saymrwulf/autoresearch-quantum
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5 commits

Author SHA1 Message Date
saymrwulf
18a7dc87be Remove pre-commit hooks, focus on local validation via app.sh 
All quality checks (ruff, mypy, tests) run through app.sh validate.
No external CI or hook infrastructure needed.
 2026-04-16 10:27:18 +02:00
saymrwulf
e7b8b02a88 Remove GitHub Actions CI — validate locally with app.sh validate 
CI ran on every push and generated failure emails. For a single-developer
project, local validation is sufficient and less noisy.
 2026-04-16 10:23:11 +02:00
saymrwulf
e7674ee5c0 Sync docs: clarify background behavior, complete command list 
- README: command table now says "in background (survives terminal close)"
  and explains foreground alternative
- THE_STORY Part 5: all 13 app.sh commands listed, background/foreground
  behavior explained, JupyterManager reference added
- THE_STORY Part 7.1: recommend app.sh bootstrap as primary setup path
 2026-04-16 09:52:24 +02:00
saymrwulf
55237d5f73 Sync all documentation with current project ground truth 
README: rewrite with Quick Start (app.sh), 335-test count, teaching layer
narrative, testing/validation section, CI/CD docs, pre-commit hooks.
THE_STORY: add Part 4 (teaching layer), Part 5 (app.sh consumer experience),
update file map with all 13 test files and teaching/notebook/paper entries.
compendium.tex: update notebook count (8→12), add Plan D cross-references.
autoresearch_quantum.tex: update test counts (21→335), add app.sh validate.
learning_objectives.md: add entry point reference and assessment type glossary.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
 2026-04-15 20:55:02 +02:00
saymrwulf
f9b8f3457f Initial commit: autoresearch-quantum — automated magic-state preparation ratchet 
Karpathy-style autoresearch engine for encoded magic-state preparation
on the [[4,2,2]] quantum error-detecting code using Qiskit Aer simulation.

Five-rung progressive search: baseline -> stability -> transfer -> factory -> Rosenfeld.
Smart challenger generation (neighbor walk + random combo + lesson-guided).
Machine-readable lesson feedback with per-dimension effects, interaction detection,
and cross-rung propagation. Factory throughput scoring. Resumable execution.
21 tests, all passing.
 2026-04-05 12:37:39 +02:00