Accelerated Prediction of Terahertz Performance Metrics in GaN IMPATT Sources via Artificial Neural Networks

Accelerated Prediction of Terahertz Performance Metrics in GaN IMPATT Sources via Artificial Neural Networks

This work investigates the application of artificial neural network (ANN)-based regression models to predict the static and dynamic characteristics of GaN impact avalanche transit time (IMPATT) sources in the terahertz (THz) frequency regime. A comprehensive dataset, derived from self-consistent qua...

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Bibliographic Details
Main Authors: Santu Mondal, Sneha Ray, Aritra Acharyya, Rudra Sankar Dhar, Arindam Biswas, Hiroaki Satoh, Gurudas Mandal, Vitaliy Maksimenko, Victor Krishtop
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Artificial neural networks (ANN)
avalanche transit time (ATT)
IMPATT diodes
large-signal simulation
machine learning
self-consistent quantum drift-diffusion (SCQDD) model
Online Access:https://ieeexplore.ieee.org/document/10988773/
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