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Programmable 200 GOPS Hopfield-inspired photonic Ising machine.

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This study introduces a novel room-temperature optoelectronic oscillator (OEO)-based Ising machine. This scalable photonic system achieves high-speed computation for complex optimization problems, outperforming existing photonic Ising machines.

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Area of Science:

  • Physics
  • Computer Science
  • Engineering

Background:

  • Ising machines are promising for NP-hard problems, but current physical implementations lack scalability, reconfigurability, speed, and stability.
  • Quantum annealers face scalability limitations due to quadratic qubit requirements for dense graphs.
  • Existing photonic Ising machines struggle with large-scale problem solving.

Purpose of the Study:

  • To introduce a programmable, stable, room-temperature optoelectronic oscillator (OEO)-based Ising machine with linear scaling.
  • To demonstrate a photonic Ising machine capable of solving large-scale combinatorial optimization problems.
  • To explore the potential of integrating digital signal processing (DSP) into optical computing for enhanced performance.

Main Methods:

  • Developed a recurrent time-encoded loop architecture using cascaded thin-film lithium niobate (TFLN) modulators, a semiconductor optical amplifier (SOA), and a DSP engine.
  • Achieved linear scaling in spin representation for problem solving.
  • Utilized inherent noise from high baud rates to escape local minima and accelerate convergence.

Main Results:

  • Demonstrated a system capable of solving fully connected problems up to 256 spins and sparse problems with over 41,000 spins.
  • Achieved potential computational speeds exceeding 200 giga operations per second (GOPS).
  • Obtained best-in-class solution quality for max-cut problems (2,000 and 20,000 spins) and ground-state solutions for number partitioning and lattice protein folding benchmarks.

Conclusions:

  • The developed OEO-based Ising machine offers a scalable, high-speed, room-temperature solution for complex optimization.
  • Integrating DSP enhances convergence and solution quality, paving the way for advanced optical computing.
  • This platform opens new frontiers in ultrafast computing for optimization, neuromorphic processing, and analogue artificial intelligence.