Quantum simulation with hybrid tensor networks

Tensor network theory and quantum simulation are respectively the key classical and quantum methods in understanding many-body quantum physics. Here we show hybridization of these two seemingly independent methods, inheriting both their distinct advantageous features of efficient representations of many-body wave functions. We introduce the framework of hybrid tensor networks with building blocks consisting of measurable quantum states and classically contractable tensors. As an example, we demonstrate efficient quantum simulation with hybrid tree tensor networks that use quantum hardware whose size is significantly smaller than the one of the target system. We numerically test our method for finding the ground state of 1D and 2D spin systems of up to 8×8 and 4×3 qubits with operations only acting on 8+1 and 4+1 qubits, respectively. Our approach paves the way to the near-term quantum simulation of large practical problems with intermediate size quantum hardware, with potential applications in quantum chemistry, quantum many-body physics, quantum field theory, and quantum gravity thought experiments.