Multiple Physical Qubits
Multiple physical qubits are the fundamental building blocks of quantum computers, and research focuses on improving their control, reducing errors, and leveraging their unique properties for computation. Current efforts concentrate on developing and optimizing quantum error correction codes, utilizing machine learning models (including neural networks and transformers) for tasks like state discrimination and decoding, and exploring hybrid quantum-classical algorithms for enhanced performance in applications such as image processing and optimization problems. These advancements are crucial for building more robust and powerful quantum computers, paving the way for breakthroughs in various scientific fields and practical applications.
Papers
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