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arXiv:2602.13876

Quantum computation and quantum error correction: the theoretical minimum

Mark Wildon

quant-phmath-phSubmitted Feb 14, 2026• Announced Feb 17, 2026• 0 citations
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Abstract

These notes introduce quantum computation and quantum error correction, emphasising the importance of stabilisers and the mathematical foundations in basic Lie theory. We begin by using the double cover map $\mathrm{SU}_2 \rightarrow \mathrm{SO}_3(\mathbb{R})$ to illustrate the distinction between states and measurements for a single qubit. We then discuss entanglement and CNOT gates, the Deutsch--Jozsa Problem, and finally quantum error correction, using the Steane $[[7,1,3]]$-code as the main example. The necessary background physics of unitary evolution and Born rule measurements is developed as needed. The circuit model is used throughout.

Comments
34 pages, 4 figures

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These notes introduce quantum computation and quantum error correction, emphasising the importance of stabilisers and the mathematical foundations in basic Lie theory. We begin by using the double cover map SU2→SO3(R)\mathrm{SU}_2 \rightarrow \mathrm{SO}_3(\mathbb{R})SU2​→SO3​(R) to illustrate the distinction between states and measurements for a single qubit. We then discuss entanglement and CNOT gates, the Deutsch--Jozsa Problem, and finally quantum error correction, using the Steane [[7,1,3]][[7,1,3]][[7,1,3]]-code as the main example. The necessary background physics of unitary evolution and Born rule measurements is developed as needed. The circuit model is used throughout.
This is a set of lecture notes suitable for a Master's course on quantum computation and information from the perspective of theoretical computer science. The first version was written in 2011, with many extensions and improvements in subsequent years. The first 10 chapters cover the circuit model and the main quantum algorithms (Deutsch-Jozsa, Simon, Shor, Hidden Subgroup Problem, Grover, quantum walks, Hamiltonian simulation and HHL). They are followed by 4 chapters about complexity, 4 chapters about distributed ("Alice and Bob") settings, a chapter about quantum machine learning, one about stabilizer states and Clifford circuits, and a final chapter about quantum error correction. Appendices A and B give a brief introduction to the required linear algebra and some other mathematical and computer science background. All chapters come with exercises, with some hints provided in Appendix C.
In Chapter 4 we introduced different quantum gates and quantum circuits and in Chapter 5 we described several quantum algorithms. So far the analysis of the algorithms and the circuits has been made with the assumption that the required unitary operations can be implemented exactly without any error. This is an abstraction. In an actual physical system that implements a quantum algorithm or a quantum circuit there are several sources of errors. The situation is similar in classical computation and to circumvent this problem error correcting codes are used in classical digital computing. Since qubits are more delicate and more susceptible to errors we need to introduce quantum error correcting codes. It is very important, as without such codes it will not be possible to build a scalable quantum computer. Such quantum error correcting codes are introduced in this chapter. However, we will not limit ourselves to the discussion of error correcting codes alone. We will also discuss more general aspects of errors and error correction, like decoherence, decoherence free subspace and fault-tolerance.
This chapter contains an introduction to the main concepts in quantum computation and entanglement. It starts with a brief introduction to computational complexity and then introduces quantum gates and quantum networks, discussing the universality issue in quantum computation. A review on the main known quantum algorithms follows, including Deutsch's, Deutsch-Jozsa's, Grover's and Shor's algorithms. The basic concepts in the theory of quantum error correction are then reviewed. The second part of the chapter is devoted to entanglement. It starts by reminding the basic definitions of entanglement and entanglement criteria for bipartite and multipartite systems, and then discusses the role that entanglement plays in the quantum algorithms described before. The chapter ends with short descriptions of NMR quantum computing, the computational model DQC1, and one-way quantum computing.
Quantum computing uses quantum-mechanical principles to enable new models of computation bexond the classical paradigm. This article presents an accessible introduction to the mathematical and conceptual foundations of quantum computing, covering qubits, quantum gates, multi-qubit systems, entanglement, and measurement. The gate-based computation model and quantum circuits are introduced, together with key notations such as universality and reversibility. As an illustrative example, the Deutsch-Josza algorithm is discussed to demonstrate how quantum algorithm can be constucted. The article concludes with a brief overview of the current state and challenges of quantum computing.
"The goal of this paper is to review the theoretical basis for achieving a faithful quantum information transmission and processing in the presence of noise. Initially, encoding and decoding, implementing gates and quantum error correction will be considered error-free. Finally, we shall relax this non-realistic assumption, introducing the quantum fault-tolerant concept. The existence of an error threshold permits us to conclude that there is no physical law preventing a quantum computer from being built. An error model based on the depolarising channel will be able to provide a simple estimate of the storage or memory computation error threshold: 5.2 10. The encoding is made by means of the [[7,1,3]] Calderbank-Shor-Steane quantum code, and Shor´s fault-tolerant method is used to measure the stabiliser´s generators."
Quantum error correction (QEC) is a critical component of quantum information processing, essential for achieving reliable quantum computation and communication. This paper investigates the mathematical basis of QEC, focusing on the fundamental concepts of entanglement, superposition, and measurement. We delve into the mathematical framework underpinning various QEC codes, including Shor's and Steane's codes, exploring their strengths and weaknesses. The core focus is on developing a novel approach based on quantum state manipulation, aiming to enhance the efficiency and robustness of QEC through the strategic application of these mathematical principles. The paper presents a detailed analysis of the mathematical properties and computational complexity associated with key QEC algorithms, demonstrating the potential for significant advancements in this field.