2021
DOI: 10.1002/qute.202100013
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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 desig… Show more

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Cited by 9 publications
(8 citation statements)
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References 37 publications
(35 reference statements)
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“…Leveraging concepts from machine learning and optimization, the control parameters of a 53 qubit quantum processor can be calibrated much faster than the system drift [337]. Automated tune-up is possible for any arrangement of coupled qubits [426]. Ultimately, for practical device operation, system calibration and control should be unified [621].…”
Section: System Identification and Calibrationmentioning
confidence: 99%
“…Leveraging concepts from machine learning and optimization, the control parameters of a 53 qubit quantum processor can be calibrated much faster than the system drift [337]. Automated tune-up is possible for any arrangement of coupled qubits [426]. Ultimately, for practical device operation, system calibration and control should be unified [621].…”
Section: System Identification and Calibrationmentioning
confidence: 99%
“…The plot demonstrates that, at 2t m,A , half of the excitation is at site 1 and the other half is in a superposition as given in Eq. (15). It is also clear from the plot that after few oscillation, at t = 8t m,A , the state of the system is almost a maximally entangled state between sites 1 and 7 as the EOF is very close to 1.…”
Section: Entanglement Generationmentioning
confidence: 76%
“…The generation of these two types of entangled states is illustrated in Fig. (15). The robustness of the bipartite maximally entangled state generated in Figure .(15) is investigated by measuring the EOF between sites 1 and 9 at the first time it forms (3t m /2), against both types of disorder, Fig (16).…”
Section: Other Entangled Statesmentioning
confidence: 99%
See 1 more Smart Citation
“…Leveraging concepts from machine learning and optimization, the control parameters of a 53 qubit quantum processor can be calibrated much faster than the system drift [333]. Automated tune-up is possible for any arrangement of coupled qubits [422]. Ultimately, for practical device operation, system calibration and control should be unified [615].…”
Section: System Identification and Calibrationmentioning
confidence: 99%