Quantum Architecture Search (QAS) automates the design of parameterized quantum circuits for variational quantum algorithms, yet existing benchmarks organize instances by molecular identity or qubit count -- criteria agnostic to Hamiltonian structure -- and rely solely on energy accuracy, which cannot detect structural failures such as over-parameterization on near-product ground states. We introduce HamQASBench, a Hamiltonian-informed diagnostic benchmark organizing 11 molecules into five structural tiers via fingerprints derived from the Pauli operator basis, computational basis representation, and ground-state entanglement.
The paper introduces HamQASBench, a structure‑aware benchmark for quantum architecture search that includes eleven molecular Hamiltonians up to fourteen qubits, exact references, and a comprehensive evaluation protocol. The protocol combines energy accuracy, success rates, reference‑relative circuit cost, local entropy profiles for non‑degenerate targets, and state identification within degenerate ground subspaces. Experiments with five methods across four search paradigms show that energy‑only comparisons miss important differences, such as varying gate counts, distinct spin components in degenerate cases, and differing entanglement profiles, while still achieving chemical accuracy on a near‑product instance.
By Jiayang Niu, Akib Karim, Yan Wang, Jie Li, Ke Deng, Azadeh Alavi, Muhammad Usman, Yongli Ren
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By Jun Dai, Olivier Nahman-L\'{e}vesque, Guillaume Rabusseau, Hong-Ye Hu, Cunlu Zhou
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By Felix J. Beckmann, Jo\~ao F. Bravo