Omkar2118/datasets huggingface dataset:
Lowest Common Ancestor Generations (LCAG) Phasespace Particle Decay Reconstruction Dataset

This dataset contains simulated synthetic particle decays, simulated using the [PhaseSpace](https://github.com/zfit/phasespace) library.
All simulated decay topologies have a common root particle of mass 100 (arbitrary units). Intermediate particles are selected at random with replacement from the following masses: [90, 80, 70, 50, 25, 20, 10].
Final state particles, which make up the leaf nodes of generated topologies, are drawn with replacement from the following masses: [1, 2, 3, 5, 12]. For each intermediate particle (including the root), we limit the minimum number of children to two, and the maximum five.
The dataset contains the resulting simulated particle physics decays, with information about the detected particle (leaves) to be used as input, and Lowest Common Ancestor Generations (LCAGs) to be used as training targets.

Tree topology creation to generate the dataset was as follows:
starting from the root particle a set of children are selected from the available intermediate and final state particles such that the sum of their masses totals less than the root, this process is then repeated for each child particle which is not a final state particle and so on until only final state particles remain.

This dataset consists of 200 topologies (unique decay processes) in total, with 16,000 samples per topology. In the paper's experiments, 2000 topologies for each of training, validation, and testing were used. Leaf node features are not normalized. We have not enforced any ordering of the nodes and leave them unsorted as created in the dataset.

Introducing paper: Learning Tree Structures from Leaves For Particle Decay Reconstruction