The canonical catalogue lists 74 quantum algorithms with their published references; a handful are rigorously proven. This is the map that separates them — by how real the advantage is today, not by industry. Each class: its algorithm, the vertical it touches, the classical champion it must beat, and the honest state right now.
Field state · july 2026 · sourced, re-audited before each verdictThe distinction that orders everything below — and that most coverage blurs:
The axis is not "which industry" — it is how real the quantum advantage is today. This ordering is what a decision-maker, or a copilot, actually needs and nobody else publishes this way.
Wins on paper, but needs error correction / millions of qubits that don't exist yet. Not runnable fights — timing maps.
The strongest case theoretically: simulate the quantum with the quantum. The bottleneck is real — where a future win is most credible, and where the baseline is hardest.
Where most of the commercial hype lives and where classical is most brutal. QAOA / annealing don't beat well-tuned classical at scale. The right terrain for the first fight — the honest "not yet" is cheap and valuable.
Where the most was promised and the least held. High-value arbiter content precisely because almost nobody says it out loud.
Protein structure prediction is not quantum — and shouldn't be implied to be. AlphaFold (classical deep learning) solved a 50-year problem. If Rosetta touches "drug discovery" it must be surgical: the quantum value is in electronic-structure precision (Tier B), not in replacing a discovery pipeline that classical AI now leads. Saying this out loud raises arbiter credibility.
A serious computational chemist reads a molecular verdict knowing AlphaFold + classical docking already work. So the claim must be narrow: plausible quantum advantage lives in electronic structure of strongly-correlated systems (transition metals, certain excited states, cases DFT approximates poorly) — not "accelerating drug discovery" broadly. The narrow, exact claim protects us; the broad one exposes us.
Start in Tier C (portfolio or mining routing), not Tier B (molecular). Counterintuitive but correct: Tier C is cheap (QAOA simulable, free tier), the champion (OR-Tools) is brutal and free — so nobody can accuse us of a weak baseline — and the expected result, "classical wins, quantum hasn't crossed yet," is exactly the product: the first honest negative with an estimated crossover.
Molecular is tempting because advantage is more plausible — and that is why it's a bad first fight: a win there would be an extraordinary claim demanding extraordinary evidence, against a baseline that needs chemistry expertise. Credibility is built with the honest negative, not the risky win.
Above is the map by tier: our reading. Here is the raw catalogue, served from the database rather than hand-written: every entry in the Quantum Algorithm Zoo with the speedup the source declares, the primary papers, and the public implementations that exist.
Two things this table does not say. Each row's speedup is what the cited source declares, not a measurement of ours: declaring is not measuring. And cataloguing is not implementing — this page shows and documents them, it does not offer them as a service. The only column we assert is the evidence one, and it is empty on almost every row.
Showing 74 of 74
The archive did not answer. The same list is at /v1/algorithms.
Everything above comes from the same database that answers the API. Download the source, recompute its sha256 and compare it with the one declared by /v1/algorithms under procedencia.instantanea_sha256: if it matches, you are looking at the same catalogue we are. Agents read it over the API or over MCP with buscar_algoritmo_cuantico.