An apparatus for combined digital and optical processing of a cryptocurrency data block includes a digital processor that computes a hash vector from the cryptocurrency data block; a laser and splitter that produces optical input signals; optical modulators that binary phase-shift key modulate the optical input signals based on the hash vector; a photonic matrix multiplier circuit that performs an optically perform a discrete matrix-vector product operation on the modulated optical input signals to produce optical output signals, where the discrete matrix-vector product operation is defined by matrix elements limited to K discrete values, where 2K17; and photodetectors and comparators that perform optoelectronic conversions of the optical output signals to produce corresponding digital electronic output signals. The digital processor performs a second hash computation on an XOR result between the digital electronic output signals and the hash vector to produce a proof of work result.

An apparatus for combined digital and optical processing of a cryptocurrency data block includes a digital processor that computes a hash vector from the cryptocurrency data block; a laser and splitter that produces optical input signals; optical modulators that binary phase-shift key modulate the optical input signals based on the hash vector; a photonic matrix multiplier circuit that performs an optically perform a discrete matrix-vector product operation on the modulated optical input signals to produce optical output signals, where the discrete matrix-vector product operation is defined by matrix elements limited to K discrete values, where 2K17; and photodetectors and comparators that perform optoelectronic conversions of the optical output signals to produce corresponding digital electronic output signals. The digital processor performs a second hash computation on an XOR result between the digital electronic output signals and the hash vector to produce a proof of work result.

The present invention provides systems and methods for optical frequency comb generation with self-generated optical harmonics in mode-locked lasers for detecting the carrier envelope offset frequency. The mode-locked laser outputs an optical frequency comb and a harmonic output. The harmonic output provides an optical heterodyne resulting in a detectable beat note. A carrier envelope offset frequency detector detects the beat note and generates an optical frequency comb signal. The signal can be used to stabilize the optical frequency comb output.

The output computing unit includes cascade-connected N number of Y coupling elements having two inputs and one output, and N number of optical intensity modulators. The N number of light intensity modulators individually modulate the intensity of a continuous light to a second optical input port, which is different from a first optical input port to which no light is input or to which a signal light from an optical output port of a Y coupling element in a previous stage, out of two optical input ports of each of the cascade-connected N number of Y coupling elements, in accordance with corresponding bits of an N-bit electric digital signal. The output light acquired from the Y coupling element 1-N in the final stage is regarded as the N-bit digital analog computing result.

A phase shifter, a quantum logic gate apparatus, an optical quantum computing apparatus, and a phase shift method, where the phase shifter includes an optical resonant cavity and a quantum point, where a resonance frequency of the optical resonant cavity is .sub.c, the quantum point is located in the optical resonant cavity, and a transition frequency of the quantum point is .sub.x, the quantum point and the optical resonant cavity are coupled to form a coupled system, and a transition energy difference of the coupled system is determined by .sub.c, .sub.x, and a coupling strength between the quantum point and the optical resonant cavity (g), and .sub.x is set.

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.

The present invention relates to a coherent optical transistor device including: first and second coherent optical laser beams from a laser source; wherein the first beam has a relatively higher power/energy than the second beam of at least 2:1; and a permanent sub-wavelength structure in a unitary section into which the first and second beams enter, which permanently modifies a refractive index in both transverse and longitudinal directions; wherein every transverse spatial grating Fourier component in the sub-wavelength structure is phase-shifted by 90 degrees (pi/2) from each of corresponding Fourier components of a spatial interference of the first and second optical beams; and a refractive index profile in the unitary structure in the longitudinal direction is permanently modified, leading to a complete transfer of energy from the first to the second optical beam, resulting in a gain mechanism that results in an amplified signal beam and an inverted signal beam.

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 passive photonics reservoir computing system comprises an optical waveguide based structure comprising a plurality of discrete nodes and a plurality of passive waveguide interconnections between the nodes for propagating the at least one photonic signal between the nodes, in which each discrete node is adapted for passively relaying the at least one photonic wave over the passive waveguide interconnections connected thereto, wherein the optical waveguide based structure comprises at least one multimode Y-junction configured for connecting three waveguides using a taper section wherein the taper section is not perfectly adiabatic. A training scheme uses a passive photonics computing system.

In the examples provided herein, an optical logic gate includes multiple couplers, where no more than two types of couplers are used in the optical logic gate, and further wherein the two types of couplers consist of: a 3-dB coupler and a weak coupler with a given transmission-to-reflection ratio. The optical logic gate also includes a first resonator, wherein the first resonator comprises a photonic crystal resonator or a nonlinear ring resonator, wherein in operation, the first resonator has a dedicated continuous wave input to bias a complex amplitude of a total field input to the first resonator such that the total field input is either above or below a nonlinear switching threshold of the first resonator, where the optical logic gate is an integrated photonic circuit.