Quickstart

This section is the front door to ARCADE. It explains what the package is trying to accomplish, how the major subsystems connect, how to install the software with the optional extras that unlock neural methods or path signatures or quantum error correction, and how to confirm that the install worked before you invest time in a long training run.

If you already know the domain and only need a command to copy, jump to Installation and then to First zoo run. If you are new to readout discrimination, read Overview of ARCADE first so the later configuration keys and metric names have a place to attach.

• Overview of ARCADE
  • What problem ARCADE solves
  • What ARCADE is not
  • Repository surfaces you will use
  • Design principles
  • Where to go next
• Installation
  • Requirements
  • Create an environment and install
  • Optional extras
  • Command line entry point
  • Building this documentation
  • Next
• Pipeline stages
  • Data preparation
  • Classification
  • Optional classifier optimization
  • Hardware estimation
  • Optional quantum error correction curves
  • Visualization and report generation
  • Mapping stages to packages
  • Next
• Verification
  • Import and console script
  • Describe a baseline method
  • Smoke-run a tiny configuration
  • Link paper data when needed
  • Optional dependency checks
  • What success looks like

Suggested reading order

1. Overview describes the scientific problem ARCADE addresses and the surfaces of the repository you will touch day to day.

2. Installation lists core and optional dependencies and the extras that pull them in.

3. Pipeline walks through each stage from raw traces to a finished report so YAML sections map onto code packages.

4. Verification gives short commands that must succeed before you trust a longer zoo run.

After Quickstart, open Guides for concrete jobs, API Reference for exact symbols, and Tutorials for a paced first bake-off.