Basics and applications of measurement-based quantum computing

Measurement-based quantum computing is a new model of quantum computing proposed by Raussendorf and Briegel in 2001. The standard model of quantum computing, namely, the circuit model, starts with the product state, and quantum gates are applied in order to create entanglement among qubits. The output state is measured only at the end of the computing to read out the computation result. On the other hand, in the measurement-based model, universal quantum computing can be done with the preparation of a multipartite quantum state and adaptive measurements on each qubit of it. It is shown that the computational power of the measurement-based quantum computing is equivalent to the circuit model. However, the measurement-based model has provided new points of view to deepen our understanding of quantum computing and to explore further relations between quantum computing and other fields of physics and information science. In fact, plenty of new results have been obtained about relations between the measurement-based quantum computing and, for example, graph theory, statistical physics, quantum communication, quantum cryptography, etc. It's inherent multipartiteness is also expected to be more suitable for multipartite information processing than the traditional circuit model. In this talk, we first review the basics of the measurement-based quantum computing, and next explain some recent applications of it to information theory, including acausal network, topological quantum computing, and secure cloud quantum computing.