Designing quantum experiments with a genetic algorithm

Nichols, Rosanna; Mineh, Lana; Rubio, Jes�s; Matthews, Jonathan C.F.; Knott, Paul A.

Abstract

We introduce a genetic algorithm that designs quantum optics experiments for engineering quantum states with specific properties. Our algorithm is powerful and flexible, and can easily be modified to find methods of engineering states for a range of applications. Here we focus on quantum metrology. First, we consider the noise-free case, and use the algorithm to find quantum states with a large quantum Fisher information (QFI). We find methods, which only involve experimental elements that are available with current or near-future technology, for engineering quantum states with up to a 100 fold improvement over the best classical state, and a 20 fold improvement over the optimal Gaussian state. Such states are a superposition of the vacuum with a large number of photons (around 80), and can hence be seen as Schrödinger-cat-like states. We then apply the two most dominant noise sources in our setting—photon loss and imperfect heralding—and use the algorithm to find quantum states that still improve over the optimal Gaussian state with realistic levels of noise. This will open up experimental and technological work in using exotic non-Gaussian states for quantum-enhanced phase measurements. Finally, we use the Bayesian mean square error to look beyond the regime of validity of the QFI, finding quantum states with precision enhancements over the alternatives even when the experiment operates in the regime of limited data.

Citation

Nichols, R., Mineh, L., Rubio, J., Matthews, J. C., & Knott, P. A. (2019). Designing quantum experiments with a genetic algorithm. Quantum Science and Technology, 4(4), Article 045012. https://doi.org/10.1088/2058-9565/ab4d89

• Journal Article Type: Article
• Acceptance Date: Oct 14, 2019
• Online Publication Date: Oct 29, 2019
• Publication Date: 2019-10
• Deposit Date: Oct 18, 2019
• Publicly Available Date: Oct 30, 2020
• Journal: Quantum Science and Technology
• Electronic ISSN: 2058-9565
• Publisher: IOP Publishing
• Peer Reviewed: Peer Reviewed
• Volume: 4
• Issue: 4
• Article Number: 045012
• DOI: https://doi.org/10.1088/2058-9565/ab4d89
• Public URL: https://nottingham-repository.worktribe.com/output/2858350
• Publisher URL: https://iopscience.iop.org/article/10.1088/2058-9565/ab4d89
• Additional Information: Journal title: Quantum Science and Technology; Article type: paper; Article title: Designing quantum experiments with a genetic algorithm; Copyright information: © 2019 IOP Publishing Ltd; Date received: 2019-06-04; Date accepted: 2019-10-14; Online publication date: 2019-10-29