Efficient experimental design of high-fidelity three-qubit quantum gates via genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@Article{devra:2018:QIP,

• author = "Amit Devra and Prithviraj Prabhu and Harpreet Singh and Arvind and Kavita Dorai",
• title = "Efficient experimental design of high-fidelity three-qubit quantum gates via genetic programming",
• journal = "Quantum Information Processing",
• year = "2018",
• volume = "17",
• number = "3",
• pages = "Article 67",
• month = mar,
• keywords = "genetic algorithms, genetic programming",
• ISSN = "1570-0755",
• URL = "https://ui.adsabs.harvard.edu/abs/2018QuIP...17...67D/abstract",
• URL = "http://link.springer.com/article/10.1007/s11128-018-1835-8",
• DOI = "doi:10.1007/s11128-018-1835-8",
• abstract = "We have designed efficient quantum circuits for the three-qubit Toffoli (controlled-controlled-NOT) and the Fredkin (controlled-SWAP) gate, optimized via genetic programming methods. The gates thus obtained were experimentally implemented on a three-qubit NMR quantum information processor, with a high fidelity. Toffoli and Fredkin gates in conjunction with the single-qubit Hadamard gates form a universal gate set for quantum computing and are an essential component of several quantum algorithms. Genetic algorithms are stochastic search algorithms based on the logic of natural selection and biological genetics and have been widely used for quantum information processing applications. We devised a new selection mechanism within the genetic algorithm framework to select individuals from a population. We call this mechanism the Luck-Choose mechanism and were able to achieve faster convergence to a solution using this mechanism, as compared to existing selection mechanisms. The optimization was performed under the constraint that the experimentally implemented pulses are of short duration and can be implemented with high fidelity. We demonstrate the advantage of our pulse sequences by comparing our results with existing experimental schemes and other numerical optimization methods.",

}

Genetic Programming entries for Amit Devra Prithviraj Prabhu Harpreet Singh Arvind Kavita Dorai

Citations