Evolutionary computation for adaptive quantum device design

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.

11 pages, 15 figures (including the Supporting Information, which has been included to the end of the paper)

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• Scalable Quantum Spin Networks from Unitary Construction
• Spatial correlations in the qubit properties of D-Wave 2000Q measured and simulated qubit networks
• Fast and efficient long-distance quantum state transfer in long-range spin-$\frac{1}{2}$ models
• State transfer analysis for linear spin chains with non-uniform on-site energies