Training data for ARPESNet

<p><strong>Datasets used for training the ARPESNet autoencoder.</strong></p> <p>Datasets:</p> <p>The training and test data are stored in the .zip files. Unzipping these will provide the files created by saving PyTorch tensors. These can be loaded with the python code:</p> <pre><code>import torch data = torch.load("filename.pt")</code></pre> <p>&nbsp;where filename can be any of the files in this repository.</p> <p><strong>train_data.zip &amp; test_data.zip:&nbsp;</strong>training and testing data, respectively. Collection of 256x256 ARPES spectra (images) obtained by randomly slicing 3D of 28 (train) and 18 (test) high resolution angle scans, covering 19 material systems: Au(110), Au(111), Bi2Se3(111), CoO2, on Au(111), CrSBr(001), Graphene on Ir(111), Graphene on Ru(0001), single-layer MoS2 on Au(111), single-layer NbSe2 on bilayer graphene, NdTe3(010), Pd(100), Pd(111), Pt(111), Rb-doped Bi2Se3(111), Ru(0001), P-&delta;-layer on Si(001), single-layer TaS2 on Au(111), single-layer WS2 on Ag(111) and&nbsp;single-layer&nbsp;WS2on Au(111).</p> <p>Each file corresponds to one material system, for which 500 images were generated, resulting in a tensor of shape 500x256x256 each.</p> <p><strong>test_imgs.pt:&nbsp;</strong>6 ARPES spectra used for visual inspection and performance test of the ARPESNet autoencoder.</p> <p><strong>cluster_centers.pt:&nbsp;</strong>ARPES spectra extracted by slicing an angle scan obtained measuring a Bi2Se3 crystal. These are used to generate simulated nanoARPES maps for testing clustering performance.</p> <p>dataset_info.csv: tabluar data describing the single datasets, their use in test or training and appropriate citation to the source publication wherre the data was first published.</p> <p>This repository contains the data related to the publication</p> <p>Steinn &Yacute;mir &Aacute;g&uacute;stsson, Mohammad Ahsanul Haque, Thi Tam Truong, Marco Bianchi, Nikita Klyuchnikov, Davide Mottin, Panagiotis Karras, Philip Hofmann;&nbsp;<strong>An autoencoder for compressing angle-resolved photoemission spectroscopy data</strong>. <em>Mach. Learn.: Sci. Technol.</em>&nbsp;<strong>6</strong> 015019 (2025) DOI: <a href="https://doi.org/10.1088/2632-2153/ada8f2" target="_blank" rel="noopener">10.1088/2632-2153/ada8f2</a></p> <p>Please cite the paper above in case of re-use of these data in a scientific publication.</p>