Neural Networks for Quantum Inverse Problems [article]

Ningping Cao, Jie Xie, Aonan Zhang, Shi-Yao Hou, Lijian Zhang, Bei Zeng
2021 arXiv   pre-print
Quantum Inverse Problem (QIP) is the problem of estimating an unknown quantum system ρ from a set of measurements, whereas the classical counterpart is the Inverse Problem of estimating a distribution from a set of observations. In this paper, we present a neural network based method for QIPs, which has been widely explored for its classical counterpart. The proposed method utilizes the quantum-ness of the QIPs and takes advantage of the computational power of neural networks to achieve higher
more » ... fficiency for the quantum state estimation. We test the method on the problem of Maximum Entropy Estimation of an unknown state ρ from partial information. Our method yields high fidelity, efficiency and robustness for both numerical experiments and quantum optical experiments.
arXiv:2005.01540v2 fatcat:imvdblmk7zdsngsl6uordrmjp4