High-Performance Computing for Quantum Information Science

Quantum information science has gained significant attention in recent years, particularly due to the growing interest in quantum computing. In particular, computational tasks that are believed to take classical supercomputers years to complete have been executed in minutes with currently available noisy quantum computers, which refutes the extended Church-Turing thesis and has a monumental significance in theoretical computer science. Since we are still at the infancy of quantum computation, tremendous effort in simulating quantum systems with classical computers is needed to further our understanding of quantum information science. In this thesis, we focus on tensor network methods, and challenge some previous quantum supremacy claims. Specifically, we simulate Gaussian boson sampling quantum supremacy experiments on a classical supercomputer. Additionally, we show another numerical study that investigate the complexity of random quantum circuits. These exercises are crucial to the field as it elucidates the real requirements of achieving quantum supremacy.