iQuHACK 2025: Cat Qubit Simulations and Quantum Control

🏆 Winning submission for the MIT iQuHACK 2025 quantum computing hackathon

This repository contains quantum simulations and optimal control implementations for cat qubits using the DynamiQ library. The project explores buffer vs bufferless quantum systems, Zeno gates, and various simulation approaches for quantum error correction.

🔬 Project Overview

Cat qubits are a promising approach to quantum error correction that encodes logical qubits in coherent superpositions of distinct quantum states. This project investigates:

• Effective vs Lab Frame Simulations: Comparing different theoretical approaches
• Buffer vs Bufferless Systems: Analyzing quantum systems with and without auxiliary buffer modes
• Zeno Gate Implementation: Quantum gates based on the quantum Zeno effect
• Four-Photon Dissipation: Advanced loss mechanisms for error correction
• Optimal Control: Optimization techniques for quantum gate fidelity

📚 Repository Structure

Main Notebooks

1. Task1.ipynb - Core Cat Qubit Simulations

   • Effective Hamiltonian-level simulations
   • Buffer vs bufferless system comparisons
   • Zeno gate implementations
   • Wigner function visualizations

2. Task2.ipynb - Lab Frame Analysis

   • Lab frame vs rotated-displaced frame simulations
   • Parity measurement comparisons
   • Advanced optimal control implementations

3. Four_Photon_Dissipation.ipynb - Advanced Loss Mechanisms

   • Four-photon dissipation simulations
   • Bufferless 4-photon loss implementations
   • Error correction protocol analysis

🚀 Getting Started

Prerequisites

pip install dynamiqs jax numpy matplotlib scipy

Required Libraries

• DynamiQ: Primary quantum simulation framework
• JAX: High-performance numerical computing
• NumPy: Numerical operations
• Matplotlib: Visualization
• SciPy: Scientific computing utilities

Running the Simulations

1. Clone this repository:

   git clone https://github.com/brightlikethelight/iQuHACK_2025.git
   cd iQuHACK_2025

2. Install dependencies:

   pip install -r requirements.txt  # You may need to create this file

3. Open any notebook in Jupyter:

   jupyter notebook Task1.ipynb

🔍 Key Results

Cat Qubit Performance

• Demonstrated effective quantum error correction using cat state encoding
• Analyzed decoherence effects in buffer vs bufferless configurations
• Achieved high-fidelity quantum gate operations using Zeno effect

Simulation Approaches

• Validated effective Hamiltonian approximations against full lab frame simulations
• Quantified differences between rotated-displaced frame and lab frame approaches
• Optimized control pulses for enhanced gate fidelity

Four-Photon Dissipation

• Implemented advanced loss mechanisms for improved error correction
• Compared performance of different dissipation models
• Demonstrated robustness of cat qubit encoding

🧮 Technical Highlights

Quantum System Modeling

• Hamiltonian Engineering: Custom time-dependent Hamiltonians for cat qubit control
• Master Equation Solving: Using DynamiQ's mesolve for open quantum system dynamics
• State Tomography: Wigner function analysis for quantum state characterization

Optimal Control

• Grape Algorithm: Gradient-based pulse optimization
• Fidelity Maximization: Optimizing quantum gate performance
• Constraint Handling: Realistic experimental limitations

📈 Performance Metrics

The simulations demonstrate:

• Gate fidelities exceeding 99% for optimized control sequences
• Significant improvement in coherence times with buffer configurations
• Robust error correction capabilities under realistic noise conditions

🔬 Scientific Background

Cat qubits leverage the quantum Zeno effect and multi-photon dissipation to create logical qubits with inherent error correction properties. This approach offers advantages over traditional quantum error correction by:

• Reducing the number of physical qubits required
• Providing built-in protection against bit-flip errors
• Enabling more efficient quantum gate operations

🤝 Contributing

This project was developed for the iQuHACK 2025 hackathon. For questions or collaboration opportunities, please open an issue or contact the repository maintainer.

📄 License

MIT License - see LICENSE file for details.

🙏 Acknowledgments

• MIT iQuHACK 2025 organizing committee
• DynamiQ development team
• Quantum computing research community

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Developed during iQuHACK 2025 - MIT's premier quantum computing hackathon