Integrating Quantum Computing with Multiconfiguration Pair-Density Functional Theory for Biological Electron Transfer

• URL: http://arxiv.org/abs/2508.07359v1
• Date: Sun, 10 Aug 2025 14:18:05 GMT
• Title: Integrating Quantum Computing with Multiconfiguration Pair-Density Functional Theory for Biological Electron Transfer
• Authors: Yibo Chen, Zirui Sheng, Weitang Li, Yong Zhang, Xun Xu, Jun-Han Huang, Yuxiang Li,
• Abstract summary: VQE-PDFT is a quantum-classical hybrid framework that integrates variational quantum eigensolver with multiconfiguration pair-density functional theory.<n>We develop shallow-depth hardware-efficient ansatz circuits to enable applications in complex biological systems.
• Score: 8.663347271382479
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Accurate calculation of strongly correlated electronic systems requires proper treatment of both static and dynamic correlations, which remains challenging for conventional methods. To address this, we present VQE-PDFT, a quantum-classical hybrid framework that integrates variational quantum eigensolver with multiconfiguration pair-density functional theory (MC-PDFT). This framework strategically employs quantum circuits for multiconfigurational wavefunction representation while utilizing density functionals for correlation energy evaluation. The hybrid strategy maintains accurate treatment of static and dynamic correlations while reducing quantum resource requirements. Benchmark validation on the Charge-Transfer dataset confirmed that VQE-PDFT achieves results comparable to conventional MC-PDFT. Building upon this, we developed shallow-depth hardware-efficient ansatz circuits and integrated them into a QM/MM multiscale architecture to enable applications in complex biological systems. This extended framework, when applied to electron transfer in the European robin cryptochrome protein ErCRY4, yielded transfer rates that align well with experimental measurements. Importantly, successful execution on actual quantum hardware demonstrates practical feasibility for biological quantum computing applications, supported by comprehensive error analysis.

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