Researchers at the National Institute of Standards and Technology (NIST) have made a silicon chip that distributes optical signals precisely across a miniature brain-like grid, showcasing a potential new design for neural networks.
Above – NIST’s grid-on-a-chip distributes light signals precisely, showcasing a potential new design for neural networks. The three-dimensional structure enables complex routing schemes, which are necessary to mimic the brain. Light could travel farther and faster than electrical signals.
The human brain has billions of neurons (nerve cells), each with thousands of connections to other neurons. Many computing research projects aim to emulate the brain by creating circuits of artificial neural networks. But conventional electronics, including the electrical wiring of semiconductor circuits, often impedes the extremely complex routing required for useful neural networks.
NIST chip overcomes a major challenge to the use of light signals by vertically stacking two layers of photonic waveguides—structures that confine light into narrow lines for routing optical signals, much as wires route electrical signals. This three-dimensional (3D) design enables complex routing schemes, which are necessary to mimic neural systems. Furthermore, this design can easily be extended to incorporate additional waveguiding layers when needed for more complex networks.
The stacked waveguides form a three-dimensional grid with 10 inputs or “upstream” neurons each connecting to 10 outputs or “downstream” neurons, for a total of 100 receivers. Fabricated on a silicon wafer, the waveguides are made of silicon nitride and are each 800 nanometers (nm) wide and 400 nm thick. Researchers created software to automatically generate signal routing, with adjustable levels of connectivity between the neurons.
Laser light was directed into the chip through an optical fiber. The goal was to route each input to every output group, following a selected distribution pattern for light intensity or power. Power levels represent the pattern and degree of connectivity in the circuit. The authors demonstrated two schemes for controlling output intensity: uniform (each output receives the same power) and a “bell curve” distribution (in which middle neurons receive the most power, while peripheral neurons receive less).
We design, fabricate, and characterize integrated photonic routing manifolds with 10 inputs and 100 outputs using two vertically integrated planes of silicon nitride waveguides. We analyze manifolds via top-view camera imaging. This measurement technique allows the rapid acquisition of hundreds of precise transmission measurements. We demonstrate manifolds with uniform and Gaussian power distribution patterns with mean power output errors (averaged over 10 sets of 10 inputs) of 0.7 and 0.9 dB, respectively, establishing this as a viable architecture for precision light distribution on-chip. We also assess the performance of the passive photonic elements comprising the system via self-referenced test structures, including high-dynamic-range beam taps, waveguide cutback structures, and waveguide crossing arrays.
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