Scalable Quantum-Classical DFT Embedding for NISQ Molecular Simulation

TL;DR

This paper introduces a scalable quantum-classical embedding method using QDFT for NISQ molecular simulations, achieving significant correlation energy recovery with practical qubit requirements.

Contribution

It presents a systematic quantum-classical embedding approach that efficiently recovers correlation energy on NISQ hardware, with benchmarks across various molecules.

Findings

Correlation energy recovery ranges from 63% to 68% across molecules.

Convergence achieved within two embedding iterations.

Approximately 60% correlation recovered with 10 qubits in a (4e,6o) active space.

Abstract

Scalable quantum-classical embedding is essential for chemically meaningful simulations on near-term NISQ hardware. Using QDFT, we show systematic recovery of correlation energy relative to the DFT baseline, benchmarked against CCSD in a fixed six-orbital active space across molecules ranging from water to naphthalene. By varying the number of embedded electrons from 2 to 8, aromatic systems saturate near 63-64 percent, while linear molecules such as carbon dioxide reach 68 percent. All systems converge within two embedding iterations under relaxed self-consistency thresholds, highlighting the robustness of the approach. A (4e,6o) active space recovers approximately 60 percent correlation using 10 qubits, providing practical guidelines for NISQ-era simulations.