Two Micron Pixel Pitch Active Matrix Spatial Light Modulator Driven by Spin Transfer Switching

Magneto-optical spatial light modulator driven by current-induced domain wall motion for holographic display applications

We have developed a magneto-optical spatial light modulator (MO-SLM) with a 10 k × 5 k pixel layout and with a pixel pitch horizontally of 1 µm and vertically of 4 µm. An MO-SLM device pixel has a magnetic nanowire made of Gd-Fe magneto-optical material whose magnetization was reversed by current-induced magnetic domain wall motion. We successfully demonstrated the reconstruction of holographic images, showing large viewing zone angles as wide as 30 degrees and visualizing different depths of the objects. These characteristics are unique to holographic images, providing physiological depth cues which may play a vital role in three-dimensional (3D) perception.

Magneto-optical diffractive deep neural network

We propose a magneto-optical diffractive deep neural network (MO-D²NN). We simulated several MO-D²NNs, each of which consists of five hidden layers made of a magnetic material that contains 100 × 100 magnetic domains with a domain width of 1 µm and an interlayer distance of 0.7 mm. The networks demonstrate a classification accuracy of > 90% for the MNIST dataset when light intensity is used as the classification measure. Moreover, an accuracy of > 80% is obtained even for a small Faraday rotation angle of π/100 rad when the angle of polarization is used as the classification measure. The MO-D²NN allows the hidden layers to be rewritten, which is not possible with previous implementations of D²NNs.