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Deep learning infers stellar parameters from short astronomical observations

By PulseAugur Editorial · [2 sources] ·

Researchers have developed a deep learning method to infer asteroseismic parameters from short astronomical observations. The model aims to efficiently analyze data from missions like TESS, which has observed hundreds of thousands of red giants. The study demonstrates the ML algorithm's ability to accurately infer key parameters such as large frequency separation and frequency at maximum power from one-month TESS and K2 observations, though with varying success rates for different datasets. AI

IMPACT Enables faster and more efficient analysis of large astronomical datasets, potentially accelerating stellar discovery and characterization.

RANK_REASON Academic paper detailing a new machine learning method for scientific research.

Read on arXiv stat.ML →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

Deep learning infers stellar parameters from short astronomical observations

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COVERAGE [2]

  1. arXiv stat.ML TIER_1 English(EN) · Nipun Ghanghas, Siddharth Dhanpal, Shravan Hanasoge, Praneeth Netrapalli, Karthikeyan Shanmugam ·

    Inferring Asteroseismic Parameters from Short Observations Using Deep Learning: Application to TESS and K2 Red Giants

    arXiv:2605.08051v1 Announce Type: cross Abstract: Asteroseismology is the study of resonant oscillations of stars to infer their internal structure and dynamics. It is also a powerful tool for precisely determining stellar parameters such as mass, radius, surface gravity, and age…

  2. arXiv stat.ML TIER_1 English(EN) · Karthikeyan Shanmugam ·

    Inferring Asteroseismic Parameters from Short Observations Using Deep Learning: Application to TESS and K2 Red Giants

    Asteroseismology is the study of resonant oscillations of stars to infer their internal structure and dynamics. It is also a powerful tool for precisely determining stellar parameters such as mass, radius, surface gravity, and age. The ongoing TESS mission, with its nearly comple…

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