Sparsified Kolmogorov-Arnold Networks for Interpretable Quantum State Tomography 事件

Sparsified Kolmogorov-Arnold Networks for Interpretable Quantum State Tomography arXiv:2606.11814v1 Announce Type: cross Abstract: Machine-learning approaches to quantum state tomography can achieve high reconstruction fidelity, but the physical structure used by the trained model often remains implicit. Here we ask whether a sparsified Kolmogorov-Arnold Network (KAN) can be used not only as a regressor, but also as an inspectable reconstruction rule whose internal organization can be checked a