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Spatial-photonic Ising machine by space-division multiplexing with physically tunable coefficients of a
Optics Express
|January 5, 2024
Summary
This study introduces a novel space-division multiplexed spatial-photonic Ising machine (SDM-SPIM) for efficient optimization. The system physically computes weighted sums, demonstrating impact of optical parameters on problem-solving capabilities.
Area of Science:
- Physics
- Optical Computing
- Computational Science
Background:
- Ising machines are crucial for solving complex optimization problems.
- Current methods face challenges in scalability and efficiency for multi-component models.
- Photonic approaches offer potential for high-speed computation.
Purpose of the Study:
- To propose and validate a space-division multiplexed spatial-photonic Ising machine (SDM-SPIM).
- To demonstrate the physical calculation of weighted Ising Hamiltonians for multi-component systems.
- To investigate the influence of optical parameters on optimization search properties.
Main Methods:
- Development of a space-division multiplexed spatial-photonic Ising machine (SDM-SPIM).
- Utilizing space-division multiplexing to tune weight coefficients as optical parameters.
- Solving knapsack problems to verify system performance and parameter impact.
- Investigating a dynamic coefficient search algorithm to improve performance.
Main Results:
- The SDM-SPIM successfully calculates weighted sums of Ising Hamiltonians for multi-component models.
- Optical parameters were shown to significantly impact the search properties of the system.
- The system demonstrated validity in solving knapsack problems.
- A dynamic coefficient search algorithm was explored for enhanced performance.
Conclusions:
- The SDM-SPIM offers a novel physical computing approach for optimization problems.
- The system integrates optical and electronic processes for Hamiltonian calculation and optimization.
- Further development of dynamic coefficient search algorithms can enhance optimization capabilities.
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