A reusable search engine
The core defines four contracts: Genome, Score, CostFunction and EvolutionarySearch. Candidate representations implement mutation, identity and serialisation; the fitness function supplies the problem-specific evaluation. Selection, elitism, plateau recovery and checkpointing stay inside the search engine.
Quantum applications without a quantum-only core
The contributed modules use HierarQcal motifs and layered circuit genomes to express circuits across qubit counts. The tutorial also demonstrates symbolic regression without quantum dependencies, showing how the same search machinery applies to a different domain.
Engineering for experimentation
The framework includes parallel evaluation through configurable job counts, metrics and artifacts, search results, checkpoints and tutorial notebooks. Quantum dependencies are opt-in, keeping the generic core separate from its application libraries.
Explore the implementation
Source access is restricted to authorised collaborators. The repository link and clone command require access.
git clone https://github.com/SAED2906/QAS.gitCode example
class MyCost(CostFunction):
def evaluate(self, genome: Genome) -> Score:
... # Supply the problem-specific evaluation.
# EvolutionarySearch handles the shared search mechanics:
# selection, mutation, elitism and checkpointing.