Zahra
Using a neural network for finding the fit for pion’s time distribution in low energy levels.
I am utilizing a fully connected neural network setup to analyze the time distribution of Pions. The input for this study consists of cell times.
In this approach, 'celltime' is used as an input parameter to predict the frequency of events using the Neural Network setup. The code is based on the PyTorch framework, you can access the code through the following link https://gitlab.cern.ch/zfarazpa/nn-for-time-distribution-analysis/ Additionally, I calculate the mean and standard deviation from the predicted results. After training, the model's output can predict event frequencies over continuous time intervals. Subsequently, we can predict the mean and standard deviation of the generated results.
During our meeting, there was a proposal to include energy and detector layer information as additional input parameters. Furthermore, the training time interval will be set to (-12.5, 12.5).
