Getting more out of quantum coherence, pushing Robust Amplitude Estimation further

A universal fault-tolerant quantum computer holds the promise to speed up computational problems that are otherwise intractable on classical computers; however, for the near term we only have access to noisy intermediate-scale quantum (NISQ) computers. A major issue for quantum algorithms, especially in the NISQ era, is that they require too many independent measurements; this motivated Robust Amplitude Estimation (RAE), which is a quantum-enhanced algorithm for estimating expectation values of Pauli operators with fewer measurements. The impact of device noise on RAE is incorporated into one of its subroutines as a circuit-depolarizing noise model, which is unrealistic and hence hinders algorithmic performance. Rather than explicitly incorporating realistic noise effects in RAE, which is infeasible, we tailor device noise to generate an effective noise model, whose impact on RAE closely resembles that of the circuit-depolarizing model. Using IBM's quantum devices, we show that our noise-tailored RAE algorithm is able to regain improvements in both bias and precision that are expected for RAE in far noisier situations. Thus our work extends the feasibility of RAE on NISQ computers, consequently bringing us one step closer towards achieving quantum advantage using these devices.