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Optimization problems often involve identifying maximum or minimum values under specific constraints. A well-known example is determining the longest horizontal pipe that can be moved around a right-angled corner, where a 3-meter-wide hallway meets a 2-meter-wide hallway. This scenario, common in architectural design and industrial transport, can be understood conceptually through geometric and trigonometric reasoning.To visualize the problem, consider the pipe as a straight line that touches...
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A toggle clamp is a mechanical device commonly used for holding and clamping objects in various applications, such as woodworking, metalworking, and assembly operations. Consider a toggle clamp subjected to a force of 200 N at the handle. The vertical clamping force can be calculated, provided the dimensions of the toggle clamp are known.
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A coherent Ising machine for 2000-node optimization problems.

Takahiro Inagaki1, Yoshitaka Haribara2,3,4, Koji Igarashi5

  • 1NTT Basic Research Laboratories, NTT Corporation, 3-1 Morinosato Wakamiya, Atsugi, Kanagawa 243-0198, Japan. inagaki.takahiro@lab.ntt.co.jp takesue.hiroki@lab.ntt.co.jp.

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Summary
This summary is machine-generated.

Researchers developed a 2000-spin network for combinatorial optimization, overcoming scalability issues in current Ising machines. This new coherent Ising machine demonstrates superior performance for complex problem-solving.

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Area of Science:

  • Quantum computing
  • Complex systems analysis
  • Combinatorial optimization

Background:

  • Combinatorial optimization problems are crucial for analyzing complex systems.
  • Mapping these problems to Ising models is a common approach.
  • Existing physical Ising machines face scalability limitations due to restricted spin couplings.

Purpose of the Study:

  • To address the scalability issues in physical Ising machines.
  • To develop a novel approach for solving complex optimization problems.
  • To implement a large-scale Ising machine with all-to-all couplings.

Main Methods:

  • Constructed a 2000-spin network with all-to-all spin-spin couplings.
  • Utilized time-multiplexed degenerate optical parametric oscillators.
  • Employed a measurement and feedback scheme for problem implementation.
  • Applied the system to maximum cut problems on arbitrary graph topologies.

Main Results:

  • Achieved a 2000-spin network, overcoming previous coupling limitations.
  • Successfully implemented maximum cut problems on graphs up to 2000 nodes.
  • Demonstrated superior accuracy and computation time compared to simulated annealing for a 2000-node complete graph.

Conclusions:

  • The developed coherent Ising machine offers a scalable solution for combinatorial optimization.
  • This approach significantly advances the potential of physical Ising machines for complex problem-solving.
  • The system shows promise for tackling large-scale optimization challenges in various scientific domains.