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  ```
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  4. **Synthetic Data Augmentation**
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- - Use this synthetic dataset to **supplement** smaller real datasets, enabling data-hungry deep learning models to generalize better.
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- ## Dataset Creation Process 🛠️
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- A Python script was used to randomly generate each column’s values within plausible ranges based on typical Si₃N₄ waveguide fabrication and performance data. The insertion loss is partially derived from the propagation loss and device length, and additional random offsets account for coupling losses and measurement variability.
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  ## Caveats & Limitations ⚠️
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  - **Synthetic Nature**: While ranges are inspired by real-world photonic designs, actual values may differ based on specific foundries, tools, and processes.
 
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  ```
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  4. **Synthetic Data Augmentation**
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+ - Use this synthetic dataset to **supplement** smaller real datasets
 
 
 
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  ## Caveats & Limitations ⚠️
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  - **Synthetic Nature**: While ranges are inspired by real-world photonic designs, actual values may differ based on specific foundries, tools, and processes.