💡 Coherent Ising Machine Simulator (CIMSimulator)

A Julia-based simulator to explore the dynamics and optimization capabilities of Coherent Ising Machines (CIMs) — analog systems inspired by optical computing architectures for solving combinatorial problems.

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📚 Overview

This repository contains a modular and extensible simulator for Coherent Ising Machines, implemented in Julia. Users can interactively explore:

• Various Ising problem configurations
• Multiple simulation methods (including chaotic modulation strategies)
• Dynamic parameter tuning and modulation
• Performance of different control schemes (e.g., CIM-CAC, CIM-CFC)

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🗂️ Repository Structure

CIMSimulator/
├── src/
│   ├── CoherentIsingMachine.jl        # Core simulation engine
│   ├── IO.jl                          # Handles input/output and config parsing
│   └── Main.jl                        # CLI entry point
├── test/
│   └── test_CoherentIsingMachine.jl   # Unit tests
├── report/
│   ├── report.pdf                     # Full technical report
│   ├── slides.pdf                     # Presentation Slides (for non-experts)
│   └── summary.pdf                    # High-level findings
├── Dockerfile                         # Docker config for environment setup
├── Project.toml                       # Project environment and dependencies
└── LICENSE                            # License information

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🚀 Quick Start

📦 Run with Docker

Make sure Docker is installed.

# Step 1: Build the Docker image
docker build -t CIMSimulator .

# Step 2: Run the simulator interactively
docker run --rm -ti CIMSimulator

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🧠 Example Workflow

1. Launch the Simulator

   docker run --rm -ti CIMSimulator

2. Follow On-screen Prompts

   • 🔧 Problem Definition: Define your Ising Hamiltonian or select from predefined cases
   • 🧪 Method Selection: Choose a simulation type:
     • CIM
     • CIM - NLF
     • CIM - CAC (Chaotic Amplitude Control)
     • CIM - CFC (Chaotic Feedback Control)
     • CIM - SFC (Separable Feedback Control)
   • 📈 Modulation Strategy: Specify how amplitudes or gain change over time
   • ⚙️ Parameter Configuration: Fine-tune your experiment parameters

3. Run the Simulation

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✅ Testing

Unit tests are included to verify simulation integrity:

julia test/test_CoherentIsingMachine.jl

Ensure you have the required dependencies from Project.toml.

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📄 Report

• 📘 Full Report (PDF)
  "Chaotic Amplitude Control for the Ising Minimization using Optical Parametric Oscillator Systems"

• 📑 Executive Summary
  Key findings and methodology overview.

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👥 Contributors

Julius H. Ramlau, James S. Cummins, and Natalia G. Berloff

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📜 License

Distributed under the MIT License.

🌐 Related Topics

Coherent Ising Machines | Optical Computing | Nonlinear Dynamics | Combinatorial Optimisation | Analog Simulation | Julia for Physics