Fengping Jin

TL;DR: The performance of the quantum approximate optimization algorithm is evaluated by using three different measures: the probability of finding the ground state, the energy expectation value, and a ratio closely related to the approximation ratio as mentioned in this paper.

TL;DR: A revised version of the massively parallel simulator of a universal quantum computer, described in this journal eleven years ago, is used to benchmark various gate-based quantum algorithms on some of the most powerful supercomputers that exist today.

TL;DR: A number of simple quantum circuits are explored as benchmarks for gate-based quantum computing devices and it is shown that circuits performing identity operations are very simple, scalable and sensitive to gate errors and are therefore very well suited for this task.

TL;DR: A corpuscular simulation model of optical phenomena that does not require the knowledge of the solution of a wave equation of the whole system and reproduces the results of Maxwell's theory by generating detection events one-by-one is presented in this paper.

TL;DR: In this paper, the success of implementing superconducting qubit-based quantum gates is analyzed by numerically solving time-dependent Schrodinger equations for a transmon system and it is found that such metrics are not reliable to predict the performance of a quantum algorithm when the gates are used repeatedly.