A 4 × 4 reconfigurable Mach-Zehnder interferometer (MZI)-based linear optical processor is investigated through its theoretical analyses and characterized experimentally. The linear transformation matrix of the structure is theoretically determined using its building block, which is a 2 × 2 reconfigurable MZI. To program the device, the linear transformation matrix of a given application is decomposed into that of the constituent MZIs of the structure. Thus, the required phase shifts for implementing the transformation matrix of the application by means of the optical processor are determined theoretically. Due to random phase offsets in the MZIs resulting from fabrication process variations, they are initially configured through an experimental protocol. The presented calibration scheme allows to straightforwardly characterize the MZIs to mitigate the possible input phase errors and determine the bar and cross states of each MZI for tuning it at the required sate before programming the device. After the configuration process, the device can be programmed to construct the linear transformation matrix of the application. In this regard, using the required bias voltages, the phase shifts obtained from the decomposition process are applied to the phase shifters of the MZIs in the device.

Implementing any linear transformation matrix through the optical channels of an on-chip reconfigurable multiport interferometer has been emerging as a promising technique for various fields of study, such as information processing and optical communication systems. Recently, the use of multiport optical interferometric-based linear structures in neural networks has attracted a great deal of attention. Optical neural networks have proven to be promising in terms of computational speed and power efficiency, allowing for the increasingly large neural networks that are being created today. This paper demonstrates the experimental analysis of programming a 4 × 4 reconfigurable optical processor using a unitary transformation matrix implemented by a single layer neural network. To this end, the Mach-Zehnder interferometers (MZIs) in the structure are first experimentally calibrated to circumvent the random phase errors originating from fabrication process variations. The linear transformation matrix of the given application can be implemented by the successive multiplications of the unitary transformation matrices of the constituent MZIs in the optical structure. The required phase shifts to construct the linear transformation matrix by means of the optical processor are determined theoretically. Using this method, a single layer neural network is trained to classify a synthetic linearly separable multivariate Gaussian dataset on a conventional computer using a stochastic optimization algorithm. Additionally, the effect of the phase errors and uncertainties caused by the experimental equipment inaccuracies and the device components imperfections is also analyzed and simulated. Finally, the optical processor is experimentally programmed by applying the obtained phase shifts from the matrix decomposition process to the corresponding phase shifters in the device. The experimental results show that the optical processor achieves 72% classification accuracy compared to the 98.9% of the simulated optical neural network on a digital computer.

The influence of gap plasmons in the third-harmonic generation of annular and H-shaped aperture arrays has been investigated. Surprisingly, the maximum third harmonic in the annular ring structures is not from the smallest gap, but rather appears for a gap of 14 nm. We interpret this result in terms of resonant plasmonic antenna design to match scattering and absorption cross sections. Unlike the annular aperture, continuous gold apertures, like the H-structure, achieve 0.45% conversion efficiency for 2 mW/μm2 CW pump power of a 100 fs pulse, which is 9 times larger than rectangular apertures we have reported in the past. Nonlinear scattering theory has been used to estimate the transmitted third-harmonic signal and is in generally good agreement with the experimental results.

We investigate the influence of localized and propagating surface plasmons on third harmonic generation from rectangular apertures in metal films. We designed optimal aperture array structures by using finite-difference time-domain simulations with nonlinear scattering theory. From this design space, we fabricated and measured the third harmonic in the region of maximal performance. We find the highest third harmonic conversion efficiency when the localized resonance is tuned to the fundamental wavelength and the propagating (Bragg) resonance is tuned to the third harmonic; this is 2.5 times larger than the case where the both localized and propagating are tuned to the fundamental wavelength. The two remaining configurations where also investigated with much lower conversion efficiency. When the Bragg resonance is tuned to the third harmonic, directivity improves the collection of third harmonic emission. On the other hand, due to the inherent absorption of gold at the third harmonic, tuning the localized surface plasmon resonance to the third harmonic is less beneficial. All cases showed quantitative agreement with the original theoretical analysis. This work points towards an optimal design criterion for harmonic generation from thin plasmonic metasurfaces.

We propose a photonic processing unit for high-density analog computation using intensity-modulation-based microring modulators (IM-MRMs). The output signal at the fixed resonance wavelength is directly intensity modulated by changing the extinction ratio (ER) of the IM-MRM . Thanks to the intensity-modulated approach, the proposed photonic processing unit is less sensitive to the inter-channel crosstalk. Simulation results reveal that the proposed design offers a maximum of 17-fold increase in wavelength channel density compared to its wavelength-modulated counterpart. Therefore, a photonic tensor core of size 512 $$\times $$ × 512 can be realized by current foundry lines. A convolutional neural network (CNN) simulator with 6-bit precision is built for handwritten digit recognition task using the proposed modulator. Simulation results show an overall accuracy of 96.76%, when the wavelength channel spacing suffers a 3-dB power penalty. To experimentally validate the system, 1000 dot product operations are carried out with a 4-bit signed system on a co-packaged photonic chip, where optical and electrical I/Os are realized using photonic and electrical wire bonding techniques. Study of the measurement results show a mean squared error (MSE) of 3.09$$\times $$ × 10$$^{-3}$$ - 3 for dot product calculations. The proposed IM-MRM, therefore, renders the crosstalk issue tractable and provides a solution for the development of large-scale optical information processing systems with multiple wavelengths.