Interpolating Evolutionary Tracks
    of Rapidly Rotating Stars


          Danielle Kumpulanian
                October 20, 2005


    Deane Peterson, Stony Brook University
Outline
• Introduction
  – Background
  – Goals
      • Accurately interpolate data
      • Determine mass of a star
  – Evolutionary track grids
• Description of project
  – Interpolation method
  – Test & results
  – Polygon problem
• Conclusion
  – Uses for interpolation
    method
• References
Introduction
• Stellar evolution: lifetime of stars
• Stars live for millions or billions of years
• Cannot observe the entire life cycle of a single
  star
• Need to piece together observations of stars of
  the same mass, at different ages (different
  points along evolutionary track)
Introduction
• Can draw predicted evolutionary track for
  a star of that mass, based on observations
• Evolutionary tracks are put into “grids”.
• Grids are published for everyone to use.
Evolutionary track grid (2D)
log(M/MSun)=0.0500   …   t (Age in years)   log(L/LSun)   …   log(Teff)   …   …




                                                                          …   …
log(M/MSun)=0.0500   …   t (Age in years)   log(L/LSun)   …   log(Teff)


log(M/MSun)=0.0750   …   t (Age in years)   log(L/LSun)   …   log(Teff)   …   …




log(M/MSun)=0.0750   …   t (Age in years)   log(L/LSun)   …   log(Teff)   …   …




log(M/MSun)=0.1000   …   t (Age in years)   log(L/LSun)   …   log(Teff)   …   …




log(M/MSun)=0.1000   …   t (Age in years)   log(L/LSun)   …   log(Teff)   …   …




log(M/MSun)=0.1250   …   t (Age in years)   log(L/LSun)   …   log(Teff)   …   …




log(M/MSun)=0.1250   …   t (Age in years)   log(L/LSun)   …   log(Teff)   …   …
Evolutionary track grid (3D)
   log(M/MSun):


   0.1250
   0.1000
   0.0750
   0.0500
Hertzsprung-Russell Diagram
Evolutionary Tracks
• Luminosity-Radius-Temperature relation:

                   L = 4πR2σT4
• Use this relation to solve for log(R/RSun):

   log(R/RSun) = 0.5{log(L/LSun) – 4[logT – logTSun]}

• Using information from grid, draw
  evolutionary tracks on a log(R/RSun) vs.
  log(L/LSun) plot.
Evolutionary tracks
Models range from log(M/MSun) = 0.0500 to log(M/MSun) = 0.7000
http://rocinante.colorado.edu/~pja/astr3730/lecture12.pdf
Interpolating evolutionary tracks of rapidly rotating stars - presentation
Goals
• Problem: large gap between masses in the
  grids…what about models for arbitrary masses?
• Solution: interpolate data for an arbitrary mass
  using the existing data in the grids.
Goals
• Problem: given observables such as L, Teff, and
  R, what is the mass of the star?
• Solution: use interpolation methods and
  determine mass or range of possible masses
  depending on which segment of the evolutionary
  track the point is on.
Evolutionary tracks
Models range from log(M/MSun) = 0.0500 to log(M/MSun) = 0.7000
Interpolation Method

wt + = (Teff − Teff 2 ) /(Teff 1 − Teff 2 )

wt − = (Teff 1 − Teff ) /(Teff 1 − Teff 2 )

 x = x1 wt + + x 2 wt −
                             x1 < x < x 2
Divide each evolutionary track
     into three segments:
                         1   Teff initial
                         2   Teff min
                         3   Teff max
                         4   Teff final
Segment 1:
Segment 2:
Segment 3:
Interpolation Method
• Calculate time ratios for each segment of track:


  C1 = (t   U
                min    −t      U
                                   0   ) /(t   L
                                                   min   −t     L
                                                                    0   )
 C 2 = (t   U
                max   −t   U
                               min     ) /(t   L
                                                   max   −t     L
                                                                    min     )

 C 3 = (t   U
                f     −t   U
                               max     ) /(t   L
                                                   f   −t   L
                                                                max     )
Interpolation Method
• Find corresponding points on the upper track for
each point on the lower track
• For each time t Li , a point t Ui is found.
• t Ui most likely does not correspond to a t U in
the grid.

•Interpolate values for log(L/LSun) and
log(Teff/Teff Sun) at points on upper track.
•Calculate log(R/RSun) for these points.
Interpolation Method
      Calculate log(R/RSun) and log(L/LSun) for each
           point along the intermediate track:
                  log( M / M Sun ) L − log(M / M Sun )
          wt + =
                 log(M / M Sun ) L − log( M / M Sun )U
                  log( M / M Sun ) − log(M / M Sun )U
          wt − =
                 log( M / M Sun ) L − log( M / M Sun )U

x1 = previous log(R/RSun) or log(L/LSun)
interpolated for upper track                  x = x1 wt + + x 2 wt −
x2 = next log(R/RSun) or log(L/LSun)                     x1 < x < x 2
interpolated for upper track
Interpolating evolutionary tracks of rapidly rotating stars - presentation
Test Results
• Interpolated track matched actual track accurate within
  ~2%.
• Distance between upper and lower tracks: log(M/MSun) =
  0.2000.
• Decrease distance → decrease %error.
• In practice, the interpolated model will be between two
  existing models, or a smaller distance between the upper
  and lower tracks.
Evolutionary tracks with polygon
Point-In-Polygon
• Threshold: horizontal line with y-coordinate of the test point
• Node: point where the threshold crosses an edge
•of the polygon

• Odd number of nodes: Inside
• Even number of nodes: Outside
• Zero nodes: Outside

• It does not matter which way
(left or right) from the test
point nodes are counted,
the result is the same.
Point-In-Polygon

Works for polygons that cross themselves:

1 node → odd → inside polygon



Works for polygons with holes or
polygons that overlap themselves:

2 nodes → even → outside polygon
Point-In-Polygon
                    What if the threshold passes through
                    a vertex of the polygon?

• Only one node can be counted, even though there
are two sides
• Make a rule: If the threshold passes through a vertex,
the point is considered “above” the threshold.
• Each side of the polygon has two endpoints.
• If the threshold passes through the endpoints of two
adjacent sides, only one side will have an endpoint
below the threshold.
   •Side a has an endpoint below & an endpoint “on-or-above” the
   threshold → count 1 node.
   •Side b has both endpoints “on-or-above” → count 0 nodes.
Point-In-Polygon
What if one side of the polygon lies
completely along the threshold?


Treat the same as last example:

   • Side c has one endpoint below the threshold and one endpoint
   “on-or-above” the threshold → count 1 node
   • Side d has two endpoints “on-or-above” → count 0 nodes.
   • Side e has two endpoints “on-or-above” → count 0 nodes.

      • Total nodes: 1 → inside polygon
Conclusion
• Method of interpolating models was developed and
  tested.
    – Accurate to better than ~1%.
• Only a portion of an existing models grid was used
    – Can easily be translated to use more of this grid or a different
      models grid
•    Tracks can be divided into three sections, and three
    polygons can be drawn with vertices at the endpoints of
    these sections.
    – Polygons can be used to determine if a single mass or a range
      of possible masses can be found.
    – Use Point-In-Polygon algorithm to determine which polygon the
      point is in.
Conclusion
• After obtaining log(L/LSun) and log(R/RSun) through
  observation, remaining properties can be
  deduced.
• Evolutionary track can be drawn.
• log(L/LSun) and log(R/RSun) are independent of
  rotation.
• Can study star’s evolutionary state and how its
  rotation affects its evolution.
• Further work needs to be done on this topic.
References
• A. Claret, Astron. Astrophys. 424, 919 (2004).
• D. R. Finley, Point-In-Polygon Algorithm (1998), URL:
  http://www.alienryderflex.com/polygon/.
Aside: Personal Challenges
•   Learn how to use Unix, Emacs, etc.
•   Learn/Re-learn C programming language
•   Figure out solutions to problems
•   Figure out how to make programs to carry
    out the calculations
Aside: Personal Challenges
• Learn how to use PGPLOT package
  – Read manual written in FORTRAN
  – Figure out how to change to C
• Make sure code was clearly written and
  commented so that others could
  understand it

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Interpolating evolutionary tracks of rapidly rotating stars - presentation

  • 1. Interpolating Evolutionary Tracks of Rapidly Rotating Stars Danielle Kumpulanian October 20, 2005 Deane Peterson, Stony Brook University
  • 2. Outline • Introduction – Background – Goals • Accurately interpolate data • Determine mass of a star – Evolutionary track grids • Description of project – Interpolation method – Test & results – Polygon problem • Conclusion – Uses for interpolation method • References
  • 3. Introduction • Stellar evolution: lifetime of stars • Stars live for millions or billions of years • Cannot observe the entire life cycle of a single star • Need to piece together observations of stars of the same mass, at different ages (different points along evolutionary track)
  • 4. Introduction • Can draw predicted evolutionary track for a star of that mass, based on observations • Evolutionary tracks are put into “grids”. • Grids are published for everyone to use.
  • 5. Evolutionary track grid (2D) log(M/MSun)=0.0500 … t (Age in years) log(L/LSun) … log(Teff) … … … … log(M/MSun)=0.0500 … t (Age in years) log(L/LSun) … log(Teff) log(M/MSun)=0.0750 … t (Age in years) log(L/LSun) … log(Teff) … … log(M/MSun)=0.0750 … t (Age in years) log(L/LSun) … log(Teff) … … log(M/MSun)=0.1000 … t (Age in years) log(L/LSun) … log(Teff) … … log(M/MSun)=0.1000 … t (Age in years) log(L/LSun) … log(Teff) … … log(M/MSun)=0.1250 … t (Age in years) log(L/LSun) … log(Teff) … … log(M/MSun)=0.1250 … t (Age in years) log(L/LSun) … log(Teff) … …
  • 6. Evolutionary track grid (3D) log(M/MSun): 0.1250 0.1000 0.0750 0.0500
  • 8. Evolutionary Tracks • Luminosity-Radius-Temperature relation: L = 4πR2σT4 • Use this relation to solve for log(R/RSun): log(R/RSun) = 0.5{log(L/LSun) – 4[logT – logTSun]} • Using information from grid, draw evolutionary tracks on a log(R/RSun) vs. log(L/LSun) plot.
  • 9. Evolutionary tracks Models range from log(M/MSun) = 0.0500 to log(M/MSun) = 0.7000
  • 12. Goals • Problem: large gap between masses in the grids…what about models for arbitrary masses? • Solution: interpolate data for an arbitrary mass using the existing data in the grids.
  • 13. Goals • Problem: given observables such as L, Teff, and R, what is the mass of the star? • Solution: use interpolation methods and determine mass or range of possible masses depending on which segment of the evolutionary track the point is on.
  • 14. Evolutionary tracks Models range from log(M/MSun) = 0.0500 to log(M/MSun) = 0.7000
  • 15. Interpolation Method wt + = (Teff − Teff 2 ) /(Teff 1 − Teff 2 ) wt − = (Teff 1 − Teff ) /(Teff 1 − Teff 2 ) x = x1 wt + + x 2 wt − x1 < x < x 2
  • 16. Divide each evolutionary track into three segments: 1 Teff initial 2 Teff min 3 Teff max 4 Teff final
  • 20. Interpolation Method • Calculate time ratios for each segment of track: C1 = (t U min −t U 0 ) /(t L min −t L 0 ) C 2 = (t U max −t U min ) /(t L max −t L min ) C 3 = (t U f −t U max ) /(t L f −t L max )
  • 21. Interpolation Method • Find corresponding points on the upper track for each point on the lower track • For each time t Li , a point t Ui is found. • t Ui most likely does not correspond to a t U in the grid. •Interpolate values for log(L/LSun) and log(Teff/Teff Sun) at points on upper track. •Calculate log(R/RSun) for these points.
  • 22. Interpolation Method Calculate log(R/RSun) and log(L/LSun) for each point along the intermediate track: log( M / M Sun ) L − log(M / M Sun ) wt + = log(M / M Sun ) L − log( M / M Sun )U log( M / M Sun ) − log(M / M Sun )U wt − = log( M / M Sun ) L − log( M / M Sun )U x1 = previous log(R/RSun) or log(L/LSun) interpolated for upper track x = x1 wt + + x 2 wt − x2 = next log(R/RSun) or log(L/LSun) x1 < x < x 2 interpolated for upper track
  • 24. Test Results • Interpolated track matched actual track accurate within ~2%. • Distance between upper and lower tracks: log(M/MSun) = 0.2000. • Decrease distance → decrease %error. • In practice, the interpolated model will be between two existing models, or a smaller distance between the upper and lower tracks.
  • 26. Point-In-Polygon • Threshold: horizontal line with y-coordinate of the test point • Node: point where the threshold crosses an edge •of the polygon • Odd number of nodes: Inside • Even number of nodes: Outside • Zero nodes: Outside • It does not matter which way (left or right) from the test point nodes are counted, the result is the same.
  • 27. Point-In-Polygon Works for polygons that cross themselves: 1 node → odd → inside polygon Works for polygons with holes or polygons that overlap themselves: 2 nodes → even → outside polygon
  • 28. Point-In-Polygon What if the threshold passes through a vertex of the polygon? • Only one node can be counted, even though there are two sides • Make a rule: If the threshold passes through a vertex, the point is considered “above” the threshold. • Each side of the polygon has two endpoints. • If the threshold passes through the endpoints of two adjacent sides, only one side will have an endpoint below the threshold. •Side a has an endpoint below & an endpoint “on-or-above” the threshold → count 1 node. •Side b has both endpoints “on-or-above” → count 0 nodes.
  • 29. Point-In-Polygon What if one side of the polygon lies completely along the threshold? Treat the same as last example: • Side c has one endpoint below the threshold and one endpoint “on-or-above” the threshold → count 1 node • Side d has two endpoints “on-or-above” → count 0 nodes. • Side e has two endpoints “on-or-above” → count 0 nodes. • Total nodes: 1 → inside polygon
  • 30. Conclusion • Method of interpolating models was developed and tested. – Accurate to better than ~1%. • Only a portion of an existing models grid was used – Can easily be translated to use more of this grid or a different models grid • Tracks can be divided into three sections, and three polygons can be drawn with vertices at the endpoints of these sections. – Polygons can be used to determine if a single mass or a range of possible masses can be found. – Use Point-In-Polygon algorithm to determine which polygon the point is in.
  • 31. Conclusion • After obtaining log(L/LSun) and log(R/RSun) through observation, remaining properties can be deduced. • Evolutionary track can be drawn. • log(L/LSun) and log(R/RSun) are independent of rotation. • Can study star’s evolutionary state and how its rotation affects its evolution. • Further work needs to be done on this topic.
  • 32. References • A. Claret, Astron. Astrophys. 424, 919 (2004). • D. R. Finley, Point-In-Polygon Algorithm (1998), URL: http://www.alienryderflex.com/polygon/.
  • 33. Aside: Personal Challenges • Learn how to use Unix, Emacs, etc. • Learn/Re-learn C programming language • Figure out solutions to problems • Figure out how to make programs to carry out the calculations
  • 34. Aside: Personal Challenges • Learn how to use PGPLOT package – Read manual written in FORTRAN – Figure out how to change to C • Make sure code was clearly written and commented so that others could understand it