Design and Analysis of Quantum Algorithms for Quantum Computing and Communications

Zhang, Yao (2021) Design and Analysis of Quantum Algorithms for Quantum Computing and Communications. PhD thesis, UNSPECIFIED.

Text (2021yaophd)
2021yaophd.pdf - Published Version
Restricted to Repository staff only until 18 June 2026.

Download (5MB)


The quantum communication, from a conceptual point of view, is a technology that uses the information transmission of quantum media to communicate. It mainly includes technologies such as quantum key distribution (QKD) and quantum teleportation. This thesis proposes a potential application of QKD in multi-user networks. In this thesis, it focuses on Carrier-sense Multiple Access (CSMA) protocol, and analyses the use of carrier-sense multiple access with collision avoidance (CSMA/CA) for QKD in the network. In addition, a multiple access QKD with channel detection protocol is also proposed. Quantum computing utilises the superposition and entanglement information of quantum states to operate and process, and its most significant advantage lies in the ”parallelism of operations”, that is, the quantum information of the superposition states is transformed once, which is equivalent to the simultaneous operation of the quantum information. Firstly, in this thesis, we propose a new quantum algorithm of calculating temporal difference to detect the moving objects in any videos. Our quantum algorithm has the complexity of calculating temporal difference in dynamic video object detection to be only O(1). Secondly, we propose a new method to encode classical input data into quantum states to represent a quantum neuron, which has a low-complexity form and can be easily utilised to construct a quantum neural network (QNN). QNN is a network which is to be composed of several quantum neurons. Thirdly, in this thesis, we re-formulate a quantum-classical hybrid model for QNN that proved to be effective, which is known as parameterised quantum circuit model, and explain it from the perspective of software design.

Item Type:
Thesis (PhD)
ID Code:
Deposited By:
Deposited On:
17 Jun 2021 17:10
Last Modified:
30 Nov 2021 09:29