Book Summary

This book will highlight recent research and technological progress on the development and implementation of Decoders for Quantum Error Correction.

Quantum computers are a revolutionary new technology which offers enormous potential to solve computationally intense problems that are currently intractable on classical computers. Due to the anticipated massive socio-economic benefits of quantum computing,  large technology companies such as Google, IBM, Intel, and Nvidia, as well as leading academic and research organisations and universities are actively developing quantum processors. Despite remarkable progress in recent years, qubits are still highly prone to errors or noise resulting from their interactions with environment, fabrication imperfections, and control errors. Therefore, a huge amount of research is focusing on developing Quantum Error Correction methods which can correct qubit errors and enable high fidelity quantum operations necessary for real-world applications. 

An integral part of Quantum Error Correction is Decoding in which error information is obtained from qubits and passed on to a classical supercomputer to obtain corrections which will be applied to qubits to fix errors. Decoding step must be done fast and at large scale to be able to rapidly correct errors for millions of qubits without their accumulation. Significant research has been done on developing various methods for Decoding which include graph-based decoders and the application of machine learning models. 

This book will focus on the Decoding step in the Quantum Error Correction pipeline and will serve as a timely and important reference on a rapidly advancing topic of research. The book will consist of Invited Chapters from leading researchers covering both academia and industry from around the world. The book will cover a broad range of topics including fundamentals of quantum error correction and decoding, methods to develop and implement decoders such as based on graph theory and artificial intelligence, progress towards real-time decoders, implementation of decoders on various quantum processor platforms such as superconducting, semiconductor, trapped-ion, photonic, and neutral atoms. The book will also present a couple of chapters discussing challenges in implementing scalable decoders and highlight future directions of research. The book will serve as a key source of learning for graduate research students, post-doctoral researchers and industry engineers who will be interested to work in the field of Quantum Error Correction and Quantum Processor hardware development.