Symbolic Pauli Propagation for Gradient-Enabled Pre-Training of Quantum Circuits
The method derives an explicit symbolic function for quantum observables as Pauli words with parameter-dependent coefficients. This allows classical pre-training of parameterized quantum circuits by using these representations to estimate gradients via the parameter-shift rule, offering a scalable way to obtain gradients before running on hardware.