Concurrent spin squeezing and field tracking with machine learning

The dataset contains Steady_squeezing.zip .a. data for steady squeezing data and characteraztionb. data for pulse rf magnetormeter Tracking1a. data of OU process for Deep learningb. data of dOU process for Deep learning Tracking2a. data of white noise process in backaction experimentb. data of white noise process in rearrange experiment codea. Randomly signal generating codeb.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 [e-mail] .