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QuantumFunction -> DifferentiableClassicalFunction
Register custom vector-Jacobian products (VJPs) or Jacobian-vector products (JVPs) for a quantum circuit execution to make it differentiable within classical ML frameworks.
Problem it solves
Classical autograd engines cannot natively backpropagate through non-computational physical or simulated quantum executions.
Consumes
Emits
The real projects this mechanism was found in. Attribution is the point — this is how the best teams actually do it.