School of Science Department of Physics 72 Quantum Computing Based on NV Center in Diamond Supervisor: YANG Sen / PHYS Student: WU Guanchu / PHYS Course: UROP 1000, Summer Quantum computing exploits the laws of quantum physics to perform specific computational tasks. NV center in diamond has been proven suitable to be used as quantum bits(qubits), and the NV electron spin can be used as the storage of quantum information and a small quantum processor. The report focuses on basic quantum computing principles and the use of NV electron spin for quantum information processing (QIP) by summarizing several dissertations. The report analyzes the Hamiltonian of the NV electron spin and the Rabi oscillation of the states. Eventually, the initialization and readout procedures using optically detected magnetic resonance (ODMR) will be introduced, and several quantum gates are deduced. Quantum Sensing with NV Center in Diamond for Many Body Physics Supervisor: YANG Sen / PHYS Student: BAI Yanze / PHYS-IRE Course: UROP 1100, Fall UROP 2100, Spring UROP 3100, Summer For solid-state color center systems represented by NV centers and silicon carbide, which follow a threelevel structure, quantum sensing stands as a crucial application. Among the various operations involved in quantum sensing, the readout of spin states holds particular significance. Conventional spin-state detection relies on the difference in fluorescence emission probability upon excitation under different spin states. Obviously, this variance in fluorescence efficiency limits the measurement contrast. In this report, we will discuss the use of optically based spin-to-charge conversion techniques to transform spin-state readout into charge-state detection, and examine the fidelity of this approach along with its impact on diverse readout outcomes for color centers. Quantum Sensing with NV Center in Diamond for Many Body Physics Supervisor: YANG Sen / PHYS Student: CHEUNG Chun Fung / PHYS Course: UROP 2100, Fall Nitrogen-vacancy defect centre in diamond has emerged as an increasingly important subject of research, due to its many current and potential applications in quantum computing and material sensing. In particular, its spin-dependent fluorescent properties are applicable in atomic force microscopy (AFM), where we can utilize the interactions between EM field and the fluorescence of NV centres in detecting electric or magnetic properties of various materials, and hence for example, magnetisation domains in a material. In order to reconstruct the magnetisation from measured magnetic fields on a sample, we employ a prebuilt neural network which we will test on for its accuracy and utility.
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