18,335 research outputs found
Triaxial projected shell model approach
The projected shell model analysis is carried out using the triaxial
Nilsson+BCS basis. It is demonstrated that, for an accurate description of the
moments of inertia in the transitional region, it is necessary to take the
triaxiality into account and perform the three-dimensional angular-momentum
projection from the triaxial Nilsson+BCS intrinsic wavefunction.Comment: 9 pages, 2 figure
Varied Signature Splitting Phenomena in Odd Proton Nuclei
Varied signature splitting phenomena in odd proton rare earth nuclei are
investigated. Signature splitting as functions of and in the angular
momentum projection theory is explicitly shown and compared with those of the
particle rotor model. The observed deviations from these rules are due to the
band mixings. The recently measured Ta high spin data are taken as a
typical example where fruitful information about signature effects can be
extracted. Six bands, two of which have not yet been observed, were calculated
and discussed in detail in this paper. The experimentally unknown band head
energies are given
Anomalous Crossing Frequency in Odd Proton Nuclei
A generic explanation for the recently observed anomalous crossing
frequencies in odd proton rare earth nuclei is given. As an example, the proton
band in Ta is discussed in detail by using the
angular momentum projection theory. It is shown that the quadrupole pairing
interaction is decisive in delaying the crossing point and the changes in
crossing frequency along the isotope chain are due to the different neutron
shell fillings
Time synchronization via the transit satellite at Mizusawa
Time signals emitted from Transit satellites and received by the NAVICODE type receiver at Mizusawa, Japan are presented. The International Latitude Observatory of Mizusawa and the U. S. Naval Observatory were compared using the time signals. Propagation delays, a receiver delay, effects of relative motion of satellites, and effects of the ionosphere are discussed
Ensemble learning of linear perceptron; Online learning theory
Within the framework of on-line learning, we study the generalization error
of an ensemble learning machine learning from a linear teacher perceptron. The
generalization error achieved by an ensemble of linear perceptrons having
homogeneous or inhomogeneous initial weight vectors is precisely calculated at
the thermodynamic limit of a large number of input elements and shows rich
behavior. Our main findings are as follows. For learning with homogeneous
initial weight vectors, the generalization error using an infinite number of
linear student perceptrons is equal to only half that of a single linear
perceptron, and converges with that of the infinite case with O(1/K) for a
finite number of K linear perceptrons. For learning with inhomogeneous initial
weight vectors, it is advantageous to use an approach of weighted averaging
over the output of the linear perceptrons, and we show the conditions under
which the optimal weights are constant during the learning process. The optimal
weights depend on only correlation of the initial weight vectors.Comment: 14 pages, 3 figures, submitted to Physical Review
On the Backbending Mechanism of Cr
The mechanism of backbending in Cr is investigated in terms of the
Projected Shell Model and the Generator Coordinate Method. It is shown that
both methods are reasonable shell model truncation schemes. These two quite
different quantum mechanical approaches lead to a similar conclusion that the
backbending is due to a band crossing involving an excited band which is built
on simultaneously broken neutron and proton pairs in the ``intruder'' subshell
. It is pointed out that this type of band crossing is usually known
to cause the second backbending in rare-earth nuclei.Comment: 4 pages, 4 figures, accepted for publication in Phys. Rev. Let
Optimization of the Asymptotic Property of Mutual Learning Involving an Integration Mechanism of Ensemble Learning
We propose an optimization method of mutual learning which converges into the
identical state of optimum ensemble learning within the framework of on-line
learning, and have analyzed its asymptotic property through the statistical
mechanics method.The proposed model consists of two learning steps: two
students independently learn from a teacher, and then the students learn from
each other through the mutual learning. In mutual learning, students learn from
each other and the generalization error is improved even if the teacher has not
taken part in the mutual learning. However, in the case of different initial
overlaps(direction cosine) between teacher and students, a student with a
larger initial overlap tends to have a larger generalization error than that of
before the mutual learning. To overcome this problem, our proposed optimization
method of mutual learning optimizes the step sizes of two students to minimize
the asymptotic property of the generalization error. Consequently, the
optimized mutual learning converges to a generalization error identical to that
of the optimal ensemble learning. In addition, we show the relationship between
the optimum step size of the mutual learning and the integration mechanism of
the ensemble learning.Comment: 13 pages, 3 figures, submitted to Journal of Physical Society of
Japa
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