Multi-user quantum key distribution with collective eavesdropping detection over collective-noise channels

A multi-user quantum key distribution protocol is proposed with single particles and the collective eavesdropping detection strategy on a star network. By utilizing this protocol, any two users of the network can accomplish quantum key distribution with the help of a serving center. Due to the utilization of the collective eavesdropping detection strategy, the users of the protocol just need to have the ability of performing certain unitary operations. Furthermore, we present three fault-tolerant versions of the proposed protocol, which can combat with the errors over different collective-noise channels.The security of all the proposed protocols is guaranteed by the theorems on quantum operation discrimination.

Robust and efficient quantum private comparison of equality with collective detection over collective-noise channels

We present a protocol for quantum private comparison of equality(QPCE) with the help of a semi-honest third party(TP).Instead of employing the entanglement,we use single photons to achieve the comparison in this protocol.By utilizing collective eavesdropping detection strategy,our protocol has the advantage of higher qubit efficiency and lower cost of implementation.In addition to this protocol,we further introduce three robust versions which can be immune to collective dephasing noise,collective-rotation noise and all types of unitary collective noise,respectively.Finally,we show that our protocols can be secure against the attacks from both the outside eavesdroppers and the inside participants by using the theorems on quantum operation discrimination.

A type of collective detection scheme with improved pigeon-inspired optimization

Purpose-With increasing demand of localization service in challenging environments where Global Navigation Satellite Systems(GNSS)signalsare considerably weak,a powerful approach,the collective detection(CD),has been developed.However,traditional CD techniques are computationally intense due to the large clock bias search space.Therefore,the purpose of this paper is to develop a new scheme of CD with less computational burden,in order to accelerate the detection and location process.Design/methodology/approach-This paper proposes a new scheme of CD.It reformulates the problem ofGNSS signal detection as an optimization problem,and solves it with the aid of an improved Pigeon-Inspired Optimization(PIO).With the improved PIO algorithm adopted,the positioning algorithm arrives to evaluate only a part of the points in the search space,avoiding the problems of grid-search method which is universally adopted.Findings-Faced with the complex optimization problem,the improved PIO algorithm proves to have good performance.In the acquisition of simulated and real signals,the proposed scheme of CD with the improved PIO algorithm also have better efficiency,precision and stability than traditional CD algorithm.Besides,the improved PIO algorithm also proves to be a better candidate to be integrated into the proposed scheme than particle swarm optimization,differential evolution and PIO.Originality/value-The novelty associated with this paper is the proposition of the new scheme of CD and the improvement of PIO algorithm.Thus,this paper introduces another possibility to ameliorate the traditional CD.

The influence of the characteristics of a collection of particles on the scattered spectral density and its applications

The far-zone scattered spectral density of a light wave on the scattering from a collection of particles is investigated, and the relationship between the character of the collection and the distribution of the scattered spectral density is discussed. It is shown that both the number of particles and their locations in the collection play roles in the distribution of the far-zone scattered spectral density. This phenomenon may provide a potential method to reconstruct the structure character of a collection of particles from measurements of the far-zone scattered spectral density.