Comment on 'Secure Communication using mesoscopic coherent states', Barbosa et al, Phys Rev Lett 90, 227901 (2003)

In a recent letter, Barbosa et al [PRL 90, 227901(2003)] claim that secure communication is possible with bright coherent pulses, by using quantum noise to hide the data from an eavesdropper. We show here that the secrecy in the scheme of Barbosa et al is unrelated to quantum noise, but rather derives from the secret key that sender and receiver share beforehand

Reply to "Comment on `Resilience of gated avalanche photodiodes against bright illumination attacks in quantum cryptography'"

This is a Reply to the Comment by Lydersen et al. [arXiv: 1106.3756v1]

Avoiding the Detector Blinding Attack on Quantum Cryptography

We show the detector blinding attack by Lydersen et al [1] will be ineffective on most single photon avalanche photodiodes (APDs) and certainly ineffective on any detectors that are operated correctly. The attack is only successful if a redundant resistor is included in series with the APD, or if the detector discrimination levels are set inappropriately

Predicting floods in a large karst river basin by coupling PERSIANN-CCS QPEs with a physically based distributed hydrological model

In general, there are no long-term meteorological or hydrological data available for karst river basins. The lack of rainfall data is a great challenge that hinders the development of hydrological models. Quantitative precipitation estimates (QPEs) based on weather satellites offer a potential method by which rainfall data in karst areas could be obtained. Furthermore, coupling QPEs with a distributed hydrological model has the potential to improve the precision of flood predictions in large karst watersheds. Estimating precipitation from remotely sensed information using an artificial neural network-cloud classification system (PERSIANN-CCS) is a type of QPE technology based on satellites that has achieved broad research results worldwide. However, only a few studies on PERSIANN-CCS QPEs have occurred in large karst basins, and the accuracy is generally poor in terms of practical applications. This paper studied the feasibility of coupling a fully physically based distributed hydrological model, i.e., the Liuxihe model, with PERSIANN-CCS QPEs for predicting floods in a large river basin, i.e., the Liujiang karst river basin, which has a watershed area of 58 270 km-2, in southern China. The model structure and function require further refinement to suit the karst basins. For instance, the sub-basins in this paper are divided into many karst hydrology response units (KHRUs) to ensure that the model structure is adequately refined for karst areas. In addition, the convergence of the underground runoff calculation method within the original Liuxihe model is changed to suit the karst water-bearing media, and the Muskingum routing method is used in the model to calculate the underground runoff in this study. Additionally, the epikarst zone, as a distinctive structure of the KHRU, is carefully considered in the model. The result of the QPEs shows that compared with the observed precipitation measured by a rain gauge, the distribution of precipitation predicted by the PERSIANN-CCS QPEs was very similar. However, the quantity of precipitation predicted by the PERSIANN-CCS QPEs was smaller. A post-processing method is proposed to revise the products of the PERSIANN-CCS QPEs. The karst flood simulation results show that coupling the post-processed PERSIANN-CCS QPEs with the Liuxihe model has a better performance relative to the result based on the initial PERSIANN-CCS QPEs. Moreover, the performance of the coupled model largely improves with parameter re-optimization via the post-processed PERSIANN-CCS QPEs. The average values of the six evaluation indices change as follows: the Nash-Sutcliffe coefficient increases by 14 %, the correlation coefficient increases by 15 %, the process relative error decreases by 8 %, the peak flow relative error decreases by 18 %, the water balance coefficient increases by 8 %, and the peak flow time error displays a 5 h decrease. Among these parameters, the peak flow relative error shows the greatest improvement; thus, these parameters are of page1506 the greatest concern for flood prediction. The rational flood simulation results from the coupled model provide a great practical application prospect for flood prediction in large karst river basins

Unconditionally secure one-way quantum key distribution using decoy pulses

We report here a complete experimental realization of one-way decoy-pulse quantum key distribution, demonstrating an unconditionally secure key rate of 5.51 kbps for a 25.3 km fibre length. This is two orders of magnitudes higher than the value that can be obtained with a non-decoy system. We introduce also a simple test for detecting the photon number splitting attack and highlight that it is essential for the security of the technique to fully characterize the source and detectors used.Comment: 10 pages, 5 figure

Quantum key distribution over 122 km of standard telecom fiber

We report the first demonstration of quantum key distribution over a standard telecom fiber exceeding 100 km in length. Through careful optimisation of the interferometer and single photon detector, we achieve a quantum bit error ratio of 8.9% for a 122km link, allowing a secure shared key to be formed after error correction and privacy amplification. Key formation rates of up to 1.9 kbit/sec are achieved depending upon fiber length. We discuss the factors limiting the maximum fiber length in quantum cryptography

The Role of Starburst-AGN composites in Luminous Infrared Galaxy Mergers: Insights from the New Optical Classification Scheme

We investigate the fraction of starbursts, starburst-AGN composites, Seyferts, and LINERs as a function of infrared luminosity (L_IR) and merger progress for ~500 infrared-selected galaxies. Using the new optical classifications afforded by the extremely large data set of the Sloan Digital Sky Survey, we find that the fraction of LINERs in IR-selected samples is rare (< 5%) compared with other spectral types. The lack of strong infrared emission in LINERs is consistent with recent optical studies suggesting that LINERs contain AGN with lower accretion rates than in Seyfert galaxies. Most previously classified infrared-luminous LINERs are classified as starburst-AGN composite galaxies in the new scheme. Starburst-AGN composites appear to "bridge" the spectral evolution from starburst to AGN in ULIRGs. The relative strength of the AGN versus starburst activity shows a significant increase at high infrared luminosity. In ULIRGs (L_IR >10^12 L_odot), starburst-AGN composite galaxies dominate at early--intermediate stages of the merger, and AGN galaxies dominate during the final merger stages. Our results are consistent with models for IR-luminous galaxies where mergers of gas-rich spirals fuel both starburst and AGN, and where the AGN becomes increasingly dominant during the final merger stages of the most luminous infrared objects.Comment: 30 pages, 19 figures, 10 tables, ApJ accepte