Lecture notes on quantum computing
Anton Frisk Kockum, Ariadna Soro, Laura Garc\'ia-\'Alvarez, Pontus, Vikst{\aa}l, Tom Douce, G\"oran Johansson, Giulia Ferrini

TL;DR
This comprehensive set of lecture notes provides a detailed theoretical overview of quantum computing, covering algorithms, error correction, different models, and intersections with machine learning, aimed at graduate students.
Contribution
It compiles and explains a broad range of quantum computing topics into an educational resource without focusing on hardware implementations.
Findings
Covers key quantum algorithms like Grover's and Shor's.
Includes discussions on quantum error correction and various models.
Explores quantum computing's intersection with machine learning.
Abstract
These are the lecture notes of the master's course "Quantum Computing", taught at Chalmers University of Technology every fall since 2020, with participation of students from RWTH Aachen and Delft University of Technology. The aim of this course is to provide a theoretical overview of quantum computing, excluding specific hardware implementations. Topics covered in these notes include quantum algorithms (such as Grover's algorithm, the quantum Fourier transform, phase estimation, and Shor's algorithm), variational quantum algorithms that utilise an interplay between classical and quantum computers [such as the variational quantum eigensolver (VQE) and the quantum approximate optimisation algorithm (QAOA), among others], quantum error correction, various versions of quantum computing (such as measurement-based quantum computation, adiabatic quantum computation, and the…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Quantum Information and Cryptography
