The $GW$ method delivers substantially improved accuracy in electronic band structure calculations over conventional Kohn–Sham density functional theory (KS-DFT) by explicitly incorporating the electron self-energy effect beyond mean-field approximations. In this work, we present an efficient NAO-PP-based $G^0{W}^0$ computational framework by interfacing the first-principles software package abacus with librpa, a library for performing low-scaling random-phase approximation and $GW$ calculations based on NAOs. Our approach employs the localized resolution of identity (LRI) technique with a compression scheme, significantly improving both computational efficiency and numerical stability. In addition, an analytic treatment of the small-$\mathbf{q}$ limit of the microscopic dielectric function reduces the need for dense $\mathbf{q}$-point sampling. Furthermore, we quantify how the choice of explicitly treated valence electrons affects the frequency-dependent macroscopic dielectric response and the resulting $G^0{W}^0$ quasiparticle energies. Systematic benchmarks validate the effectiveness of our compression scheme and real-space tensor filtering strategies, demonstrating both high accuracy and significant computational efficiency gains. Comparisons with established $G^0{W}^0$ implementations show excellent agreement in band structures and band gaps, confirming $\mathrm{ABACUS}+\mathrm{LibRPA}$ as a reliable and efficient platform for large-scale $G^0{W}^0$ simulations.

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• Band gap
• Electronic structure
• Spin-orbit coupling
• Semiconductors
• Band structure methods
• First-principles calculations
• GW method
• Pseudopotentials