Quantum Collapse

A scenario simulator for systemic risk during the post-quantum transition: what breaks, and in what order, when a cryptographically-relevant quantum computer (CRQC) defeats RSA/ECC across interdependent infrastructure?

It is not a forecast. It is a tool for exploring how failure cascades through a dependency graph under stated, documented assumptions — and how fast post-quantum migration contains the damage.

Two-project arc. Quantum Collapse asks "what breaks when CRQC arrives?" QEC Lab answers "what does a fault-tolerant quantum computer actually need to run Shor's?"

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Features

• 17-node infrastructure dependency graph — Certificate Authorities, banks, payment networks, cloud providers, telcos, hospitals, emergency services
• BFS cascade propagation — failure flows downstream; nodes survive only if their PQC migration % clears the threshold
• Staggered animation — cascade unfolds level-by-level with CSS keyframe animations (no rAF dependency)
• Migration sensitivity analysis — sweep 0 → 100 % migration rate and watch the failure count curve
• Mosca's Inequality calculator — interactive X/Y/Z sliders with live "LATE BY N YEARS" verdict
• Cascade timeline — per-level failure sequence rendered after each run
• 4 scenario presets — Tier-1 CA, Dual CA, Cloud Cascade, Payment Collapse
• Risk heat map toggle — recolor nodes by individual risk score instead of sector

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Architecture

backend/
  quantum_collapse/
    topology.py    # 17-node NetworkX DiGraph with crypto + criticality metadata
    cascade.py     # BFS propagation engine
    risk.py        # per-node risk scoring from crypto-vulnerability assumptions
  server.py        # FastAPI — /api/graph · /api/cascade · /api/sensitivity
  demo.py          # CLI demo, no server needed

frontend/
  index.html       # standalone — D3 v7 force graph + full control sidebar

docs/
  DESIGN.md        # documented assumptions behind every number

Composite risk formula (post-cascade):

• Failed node contributes criticality / 5 (full crypto exposure)
• Survived node contributes its pre-computed risk score

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Run it

Interactive dashboard

cd backend
pip install -r requirements.txt
uvicorn server:app --reload

Then open frontend/index.html in a browser. The page connects to http://localhost:8000, loads the graph, and is ready to simulate. No build step.

CLI demo (no server needed)

cd backend
python demo.py

Compromises GlobalCA, prints a sensitivity sweep to stdout, writes cascade.png.

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Decision thresholds

Score	Colour	Meaning
< 0.30	green	low systemic exposure
0.30 – 0.59	amber	moderate — migration urgency increasing
≥ 0.60	red	critical — cascade probable under partial CRQC capability

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Why the numbers aren't made up

Crypto vulnerabilities are keyed to the public consensus behind NIST's PQC standards (FIPS 203/204/205, 2024). Migration percentages and criticality scores are illustrative knobs — the project's point is sensitivity analysis over those knobs, not false precision. See docs/DESIGN.md.

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License

MIT © 2026 Pyhroff