An integrated optical circuit for an optical neural network is provided. The integrated optical circuit is configured to process a phase-encoded optical input signal and to provide a phase-encoded output signal depending on the phase-encoded optical input signal. The phase-encoded output signal emulates a synapse functionality with respect to the phase-encoded optical input signal. A related method and a related design structure are further provided.

An optical neural network is constructed based on photonic integrated circuits to perform neuromorphic computing. In the optical neural network, matrix multiplication is implemented using one or more optical interference units, which can apply an arbitrary weighting matrix multiplication to an array of input optical signals. Nonlinear activation is realized by an optical nonlinearity unit, which can be based on nonlinear optical effects, such as saturable absorption. These calculations are implemented optically, thereby resulting in high calculation speeds and low power consumption in the optical neural network.

A system for parallel photonic computation, preferably including a source module, a plurality of input modulator units, an optical interference unit (OIU), and a plurality of detector banks. An OIU, preferably including one or more unitary matrix modules and optionally including a diagonal matrix module. An input modulator, which can include one or more waveguides, couplers, and/or modulator banks. A method for parallel photonic computing, preferably including encoding input vectors, performing a desired matrix operation, and receiving output values, and optionally including performing electronic computations and/or performing further optical computations based on the outputs, which can function to compute the results of a matrix operation on many different input vectors in parallel.

An optical computing device including a parametric oscillator array, an interaction computing matrix, a first feedback module connected to two ends of the parametric oscillator array, and a second feedback module connected to the parametric oscillator array and the interaction computing array. The parametric oscillator array is configured to receive a first group of signals, and generate a first group of optical signals including a plurality of first optical signals. The interaction computing array is configured to receive the first group of optical signals, and perform matrix operation on the first group of optical signals. The first feedback module is configured to receive the first group of optical signals, and transmit the first group of optical signals to the parametric oscillator array. The second feedback module is configured to receive the second group of optical signals, and transmit the second group of optical signals to the parametric oscillator array.

Embodiments of the present disclosure are directed toward techniques and configurations for optical couplers comprising a first optical waveguide and a second optical waveguide coupled to form a 2×2 optical unitary matrix to receive a respective first input optical signal and a second input optical signal. In embodiments the first optical waveguide and second optical waveguide form arms that converge alongside each other to direct the first input optical signal and the second input optical signal along a path that integrates a plurality of tunable phase shifters to transform the first input optical signal or the second input optical signal into a first output optical signal and second output optical signal to be output from the 2×2 optical unitary matrix. Additional embodiments may be described and claimed.

Described herein are photonic sources and related system architectures that can satisfy the optical power requirements of large photonic accelerators. Some embodiments relate to a computer comprising a photonic accelerator configured to perform matrix multiplication; a fiber array optically coupled to the photonic accelerator; and a photonic source optically coupled to the fiber array. The photonic source comprising a laser array comprising a plurality of monolithically co-integrated lasers, and a coupling lens array comprising a plurality of monolithically co-integrated lenses, the coupling lens array optically coupling the laser array to the fiber array. The laser array is configured to output between 0.1 W and 10 W of optical power.

A system performing optical and/or electro-optical tensor operations and featuring a photonic dot product engine with a first input and a second input and summation to perform multiply-accumulate operations. The first and/or second input is a matrix, and/or a vector, and/or scalar. The system is a Photonic Tensor Core.

Systems and methods that include: providing input information in an electronic format; converting at least a part of the electronic input information into an optical input vector; optically transforming the optical input vector into an optical output vector based on an optical matrix multiplication; converting the optical output vector into an electronic format; and electronically applying a non-linear transformation to the electronically converted optical output vector to provide output information in an electronic format. In some examples, a set of multiple input values are encoded on respective optical signals carried by optical waveguides. For each of at least two subsets of one or more optical signals, a corresponding set of one or more copying modules splits the subset of one or more optical signals into two or more copies of the optical signals. For each of at least two copies of a first subset of one or more optical signals, a corresponding multiplication module multiplies the one or more optical signals of the first subset by one or more matrix element values using optical amplitude modulation. For results of two or more of the multiplication modules, a summation module produces an electrical signal that represents a sum of the results of the two or more of the multiplication modules.

A system for photonic computing, preferably including an input module, computation module, and/or control module, wherein the computation module preferably includes one or more filter banks and/or detectors. A photonic filter bank system, preferably including two waveguides and a plurality of optical filters optically coupled to one or more of the waveguides. A method for photonic computing, preferably including controlling a computation module, controlling an input module, and/or receiving outputs from the computation module.

An optical neural network is constructed based on photonic integrated circuits to perform neuromorphic computing. In the optical neural network, matrix multiplication is implemented using one or more optical interference units, which can apply an arbitrary weighting matrix multiplication to an array of input optical signals. Nonlinear activation is realized by an optical nonlinearity unit, which can be based on nonlinear optical effects, such as saturable absorption. These calculations are implemented optically, thereby resulting in high calculation speeds and low power consumption in the optical neural network.