Phase-space simulations of feedback coherent Ising machines

Area of Science:

• Quantum Computing
• Computational Physics
• Optimization

Background:

• The coherent Ising machine (CIM) is a quantum computing architecture with potential for solving complex problems.
• Exact simulations of quantum systems are computationally demanding, limiting the study of devices like the CIM.
• Developing efficient simulation techniques is crucial for advancing quantum computing hardware and applications.

Purpose of the Study:

• To introduce a new, exact positive-P phase-space simulation technique for the coherent Ising machine quantum computer.
• To demonstrate that by designing the coupling matrix, general hard optimization problems can be solved using this technique.
• To validate the technique through computational simulations of a photonic parametric network implementing the CIM.

Main Methods:

• Development of an exact positive-P phase-space algorithm tailored for quantum simulations.
• Design of specific coupling matrices to map general hard optimization problems onto the CIM.
• Implementation of computational quantum simulations using a feedback-type photonic parametric network.

Main Results:

• Successful demonstration of exact positive-P phase-space simulations for the coherent Ising machine.
• Validation of the technique's capability to solve general hard optimization problems.
• Obtained success rate results from scalable quantum simulations of quantum feedback devices.

Conclusions:

• The presented phase-space simulation technique offers an exact and scalable method for studying the coherent Ising machine.
• This approach facilitates the investigation of CIM's potential for solving complex optimization problems.
• The findings pave the way for more efficient quantum simulations of quantum feedback systems.