Taylor658/frequency-dispersion

# Frequency Dispersion Dataset 📡

> **Description**  
> This dataset provides **100,000 synthetic rows** to model **frequency dispersion** in photonic waveguides. It includes essential parameters such as **group index**, **chromatic dispersion**, and **mode group delay** across varying wavelength ranges, enabling simulation and optimization of waveguide designs for optical chips.

## Key Highlights ✨
- **Focus**: Frequency-dependent behavior of waveguides, specifically for **optical chips**.  
- **Columns**: 21 structured columns capturing wavelength ranges, material properties, dispersion metrics, and loss measurements.  
- **Size**: 100,000 rows, suitable for training machine learning models, validating designs, and simulating performance.  
- **Use Cases**:  
  - **Modeling dispersion effects** in optical communication systems.  
  - **Broadband photonic device design** for minimal dispersion.  
  - **Waveguide optimization** for real-world environmental conditions.  

## Dataset Structure 🏗️
Each row corresponds to a **single configuration or simulation result** for a waveguide, including:

1. **Wavelength Range**  
   - `wavelength_min` (nm): Minimum operating wavelength.  
   - `wavelength_max` (nm): Maximum operating wavelength.

2. **Dispersion Metrics**  
   - `group_index_min` and `group_index_max`: Group index values at the wavelength limits.  
   - `chromatic_dispersion` (ps/nm·km): Quantifies dispersion over the wavelength range.  
   - `mode_group_delay_min` and `mode_group_delay_max` (ps/m): Signal delay per meter.  
   - `material_dispersion` and `waveguide_dispersion`: Separate contributions to total dispersion.  

3. **Effective Index**  
   - `effective_index_at_min`: Effective refractive index at minimum wavelength.  
   - `effective_index_at_max`: Effective refractive index at maximum wavelength.  
   - `effective_index_change`: Change in refractive index across the range.

4. **Material Properties**  
   - `waveguide_material`: Core material (e.g., Silicon Nitride).  
   - `cladding_material`: Cladding material (e.g., Silicon Dioxide).  

5. **Loss and Environmental Parameters**  
   - `propagation_loss_min` and `propagation_loss_max` (dB/cm): Losses at wavelength limits.  
   - `temperature` (°C): Operating temperature.  
   - `signal_bandwidth` (GHz): Signal bandwidth.  
   - `device_length` (mm): Waveguide length.

6. **Metadata**  
   - `measurement_method`: Method used for data collection (e.g., Optical Time Domain Reflectometry).  
   - `measurement_uncertainty` (%): Error margin in data.

---

## Example Row
```text
wavelength_min                = 1260.0  
wavelength_max                = 1625.0  
group_index_min               = 1.50500  
group_index_max               = 1.52500  
chromatic_dispersion          = 10.25  
mode_group_delay_min          = 0.12  
mode_group_delay_max          = 0.18  
effective_index_at_min        = 1.45200  
effective_index_at_max        = 1.45900  
effective_index_change        = 0.00700  
waveguide_material            = Silicon Nitride (Si₃N₄)  
cladding_material             = Silicon Dioxide (SiO₂)  
propagation_loss_min          = 0.2  
propagation_loss_max          = 0.4  
measurement_method            = Optical Time Domain Reflectometry  
measurement_uncertainty       = 1.5  
temperature                   = 25.0  
signal_bandwidth              = 50.0  
device_length                 = 10.0  
material_dispersion           = 3.20  
waveguide_dispersion          = 7.05  

---

How to Use 💡

1. Download/Clone

   • Download the dataset manually or use Hugging Face’s datasets library:

     from datasets import load_dataset
     
     dataset = load_dataset("username/frequency-dispersion")
     

2. Loading and Exploration

   • Load into Python using pandas for quick exploration:

     import pandas as pd
     
     df = pd.read_csv("frequency-dispersion.csv")
     print(df.head())
     

3. Machine Learning

   • Use the dataset for regression tasks like predicting chromatic dispersion or group delay:

     features = df[[
         "wavelength_min", "wavelength_max", "temperature", 
         "signal_bandwidth", "device_length"
     ]]
     target = df["chromatic_dispersion"]
     
     # Train a regression model, e.g., scikit-learn, XGBoost, etc.
     

4. Performance Simulation

   • Model frequency dispersion effects and validate designs against target specifications.

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Caveats & Limitations ⚠️

• Synthetic Data: Generated based on typical photonic designs and may not represent all real-world scenarios.
• Simplifications: Assumes ideal waveguides with no fabrication-induced imperfections.
• Measurement Noise: measurement_uncertainty is a simulated value, not derived from real measurements.

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License 📄

This dataset is available under the MIT License. You are free to modify, distribute, and use it for commercial or non-commercial purposes—just provide attribution.

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Citation & Acknowledgments 🙌

If you use this dataset in your research or applications, please cite it as follows:

@misc{frequency_dispersion_dataset_2025,
  title  = {Frequency Dispersion Dataset (Synthetic)},
  author = {https://huggingface.co./Taylor658},
  year   = {2025},
  how published = {\url{https://huggingface.co./datasets/taylor658/frequency-dispersion}}
}

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Contributing 🧑‍💻

We welcome contributions!