Minimum-variance binary selection

Track: exact-K binary selection. Interface: Python baseline API.

Enumerates all size-K subsets, selects the one with minimum variance, and reports its full mean–variance objective.

Dependencies: NumPy; no extra dependencies.

Key parameters: k fixes the subset size; lam and alpha affect reported scoring.

Guarantees and limits: Globally minimizes variance over the enumerated subsets, subject to floating-point scoring. It does not optimize the return term; enumeration is practical only for small instances.

Example

Use the shared inputs.

from vqe_portfolio.baselines import minimum_variance_binary_baseline

x, objective = minimum_variance_binary_baseline(mu, Sigma, lam=4.0, alpha=0.0, k=2)