[ENTRY] Feeding many trolls

[Praveen91299]

Team Name:

Team qumulus nimbus Praveen Jayakumar [email protected]

Project Description:

We provide a pennylane implementation of single qubit universal quantum classifier similar to that presented in [1] and [2]. We then provide an efficient method to parallely process classical data using a qram setup for the universal single qubit classifier.

We then attempt to address quantum classifiers by data reuploading for Quantum Data for experiments when we have copies of the quantum state and show it's performance. We observe that it does not help improve the performance of the classifier.

We use the universal quantum classifier method made earlier and fidelity based measurement strategies described in [1] to demonstrate a method of quantum music learning and generation by recasting the classifier into a markov chain like setup. We provide implementation for 7 note scales, 12 note full octaves and 5 note pentatonic scales. This method can be extended to different mappings too which is left for future work.

Presentation:

Jupyter notebook

Source code:

GitHub Repository

[co9olguy]

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