Concurrent spin squeezing and field tracking with machine learning

The dataset contains:

1. Steady_squeezing.zip a) data for steady squeezing data and characteraztion b) data for pulse RF magnetormeter
2. Tracking1.zip a) data of OU process for Deep learning b) data of OU-jump process for Deep learning
3. Tracking2.zip a) data of white noise process in backaction experiment b) data of white noise process in rearrange experiment
4. Code a) Randomly signal generating code b) Deep learning codec.data pre-processing code

The network is implemented using the torch 1.13.1 framework and CUDA 11.6 on Python 3.8.8. All weights are initialized with the torch default.

The training process is run on a computer with CPU Intel(R) CoreTM i7-8700 and GPU NVIDIA GeForce RTX 2070 (8G RAM).

Any questions about the codes or dataset are welcomed to the email 20110190074@fudan.edu.cn .