skills.rest
dsa110
dsa110OFFICIAL
Explore all skills by this author →
WebsiteGitHub

Photometry Skill

Perform adaptive binning photometry and calculate variability metrics for astronomical sources.

Updated Aug 27, 2026
Search Tags:#astronomy#photometry#radio astronomy#ESE detection#flux measurement#variability detection
One-click install
npx skills add https://github.com/dsa110/dsa110-contimg --skill photometry-skill
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: Photometry Skill
Source: https://github.com/dsa110/dsa110-contimg/tree/main/backend/.github/skills/photometry
Command: npx skills add https://github.com/dsa110/dsa110-contimg --skill photometry-skill

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill automates the measurement of astronomical source fluxes and the detection of their variability, crucial for identifying transient astronomical events.

Core Features & Use Cases

  • Adaptive Binning: Dynamically adjusts frequency channels for optimal signal-to-noise ratio (SNR) in flux measurements.
  • Variability Analysis: Calculates metrics like Eta (η), V, and sigma-deviation to identify sources with changing brightness.
  • Use Case: Automatically process daily radio astronomy data to detect and flag newly appearing or flaring celestial objects by analyzing their flux variations over time.

Quick Start

Run the photometry skill to process a measurement set and detect variable sources.

Frequently Asked Questions about Photometry Skill

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

FAQPage Schema
How do I measure astronomical source fluxes and detect variability in radio astronomy data?▼

Adaptive binning photometry dynamically adjusts frequency channels to achieve optimal signal-to-noise ratio for flux measurement, ensuring precise quantification of astronomical source brightness even in noisy radio astronomy datasets.

How do I calculate variability metrics like Eta and V for astronomical sources?▼

Calculate variability metrics like Eta, V, and sigma-deviation by running Python scripts that evaluate flux variations over time, identifying sources with changing brightness for transient event detection.

Can I use adaptive binning photometry for transient event detection in radio astronomy pipelines?▼

Adaptive binning photometry integrates into radio astronomy data processing pipelines, automatically adjusting frequency channels to meet configurable SNR targets for transient event detection and source monitoring.

What is the best way to detect newly appearing or flaring celestial objects from daily radio data?▼

Detect newly appearing or flaring celestial objects by processing daily radio astronomy data to analyze flux variations over time, applying configurable variability thresholds to automatically flag transient astronomical events.

How do I configure SNR targets and variability thresholds for flux measurement?▼

Configure SNR targets and variability thresholds within the photometry Python scripts to control the sensitivity of adaptive binning frequency channels and the strictness of variable source flagging.

Does radio astronomy photometry require any external dependencies?▼

Radio astronomy photometry scripts operate independently without external dependencies, relying solely on Python scripts to perform adaptive binning and calculate variability metrics for source monitoring.

Related Skills

Explore More Data & Analytics Skills→
eLafoeLafo
1

Context Engineering

Orchestrate c₁–c₆ context lifecycle with 4-D quality assessment.

Community
Intermediate
samjhechtsamjhecht
4

frontend-visual-regression-testing

Compare UI component screenshots against baselines to detect visual regressions.

Community
Advanced
thinhtt264thinhtt264

android-gradle-logic

Centralize Android Gradle build logic with convention plugins and version catalogs.

Community
Advanced
peabody124peabody124
3

gait-metrics

Compute spatiotemporal gait metrics and GDI from kinematic reconstructions.

Community
Advanced