Fine-grained quantum computational supremacy (1901.01637v4)

Abstract: Output probability distributions of several sub-universal quantum computing models cannot be classically efficiently sampled unless some unlikely consequences occur in classical complexity theory, such as the collapse of the polynomial-time hierarchy. These results, so called quantum supremacy, however, do not rule out possibilities of super-polynomial-time classical simulations. In this paper, we study "fine-grained" version of quantum supremacy that excludes some exponential-time classical simulations. First, we focus on two sub-universal models, namely, the one-clean-qubit model (or the DQC1 model) and the HC1Q model. Assuming certain conjectures in fine-grained complexity theory, we show that for any $a>0$ output probability distributions of these models cannot be classically sampled within a constant multiplicative error and in $2^{(1-a)N+o(N)}$ time, where $N$ is the number of qubits. Next, we consider universal quantum computing. For example, we consider quantum computing over Clifford and $T$ gates, and show that under another fine-grained complexity conjecture, output probability distributions of Clifford-$T$ quantum computing cannot be classically sampled in $2^{o(t)}$ time within a constant multiplicative error, where $t$ is the number of $T$ gates.