Quantum Modeler · Custom QUBO

Model optimization problems as QUBOs. Validate small instances with quantum simulation.

Define a Binary Quadratic Model, inspect its Ising Hamiltonian, execute bounded QAOA, verify the original energy exactly, project larger models and export the circuit.

A QUBO (Quadratic Unconstrained Binary Optimization) uses binary variables and linear or pairwise interactions: E(x) = c + Σ aᵢxᵢ + Σ bᵢⱼxᵢxⱼ. Substituting xᵢ = (1 − Zᵢ)/2 gives the QAOA cost Hamiltonian.

Local execution limit: 8 variables. Minimization only. Negate objective coefficients to convert maximization. Business constraints must already be encoded in your coefficients.

Define your QUBO

Binary objectiveReducing this count removes coefficients and interactions outside the new range.

Linear coefficients

All coefficient magnitudes ≤ 1,000,000. Very small differences may fall below numerical/search tolerances.
Sparse interactions

Each distinct pair appears once; reversed duplicates are rejected. Use linear coefficients for xᵢ² = xᵢ.

Execution and projectionSupply both or leave both blank. At most N(N−1)/2 distinct target pairs. Projection is analysis only — the larger model is not executed.
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Ready to validate a small binary objective.

NOT CLAIMED

Modelling evidence, explicit limits

Ideal/noiseless simulation on classical hardware; p=1 with at most 64 parameter evaluations. No quantum advantage, speedup, scalability proof, physical QPU execution, fault-tolerant resource estimates, QAOA global optimality or production optimization quality is demonstrated. Larger targets are symbolic projections only.