The quantum enhanced classical sensor network consists of K clusters of Ne entangled quantum states that have been trialled r times, each feeding into a classical estimation process. Previous literature has shown that each cluster can ideally achieve an estimation variance of 1/N2e r for sufficient r. We begin by deriving the optimal values for the minimum mean squared error of this quantum enhanced classical system. We then show that if noise is absent in the classical estimation process, the mean estimation error will decay like Ω (1/KN2e r). However, when noise is present we find that the mean estimation error will decay like Ω (1/K), so that all the sensing gains obtained from the individual quantum clusters will be lost
In the near-term, the number of qubits in quantum computers will be limited to a few hundreds. There...
Quantum machine learning algorithms could provide significant speed-ups over their classical counter...
International audienceFor parameter estimation from an N-component composite quantum system, it is k...
In this dissertation,we mainly focus on distributed quantum sensing which uses different sensing nod...
We introduce a general model for a network of quantum sensors, and we use this model to consider the...
Quantum metrology takes advantage of nonclassical resources such as squeezing and entanglement to ac...
We compare the performance of a quantum radar based on two-mode squeezed states with a classical rad...
Entanglement has shown promise in enhancing information processing tasks in a sensor network, via di...
We show that quantum-to-classical channels, i.e., quantum measurements, can be asymptotically simula...
Entanglement is a unique resource for quantum-enhanced applications. When employed in sensing, share...
Any physical transformation that equally distributes quantum information over a large number M of us...
Quantum sensors have the characteristics of high sensitivity, high accuracy and strong stability and...
Realistic quantum sensors face a trade-off between the number of sensors measured in parallel and th...
A distributed sensing protocol uses a network of local sensing nodes to estimate a global feature of...
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Physics, 2018.Cataloged from PD...
In the near-term, the number of qubits in quantum computers will be limited to a few hundreds. There...
Quantum machine learning algorithms could provide significant speed-ups over their classical counter...
International audienceFor parameter estimation from an N-component composite quantum system, it is k...
In this dissertation,we mainly focus on distributed quantum sensing which uses different sensing nod...
We introduce a general model for a network of quantum sensors, and we use this model to consider the...
Quantum metrology takes advantage of nonclassical resources such as squeezing and entanglement to ac...
We compare the performance of a quantum radar based on two-mode squeezed states with a classical rad...
Entanglement has shown promise in enhancing information processing tasks in a sensor network, via di...
We show that quantum-to-classical channels, i.e., quantum measurements, can be asymptotically simula...
Entanglement is a unique resource for quantum-enhanced applications. When employed in sensing, share...
Any physical transformation that equally distributes quantum information over a large number M of us...
Quantum sensors have the characteristics of high sensitivity, high accuracy and strong stability and...
Realistic quantum sensors face a trade-off between the number of sensors measured in parallel and th...
A distributed sensing protocol uses a network of local sensing nodes to estimate a global feature of...
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Physics, 2018.Cataloged from PD...
In the near-term, the number of qubits in quantum computers will be limited to a few hundreds. There...
Quantum machine learning algorithms could provide significant speed-ups over their classical counter...
International audienceFor parameter estimation from an N-component composite quantum system, it is k...