Faster Amplitude Estimation
arXiv:2003.02417 · doi:10.26421/QIC20.13-14-2
Abstract
In this paper, we introduce an efficient algorithm for the quantum amplitude estimation task which works in noisy intermediate-scale quantum(NISQ) devices. The quantum amplitude estimation is an important problem which has various applications in fields such as quantum chemistry, machine learning, and finance. Because the well-known algorithm for the quantum amplitude estimation using the phase estimation cannot be executed in NISQ devices, alternative approaches have been proposed in recent literature. Some of them provide a proof of the upper bound which almost achieves the Heisenberg scaling. However, the constant factor is large and thus the bound is loose. Our contribution in this paper is to provide the algorithm such that the upper bound of query complexity almost achieves the Heisenberg scaling and the constant factor is small.
10 pages
References in corpus (4)
Cited by in corpus (15)
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- The Problem with Grover-Rudolph State Preparation for Quantum Monte-Carlo
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- Noisy quantum amplitude estimation without noise estimation
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- Linear Regression by Quantum Amplitude Estimation and its Extension to Convex Optimization
- Noise-Aware Quantum Amplitude Estimation
- Comparison of Amplitude Estimation Algorithms by Implementation
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- Quantum Approximate Counting with Nonadaptive Grover Iterations
- Quantum State Preparation and Non-Unitary Evolution with Diagonal Operators