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PreprintCC BY 4.0arXiv

Energy Accuracy Is Not Enough: A Structure-Aware Benchmark and Evaluation Protocol for Quantum Architecture Search

Abstract

Quantum architecture search for molecular ground-state estimation is commonly evaluated through energy accuracy, which does not describe circuit cost or the physical properties of the prepared state. We introduce HamQASBench, a structure-aware benchmark comprising eleven molecular Hamiltonians of up to fourteen qubits, selected using Hamiltonian and target-state properties and supplied with exact references. Its evaluation protocol combines energy accuracy and success rates with reference-relative circuit cost, local entropy profiles for non-degenerate targets, and state identification within degenerate ground subspaces. Experiments with five methods spanning four search paradigms reveal differences hidden by energy-only comparisons. On a near-product instance under the shallow search budget, the best outputs of all five methods reach chemical accuracy while using between two and sixty-two gates. Equal-energy outputs on a degenerate instance occupy distinct spin components. Local entropy profiles distinguish inaccurate outputs and show that entangling-gate counts need not reflect realized entanglement. Across the molecular instance ladder, product-state outputs can meet or miss chemical accuracy, motivating interpretation of success alongside target-state properties. These results support retaining energy as the task-success criterion while using circuit-cost and state diagnostics for more informative comparisons. The benchmark instances, references, evaluation implementation, and per-run data are released for reuse.

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BibTeX
@misc{niu2026energy,
  title = {{Energy Accuracy Is Not Enough: A Structure-Aware Benchmark and Evaluation Protocol for Quantum Architecture Search}},
  author = {Jiayang Niu and Akib Karim and Yan Wang and Jie Li and Ke Deng and Azadeh Alavi and Muhammad Usman and Yongli Ren},
  howpublished = {arXiv},
  year = {2026},
  month = sep,
  doi = {10.48550/arxiv.2607.04845},
  eprint = {2607.04845},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2607.04845},
  note = {CC BY 4.0},
}
RIS
TY  - UNPB
TI  - Energy Accuracy Is Not Enough: A Structure-Aware Benchmark and Evaluation Protocol for Quantum Architecture Search
AU  - Jiayang Niu
AU  - Akib Karim
AU  - Yan Wang
AU  - Jie Li
AU  - Ke Deng
AU  - Azadeh Alavi
AU  - Muhammad Usman
AU  - Yongli Ren
PY  - 2026
DA  - 2026/09/11
PB  - arXiv
DO  - 10.48550/arxiv.2607.04845
UR  - https://arxiv.org/abs/2607.04845
AB  - Quantum architecture search for molecular ground-state estimation is commonly evaluated through energy accuracy, which does not describe circuit cost or the physical properties of the prepared state. We introduce HamQASBench, a structure-aware benchmark comprising eleven molecular Hamiltonians of up to fourteen qubits, selected using Hamiltonian and target-state properties and supplied with exact references. Its evaluation protocol combines energy accuracy and success rates with reference-relative circuit cost, local entropy profiles for non-degenerate targets, and state identification within degenerate ground subspaces. Experiments with five methods spanning four search paradigms reveal differences hidden by energy-only comparisons. On a near-product instance under the shallow search budget, the best outputs of all five methods reach chemical accuracy while using between two and sixty-two gates. Equal-energy outputs on a degenerate instance occupy distinct spin components. Local entropy profiles distinguish inaccurate outputs and show that entangling-gate counts need not reflect realized entanglement. Across the molecular instance ladder, product-state outputs can meet or miss chemical accuracy, motivating interpretation of success alongside target-state properties. These results support retaining energy as the task-success criterion while using circuit-cost and state diagnostics for more informative comparisons. The benchmark instances, references, evaluation implementation, and per-run data are released for reuse.
ER  -