Grover

Grover’s algorithm searches a 2**n-item database for marked items with quadratic speed-up over classical linear search.

Usage

from microquantum import SearchProblem
from microquantum.algorithms import GroverSearch

problem = SearchProblem(num_qubits=3, target=[1, 5], name="find-1-and-5")
print(problem.validate())               # []

grover = GroverSearch.from_problem(problem)
result = grover.solve(problem, seed=0)

print(result.most_probable)              # 1 — one of the marked items
print(result.num_iterations)             # 1 Grover iteration
print(result.success_probability)        # ~1.0

Problem types

SearchProblem is constructed from an explicit targets list or, in the classic form, from the problem’s decoder — the oracle marks a subset of the computational-basis states.

Notes

• The number of iterations is derived from the number of marked items; @staticmethod-style from_problem sets it automatically.

• An optional user-supplied oracle callable is supported (see the GroverSearch API reference).

Result

GroverResult carries found_items, the sampled bitstring counts, num_queries and success flags — all JSON-safe.