We consider a coherent-classical estimation scheme for a class of linear quantum systems. It comprises an estimator that is a mixed quantum-classical system without involving coherent feedback. The estimator yields a classical estimate of a variable for the quantum plant. We demonstrate that for a passive plant that can be characterized by annihilation operators only, such coherent-classical estimation provides no improvement over purely-classical estimation. An example is also given which shows that if the plant is not assumed to be an annihilation operator only quantum system, it is possible to get better estimates with such coherent-classical estimation compared with purely-classical estimation.We consider a coherent-classical estimation scheme for a class of linear quantum systems. It comprises an estimator that is a mixed quantum-classical system without involving coherent feedback. The estimator yields a classical estimate of a variable for the quantum plant. We demonstrate that for a passive plant that can be characterized by annihilation operators only, such coherent-classical estimation provides no improvement over purely-classical estimation. An example is also given which shows that if the plant is not assumed to be an annihilation operator only quantum system, it is possible to get better estimates with such coherent-classical estimation compared with purely-classical estimation.

arXiv:1403.5348IEEE Conference on Decision and Control (CDC)Dec 1, 20146 citations

Quantum Estimation Theory

Yu Watanabe

Springer thesesDec 17, 20138 citations

Quantum estimation bound of the Gaussian matrix permanent

Joonsuk Huh

Exact calculation and even multiplicative error estimation of matrix permanent are challenging for both classical and quantum computers. Regarding the permanents of random Gaussian matrices, the additive error estimation is closely linked to boson sampling and achieving multiplicative error estimation requires exponentially many samplings. Our formula for matrix permanents and its corresponding quantum expression have enabled better estimation of the average additive error for random Gaussian matrices compared to Gurvits' classical sampling algorithm. The well-known Ryser formula has been converted into a quantum permanent estimator. When dealing with real random Gaussian square matrices of size $N$ , the quantum estimator can approximate the matrix permanent with an additive error smaller than $\ensuremath{\epsilon}{(\sqrt{\mathrm{e}N})}^{N}$, where $\ensuremath{\epsilon}$ is the estimation precision. In contrast, Gurvits' classical sampling algorithm has an estimation error of $\ensuremath{\epsilon}{(2\sqrt{N})}^{N}$, which is exponentially larger ( $1.{2}^{N}$ ) than the quantum method. As expected, the quantum additive error bound fails to reach the multiplicative error bound of ${(2\ensuremath{\pi}N)}^{1/4}\ensuremath{\epsilon}{(\sqrt{N/\mathrm{e}})}^{N}$. Additionally, the quantum permanent estimator can be up to quadratically faster than the classical estimator when using quantum phase estimation-based amplitude estimation.Exact calculation and even multiplicative error estimation of matrix permanent are challenging for both classical and quantum computers. Regarding the permanents of random Gaussian matrices, the additive error estimation is closely linked to boson sampling and achieving multiplicative error estimation requires exponentially many samplings. Our formula for matrix permanents and its corresponding quantum expression have enabled better estimation of the average additive error for random Gaussian matrices compared to Gurvits' classical sampling algorithm. The well-known Ryser formula has been converted into a quantum permanent estimator. When dealing with real random Gaussian square matrices of size $N$, the quantum estimator can approximate the matrix permanent with an additive error smaller than $\ensuremath{\epsilon}{(\sqrt{\mathrm{e}N})}^{N}$, where $\ensuremath{\epsilon}$ is the estimation precision. In contrast, Gurvits' classical sampling algorithm has an estimation error of $\ensuremath{\epsilon}{(2\sqrt{N})}^{N}$, which is exponentially larger ($1.{2}^{N}$) than the quantum method. As expected, the quantum additive error bound fails to reach the multiplicative error bound of ${(2\ensuremath{\pi}N)}^{1/4}\ensuremath{\epsilon}{(\sqrt{N/\mathrm{e}})}^{N}$. Additionally, the quantum permanent estimator can be up to quadratically faster than the classical estimator when using quantum phase estimation-based amplitude estimation.

arXiv:2205.01328Physical Review AJan 13, 20256 citations

Quantum estimation theory

Sanjoy K. Mitter, Stephen K. Young

Springer eBooksOct 5, 20059 citations

Parameter Estimation of Quantum Channels

Zhengfeng Ji, Guoming Wang, Runyao Duan +2 more

The efficiency of parameter estimation of quantum channels is studied in this paper. We introduce the concept of programmable parameters to the theory of estimation. It is found that programmable parameters obey the standard quantum limit strictly; hence, no speedup is possible in its estimation. We also construct a class of nonunitary quantum channels whose parameter can be estimated in a way that the standard quantum limit is broken. The study of estimation of general quantum channels also enables an investigation of the effect of noises on quantum estimation.The efficiency of parameter estimation of quantum channels is studied in this paper. We introduce the concept of programmable parameters to the theory of estimation. It is found that programmable parameters obey the standard quantum limit strictly; hence, no speedup is possible in its estimation. We also construct a class of nonunitary quantum channels whose parameter can be estimated in a way that the standard quantum limit is broken. The study of estimation of general quantum channels also enables an investigation of the effect of noises on quantum estimation.

arXiv:quant-ph/0610060IEEE Transactions on Information TheoryOct 22, 2008120 citations

Universal quantum estimation

Giacomo Mauro D’Ariano

Physics Letters AApr 1, 200036 citations

N

, the quantum estimator can approximate the matrix permanent with an additive error smaller than $\ensuremath{\epsilon}{(\sqrt{\mathrm{e}N})}^{N}$, where $\ensuremath{\epsilon}$ is the estimation precision. In contrast, Gurvits' classical sampling algorithm has an estimation error of $\ensuremath{\epsilon}{(2\sqrt{N})}^{N}$, which is exponentially larger (

1.{2}^{N}

) than the quantum method. As expected, the quantum additive error bound fails to reach the multiplicative error bound of ${(2\ensuremath{\pi}N)}^{1/4}\ensuremath{\epsilon}{(\sqrt{N/\mathrm{e}})}^{N}$. Additionally, the quantum permanent estimator can be up to quadratically faster than the classical estimator when using quantum phase estimation-based amplitude estimation.