Entanglement Witness Derived By Using Kolmogorov-Arnold Networks

We utilize Kolmogorov-Arnold Networks to design an interpretable model capable of detecting quantum entanglement within a set of nine-parameter two-qubit states. This network serves as an entanglement witness, achieving an accuracy of $94\mathrm{\%}$ in distinguishing entangled states. Additionally, by analyzing the output functions of the KAN models, we explore the significance of each parameter (feature) in identifying the presence of entanglement. This analysis enables us to rank the features and eliminate the less significant ones, leading to the development of new entanglement witness functions that rely on fewer number of features, and hence do not require complete state tomography for their evaluation.