Quantum-inspired clustering with light
arXiv:2405.04142 · doi:10.1038/s41598-024-73053-z
Abstract
This article introduces a novel approach to perform the simulation of a single qubit quantum algorithm using laser beams. Leveraging the polarization states of photonic qubits, and inspired by variational quantum eigensolvers, we develop a variational quantum algorithm implementing a clustering procedure following the approach proposed by some of us in SciRep 13, 13284 (2023). A key aspect of our research involves the utilization of non-orthogonal states within the photonic domain, harnessing the potential of polarization schemes to reproduce unitary circuits. By mapping these non-orthogonal states into polarization states, we achieve an efficient and versatile quantum information processing unit which serves as a clustering device for a diverse set of datasets.
5 pages, 5 figures
References in corpus (8)
- Variational Quantum Algorithms
- Noisy intermediate-scale quantum (NISQ) algorithms
- The effect of data encoding on the expressive power of variational quantum machine learning models
- Quantum machine learning beyond kernel methods
- Efficient tensor network simulation of IBM's Eagle kicked Ising experiment
- Efficient tensor network simulation of IBM's largest quantum processors
- Warm-Starting and Quantum Computing: A Systematic Mapping Study
- Universal classical optical computing inspired by quantum information process