Audio-SDS is a framework that applies the Score Distillation Sampling (SDS) concept to audio diffusion models. This technique can perform various audio tasks, such as physically guided impact sound synthesis and prompt-based source separation, without requiring specialized datasets by leveraging large pre-trained models. Its main advantage is making complex audio generation tasks more efficient through iterative optimization. This technology has broad application prospects and can provide a solid foundation for future research in audio generation and processing.