2D Tensor Network Methods for Simulation of Spin Models on Quantum Computers

Tensor network states (TNS) provide an efficient framework for simulating quantum many-body systems with complex entanglement. We apply several classes of tensor networks to study the real-time dynamics of spin models in two dimensions. Our results show that TNS can enhance the accuracy of real-time simulations on noisy quantum hardware. Furthermore, we use these methods to assess the classical simulation complexity of programmable quantum simulation experiments in Quantinuum's trapped-ion quantum processors, providing benchmarks and insights for programmable digital quantum devices