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I'm still investigating the TFQ whitepaper.

In one section of the paper, the authors say this with respect to Quantum Datasets

In general, [a quantum dataset] might come from a given black-box source...
However, as current quantum computers cannot import quantum data from external sources, the user has to specify quantum circuits which generate the data. Quantum datasets are prepared using unparameterized cirq.Circuit objects and are injected into the computational graph using tfq.convert_to_tensor

As I would like to investigate datasets like (QM9, QM8, etc.) and was hoping there was a way to involve TFQ/Cirq, this has raised a few questions for me.


Are there current methods for importing datasets containing Quantum Data onto a Quantum Computer? Similarly, is it possible to use TFQ or CIRQ or a similar Quantum-Computing/QML library to explore datasets like this in a way that garners a benefit from the use of Quantum Circuits and other Quantum Computer specific attributes?


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