Viscosity in spherically symmetric accretion     

Arnab K. Ray 《Monthly notices of the Royal Astronomical Society》2003,344(4):1085-1090

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Point source detection using the Spherical Mexican Hat Wavelet on simulated all-sky Planck maps     

P. Vielva  E. Martínez-González  J. E. Gallegos  L. Toffolatti  J. L. Sanz 《Monthly notices of the Royal Astronomical Society》2003,344(1):89-104

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Light-curve classification in massive variability surveys – I. Microlensing     

Vasily Belokurov  N. Wyn Evans  Yann Le Du 《Monthly notices of the Royal Astronomical Society》2003,341(4):1373-1384

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The effect of radiative feedback on Bondi–Hoyle flow around a massive star     

Richard Edgar  Cathie Clarke 《Monthly notices of the Royal Astronomical Society》2004,349(2):678-686

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The environmental dependence of clustering in hierarchical models     

Ummi Abbas  Ravi K. Sheth 《Monthly notices of the Royal Astronomical Society》2005,364(4):1327-1336

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Numerical simulations of weak lensing measurements     

David J. Bacon  Alexandre Refregier  Douglas Clowe  Richard S. Ellis 《Monthly notices of the Royal Astronomical Society》2001,325(3):1065-1074

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'Hyper-parameters' approach to joint estimation: applications to Cepheid-calibrated distances and X-ray clusters     

Pirin Erdogdu  Stefano Ettori  Ofer Lahav 《Monthly notices of the Royal Astronomical Society》2003,340(2):573-579

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Star cluster ecology – V. Dissection of an open star cluster: spectroscopy     

Simon F. Portegies Zwart †  Piet Hut  Stephen L. W. McMillan  Junichiro Makino 《Monthly notices of the Royal Astronomical Society》2004,351(2):473-486

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Automated Separation of Stars and Normal Galaxies Based on Statistical Mixture Modeling with RBF Neural Networks     

Dong-Mei Qin  Ping Guo  Zhan-Yi Hu  Yong-Heng ZhaoNational Laboratory of Pattern Recognition Laboratory  Institute of Automation  Chinese Academy of Sciences  Beijing  dmqin@nlpr.ia.ac.cnDepartment of Computer Sciences  Beijing Normal University  Beijing National Astronomical Observatories  Chinese Academy of Sciences  Beijing 《中国天文和天体物理学报》2003,3(3)

For LAMOST, the largest sky survey program in China, the solution of the problem of automatic discrimination of stars from galaxies by spectra has shown that the results of the PSF test can be significantly refined. However, the problem is made worse when the redshifts of galaxies are not available. We present a new automatic method of star/(normal) galaxy separation, which is based on Statistical Mixture Modeling with Radial Basis Function Neural Networks (SMM-RBFNN). This work is a continuation of our previous one, where active and non-active celestial objects were successfully segregated. By combining the method in this paper and the previous one, stars can now be effectively separated from galaxies and AGNs by their spectra-a major goal of LAMOST, and an indispensable step in any automatic spectrum classification system. In our work, the training set includes standard stellar spectra from Jacoby's spectrum library and simulated galaxy spectra of EO, SO, Sa, Sb types with redshift ranging from 0 to 1  相似文献   

A simple model for the evolution of disc galaxies: the Milky Way     

Thorsten Naab  Jeremiah P. Ostriker 《Monthly notices of the Royal Astronomical Society》2006,366(3):899-917

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