Logic Gate

Logic gates are fundamental building blocks of digital circuits, and research focuses on optimizing their design and implementation for improved performance and efficiency. Current efforts involve applying machine learning techniques, such as transformer networks and graph neural networks, to automate logic synthesis and improve the prediction of circuit quality metrics. This research is significant because it addresses challenges in electronic design automation, potentially leading to faster, smaller, and more energy-efficient computing systems, and also explores novel implementations using spiking neural networks and metamaterials. Furthermore, investigations into fault-tolerant and probabilistic logic gates are enhancing the reliability and robustness of digital systems.