Erwin Brüning

Francesco Petruccione

Based on eight extensive lectures selected from those given at the renowned Chris Engelbrecht Summer School in Theoretical Physics in South Africa, this text on the theoretical foundations of quantum information processing and communication covers an array of topics, including quantum probabilities, open systems, and non-Markovian dynamics and decoherence. It also addresses quantum information and relativity as well as testing quantum mechanics in high energy physics. Because these self-contained lectures discuss topics not typically covered in advanced undergraduate courses, they are ideal for post-graduate students entering this field of research. Some of the lectures are written at a more introductory level while others are presented as tutorials that survey recent developments and results in various subfields.

Selected Topics

Theoretical Foundations of Quantum Information Processing and Communication

Maria Schuld

Quantum machine learning investigates how quantum computers can be used for data-driven prediction and decision making. The books summarises and conceptualises ideas of this relatively young discipline for an audience of computer scientists and physicists from a graduate level upwards. It aims at providing a starting point for those new to the field, showcasing a toy example of a quantum machine learning algorithm and providing a detailed introduction of the two parent disciplines. For more advanced readers, the book discusses topics such as data encoding into quantum states, quantum algorithms and routines for inference and optimisation, as well as the construction and analysis of genuine ``quantum learning models''. A special focus lies on supervised learning, and applications for near-term quantum devices.

Francesco Petruccione

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