The 21-cm forest is a powerful probe for exploring the small-scale structures in the early universe. In this work, the authors use deep learning-driven likelihood-free parameter inference to quickly and accurately estimate parameters from minimally simulated datasets, while addressing the challenge of non-Gaussian likelihood function
- Tian-Yang Sun
- Yue Shao
- Xin Zhang
