Rapid non-adiabatic loading in an optical lattice

We present a scheme for non-adiabatically loading a Bose-Einstein condensate into the ground state of a one dimensional optical lattice within a few tens of microseconds typically, i.e. in less than half the Talbot period. This technique of coherent control is based on sequences of pulsed perturbations and experimental results demonstrate its feasibility and effectiveness. As the loading process is much shorter than the traditional adiabatic loading timescale, this method may find many applications.Comment: 5 pages, 4 figure

Mode competition in superradiant scattering of matter waves

Superradiant Rayleigh scattering in a Bose gas released from an optical lattice is analyzed with incident light pumping at the Bragg angle for resonant light diffraction. We show competition between superradiance scattering into the Bragg mode and into end-fire modes clearly leads to suppression of the latter at even relatively low lattice depths. A quantum light-matter interaction model is proposed for qualitatively explaining this result.Comment: 6 pages, 6 figures, accepted by PR

Roughness with a finite correlation length in the Microtrap

We analyze the effects of roughness in the magnitude of the magnetic field produced by a current carrying microwire, which is caused by geometric fluctuation of the edge of wire. The relation between the fluctuation of the trapping potential and the height that atom trap lies above the wire is consistent with the experimental data very well, when the colored noise with a finite correlation length is considered. On this basis, we generate the random potential and get the density distribution of the BEC atoms by solving the Gross-Pitaevskii equation, which coincides well with the experimental image, especially in the number of fragmentations. The results help us further understand the nature of the fluctuation and predict the possible application in the precise measurement.Comment: 6 pages, 7 figure

Comparison Study of Feedforward Fully-connected Neural Networks Vs. Cascade Correlation Networks for Prediction of Soil Moisture Content

Computer Science

Some Results on the Symmetric Representation of the Generalized Drazin Inverse in a Banach Algebra

[EN] Based on the conditions ab(2) = 0 and b pi(ab) is an element of A(d), we derive that (ab)(n), (ba)(n), and ab + ba are all generalized Drazin invertible in a Banach algebra A, where n is an element of N and a and b are elements of A. By using these results, some results on the symmetry representations for the generalized Drazin inverse of ab + ba are given. We also consider that additive properties for the generalized Drazin inverse of the sum a + b.This work was supported by the National Natural Science Foundation of China (grant number: 11361009, 61772006,11561015), the Special Fund for Science and Technological Bases and Talents of Guangxi (grant number: 2016AD05050, 2018AD19051), the Special Fund for Bagui Scholars of Guangxi (grant number: 2016A17), the High level innovation teams and distinguished scholars in Guangxi Universities (grant number: GUIJIAOREN201642HAO), the Natural Science Foundation of Guangxi (grant number: 2017GXNSFBA198053, 2018JJD110003), and the open fund of Guangxi Key laboratory of hybrid computation and IC design analysis (grant number: HCIC201607).Qin, Y.; Liu, X.; Benítez López, J. (2019). Some Results on the Symmetric Representation of the Generalized Drazin Inverse in a Banach Algebra. Symmetry (Basel). 11(1):1-9. https://doi.org/10.3390/sym11010105S19111González, N. C. (2005). Additive perturbation results for the Drazin inverse. Linear Algebra and its Applications, 397, 279-297. doi:10.1016/j.laa.2004.11.001Zhang, X., & Chen, G. (2006). The computation of Drazin inverse and its application in Markov chains. Applied Mathematics and Computation, 183(1), 292-300. doi:10.1016/j.amc.2006.05.076Castro-González, N., Dopazo, E., & Martínez-Serrano, M. F. (2009). On the Drazin inverse of the sum of two operators and its application to operator matrices. Journal of Mathematical Analysis and Applications, 350(1), 207-215. doi:10.1016/j.jmaa.2008.09.035Qiao, S., Wang, X.-Z., & Wei, Y. (2018). Two finite-time convergent Zhang neural network models for time-varying complex matrix Drazin inverse. Linear Algebra and its Applications, 542, 101-117. doi:10.1016/j.laa.2017.03.014Stanimirovic, P. S., Zivkovic, I. S., & Wei, Y. (2015). Recurrent Neural Network for Computing the Drazin Inverse. IEEE Transactions on Neural Networks and Learning Systems, 26(11), 2830-2843. doi:10.1109/tnnls.2015.2397551Koliha, J. J. (1996). A generalized Drazin inverse. Glasgow Mathematical Journal, 38(3), 367-381. doi:10.1017/s0017089500031803Hartwig, R. E., Wang, G., & Wei, Y. (2001). Some additive results on Drazin inverse. Linear Algebra and its Applications, 322(1-3), 207-217. doi:10.1016/s0024-3795(00)00257-3Djordjević, D. S., & Wei, Y. (2002). Additive results for the generalized Drazin inverse. Journal of the Australian Mathematical Society, 73(1), 115-126. doi:10.1017/s1446788700008508Liu, X., Xu, L., & Yu, Y. (2010). The representations of the Drazin inverse of differences of two matrices. Applied Mathematics and Computation, 216(12), 3652-3661. doi:10.1016/j.amc.2010.05.016Yang, H., & Liu, X. (2011). The Drazin inverse of the sum of two matrices and its applications. Journal of Computational and Applied Mathematics, 235(5), 1412-1417. doi:10.1016/j.cam.2010.08.027Harte, R. (1992). On generalized inverses in C*-algebras. Studia Mathematica, 103(1), 71-77. doi:10.4064/sm-103-1-71-77Djordjevic, D. S., & Stanimirovic, P. S. (2001). On the Generalized Drazin Inverse and Generalized Resolvent. Czechoslovak Mathematical Journal, 51(3), 617-634. doi:10.1023/a:1013792207970Cvetković-Ilić, D. S., Djordjević, D. S., & Wei, Y. (2006). Additive results for the generalized Drazin inverse in a Banach algebra. Linear Algebra and its Applications, 418(1), 53-61. doi:10.1016/j.laa.2006.01.015Liu, X., Qin, X., & Benítez, J. (2016). New additive results for the generalized Drazin inverse in a Banach algebra. Filomat, 30(8), 2289-2294. doi:10.2298/fil1608289lMosić, D., Zou, H., & Chen, J. (2017). The generalized Drazin inverse of the sum in a Banach algebra. Annals of Functional Analysis, 8(1), 90-105. doi:10.1215/20088752-3764461González, N. C., & Koliha, J. J. (2004). New additive results for the g-Drazin inverse. Proceedings of the Royal Society of Edinburgh: Section A Mathematics, 134(6), 1085-1097. doi:10.1017/s0308210500003632Mosić, D. (2014). A note on Cline’s formula for the generalized Drazin inverse. Linear and Multilinear Algebra, 63(6), 1106-1110. doi:10.1080/03081087.2014.92296

Production of Bioactive Isothiocyanates by Bacterial Myrosinase

Isothiocyanates (ITCs) are bioactive products found in several plants belonging to the Brassicaceae family, and are produced as defense upon disruption of the tissue by herbivores or pathogens, but in humans they have shown anti-cancer and anti-inflammatory properties. Although we know gut microbes can hydrolyze GSL into ITC, the mechanism is not known. With improved detection methods, the aim of this experiment is to explore whether the gut microbial myrosinase β-glucosidase found within the genome of E. coli Nissle 1917 can hydrolyze glucosinolates (GSLs) into detectable ITCs

The generalized inverses of tensors via the C-Product

This paper studies the issues about the generalized inverses of tensors under the C-Product. The aim of this paper is threefold. Firstly, this paper present the definition of the Moore-Penrose inverse, Drazin inverse of tensors under the C-Product. Moreover, the inverse along a tensor is also introduced. Secondly, this paper gives some other expressions of the generalized inverses of tensors by using several decomposition forms of tensors. Finally, the algorithms for the Moore-Penrose inverse, Drazin inverse of tensors and the inverse along a tensor are established