A web-based simulator for Electromagnetically Induced Transparency (EIT) quantum memory, allowing users to visualize and understand the process of light storage and retrieval in atomic ensembles.
This simulator implements a numerical model of photon storage and retrieval in a Λ-type atomic ensemble, based on the formalism developed in Gorshkov et al., Phys. Rev. A 76, 033805 (link). It provides an interactive way to explore:
- Light pulse propagation through an atomic medium
- Storage of light in atomic coherence
- Retrieval of stored light
- Comparison between slow light and memory protocols
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Interactive Parameters: Adjust various physical parameters through an intuitive interface:
- Atomic properties (medium length, optical depth)
- Field parameters (detuning, control field strength)
- Timing parameters (pulse width, control field timing)
- Simulation parameters (grid resolution, duration)
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Real-time Visualization:
- Temporal evolution of field intensities
- Spatiotemporal evolution of field and spin wave intensities
- Visual indication of the atomic medium region
- Progress tracking during simulation
- Clone the repository:
git clone https://github.com/yourusername/Simulator_EIT_memory.git
cd Simulator_EIT_memory- Install the required dependencies:
pip install -r requirements.txt- Run the application:
streamlit run app.py-
Adjust the simulation parameters in the sidebar:
- Set atomic properties (medium length, optical depth)
- Configure field parameters (detuning, control field)
- Adjust timing parameters
- Fine-tune simulation settings
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Click "Run Simulation" to start the calculation
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Observe the results:
- Top plot shows temporal evolution of field intensities
- Bottom plots show spatiotemporal evolution of field and spin wave intensities
- The atomic medium region is marked in the spatiotemporal plots
The simulator implements the Maxwell-Bloch equations for a Λ-type atomic system:
- Propagation equation for the probe field
- Coupled atomic equations for polarization and spin wave
- Control field protocols for storage and retrieval
For detailed theoretical background, see the "More information about EIT memory" section in the application.
- Python 3.7+
- Streamlit
- NumPy
- SciPy
- Plotly