Park Hwiwoo, Park Jun H, Hwang Jungseek
Department of Physics, Sungkyunkwan University, Suwon, Gyeonggi-do, 16419, Republic of Korea.
School of Mechanical Engineering, Sungkyunkwan University, Suwon, Gyeonggi-do, 16419, Republic of Korea.
Sci Rep. 2024 Apr 19;14(1):9042. doi: 10.1038/s41598-024-59594-3.
We propose the regularized recurrent inference machine (rRIM), a novel machine-learning approach to solve the challenging problem of deriving the pairing glue function from measured optical spectra. The rRIM incorporates physical principles into both training and inference and affords noise robustness, flexibility with out-of-distribution data, and reduced data requirements. It effectively obtains reliable pairing glue functions from experimental optical spectra and yields promising solutions for similar inverse problems of the Fredholm integral equation of the first kind.
我们提出了正则化递归推理机（rRIM），这是一种新颖的机器学习方法，用于解决从测量的光谱中推导配对胶水函数这一具有挑战性的问题。rRIM将物理原理纳入训练和推理过程中，具有抗噪声能力、对分布外数据的灵活性以及降低的数据要求。它能有效地从实验光谱中获得可靠的配对胶水函数，并为第一类Fredholm积分方程的类似反问题提供了有前景的解决方案。
