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Evolutionary Computation for Adaptive Quantum Device Design

Luke Mortimer, Marta P. Estarellas, Timothy P. Spiller, Irene D'Amico

2021Advanced Quantum Technologies17 citationsDOIOpen Access PDF

Abstract

Abstract As noisy intermediate‐scale quantum (NISQ) devices grow in number of qubits, determining good or even adequate parameter configurations for a given application, or for device calibration, becomes a cumbersome task. An evolutionary algorithm is presented here which allows for the automatic tuning of the parameters of any arrangement of coupled qubits, to perform a given task with high fidelity. The algorithm's use is exemplified with the generation of schemes for the distribution of quantum states and the design of multi‐qubit gates. The algorithm is demonstrated to converge very rapidly, yielding unforeseeable designs of quantum devices that perform their required tasks with excellent fidelities. Given these promising results, practical scalability, and application versatility, the approach has the potential to become a powerful technique to aid the design and calibration of NISQ devices.

Topics & Concepts

Computer scienceQuantumTask (project management)Quantum computerComputationAlgorithmQuantum key distributionCalibrationEvolutionary algorithmQuantum algorithmGenetic algorithmTheoretical computer scienceEvolutionary computationQuantum phase estimation algorithmMeasurement deviceKey (lock)Quantum systemProbability distributionQuantum gateAlgorithm designComputer engineeringQuantum Computing Algorithms and ArchitectureNeural Networks and Reservoir ComputingEvolutionary Algorithms and Applications