- author = "Christian Wood and Alberto Moraglio",
- title = "Noise Resilient Quantum Circuit Design by Multi-Objective Genetic Algorithm",
- booktitle = "GECCO Student Workshop",
- year = "2025",
- editor = "Alexander Brownlee",
- pages = "2612--2615",
- address = "Malaga, Spain",
- series = "GECCO '25 Companion",
- month = "14-18 " # jul,
- organisation = "SIGEVO",
- publisher = "Association for Computing Machinery",
- publisher_address = "New York, NY, USA",
- keywords = "genetic algorithms, genetic programming, evolutionary algorithms, quantum logic gates, quantum fourier transform, QFT, qiskit, NISQ",
- isbn13 = "979-8-4007-1464-1",
-
URL = "
https://doi.org/10.1145/3712255.3734316",
-
DOI = "
doi:10.1145/3712255.3734316",
- size = "4 pages",
- abstract = "Designing quantum circuits is a major challenge due to their sensitivity to noise and the complexity of quantum logic. This paper presents an evolutionary algorithm that balances multiple design criteria, namely fidelity and circuit depth, by combining them into a single scalarised fitness function. This approach enables efficient optimisation while avoiding the computational cost of fully multi-objective methods. A novel circuit representation and set of noise-aware genetic operators are introduced, and the technique is applied to evolve implementations of the Quantum Fourier Transform (QFT) for two- and three-qubit systems. Experimental results show that evolved circuits match or exceed ideal fidelity and outperform textbook QFT implementations under simulated noise. These findings highlight the potential of hardware-aware evolutionary design for producing circuits that are both accurate and resilient on near-term quantum hardware.",
-
notes = "list of tuples representation, rank selection,
33percent elistim, crossover and mutation. fitness,
Uhlmann fidelity, AerSimulator
GECCO-2025 Student Workshop workshop
A Recombination of the 34th International Conference on Genetic Algorithms (ICGA) and the 30th Annual Genetic Programming Conference (GP)",
