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Figure 1. The framework of the GCO algorithm for optimizing parameters in PQC.
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Figure 2. The parameterized quantum circuit (PQC) for classification tasks (a) and the details for uploading training data Xi and parameter θ into the PQC (b), where Xi = (x1,x2,…,xn) and θ = (θ1,θ2,…,θn).
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Figure 3. The cost value against the time for the three classification tasks in four types of noise by using GCO (red), BO (blue), BCO (black), and the adam-based method (pink) algorithms.
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Figure 4. The classification accuracy against the time respectively for the three classification tasks in four types of noise by using GCO (red), BO (blue), BCO (black), and the adam-based method (pink) algorithms.
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