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photutils

Detect sources and perform aperture photometry on astronomical images with Python.

19|2|Updated Jan 31, 2026
Search Tags:#astronomy#image analysis#astrophysics#photometry#source detection#aperture photometry
One-click install
npx skills add https://github.com/tondevrel/scientific-agent-skills --skill photutils
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: photutils
Source: https://github.com/tondevrel/scientific-agent-skills/tree/main/skills/photutils
Command: npx skills add https://github.com/tondevrel/scientific-agent-skills --skill photutils

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires astropy, numpy, matplotlib, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the precise measurement of brightness (photometry) and the detection of celestial objects within astronomical images, which is crucial for scientific analysis.

Core Features & Use Cases

  • Source Detection: Identifies stars, galaxies, and other point-like or extended sources in images.
  • Photometry: Quantifies the brightness of detected sources using various aperture methods.
  • Background Estimation: Accurately subtracts sky background variations for reliable measurements.
  • PSF Fitting: Handles crowded fields by modeling and fitting the Point Spread Function of sources.
  • Use Case: Analyze images from telescopes to measure the flux of thousands of stars in a galaxy cluster, enabling studies of stellar populations.

Quick Start

Use the photutils skill to detect sources in the provided astronomical image and perform circular aperture photometry with a radius of 5 pixels.

Frequently Asked Questions about photutils

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I measure the brightness of stars in astronomical images?▼

Aperture photometry measures the brightness of celestial sources in astronomical images by summing pixel values within a defined circular radius. This Skill automates that process using Python to quantify the flux of detected stars.

What is the best way to detect point-like sources in telescope data?▼

Source detection identifies point-like or extended celestial objects in telescope data by applying detection algorithms to astronomical images. This Skill automates finding stars and galaxies for scientific analysis.

How do I subtract sky background variations for reliable photometry?▼

Background estimation subtracts sky background variations from astronomical images to ensure reliable photometry. This Skill accurately calculates and removes these background variations before measuring source brightness.

Can I use astropy and numpy for source detection in crowded fields?▼

Yes, you can use astropy and numpy for source detection in crowded fields. This Skill relies on astropy for unit handling and uses PSF fitting to model the Point Spread Function of overlapping sources.

Do I need matplotlib to visualize astronomical image analysis results?▼

You need matplotlib to visualize astronomical image analysis results because it handles data visualization and plotting. This Skill requires matplotlib alongside astropy and numpy for complete data manipulation and visualization.

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