Data repository for "Minimial-Risk Training Samples for QNN Training from Measurements"

<p>Replication code and experiment result data for training Quantum Neural Networks with entangled data using one-dimensional projectors as observables. This is the version of the code that was used to generate the experiment results in the related publication. </p> <p><b>Experiments</b>:<br /> - <code>exp_inf_coeffvariation.py</code>: Trains QNNs using training samples of varying Schmidt rank with fixed vector as Schmidt basis state. Varies the associated Schmidt coefficient.<br /> - <code>exp_inf_random.py</code>: Trains QNNs using random training data.<br/> </p> <p> <b>Experiment results:</b><br /> - <code>exp_inf_coeffvariation.zip</code> and <code>exp_inf_random.zip</code> contain the raw experiment results for both experiments.<br /> - For each combination of controlled variables there is one directory containing the result of all 20 runs of the training process.<br /> - The results for each run are comprised of 3 files: <br />   - <code>[id]_losses.npy</code>: The loss during the training process<br />   - <code>[id]_params.npy</code>: The parameters of the QNN after the training process.<br />   - <code>[id]_V.npy</code>: The trained QNN exported as a 2^4 * 2^4 unitary matrix. </p> <p> <b>Analysis of data</b> (<code>data_extraction.py</code>):<br /> - Computes means and standard deviation of various risk measures and saves the results </p> <p> <b>Plots</b> (<code>plot_obs_risk.py</code>):<br /> - Plots the risk w.r.t. the observable for both experiments based on the analysed data obtained from <code>data_extraction.py</code>.<br /> - Generates <code>plot_coeffvariation.pdf</code> and <code>plot_random.pdf</code>. </p>