We use the random forest to regress surface effective temperatures of stars in APOGEE from SDSS DR16 and LAMOST DR6. When NUV-u, u-g, g-r, r-i, i-J, J-H, H-K, K-WISE_4_5 magnitudes are used as machine learning features, coefficient determination regression 94.91% 90.46% LAMOST. The standard deviation prediction pipeline 93.89K 113.10K NUV-J, 94.37% 88.89% is 96.59K 119.92K J-H most important fe...

We report the discovery of 4 new strong lensing systems by visual inspection of the Sloan Digital Sky Survey images of galaxy clusters in Data Release 6 (SDSS DR6). Two of them show Einstein rings, and the others show tangential giant arcs. These arcs or rings have large angle separations of > 8 from the bright central galaxies and show blue color compared to the red cluster galaxies. In additi...

We discovered strong gravitational lensing in 4 galaxy clusters by visual inspection of the Sloan Digital Sky Survey images in Data Release 6 (SDSS DR6). Two of them show the Einstein rings, and the other two show tangential giant arcs. These arcs or rings have large angle separations of > 8 from the bright central galaxies. The lensed images in general are bluer than cluster member galaxies. T...

Noisy distance estimates associated with photometric rather than spectroscopic redshifts lead to a mis-estimate of the luminosities, and produce a correlated mis-estimate of the sizes. We consider a sample of early-type galaxies from the SDSS DR6 and apply the generalization of the Vmax method to correct for these biases. We show that our technique recovers the true redshift, magnitude and size...

There are many factors that lead to the huge difference in stellar spectra, most important of which atmospheric physical parameters, namely, effective temperature, surface gravity and chemical abundance. This study is based on classified star data LAMOST DR6 with a temperature value 7500-9000K signal-to-noise ratio S/N greater than 50. The results two methods compared through regression verific...