Quantum Modeler · Portfolio Selection

Portfolio Selection

Select exactly K assets using supplied expected returns and covariance. Minimize riskWeight × xᵀΣx − returnsᵀx. Binary asset holdings only; no fractional allocation, market feeds, or trading.

Execute at most 8 total qubits using an ideal classical statevector simulator. Symbolic scaling does not execute or solve a larger instance.

Build your problem

The starter selects asset 0. With risk weight 1, its exact objective is 1 − 3 = −2.

Problem inputsSpace or comma-separated finite numbers. The API checks symmetry and positive semidefiniteness within documented tolerances.
Execution settings

Depth 1 QAOA, at most 64 parameter evaluations. One completed build uses one run when usage limits are enabled.

Qubit budget

All decision and auxiliary variables count toward the limit. The API validates all constraints before reserving a run.

Read the mathematical methodology

Ready to validate a small instance.

Planned model families

TSP · Job Scheduling · Vehicle Routing remain roadmap items, not executable solvers.

No quantum advantage, real-QPU performance, physical-qubit requirement, or production-scale solution quality is claimed.