[Submitted on 22 Oct 2024]
A Machine Learning Approach to Trapped Many-Fermion Systems
Paulo F. Bedaque · Hersh Kumar · Andy Sheng
We apply a variational Ansatz based on neural networks to the problem of spin- fermions in a harmonic trap interacting through a short distance potential. We showed that standard machine learning techniques lead to a quick convergence to the ground state, especially in weakly coupled cases. Higher couplings can be handled efficiently by increasing the strength of interactions during "training".
- Comments:
- 8 pages, 5 figures
- Subjects:
- Nuclear Theory (nucl-th); cond-mat.dis-nn (cond-mat.dis-nn); Quantum Physics (quant-ph)
- arXiv:
- 2410.17383 [pdf]