Abstract
Within the framework of many-body perturbation theory based on Green's functions, the approximation has emerged as a pivotal method for computing quasiparticle energies and excitation spectra. However, its high computational cost and steep scaling present significant challenges for applications to large molecular systems. In this work, we extend the block tensor decomposition (BTD) algorithm, recently developed in our previous work [J. Chem. Phys. 163, 174109 (2025)] for low-rank tensor compression, to enable a formally -scaling algorithm. By integrating BTD with an imaginary-time formalism and introducing a real space screening strategy for the polarizability, we achieve an observed scaling of approximately in test systems. Key parameters of the algorithm are optimized on the S66 dataset using the JADE algorithm, ensuring a balanced compromise between accuracy and efficiency. Our BTD-based random phase approximation also exhibits scaling, and eigenvalue-self-consistent calculations become feasible for systems with over 3000 basis functions. This work establishes BTD as an efficient and scalable approach for large-scale calculations in molecular systems.