Research paperComputational MultiscaleTheoreticalOptimizing Quantum Photonic Integrated Circuits using Differentiable Tensor NetworksMathias Van Regemortel, Thomas Van VaerenbergharXiv·2026·10.48550/arxiv.2509.11861·arXiv:2509.11861AbstractWe present a gradient-based optimization method for quantum photonic integrated circuits, composed of nonlinear unitary coupling gates and stochastic nonunitary components for sampling photonic losses. Differentiable tensor networks are used to simulate low-photon-occupation quantum circuits and to optimize designs for quantum state preparation and quantum phase-sensing readout, with field simulations of GaAs-based samples used to characterize the gate architecture.Read more
GaAs-based planar heterostructure / etched photonic integrated circuit baseline used to characterize the gate architecture with field simulations.No measurements recordedSimulatedGaAsStudied MaterialExpand
Research paperComputational MultiscaleTheoreticalOptimizing Quantum Photonic Integrated Circuits using Differentiable Tensor NetworksMathias Van Regemortel, Thomas Van VaerenbergharXiv·2026·10.48550/arxiv.2509.11861·arXiv:2509.11861AbstractWe present a gradient-based optimization method for quantum photonic integrated circuits, composed of nonlinear unitary coupling gates and stochastic nonunitary components for sampling photonic losses. Differentiable tensor networks are used to simulate low-photon-occupation quantum circuits and to optimize designs for quantum state preparation and quantum phase-sensing readout, with field simulations of GaAs-based samples used to characterize the gate architecture.Read more
GaAs-based planar heterostructure / etched photonic integrated circuit baseline used to characterize the gate architecture with field simulations.No measurements recordedSimulatedGaAsStudied MaterialExpand
Research paperComputational MultiscaleTheoreticalOptimizing Quantum Photonic Integrated Circuits using Differentiable Tensor NetworksMathias Van Regemortel, Thomas Van VaerenbergharXiv·2026·10.48550/arxiv.2509.11861·arXiv:2509.11861AbstractWe present a gradient-based optimization method for quantum photonic integrated circuits, composed of nonlinear unitary coupling gates and stochastic nonunitary components for sampling photonic losses. Differentiable tensor networks are used to simulate low-photon-occupation quantum circuits and to optimize designs for quantum state preparation and quantum phase-sensing readout, with field simulations of GaAs-based samples used to characterize the gate architecture.Read more
GaAs-based planar heterostructure / etched photonic integrated circuit baseline used to characterize the gate architecture with field simulations.No measurements recordedSimulatedGaAsStudied MaterialExpand
Research paperComputational MultiscaleTheoreticalOptimizing Quantum Photonic Integrated Circuits using Differentiable Tensor NetworksMathias Van Regemortel, Thomas Van VaerenbergharXiv·2026·10.48550/arxiv.2509.11861·arXiv:2509.11861AbstractWe present a gradient-based optimization method for quantum photonic integrated circuits, composed of nonlinear unitary coupling gates and stochastic nonunitary components for sampling photonic losses. Differentiable tensor networks are used to simulate low-photon-occupation quantum circuits and to optimize designs for quantum state preparation and quantum phase-sensing readout, with field simulations of GaAs-based samples used to characterize the gate architecture.Read more
GaAs-based planar heterostructure / etched photonic integrated circuit baseline used to characterize the gate architecture with field simulations.No measurements recordedSimulatedGaAsStudied MaterialExpand
