We propose a procedure to extract multiple parameters from the spectral characteristic of a single photonic integrated circuit. We applied the method on high order silicon Mach-Zehnder lattice filters:1 these filters are realized by cascading delay stages and directional couplers of different length. Because of their cascaded nature and steep roll-off properties, these devices can be used to accurately extract properties of the waveguides and the directional couplers. The spectral transmission is measured between the inputs and the outputs. This result is compared to a full CAPHE optical circuit simulation with parametric behavioral models for the waveguide and the directional couplers. An evolutionary fitting algorithm based on the covariance matrix adaptation method is used to match the circuit simulation with the measurement. This black box approach gives us fast and accurate parameter extraction with a reduced number of iteration steps. The quadratic error between measurement and simulation of each iteration is used as feedback for the evolutionary algorithm that adapts the test values for the following step. The objective of our analysis is an accurate, wavelength-dependent model for the waveguide group index and the directional couplers. The proposed method has been used for wafer scale parameter extraction. Our fast method makes it possible to extract the parameters in real time, and correlate the functional parameters of the waveguides with process statistics collected during fabrication. The obtained parameters are in substantial agreement with the results of the simulations used in the design, and can be used to further improve behavioral models that correlate the manufacturing process data with the optical performance.
All-optical spiking neural networks would allow high speed parallelized processing of time-encoded information, using the same energy efficient computational principles as our brain. As the neurons in these networks need to be able to process pulse trains, they should be excitable. Using simulations, we demonstrate Class 1 excitability in optically injected microdisk lasers, and propose a cascadable optical spiking neuron design. The neuron has a clear threshold and an integrating behavior. In addition, we show that the optical phase of the input pulses can be used to create inhibitory, as well as excitatory perturbations. Furthermore, we incorporate our optical neuron design in a topology that allows a disk to react on excitations from other disks. Phase tuning of the intermediate connections allows to control the disk response. Additionally, we investigate the sensitivity of the disk circuit to deviations in driving current and locking signal wavelength detuning. Using state-of-the-art fabrication techniques for microdisk laser, the standard deviation of the lasing wavelength is still about one order of magnitude too large. Finally, as the dynamical behavior of the microdisks is identical to the behavior in Semiconductor Ring Lasers (SRL), we compare the excitability mechanism due to optically injection with the previously proposed excitability due to asymmetry in the intermodal coupling in SRLs, as the latter mechanism can also be induced in disks due to, e.g., asymmetry in the external reaction. In both cases, the symmetry between the two counter-propagating modes of the cavity needs to be broken to prevent switching to the other mode, and allow the system to relax to its initial state after a perturbation. However, the asymmetry due to optical injection results in an integrating spiking neuron, whereas the asymmetry in the intermodal coupling is known to result in a resonating spiking neuron.
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