astronomy-cosmology
# astronomy-cosmology This skill analyzes astronomical observations and cosmological data through systematic processing of telescope data, celestial mechanics calculations, and physical parameter derivation. Use it when users inquire about stellar properties, galaxy characteristics, exoplanet parameters, cosmological models, or large-scale universe structure, requiring integration of observational databases like Gaia, SDSS, and NED with computational modeling techniques.
git clone --depth 1 https://github.com/beita6969/ScienceClaw /tmp/astronomy-cosmology && cp -r /tmp/astronomy-cosmology/skills/astronomy-cosmology ~/.claude/skills/astronomy-cosmologySKILL.md
## 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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