astropy

What it does

This skill enables AI agents to perform advanced astronomical data analysis using Python's Astropy library. It handles tasks ranging from coordinate transformations and unit conversions to manipulating time series and fitting models to observational data.

When to use it

• Coordinate Systems: Converting celestial coordinates between different reference frames (e.g., ICRS, Galactic) or calculating angular separations between objects.
• Unit Management: Performing complex physics calculations where automatic unit conversion and consistency checking are critical for accuracy.
• Time Analysis: Processing astronomical time scales (like TDB or TT) to correct for relativistic effects in observation logs.
• Data Fitting: Applying statistical models to light curves or spectral data to extract physical parameters from noisy observations.

Key capabilities

• Coordinate system transformations and frame conversions
• Physical unit handling and automatic conversion
• Time scale management and astronomical time calculations
• Data fitting and model optimization for scientific datasets
• Sky coordinate geometry and angular distance computations

Example prompts

• "Convert the coordinates of M31 from Galactic to Equatorial systems using Astropy."
• "Analyze this light curve data, converting all timestamps to TDB and fitting a sinusoidal model to determine the period."
• "Calculate the angular separation between two stars given their RA and Dec in degrees."

Tips & gotchas

Ensure your environment has the astropy package installed via pip or conda before invoking this skill. For best results, provide raw numerical data with explicit units rather than relying on the agent to infer them from context strings.