立富 陳 | National Taiwan University (original) (raw)
立富 陳
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There are fundamental limits on how accurately one can determine the state of a quantum system du... more There are fundamental limits on how accurately one can determine the state of a quantum system due to the existence of non-orthogonal quantum states. The indistinguishability of quantum states poses a series of challenges in quantum communication and quantum information processing. In this report, we give an overview of various strategies for quantum state discrimination and discuss their connections.
Parameter estimation plays a crucial role in statistics, communication systems, machine learning,... more Parameter estimation plays a crucial role in statistics, communication systems, machine learning, and other domains. There are many techniques for parameter estimation. A common framework used is maximum likelihood estimation. However, while maximum likelihood estimators enjoy good properties in statistics, such as consistency and asymptotic efficiency, they often have no closed-form expression due to the necessity of solving nonlinear optimization problems. In this term project, we applied the methods for nonlinear programming to solve the maximum likelihood estimate for fitting the score distribution of the students taking EE 2007.
short essay regarding Nano-electronics
There are fundamental limits on how accurately one can determine the state of a quantum system du... more There are fundamental limits on how accurately one can determine the state of a quantum system due to the existence of non-orthogonal quantum states. The indistinguishability of quantum states poses a series of challenges in quantum communication and quantum information processing. In this report, we give an overview of various strategies for quantum state discrimination and discuss their connections.
Parameter estimation plays a crucial role in statistics, communication systems, machine learning,... more Parameter estimation plays a crucial role in statistics, communication systems, machine learning, and other domains. There are many techniques for parameter estimation. A common framework used is maximum likelihood estimation. However, while maximum likelihood estimators enjoy good properties in statistics, such as consistency and asymptotic efficiency, they often have no closed-form expression due to the necessity of solving nonlinear optimization problems. In this term project, we applied the methods for nonlinear programming to solve the maximum likelihood estimate for fitting the score distribution of the students taking EE 2007.
short essay regarding Nano-electronics