Method and system for dual-neuron large-scale intelligent optical computing

A system for dual-neuron large-scale intelligent optical computing, comprising:

• a processor, and
• a memory communicatively connected to the processor and storing computer executable instructions;
• wherein the processor is configured to:
• construct an optoelectronic computing unit, and obtain an optical neuron by modeling the optoelectronic computing unit;
• abstract the optical neuron as an artificial neuron based on a mathematical abstraction manner;
• construct an optoelectronic neural network by connecting a plurality of artificial neurons, and perform a global optimization on network parameters of all the plurality of artificial neurons by applying end-to-end gradient descent on the optoelectronic neural network;
• optimize physical parameters of the optical neuron based on the artificial neuron after the global optimization;
• and
• compute the optoelectronic neural network based on the optimized parameters of the optical neuron.

A non-transitory computer-readable storage medium storing computer executable instructions,

• wherein the computer executable instructions, when executed by a processor, are configured to implement a method for dual-neuron large-scale intelligent optical computing, comprising:
• constructing an optoelectronic computing unit, and obtaining an optical neuron by modeling the optoelectronic computing unit;
• abstracting the optical neuron as an artificial neuron based on a mathematical abstraction manner;
• constructing an optoelectronic neural network by connecting a plurality of artificial neurons, and performing a global optimization on network parameters of all the plurality of artificial neurons by applying end-to-end gradient descent on the optoelectronic neural network;
• optimizing physical parameters of the optical neuron based on the artificial neuron after the global optimization;
• and
• computing the optoelectronic neural network based on the optimized parameters of the optical neuron.