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astronomy-cosmology

Analyzes astronomical observations and cosmological models including telescope data processing, celestial mechanics calculations, stellar evolution, galaxy classification, and cosmological parameter estimation; trigger when users discuss stars, galaxies, exoplanets, dark matter, or the universe's large-scale structure.

Star
962
Category
Science
License
MIT
Last commit
Oct 8, 2026

skills/astronomy-cosmology/SKILL.md

View on GitHub

When to Trigger

Activate this skill when the user mentions:

  • Telescope observations, photometry, spectroscopy, astrometry
  • Celestial mechanics, orbital calculations, Kepler's laws
  • Stellar evolution, HR diagram, spectral classification
  • Galaxy morphology, redshift, distance ladder
  • Cosmological models, dark matter, dark energy, CMB
  • Exoplanet detection, transit method, radial velocity
  • Gravitational waves, black holes, neutron stars

Step-by-Step Methodology

  1. Define the astronomical question - Specify the object type (star, galaxy, nebula, exoplanet), observational band (optical, radio, X-ray, IR), and physical quantity of interest (distance, mass, luminosity, composition).
  2. Data acquisition - Identify relevant surveys and archives: Gaia for astrometry, SDSS for optical spectra/photometry, 2MASS/WISE for IR, Chandra for X-ray. Download data using VO (Virtual Observatory) tools or API queries.
  3. Calibration and reduction - Apply bias subtraction, flat-fielding, wavelength/flux calibration. For photometry: aperture or PSF fitting. For spectroscopy: sky subtraction, continuum normalization. Report signal-to-noise ratios.
  4. Physical parameter derivation - Compute distances (parallax, standard candles, redshift-distance relation using appropriate cosmology). Derive masses (Kepler's third law, virial theorem, mass-luminosity relation). Determine compositions from spectral line analysis.
  5. Modeling - Fit observational data with physical models: stellar atmosphere models (ATLAS, PHOENIX), N-body simulations for dynamics, cosmological models (LCDM, wCDM). Use MCMC or nested sampling for parameter estimation.
  6. Cosmological calculations - Use standard cosmological parameters (H0, Omega_m, Omega_Lambda). Compute comoving distances, lookback times, luminosity distances. Note current tensions (H0 tension between early and late universe).
  7. Visualization - Produce standard astronomical plots: HR diagrams, light curves, spectra, sky maps in appropriate coordinate systems (equatorial, galactic). Use logarithmic scales where appropriate.

Key Databases and Tools

  • NASA/IPAC Extragalactic Database (NED) - Extragalactic object data
  • SIMBAD / VizieR - Stellar object data and catalog queries
  • Gaia Archive - Astrometric and photometric data
  • SDSS SkyServer - Optical survey data
  • NASA Exoplanet Archive - Confirmed exoplanet parameters
  • Astropy - Python astronomy library
  • MAST (STScI) - Hubble, JWST, and other mission archives

Output Format

  • Coordinates in standard systems: RA/Dec (J2000) or Galactic (l, b).
  • Distances with method and uncertainty (parallax, photometric, spectroscopic).
  • Physical quantities in CGS or SI with astronomical conventions (solar units, parsecs, magnitudes).
  • Spectra with wavelength/frequency axis, flux units, and line identifications.

Quality Checklist

  • Coordinate system and epoch explicitly stated
  • Distance method and its systematic uncertainties discussed
  • Cosmological parameters (H0, Omega_m) specified when used
  • Photometric system (Vega, AB) identified for magnitudes
  • Extinction/reddening corrections applied where relevant
  • Instrument and survey limitations acknowledged
  • Error propagation through derived quantities
  • Known systematic effects (selection bias, Malmquist bias) addressed

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