A Survey of Quantum Alternatives to Randomized Algorithms: Monte Carlo
Integration and Beyond
- URL: http://arxiv.org/abs/2303.04945v1
- Date: Wed, 8 Mar 2023 23:39:49 GMT
- Title: A Survey of Quantum Alternatives to Randomized Algorithms: Monte Carlo
Integration and Beyond
- Authors: Philip Intallura and Georgios Korpas and Sudeepto Chakraborty and
Vyacheslav Kungurtsev and Jakub Marecek
- Abstract summary: We focus on the potential to obtain a quantum advantage in the computational speed of Monte Carlo procedures using quantum circuits.
We revisit the quantum algorithms that could replace classical Monte Carlo and then consider both the existing quantum algorithms and the potential quantum realizations.
- Score: 7.060988518771793
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Monte Carlo sampling is a powerful toolbox of algorithmic techniques widely
used for a number of applications wherein some noisy quantity, or summary
statistic thereof, is sought to be estimated. In this paper, we survey the
literature for implementing Monte Carlo procedures using quantum circuits,
focusing on the potential to obtain a quantum advantage in the computational
speed of these procedures. We revisit the quantum algorithms that could replace
classical Monte Carlo and then consider both the existing quantum algorithms
and the potential quantum realizations that include adaptive enhancements as
alternatives to the classical procedure.
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