Concurrent spin squeezing and field tracking with machine learning

The dataset contains:Steady_squeezing.zip <b>a)</b> data for steady squeezing data and characteraztion <b>b)</b> data for pulse RF magnetormeterTracking1.zip <b>a)</b> data of OU process for Deep learning <b>b)</b> data of OU-jump process for Deep learningTracking2.zip <b>a)</b> data of white noise process in backaction experiment <b>b) </b>data of white noise process in rearrange experimentCode <b>a)</b> Randomly signal generating code <b>b)</b> Deep learning codec.data pre-processing codeThe 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] .