We prepare single layer potassium-doped iron selenide (110) film by molecular beam expitaxy. Such a single layer film can be viewed as a two-dimensional system composed of weakly coupled two-leg iron ladders. Scanning tunneling spectroscopy reveals t
hat superconductivity is developed in this two-leg ladder system. The superconducting gap is similar to that of the multi-layer films. However, the Fermi surface topology given by first-principles calculation is remarkably different from that of the bulk materials. Our results suggest that superconducting pairing is very short-ranged or takes place rather locally in iron-chalcogenides. The superconductivity is most likely driven by electron-electron correlation effect and is insensitive to the change of Fermi surfaces.
We demonstrate the trajectory measurement of the single neutral atoms deterministically using a high-finesse optical micro-cavity. Single atom strongly couples to the high-order transverse vacuum TEM_{10} mode, instead of the usual TEM_{00} mode, and
the parameter of the system is (g_{10},kappa ,gamma )=2pi times (20.5,2.6,2.6)MHz. The atoms simply fall down freely from the magneto-optic trap into the cavity modes and the trajectories of the single atoms are linear. The transmission spectrums of atoms passing through the TEM10 mode are detected by a single photon counting modules and well fitted. Thanks to the tilted cavity transverse TEM10 mode, which is inclined to the vertical direction about 45 degrees and it helps us, for the first time, to eliminate the degenerate trajectory of the single atom falling through the cavity and get the unique atom trajectory. Atom position with high precision of 0.1{mu}m in the off-axis direction (axis y) is obtained, and the spatial resolution of 5.6{mu}m is achieved in time of 10{mu}s along the vertical direction (axis x). The average velocity of the atoms is also measured from the atom transits, which determines the temperature of the atoms in magneto-optic trap, 186{mu}K {pm} 19{mu}K.
We exam various geometric active contour methods for radar image segmentation. Due to special properties of radar images, we propose our new model based on modified Chan-Vese functional. Our method is efficient in separating non-meteorological noises from meteorological images.
