42 quantum tools, one URL: a field guide for non-PhDs

Most quantum computing platforms ask you to choose a framework, learn its DSL, write your own circuits, manage your own backends, and parse your own counts. We took the other path: 42 ready-to-run tools, each built around a real-world question, each with a plain-English form, each returning an answer you can act on. This piece walks through what those 42 tools actually do, grouped by what they're for.

1. Hardware benchmarks (5 tools)

These tell you how good a given quantum backend is on the day you ran your circuit. They're not flashy, but they're the bedrock of every credible claim downstream.

• Quantum Volume (QV) — IBM's headline number for "how big a square circuit can this device run before noise wrecks it?"
• Cross-Entropy Benchmarking (XEB) — Google's metric. Compares the measured distribution to the ideal one.
• Mirror Benchmarking — apply a random circuit and its inverse; the ideal answer is the initial state. Anything else is noise.
• Randomized Benchmarking (RB) — estimates the average gate error per Clifford.
• Iterative Phase Estimation (IPE) — measures a known phase with a single ancilla. Tests coherence + readout in one shot.

2. Chemistry (24 molecules)

The Variational Quantum Eigensolver (VQE) with a UCCSD ansatz computes the ground-state energy of a molecule. We have 24 molecules ready to run, from H₂ to LiH to BeH₂ to small organics, each with an editable bond length so you can produce real potential-energy curves. The reference energies come from published quantum chemistry calculations (cited in every report). If your answer disagrees with the literature by more than the error bar, you have a hardware story; if it agrees, you have a calibration story.

3. Finance (5 tools)

The classical finance world has solved these problems already. Why run them on a quantum computer? Three reasons: education (the QAE speedup is a textbook example you can hold), benchmarking (comparing a quantum run to Black-Scholes is the cleanest test of whether the encoding is correct), and forward planning (the algorithms scale to problems where the classical Monte Carlo budget eventually breaks).

• Black-Scholes via QAE — European option pricing with quantum amplitude estimation.
• Heston stochastic volatility — measurement-driven now (previously fabricated; we fixed it this campaign).
• SABR — same story. The vol surface comes out of measured probabilities.
• Value at Risk (VaR) — portfolio-level risk from a measured loss distribution.
• Credit Risk — default probabilities from amplitude estimation.

4. Algorithms (the textbook 14)

The teaching tools. Each is the right answer to a small question, with a real implementation rather than a slide deck:

• Bell pair, GHZ state — the entanglement primitives.
• Quantum Teleportation, Superdense Coding — what entanglement actually gets you.
• Grover's algorithm, Grover SAT — the canonical quadratic speedup.
• Shor's algorithm — factors derived from the measured period plus the chosen base. Real, not theatrical.
• Quantum Fourier Transform (QFT), Quantum Phase Estimation (QPE) — the workhorses behind everything else.
• Hamiltonian Simulation, Hubbard model — physics in a box.
• Quantum Walk — the building block of QAOA-style search.
• MaxCut, Knapsack — combinatorial optimization toys with serious downstream applications.
• Variational Quantum Classifier (VQC) — the simplest quantum machine-learning model that actually trains.

5. Optimization & CFD (3 tools)

• Route Optimizer — real OSM/OSRM geography. Pick N cities, get an optimized tour solved as a QUBO.
• Quantum CFD Solver — 2D Convecting Taylor-Green Vortex with a real Chorin projection time-march; quantum HHL on the pressure-Poisson linear solve. For aerodynamics, weather, and general incompressible Navier-Stokes work.
• VLAM Weight Compression (vlam-compress) — tensor- network model compression for Vision-Language-Action models. For shrinking large transformer weights onto embedded SoCs in autonomous-driving and robotics deployments.

6. Production research tools (biotech, energy, financial services)

• Allosteric Site Scanner — quantum walk on a protein contact graph for druggable-target discovery on cryptic and allosteric binding pockets.
• Grid Expansion Planning — QUBO formulation of which transmission lines to upgrade. For utility planners reinforcing distribution networks under congestion.
• Quantum Fraud Detector — quantum classifier on credit-card transactions. Honest feature labels, no synthetic magic, benchmarked vs LightGBM and XGBoost classical baselines.

What's missing (on purpose)

We don't sell tools that lie. Six tools in the catalog are flagged in our internal audit as "works but not fully polished" — for example, the portfolio tool's risk/horizon knobs are inert; the quantum walk's shift operator is an approximation. Those flags are public. We'd rather ship 36 calibrated tools and tell you the truth about 6 than ship 42 polished-looking lies.

How to pick one

If you want…

• To learn → start with Bell, GHZ, Grover, then QFT.
• To benchmark a backend → QV + Mirror + RB on the same day.
• To replicate a published quantum-chemistry result → VQE on H₂ at the published bond length.
• To explore quantum + finance → Black-Scholes via QAE first; it's the calibration baseline for everything else.
• To see something real for the boss → Route Optimizer with 6 cities. Visual, intuitive, runs on hardware.

Every tool above is sitting behind one sign-in at quantum-gap.com. Simulator runs are free. Hardware runs are $5 per QPU second.