tensorflow / tensorflow/quantum
[Discussion] Gradient of state op
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- Python
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Description
It was pointed out in #256 by @refraction-ray that once we had implemented the adjoint differentiation scheme, it might be possible for us to make our calculate_state op differentiable as well. Though initially we felt that giving people too many powerful tools outside of what is actually possible on a true QC was not the best idea, I feel like since we are catering towards more expert users adding this feature will be fine (since experts will know you can't differentiate through a whole state or calculate a whole state when running on a NiSQ chip).
@refraction-ray do you have any more inputs on implementation that you would like to share ?
@zaqqwerty and @jaeyoo how do you feel about allowing for state vectors to be differentiable ?
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Research direction
Review the calculate_state operation and the adjoint differentiation discussion in issue #256 first. A complete contribution would need an agreed scope for differentiating state vectors and tests demonstrating the intended behavior, but this issue does not identify files or acceptance criteria.
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Assessment
- Tech stack
- python, tensorflow
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100