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Clifford-efficient sparse state preparation for molecular wavefunctions
arXiv
Authors: Yingrong Chen, Nathan A. Baker, Rushi Gong, Conrad S. N. Johnston, Brad Lackey, Hongbin Liu, Sasha Schmidt, Yuan Su, David B. Williams-Young, Yinuo Yang
Year
2026
Paper ID
75464
Status
Preprint
Abstract Read
~2 min
Abstract Words
212
Citations
N/A
Abstract
Sparse quantum state preparation concerns an n-qubit target state that is a superposition of only d ll 2n computational basis states. Existing approaches exploit this sparsity by compressing these d basis states and their amplitudes onto a smaller set of qubits, called the dense register, before expanding the prepared state to the full register. Rather than relying on the permutation-based compression used in prior work, we exploit affine relationships among the binary configurations over the finite field operatorname{GF}(2) to reduce both the non-Clifford gate count and the ancillary qubit count. Invertible affine transformations over operatorname{GF}(2), comprising Gaussian elimination and all-ones-row removal, first reduce the dense register from n to the rank r using only Clifford gates and no ancillary qubits. An optional binary encoding stage then trades additional Toffoli gates and ancillary qubits for further compression to the minimum lceillog2 drceil dense qubits needed to represent d distinct configurations. For chemically relevant wavefunctions, such as those obtained from selected configuration interaction calculations, shared electronic excitation patterns produce many of these affine relationships, enabling substantial Clifford-only compression before binary encoding. Across the molecular benchmarks, our method requires the fewest ancillary qubits among the evaluated sparse state preparation methods while maintaining comparable non-Clifford gate counts when using binary encoding.
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- This paper contributes to the Quantum Chemistry research area in the Quantum Articles archive.
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- Sparse quantum state preparation concerns an n-qubit target state that is a superposition of only d ll 2^n computational basis states.
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