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MEMS Oscillators-Network-Based Ising Machine with Grouping Method.

Yi Deng1,2, Yi Zhang1,2,3, Xinyuan Zhang1,2

  • 1Department of Electrical and Electronic Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong, 999077, China.

Advanced Science (Weinheim, Baden-Wurttemberg, Germany)
|May 2, 2024
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Summary
This summary is machine-generated.

This study introduces a novel, fast Ising machine using lithium niobate oscillators for complex combinatorial optimization problems. The new design achieves high speeds and competitive performance with lower hardware complexity.

Keywords:
Ising machineMEMS oscillatorMax‐Cutcombinatorial optimizationsemidefinite programming relaxation

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Area of Science:

  • Physics and Engineering
  • Computer Science
  • Artificial Intelligence

Background:

  • Combinatorial optimization (CO) problems are computationally complex (NP-complete/NP-hard), posing challenges for traditional digital computers.
  • Existing continuous-time Ising machine solvers often match digital hardware speeds and increase complexity through binarization.
  • There is a need for faster, lower-complexity hardware solutions for solving CO problems.

Purpose of the Study:

  • To propose a novel device-algorithm co-design for fast, sub-optimal solution finding in CO problems.
  • To develop a low-complexity Ising machine using a piezoelectric lithium niobate (LiNbO3) microelectromechanical system (MEMS) oscillator network.
  • To solve Max-cut and graph coloring problems efficiently.

Main Methods:

  • Designed a LiNbO3 MEMS oscillator network-based Ising machine operating without second-harmonic injection locking (SHIL).
  • Utilized a piezoelectric LiNbO3 oscillator network for high-speed operation (>9 GHz).
  • Implemented an innovative grouping method for algorithm-device co-design.

Main Results:

  • The LiNbO3 oscillator network achieved operating speeds exceeding 9 GHz, significantly faster than many existing Ising machines.
  • The proposed method achieved performance guarantees of 0.878 for Max-cut and 0.658 for graph coloring.
  • Performance is comparable to Ising machines that employ binarization, but with reduced hardware complexity.

Conclusions:

  • The novel device-algorithm co-design enables fast, low-complexity Ising machines for combinatorial optimization.
  • The LiNbO3 MEMS oscillator network represents a promising hardware platform for high-speed CO problem solving.
  • This approach offers a viable alternative to binarized Ising machines, balancing speed, performance, and hardware demands.