Enable QEC and FTQC curves

The optional quantum error correction stage maps readout classifier outputs into stim noise models, then estimates logical error rate and wall-clock QEC cycle time. Idle / wait noise scales with readout duration plus a constant post-acquire control overhead. Cycle wall-clock is readout + control + decoder latency.

Install the QEC extra first:

pip install -e ".[qec]"

That extra pulls in Stim and PyMatching. Optional: beliefmatching for the BB default decoder. Without the extra, enabling qec fails at import time.

YAML configuration

qec:
  enabled: true
  codes: [surface, color, bb]
  experiments: [memory]
  decoders:
    surface: pymatching
    color: sinter_internal
    bb: belief_matching
  control_overhead_ns: 100.0
  tau_idle_ns: 50000.0
  include_decode_in_idle: false
  ler_duration_curve: true
  synthetic_duration_curve: true
  curve_shots: 2000
  readout_binding:
    full_readout_ns: 500
    scale_idle_with_duration: true

What each code is

Code	Circuit	Default decoder
`surface`	stim `surface_code:rotated_memory_z`	pymatching
`color`	stim `color_code:memory_xyz`	sinter_internal (pymatching)
`bb`	bivariate bicycle CSS code-capacity memory (circulant A,B)	belief_matching

walking_surface remains an experimental stub (surface + magic noise) and is not part of the public FTQC story.

Set synthetic_duration_curve when classifiers did not run a duration sweep and you still want illustrative length-versus-error points. Prefer real sweep points when they exist.

arcade run path/to/config.yaml

Demo export for the website:

python scripts/export_qec_figures.py --shots 200

Caveats

Demo curves use small shot counts; captions say so.
BB is code-capacity (not a full circuit-level BB schedule).
Idle map p = 1 - exp(-T/τ) is a coherence-scale model — set tau_idle_ns for your device.