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calibration-imaging

Orchestrate radio astronomy calibration, flagging, imaging, and mosaicking workflows.

Updated Aug 27, 2026
Search Tags:#data processing#calibration#astronomy#imaging#radio astronomy#mosaicking
One-click install
npx skills add https://github.com/dsa110/dsa110-contimg --skill calibration-imaging
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: calibration-imaging
Source: https://github.com/dsa110/dsa110-contimg/tree/main/docs/skills/calibration-imaging
Command: npx skills add https://github.com/dsa110/dsa110-contimg --skill calibration-imaging

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill streamlines the complex process of calibrating and imaging radio astronomy data, ensuring the creation of science-quality astronomical images.

Core Features & Use Cases

  • Data Calibration: Apply calibration recipes to raw radio telescope data.
  • Flagging: Implement strategies to identify and remove corrupted or noisy data.
  • Imaging & Mosaicking: Generate continuum images from calibrated data, including mosaic creation for large fields.
  • Self-Calibration: Refine imaging through iterative self-calibration processes.

Quick Start

Use the calibration-imaging skill to run a mosaic photometry test on the provided data.

Frequently Asked Questions about calibration-imaging

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

FAQPage Schema
How do I calibrate and image radio astronomy data?▼

You calibrate and image radio astronomy data by orchestrating workflows that apply calibration recipes, define flagging strategies, and parameterize imaging to generate science-quality continuum images.

What is flagging in radio astronomy data processing?▼

Flagging in radio astronomy data processing is the mechanism of implementing strategies to identify and remove corrupted or noisy data from raw telescope observations before imaging.

How do I generate mosaics from radio astronomy continuum images?▼

Mosaicking generates large field continuum images from calibrated radio astronomy data by parameterizing imaging workflows and combining overlapping fields of view into a single science-quality mosaic.

Can I refine radio astronomy imaging using self-calibration?▼

Yes, self-calibration refines radio astronomy imaging through iterative processes that apply calibration recipes repeatedly to improve the fidelity of the generated science-quality continuum images.

What data product identification and validation protocols are required for radio astronomy imaging?▼

Radio astronomy imaging requires strict adherence to specific data product identification and output validation protocols to ensure the generated continuum images meet science-quality standards.

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