94,300 research outputs found
Microscopic Description of Band Structure at Very Extended Shapes in the A ~ 110 Mass Region
Recent experiments have confirmed the existence of rotational bands in the A
\~ 110 mass region with very extended shapes lying between super- and
hyper-deformation. Using the projected shell model, we make a first attempt to
describe quantitatively such a band structure in 108Cd. Excellent agreement is
achieved in the dynamic moment of inertia J(2) calculation. This allows us to
suggest the spin values for the energy levels, which are experimentally
unknown. It is found that at this large deformation, the sharply down-sloping
orbitals in the proton i_{13/2} subshell are responsible for the irregularity
in the experimental J(2), and the wave functions of the observed states have a
dominant component of two-quasiparticles from these orbitals. Measurement of
transition quadrupole moments and g-factors will test these findings, and thus
can provide a deeper understanding of the band structure at very extended
shapes.Comment: 4 pages, 3 eps figures, final version accepted by Phys. Rev. C as a
Rapid Communicatio
Entanglement changing power of two-qubit unitary operations
We consider a two-qubit unitary operation along with arbitrary local unitary
operations acts on a two-qubit pure state, whose entanglement is C_0. We give
the conditions that the final state can be maximally entangled and be
non-entangled. When the final state can not be maximally entangled, we give the
maximal entanglement C_max it can reach. When the final state can not be
non-entangled, we give the minimal entanglement C_min it can reach. We think
C_max and C_min represent the entanglement changing power of two-qubit unitary
operations. According to this power we define an order of gates.Comment: 11 page
Projection Measurement of the Maximally Entangled N-Photon State for a Demonstration of N-Photon de Broglie Wavelength
We construct a projection measurement process for the maximally entangled
N-photon state (the NOON-state) with only linear optical elements and
photodetectors. This measurement process will give null result for any N-photon
state that is orthogonal to the NOON state. We examine the projection process
in more detail for N=4 by applying it to a four-photon state from type-II
parametric down-conversion. This demonstrates an orthogonal projection
measurement with a null result. This null result corresponds to a dip in a
generalized Hong-Ou-Mandel interferometer for four photons. We find that the
depth of the dip in this arrangement can be used to distinguish a genuine
entangled four-photon state from two separate pairs of photons. We next apply
the NOON state projection measurement to a four-photon superposition state from
two perpendicularly oriented type-I parametric down-conversion processes. A
successful NOON state projection is demonstrated with the appearance of the
four-photon de Broglie wavelength in the interference fringe pattern.Comment: 8 pages, 3 figures, new title, some content change, replaced Fig.
The Child is Father of the Man: Foresee the Success at the Early Stage
Understanding the dynamic mechanisms that drive the high-impact scientific
work (e.g., research papers, patents) is a long-debated research topic and has
many important implications, ranging from personal career development and
recruitment search, to the jurisdiction of research resources. Recent advances
in characterizing and modeling scientific success have made it possible to
forecast the long-term impact of scientific work, where data mining techniques,
supervised learning in particular, play an essential role. Despite much
progress, several key algorithmic challenges in relation to predicting
long-term scientific impact have largely remained open. In this paper, we
propose a joint predictive model to forecast the long-term scientific impact at
the early stage, which simultaneously addresses a number of these open
challenges, including the scholarly feature design, the non-linearity, the
domain-heterogeneity and dynamics. In particular, we formulate it as a
regularized optimization problem and propose effective and scalable algorithms
to solve it. We perform extensive empirical evaluations on large, real
scholarly data sets to validate the effectiveness and the efficiency of our
method.Comment: Correct some typos in our KDD pape
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