High-performance simulation of Rydberg atom arrays with tensor networks

Analog Hamiltonian Simulation (AHS) is a computational paradigm, that follows the original Feynman’s proposal of simulation of complex quantum systems using a highly controllable analogue system.

AHS is becoming an actively growing field of quantum computing with the leading hardware platforms based on the reconfigurable Rydberg atom arrays. Neutral atom simulators allow to study in-situ non-trivial quantum phases of matter such as topological spin liquids and can be a used as quantum annealers to solve classical combinatorial problems, such as weighted Maximum Independent Set (wMIS).

Despite a significant interest in the neutral atom arrays in quantum computing community, there is a lack of software tooling and high performance simulation software packages to study dynamics of Rydberg systems, in particular based on modern tensor network methods.

By leveraging Julia implementation of iTensor tensor network package we were able to simulate AHS programs, that are emulating annealing protocol for Quantum Approximate Optimization Algorithm (QAOA) for solving wMIS problems on randomized 2D graphs comprising ~250 atoms. By employing TEBD algorithm we showed that even a modest matrix product states bond dimension is sufficient to achieve a high fidelity solution of the wMIS problem.