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The Quantum Qanary

Real-time dashboard tracking quantum computing's approach to breaking cryptography.

Live dashboard: jschulman.github.io/quantum-qanary

What This Tracks

Signal Source Update Frequency
Alert Level Milestone triggers + manual override On change
RSA Factoring Ladder Academic papers, vendor publications On event
ECDLP Ladder Academic papers, vendor publications On event
Hardware Progress Vendor announcements, press releases On event
PQC Adoption Matrix Product changelogs, security advisories Weekly
Blockchain PQC Status Chain governance, dev forums, GitHub Weekly
Government Funding CRS, RAND, CSIS, government reports Monthly
Research Velocity arXiv API (quant-ph, cs.CR) Daily
Q-Day Distance Estimate Weighted composite of above signals Weekly

Alert Levels

The dashboard uses a traffic-light system based on observable milestones:

  • GREEN — No quantum computer has factored anything beyond 21 bits using Shor's algorithm
  • YELLOW — Credible hardware demonstrations or government commitments signal accelerating timelines
  • ORANGE — Quantum factoring reaches ~100 bits, or insurance carriers begin requiring PQC readiness
  • RED — RSA-512 or 128-bit ECDLP broken by quantum computer (the canary is dead)

The Canary Ladders

Two parallel ladders track quantum progress toward breaking cryptography:

RSA Ladder — Tracks quantum factoring from 15-bit (achieved 2001) through RSA-2048 (Q-Day). The canary rung is RSA-512: once quantum computers reach this level, breaking RSA-2048 becomes an engineering problem, not a physics problem.

ECDLP Ladder — Tracks quantum attacks on elliptic curve cryptography. The canary rung is 128-bit ECDLP: this triggers the blockchain migration race, as Bitcoin and Ethereum keys use secp256k1 (256-bit).

Mosca's Theorem

The interactive calculator implements Mosca's inequality: if your data needs to stay secret for X years, and migrating to PQC takes Y years, and quantum computers break current encryption in Z years, start now if X + Y > Z.

Architecture

collectors/           Python scripts fetching live data
  arxiv_quantum.py      arXiv paper counts (daily)
  github_pqc.py         PQC library activity (weekly)
  alert_checker.py      Alert level computation (weekly)
normalizers/
  qday_distance.py      Weighted Q-Day distance estimate
data/                 Curated JSON data files (trigger files)
  alerts/               Alert status and triggered milestones
  factoring/            RSA and ECDLP canary ladders
  hardware/             Qubit records and roadmap targets
  adoption/             PQC deployment matrix
  blockchain/           Chain PQC readiness
  funding/              Government and private investment
  milestones/           Historical timeline
docs/                 Static dashboard (GitHub Pages)
  index.html            Single-page dashboard
  style.css             Dark mode styles
  dashboard.js          Chart.js visualizations + Mosca calculator
  data/                 Copy of data/ served to browser
.github/workflows/    Automated collection schedules

How It Updates

Automated: GitHub Actions run collectors on schedule (daily/weekly/monthly) and commit results.

Manual (trigger files): Edit any JSON file in data/, push, and the dashboard rebuilds automatically. Key trigger files:

  • data/alerts/status.json — Set override field to manually change alert level
  • data/factoring/records.json — Add new factoring milestones
  • data/hardware/qubit_records.json — Add hardware announcements
  • data/adoption/pqc_deployments.json — Update PQC deployment status
  • data/blockchain/pqc_status.json — Update chain readiness

Methodology

See METHODOLOGY.md for detailed documentation of how alert levels, Q-Day distance estimates, and risk components are calculated.

License

MIT

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Real-time dashboard tracking quantum computing's approach to breaking cryptography (Q-Day)

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