Determining Separability with Entanglement of Formation and Entanglement Sudden Death

Chen, Xiao-yu

doi:10.1088/0256-307x/32/1/010301

Cited by 4 publications

(2 citation statements)

References 16 publications

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“…Due to the presence of the atmosphere attenuation and background noises, losing one or more entangled photons is easy to happen. [28,37] This phenomenon can make the fully entangled photons scheme completely useless for the improvement of QKD performance. Since the loss of a single photon from a maximally entangled state would destroy the entanglement property, the gain in time-of-arrival accuracy afforded by the fully entangled photons scheme would become zero.…”

Section: Qkd Performance In Lossy Channelmentioning

confidence: 99%

Performance optimization for quantum key distribution in lossy channel using entangled photons

Yu¹,

Xu²,

Zhang

et al. 2017

Chinese Phys. B

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In quantum key distribution (QKD), the times of arrival of single photons are important for the keys extraction and time synchronization. The time-of-arrival (TOA) accuracy can affect the quantum bit error rate (QBER) and the final key rate. To achieve a higher accuracy and a better QKD performance, different from designing more complicated hardware circuits, we present a scheme that uses the mean TOA of M frequency-entangled photons to replace the TOA of a single photon. Moreover, to address the problem that the entanglement property is usually sensitive to the photon loss in practice, we further propose two schemes, which adopt partially entangled photons and grouping-entangled photons, respectively. In addition, we compare the effects of these three alternative schemes on the QKD performance and discuss the selection strategy for the optimal scheme in detail. The simulation results show that the proposed schemes can improve the QKD performance compared to the conventional single-photon scheme obviously, which demonstrate the effectiveness of the proposed schemes.

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Section: Qkd Performance In Lossy Channelmentioning

confidence: 99%

Performance optimization for quantum key distribution in lossy channel using entangled photons

Yu¹,

Xu²,

Zhang

et al. 2017

Chinese Phys. B

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show abstract

“…[3] Superposition and entanglement of quantum states make quantum algorithms especially suitable for high-dimensional data computation in machine learning. [4] Recently, researchers proposed a series of quantum machine learning algorithms, such as classification, [5][6][7][8][9][10][11] clustering, [12][13][14][15] dimensionality reduction, [16][17][18][19][20][21][22]24] and neural networks. [25][26][27][28][29] These algorithms accelerate the development of quantum machine learning.…”

Section: Introductionmentioning

confidence: 99%

Quantum partial least squares regression algorithm for multiple correlation problem

Hou¹,

Li²,

Chen³

et al. 2022

Chinese Phys. B

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Partial least squares (PLS) regression is an important linear regression method that efficiently addresses the multiple correlation problem by combining principal component analysis and multiple regression. In this paper, we present a quantum partial least squares (QPLS) regression algorithm. To solve the high time complexity of the PLS regression, we design a quantum eigenvector search method to speed up principal components and regression parameters construction. Meanwhile, we give a density matrix product method to avoid multiple access to quantum random access memory (QRAM) during building residual matrices. The time and space complexities of the QPLS regression are logarithmic in the independent variable dimension n, the dependent variable dimension w, and the number of variables m. This algorithm achieves exponential speed-ups over the PLS regression on n, m, and w. In addition, the QPLS regression inspires us to explore more potential quantum machine learning applications in future works.

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The Role of Al Reaction Rate in the Damage Effect and Energy Output of RDX‐Based Aluminized Explosives in Concrete

Zhou

Chen

Yuan

et al. 2019

Propellants Explo Pyrotec

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This paper aims to improve the understanding of how the aluminum reaction rate affects the damage effect and energy output of RDX‐based aluminized explosives in concrete. A calculation method for the dynamic response of concrete and energy output of RDX‐based aluminized explosive is proposed based on the time‐dependent Jones‐Wilkins‐Lee equation of state (JWL‐EOS), cavity expansion model and energy partition theory, which is in turn verified through experiments with 70 g RDX/Al/wax (65 %/30 %/5 %) charge embedded in concrete. Based on the proposed method, the dynamic response of concrete and energy output of RDX/Al/wax with four different aluminum reaction rates were calculated. The results indicate a positive correlation between the crushed region radius and the aluminum reaction rate, and that the cracked region radius is inversely proportional to the aluminum reaction rate. For the energy output of RDX/Al/wax, the shock wave energy grows with increasing aluminum reaction rate, while the detonation products expansion energy increases and then drops with rising aluminum reaction rate, peaking at 2.37 MJ/kg when the Al reaction rate constant M=0.02. The calculation method presented in this paper are of great significance for investigating and improving the performance of RDX‐based aluminized explosives in concrete.

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Determining Separability with Entanglement of Formation and Entanglement Sudden Death

Cited by 4 publications

References 16 publications

Performance optimization for quantum key distribution in lossy channel using entangled photons

Performance optimization for quantum key distribution in lossy channel using entangled photons

Quantum partial least squares regression algorithm for multiple correlation problem

The Role of Al Reaction Rate in the Damage Effect and Energy Output of RDX‐Based Aluminized Explosives in Concrete

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