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SUMMARY:EncoTESS: Age Inference from Raw TESS Light Curves
DTSTART;VALUE=DATE-TIME:20261028T173500Z
DTEND;VALUE=DATE-TIME:20261028T174500Z
DTSTAMP;VALUE=DATE-TIME:20261025T100850Z
UID:indico-contribution-3640@nyx.physics.mcgill.ca
DESCRIPTION:Speakers: Phil Van-Lane (University of Toronto\; University of
  California San Diego)\nStellar ages are a foundational component of astro
 nomy research\, but are notoriously difficult to measure for low mass main
  sequence stars. Fortunately\, variability indicators such as rotation per
 iod\, flaring rate\, and amplitude of flux variability can provide some ag
 e constraints\, but they evolve in nonlinear and non-monotonic ways. Furth
 ermore\, these indicators are typically characterized as summary statistic
 s from time series data\, but these are often noisy\, treated independentl
 y\, and do not capture all of the useful information contained in raw ligh
 t curves. With the recent advances in ML/AI and computing combined with th
 e vast number of light curves available from Kepler and TESS\, there is a 
 prime opportunity to apply more data-driven methods. To that end\, I have 
 developed and here present \\texttt{EncoTESS}: a Time Series Foundation Mo
 del that can be used to estimate stellar ages from raw TESS light curves w
 ithout using summary statistics. I show that through self-supervised train
 ing\, \\texttt{EncoTESS} naturally captures stellar variability\, and that
  it can be used to infer the ages of young M dwarfs with more accuracy and
  precision than rotation-based models. \\texttt{EncoTESS} is designed with
  consideration of crucial systematics such as noisy\, heteroskedastic data
  with large gaps\, and implements an architecture expandable to multi-cade
 nce and multi-survey light curves for broader applicability in the future.
  It is also ~1% of the size of typical literature Time Series Foundation M
 odels\, and can be run easily on any modern laptop.\n\nhttps://nyx.physics
 .mcgill.ca/event/587/contributions/3640/
LOCATION:Online 
URL:https://nyx.physics.mcgill.ca/event/587/contributions/3640/
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