Make a classifier for quantum data

The pitch

Classifiers are widely used in (classical) machine learning, e.g., for recognizing faces, objects, or characters in an image. By now, they are so well-advanced that they can compete with human-level abilities (think about how hard CAPTCHAs are getting for even a human to decipher). However, it should be hard for a classical classifier to work well on quantum data.

The goal of this project is to make a quantum classifier which can distinguish different types of quantum data. For example, it could be trained to distinguish between entangled and non-entangled states, or discriminate states which are easily simulated (e.g., those generated by Clifford circuits) from those which are hard to simulate.

What will you make?

Code which demonstrates the quantum-data classifier in action. Another form of deliverable could be a Pull Request on pennylane.ai/qml which implements and shows off the model

Helpful skills

Experience training machine learning models
Good understanding of quantum mechanics
Exposure to ansatz circuits and models in quantum machine learning

Team members

Any confirmed members of the team should be listed here. This lets others know what opportunities are still available.

For best results, include github and slack usernames for the team members.

- Team member 1 - @yourgithubname - yourslackname
- Team member 2 - @theirgithubname - theirslackname

GitHub repo

Set up your hackathon project with its own GitHub repo and link it here for the judges.

https://github.com/username/reponame

XanaduAI / QHack-2019