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Quantum amplitude estimation algorithms on IBM quantum devices [PDF]
Quantum Communications and Quantum Imaging XVIII, 2020 Since the publication of the Quantum Amplitude Estimation (QAE) algorithm by Brassard et al., 2002, several variations have been proposed, such as Aaronson et al., 2019, Grinko et al., 2019, and Suzuki et al., 2020. The main difference between the original and the variants is the exclusion of Quantum Phase Estimation (QPE) by the latter.
Rao, Pooja +4 more
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Quantum Fourier Iterative Amplitude Estimation
2023 IEEE International Conference on Quantum Computing and Engineering (QCE), 2023 17 pages, 5 figures, 2 ...
de Lejarza, Jorge J. Martínez +3 more
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The Quantum Amplitude Estimation Algorithms on Near-Term Devices: A Practical Guide
Quantum Reports, 2023 The Quantum Amplitude Estimation (QAE) algorithm is a major quantum algorithm designed to achieve a quadratic speed-up. Until fault-tolerant quantum computing is achieved, being competitive over classical Monte Carlo (MC) remains elusive.
Marco Maronese +3 more
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Noise tailoring for robust amplitude estimation
New Journal of Physics, 2023 A universal fault-tolerant quantum computer holds the promise to speed up computational problems that are otherwise intractable on classical computers; however, for the next decade or so, our access is restricted to noisy intermediate-scale quantum (NISQ)
Archismita Dalal, Amara Katabarwa
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Towards Quantum Advantage in Financial Market Risk using Quantum Gradient Algorithms [PDF]
Quantum, 2022 We introduce a quantum algorithm to compute the market risk of financial derivatives. Previous work has shown that quantum amplitude estimation can accelerate derivative pricing quadratically in the target error and we extend this to a quadratic error ...
Nikitas Stamatopoulos +3 more
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Random-depth Quantum Amplitude Estimation
, 2023 The maximum likelihood amplitude estimation algorithm (MLAE) is a practical solution to the quantum amplitude estimation problem with Heisenberg limit error convergence. We improve MLAE by using random depths to avoid the so-called critical points, and do numerical experiments to show that our algorithm is approximately unbiased compared to the ...
Lu, Xi, Lin, Hongwei
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Error Resilient Quantum Amplitude Estimation from Parallel Quantum Phase Estimation
, 2022 We show how phase and amplitude estimation algorithms can be parallelized. This can reduce the gate depth of the quantum circuits to that of a single Grover operator with a small overhead. Further, we show that for quantum amplitude estimation, the parallelization can lead to vast improvements in resilience against quantum errors. The resilience is not
Braun, M. C. +3 more
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Quantum algorithm for credit valuation adjustments
New Journal of Physics, 2022 Quantum mechanics is well known to accelerate statistical sampling processes over classical techniques. In quantitative finance, statistical samplings arise broadly in many use cases.
Javier Alcazar +6 more
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A Hybrid Quantum Image-Matching Algorithm
Entropy, 2022 Image matching is an important research topic in computer vision and image processing. However, existing quantum algorithms mainly focus on accurate matching between template pixels, and are not robust to changes in image location and scale. In addition,
Guoqiang Shu +4 more
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Average-Case Verification of the Quantum Fourier Transform Enables Worst-Case Phase Estimation [PDF]
Quantum, 2022 The quantum Fourier transform (QFT) is a key primitive for quantum computing that is typically used as a subroutine within a larger computation, for instance for phase estimation.
Noah Linden, Ronald de Wolf
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