Optimal method are applied in characterizing and reconstructing designed unitary matrices on linear optical circuit. The scheme is based on the measurement of single-photon and two-photon statistics using coherent beams.NRF (Natl Research Foundation, S’pore)Accepted versio
Quantum state discrimination is a well-known problem in quantum information theory, that has already...
Significant challenges remain with the development of macroscopic quantum computing, hardware proble...
Matrix quantum mechanics plays various important roles in theoreticalphysics, such as a holographic ...
We study quantum learning algorithms for quantum measurements. The optimal learning algorithm is der...
Finding optimal measurement schemes in quantum state tomography is a fundamental problem in quantum ...
This doctoral dissertation is a comprehensive study on a novel method based on unitary synaptic weig...
Quantum Machine learning is a promising technology that is related to the study of computing. Due to...
In the current noisy intermediate-scale quantum (NISQ) era, quantum machine learning is emerging as ...
This thesis illustrates the use of machine learning algorithms and exact numerical methods to study ...
Quantum computing represents a promising paradigm for solving complex problems, such as large-number...
Recent progress implies that a crossover between machine learning and quantum information processing...
Models that combine quantum mechanics (QM) with machine learning (ML) promise to deliver the accurac...
Machine learning is a promising application of quantum computing, but challenges remain for implemen...
INST: L_200A modern számítástechnika jelentős eredményei közé tartozik a gépi tanulás alapvető a...
We study quantum learning algorithms for quantum measurements. The optimal learning algorithm is der...
Quantum state discrimination is a well-known problem in quantum information theory, that has already...
Significant challenges remain with the development of macroscopic quantum computing, hardware proble...
Matrix quantum mechanics plays various important roles in theoreticalphysics, such as a holographic ...
We study quantum learning algorithms for quantum measurements. The optimal learning algorithm is der...
Finding optimal measurement schemes in quantum state tomography is a fundamental problem in quantum ...
This doctoral dissertation is a comprehensive study on a novel method based on unitary synaptic weig...
Quantum Machine learning is a promising technology that is related to the study of computing. Due to...
In the current noisy intermediate-scale quantum (NISQ) era, quantum machine learning is emerging as ...
This thesis illustrates the use of machine learning algorithms and exact numerical methods to study ...
Quantum computing represents a promising paradigm for solving complex problems, such as large-number...
Recent progress implies that a crossover between machine learning and quantum information processing...
Models that combine quantum mechanics (QM) with machine learning (ML) promise to deliver the accurac...
Machine learning is a promising application of quantum computing, but challenges remain for implemen...
INST: L_200A modern számítástechnika jelentős eredményei közé tartozik a gépi tanulás alapvető a...
We study quantum learning algorithms for quantum measurements. The optimal learning algorithm is der...
Quantum state discrimination is a well-known problem in quantum information theory, that has already...
Significant challenges remain with the development of macroscopic quantum computing, hardware proble...
Matrix quantum mechanics plays various important roles in theoreticalphysics, such as a holographic ...
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