Dataset for Optimal cross-correlation technique to search for strongly lensed gravitational waves

This dataset accompanies the OCCAM pipeline paper (https://doi.org/10.48550/arXiv.2601.22138), in which we present a cross-correlation-based method to search for strongly lensed gravitational wave candidates. The dataset contains population_samples_*.zip: samples from lensed and unlensed gravitational wave populations, which are used for the single-detector (Hanford) and multi-detector (HLV) analyses to assess the pipeline, ROC_*.csv: ROC values (FPP, TPP) corresponding to the result plots in Figs. 3 (single detector) and 4 (multi-detector) of the paper, read_data.ipynb: a Python notebook file to help with the usage of the data files. The population samples are generated following the More and More paper (https://doi.org/10.1093/mnras/stac1704), and filtered using the following criteria: For the single-detector analysis, we select events with an optimal matched-filter SNR threshold of 10 in the Hanford detector. For the multi-detector analysis, we choose events with a network optimal matched-filter SNR threshold of 8 in the HLV network, and 4 for individual detectors. The sample size is kept the same as in the single-detector analysis. The final version of the population samples that were used in the paper is provided here. The reader is requested to refer to the original OCCAM pipeline paper for more details.