Clifford disentanglers for entanglement reduction in molecular electronic structure simulations

• URL: http://arxiv.org/abs/2606.12056v1
• Date: Wed, 10 Jun 2026 13:22:04 GMT
• Title: Clifford disentanglers for entanglement reduction in molecular electronic structure simulations
• Abstract summary: Entanglement is a key bottleneck limiting the efficiency of quantum simulations of molecular electronic structures.<n>We extend Clifford disentanglers as a structure-preserving approach to entanglement reduction.<n>We show that Clifford disentanglers can also benefit quantum simulations such as the shallow-circuit variational quantum eigensolver calculations.
• Score: 10.116379687096314
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Entanglement is a key bottleneck limiting the efficiency of tensor-network and quantum simulations of molecular electronic structures. Here, we systematically assess and extend Clifford disentanglers as a structure-preserving approach to entanglement reduction: they can modify the entanglement structure of qubit wavefunctions while retaining the Pauli-string form of qubit Hamiltonians. To enable a practical search over Clifford transformations, we classify Clifford operators by their action on the Schmidt spectrum across a bipartition, reducing the two- and four-qubit search spaces to 20 and 91392 representatives, respectively. Embedded in an iterative Clifford-augmented matrix product state framework, these transformations reduce the energy errors at fixed bond dimension for the molecular test cases studied and mitigate the dependence on orbital orderings and fermion-to-qubit mappings. We further show that Clifford disentanglers can also benefit quantum simulations such as the shallow-circuit variational quantum eigensolver calculations. Together, these results establish Clifford disentanglers as a useful structure-preserving entanglement-engineering tool for tensor-network and quantum simulations of molecular electronic structure, while also clarifying their correlation dependence and motivating future developments.

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