Cordic core based quantum readout processing block design on FPGA
This dissertation studies the design of a quantum readout processing module based on the CORDIC core. This module is implemented on the FPGA platform and is mainly used for reading qubit states in quantum computing. As an emerging technology, quantum computing processes qubit information mainly util...
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Format: | Thesis-Master by Coursework |
Language: | English |
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Nanyang Technological University
2024
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Online Access: | https://hdl.handle.net/10356/179462 |
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Institution: | Nanyang Technological University |
Language: | English |
Summary: | This dissertation studies the design of a quantum readout processing module based on the CORDIC core. This module is implemented on the FPGA platform and is mainly used for reading qubit states in quantum computing. As an emerging technology, quantum computing processes qubit information mainly utilizing two quantum principles, namely superposition and entanglement, showing unique computing advantages compared to traditional computing models. However, the practical application of quantum computing still faces challenges such as the stability of qubits, the complexity of error correction, and system scalability. The accurate readout of qubits is a key link to achieve efficient quantum computing, so it is particularly important to design an efficient quantum readout processing module.
This project proposes the design of a new quantum readout processing module that uses the CORDIC algorithm to calculate the required sine and cosine values, and a phase accumulator-based direct digital frequency synthesizer (DDFS) to generate the local oscillation signal, thereby achieving precise readout of qubits. Through detailed system design and analysis of simulation results, this dissertation demonstrates the high efficiency and superiority of the proposed block. Simulation results present that this design can achieve high-precision judgment on the state of qubits while maintaining low hardware resource consumption.
In addition, this study also explores the application of three different machine learning algorithms (linear regression algorithm, nearest neighbor algorithm, and decision tree algorithm) in the judgment of quantum state, and evaluates the performance and efficiency of these algorithms in hardware implementation. By comparison, this dissertation provides insights into how to choose the most appropriate algorithm to optimize a quantum readout processing module.
In summary, this dissertation not only proposes a new quantum readout processing module design, but also validating the design's effectiveness through experimental testing., providing valuable technical support and theoretical foundation for the development of quantum computing hardware. The simulation results of this project will help promote the transformation of quantum computing from theory to practicality, and possess significant theoretical importance and application value. |
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