7,901 research outputs found
The disappearance of a narrow Mg II absorption system in quasar SDSS J165501.31+260517.4
In this letter, we present for the first time, the discovery of the
disappearance of a narrow Mg II absorption system
from the spectra of quasar SDSS J165501.31+260517.4 (). This
absorber is located at , and has a velocity offset of
with respect to the quasar. According to the velocity
offset and the line variability, this narrow Mg II
absorption system is likely intrinsic to the quasar. Since the corresponding UV
continuum emission and the absorption lines of another narrow Mg II
absorption system at are very
stable, we think that the disappearance of the absorption system is unlikely to
be caused by the change in ionization of absorption gas. Instead, it likely
arises from the motion of the absorption gas across the line of sight
Gauge invariant hydrogen atom Hamiltonian
For quantum mechanics of a charged particle in a classical external
electromagnetic field, there is an apparent puzzle that the matrix element of
the canonical momentum and Hamiltonian operators is gauge dependent. A
resolution to this puzzle is recently provided by us in [2]. Based on the
separation of the electromagnetic potential into pure gauge and gauge invariant
parts, we have proposed a new set of momentum and Hamiltonian operators which
satisfy both the requirement of gauge invariance and the relevant commutation
relations. In this paper we report a check for the case of the hydrogen atom
problem: Starting from the Hamiltonian of the coupled electron, proton and
electromagnetic field, under the infinite proton mass approximation, we derive
the gauge invariant hydrogen atom Hamiltonian and verify explicitly that this
Hamiltonian is different from the Dirac Hamiltonian, which is the time
translation generator of the system. The gauge invariant Hamiltonian is the
energy operator, whose eigenvalue is the energy of the hydrogen atom. It is
generally time-dependent. In this case, one can solve the energy eigenvalue
equation at any specific instant of time. It is shown that the energy
eigenvalues are gauge independent, and by suitably choosing the phase factor of
the time-dependent eigenfunction, one can ensure that the time-dependent
eigenfunction satisfies the Dirac equation.Comment: 7 pages, revtex4, some further discussion on Dirac Hamiltonian and
the gauge invariant Hamiltonian is added, one reference removed; new address
of some of the authors added, final version to appear in Phys. Rev.
Superconducting proximity effect to the block antiferromagnetism in KFeSe
Recent discovery of superconducting (SC) ternary iron selenides has block
antiferromagentic (AFM) long range order. Many experiments show possible
mesoscopic phase separation of the superconductivity and antiferromagnetism,
while the neutron experiment reveals a sizable suppression of magnetic moment
due to the superconductivity indicating a possible phase coexistence. Here we
propose that the observed suppression of the magnetic moment may be explained
due to the proximity effect within a phase separation scenario. We use a
two-orbital model to study the proximity effect on a layer of block AFM state
induced by neighboring SC layers via an interlayer tunneling mechanism. We
argue that the proximity effect in ternary Fe-selenides should be large because
of the large interlayer coupling and weak electron correlation. The result of
our mean field theory is compared with the neutron experiments
semi-quantitatively. The suppression of the magnetic moment due to the SC
proximity effect is found to be more pronounced in the d-wave superconductivity
and may be enhanced by the frustrated structure of the block AFM state.Comment: 6 pages, 6 figure
CNN Profiler on Polar Coordinate Images for Tropical Cyclone Structure Analysis
Convolutional neural networks (CNN) have achieved great success in analyzing
tropical cyclones (TC) with satellite images in several tasks, such as TC
intensity estimation. In contrast, TC structure, which is conventionally
described by a few parameters estimated subjectively by meteorology
specialists, is still hard to be profiled objectively and routinely. This study
applies CNN on satellite images to create the entire TC structure profiles,
covering all the structural parameters. By utilizing the meteorological domain
knowledge to construct TC wind profiles based on historical structure
parameters, we provide valuable labels for training in our newly released
benchmark dataset. With such a dataset, we hope to attract more attention to
this crucial issue among data scientists. Meanwhile, a baseline is established
with a specialized convolutional model operating on polar-coordinates. We
discovered that it is more feasible and physically reasonable to extract
structural information on polar-coordinates, instead of Cartesian coordinates,
according to a TC's rotational and spiral natures. Experimental results on the
released benchmark dataset verified the robustness of the proposed model and
demonstrated the potential for applying deep learning techniques for this
barely developed yet important topic.Comment: Submitted to AAAI202
Diaquabis(tetrazolo[1,5-a]pyridine-8-carboxylato-κ2 N 1,O)cobalt(II) dihydrate
In the title compound, [Co(C6H3N4O2)2(H2O)2]·2H2O, the CoII atom is located on an inversion center in a slightly distorted octahedral environment formed by the O atoms of two water molecules, and the N and O atoms of the chelating tetrazolo[1,5-a]pyridine-8-carboxylate anions. Hydrogen bonds of the O—H⋯O and O—H⋯N types result in a three-dimensional supramolecular network
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