Post-selection in noisy Gaussian boson sampling: part is better than whole

Gaussian boson sampling is originally proposed to show quantum advantage with quantum linear optical elements.Recently, several experimental breakthroughs based on Gaussian boson sampling pointing to quantum computing supremacy have been presented.However, due to technical limitations, the computation results of Gaussian boson sampling are influenced severely by photon loss. Here, we present an efficient and practical method to reduce the negative effect caused by photon loss with no hardware modifications. Our method takes the data post-selection process that discards low-quality data according to our criterion to improve the performance of the final computational results, say part is better than whole. Besides improving the robustness of computation results of current GBS devices, this photon loss mitigation method may also benefit the further development of GBS-based quantum algorithms