feat/Quantum art visualization #183
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toncho11
reviewed
Sep 30, 2023
| @@ -98,12 +98,19 @@ def get_mne_sample(n_trials=10, include_auditory=False): | |||
| return X, y | |||
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| def get_qiskit_dataset(): | |||
| def get_qiskit_dataset(n_samples=30): | |||
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Wouldn't be confusing for someone who wants the entire dataset to get only 30 samples when calling the function without parameters?
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This dataset is generated. So you have to specify somehow the number of samples you want.
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I see. Then the name could be "generate_qiskit_dataset".
| # the variational quantum circuit which is used by VQC. | ||
| # | ||
| # The idea is simple : | ||
| # - We initialize a VQC with different number of parameters and number of samples |
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Add . at the end of this sentence.
| # | ||
| # The idea is simple : | ||
| # - We initialize a VQC with different number of parameters and number of samples | ||
| # - We train the VQC a couple of time and we store the fitted weights. |
| # The idea is simple : | ||
| # - We initialize a VQC with different number of parameters and number of samples | ||
| # - We train the VQC a couple of time and we store the fitted weights. | ||
| # - We compute variability of the weight and display it in a fashion way. |
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This is a PR, which explores a topic of quantum computing called quantum art, that is, some kind of artistic visualization of quantum.
We can find some examples here, where noise inside quantum calculation is used to generate bubbles. The number of bubbles and the size of each bubble then directly depend on the noise model inside the quantum computer.
In this PR, the fitted weight of the variational circuit inside VQC is displayed in a spiral. The number of "branches" in the spiral depends on the number of parameters, and the "larger" of each branch depends on the variability of the weights.