Evolving Quantum Circuits Using Genetic Algorithm
EH '02 Proceedings of the 2002 NASA/DoD Conference on Evolvable Hardware (EH'02)
Arithmetic on a distributed-memory quantum multicomputer
ACM Journal on Emerging Technologies in Computing Systems (JETC)
Automatic Synthesis for Quantum Circuits Using Genetic Algorithms
ICANNGA '07 Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part I
Quantum Circuit Simplification and Level Compaction
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Performance analysis for genetic quantum circuit synthesis
ICAISC'10 Proceedings of the 10th international conference on Artifical intelligence and soft computing: Part II
Adaptive vs. self-adaptive parameters for evolving quantum circuits
ICES'10 Proceedings of the 9th international conference on Evolvable systems: from biology to hardware
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The contribution presented herein proposes an adaptive genetic algorithm applied to quantum logic circuit synthesis that dynamically adjusts its control parameters. The adaptation is based on statistical data analysis for each genetic operator type, in order to offer the appropriate exploration at algorithm runtime without user intervention. The applied performance measurement attempts to highlight the "good" parameters and to introduce an intuitive meaning for the statistical results. The experimental results indicate an important synthesis runtime speedup. Moreover, while other GA approaches can only tackle the synthesis for quantum circuits over a small number of qubits, this algorithm can be employed for circuits that process up to 5-6 qubits.