Quantum-enhanced stochastic analysis

The recent algorithm for quantum-enhanced analysis of discrete stochastic processes estimates expectation values of the random variables of a simulated process, achieving optimal sampling variance. In this paper, the algorithm was adapted to include a memory efficient unitary simulator acting step-w...

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Bibliographic Details
Main Author: Chang, Derek Ding Cong
Other Authors: Gu Mile
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2023
Subjects:
Online Access:https://hdl.handle.net/10356/166392
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Institution: Nanyang Technological University
Language: English
Description
Summary:The recent algorithm for quantum-enhanced analysis of discrete stochastic processes estimates expectation values of the random variables of a simulated process, achieving optimal sampling variance. In this paper, the algorithm was adapted to include a memory efficient unitary simulator acting step-wise. The construction of the unitary and its implementation on quantum circuits were demonstrated for the perturbed coin process. The algorithm was further expanded by implementing quantum amplitude estimation with maximum likelihood estimation post-processing. The required quantum circuit for this was also demonstrated. It was found that the original algorithm can be boosted with amplitude estimation to achieve lower estimation error. However, it requires a minimum query complexity and there is no clear quantum speedup in sampling convergence rate.