Gradient-based optimization of quantum photonic circuits is achieved via differentiable tensor networks that model nonlinear unitary gates and stochastic losses at low photon numbers.
Antibunching and un- conventional photon blockade with gaus- sian squeezed states.Physical Review A, 90(6):063824
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Optimizing Quantum Photonic Integrated Circuits using Differentiable Tensor Networks
Gradient-based optimization of quantum photonic circuits is achieved via differentiable tensor networks that model nonlinear unitary gates and stochastic losses at low photon numbers.