Optical Ising Machine With Modular All-Optical Feedback
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Solution Overview
Problem
Existing optical Ising machines face limitations in scalability and efficiency due to the need for iterative matrix-vector multiplication, which is constrained by the physical dimensions of the optical system, and require electronic bottlenecks for feedback processing.
Innovation Solution
An optical Ising machine design that utilizes a splitting tree, intensity and phase modulators, an optical matrix processing unit, homodyne detection, and a feedback circuit to perform all-optical computation, enabling matrix partitioning and phase encoding, allowing for scalable and fast computation without electronic bottlenecks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If iterative matrix-vector multiplication is used in optical Ising machines, then combinatorial optimization problems can be solved through ground state search, but the physical dimensions of the optical system limit the vector size and computational scalability
Solution Approach 1:
The patent divides the optical system into multiple functional modules: a splitting tree that divides the input beam into M beams, M modulators that encode the input vector, an optical matrix processing unit that performs matrix multiplication, and M detectors that read out the output. This modular segmentation allows the system to handle larger vector sizes by adding more modules rather than increasing the physical dimensions of individual components.
Solution Approach 2:
The patent transitions from traditional electronic computation to optical computation by encoding vector components into optical beam properties (amplitude and phase). The matrix processing unit performs multiplication operations in the optical domain using beam combiners and phase modulators, enabling scalable computation by leveraging the dimensional space of optical beams rather than being constrained by electronic component size.
2Speed
If electronic feedback processing is used in optical Ising machines, then iterative optimization can be implemented, but electronic bottlenecks limit computation speed
Solution Approach 1:
The patent replaces electronic feedback processing with optical feedback mechanisms. The output of the optical matrix processing unit is fed back to the modulators through optical pathways, eliminating the need for electronic conversion and processing. This substitution of electronic mechanisms with optical ones removes the electronic bottleneck and enables faster iterative optimization at the speed of light.
Solution Approach 2:
The patent introduces optical modulators as intermediaries that can be dynamically controlled to implement feedback. These modulators serve as the interface between the optical computation and the feedback control, allowing iterative optimization to be performed entirely in the optical domain without requiring electronic intervention in the feedback loop.
3Productivity
If matrix-vector multiplication is performed optically, then computation can be performed at the speed of light, but the vector size is limited by the number of optical components
Solution Approach 1:
The patent designs the optical matrix processing unit to be universally applicable for handling vectors of any size M. The same basic architecture of beam splitters, modulators, and detectors can be scaled to process increasingly large vectors by simply adding more beams and components, rather than requiring fundamentally different hardware for larger problem sizes.
Solution Approach 2:
The patent employs dynamically controllable modulators that can be programmed to implement different matrix operations. This dynamic reconfigurability allows the same physical system to adapt to different vector sizes and problem configurations, enabling the system to scale its effective capacity by changing the control parameters rather than by adding fixed hardware components.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables exceptionally fast and robust all-optical computation with high success rates and superior error tolerance, capable of handling large-scale optimization problems efficiently.
Implementation Method 1
a splitting tree for splitting a reference optical signal into M beams and at least one reference beam
Implementation Method 2
M intensity and/or phase modulators to encode an input vector of size M by respective amplitudes and/or phases of the M beams
Implementation Method 3
an optical matrix processing unit configured to perform multiplication of the input vector of size M and a matrix of size M×M to generate an output vector of size M encoded on the M beams
Implementation Method 4
a homodyne detection circuit configured to extract respective amplitudes and phases of the M beams after the optical matrix processing unit for determining components of the output vector of size M
Data Source
AI summary
An optical Ising machine and a method of applying an optical Ising machine for solving a combinatorial optimization problem. The method comprises the steps of splitting a reference optical signal into M beams and at least one reference beam; encoding an input vector of size M by respective amplitudes and/or phases of the M beams; performing multiplication of the input vector of size M and a matrix of size M×M to generate an output vector of size M encoded on the M beams; extracting respective amplitudes and phases of the M beams after the optical matrix processing unit using the reference beam for determining components of the output vector of size M; and applying new phase biases in the encoding of respective ones of the M beams based on the components of the output vector of size M for a next iteration of the optical Ising machine.