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I am trying to find any references to train PQCs to map any probability distribution to a Normal Distribution. Suppose I have MNIST dataset, I want to apply PQC and make the readout distribution to be close to a discrete Normal distribution. Is it possible ?

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Yes, you can make use of Quantum Generative Adversarial networks and train the parameterized quantum circuit to load any distribution that you want. Here's an example of one such implementation:

Quantum GAN Implementation

Or this paper with this github repo

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  • $\begingroup$ Okay, but is there something like stable diffusion/VAE ? $\endgroup$ Commented Mar 20 at 17:22
  • $\begingroup$ Yes, this : github.com/YMajid/… $\endgroup$ Commented Mar 21 at 10:50
  • $\begingroup$ I went thru the code, it doesn't really construct any Quantum Circuit. it constructs a classical VAE to mimic a quantum state rather. $\endgroup$ Commented Mar 25 at 11:18

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