paper.

57


Download ppt "Jeff Byron Variable Stars South and Northern Sydney Astronomical Society."

Similar presentations


Ads by Google