4,564 research outputs found
The NLO contributions to the scalar pion form factors and the annihilation corrections to the decays
In this paper, by employing the factorization theorem, we made the
first calculation for the space-like scalar pion form factor at
the leading order (LO) and the next-to-leading order (NLO) level, and then
found the time-like scalar pion form factor by analytic
continuation from the space-like one. From the analytical evaluations and the
numerical results, we found the following points: (a) the NLO correction to the
space-like scalar pion form factor has an opposite sign with the LO one but is
very small in magnitude, can produce at most decrease to LO result in
the considered region; (b) the NLO time-like scalar pion form factor
describes the contribution to the
factorizable annihilation diagrams of the considered decays,
i.e. the NLO annihilation correction; (c) the NLO part of the form factor
is very small in size, and is almost independent with the
variation of cutoff scale , but this form factor has a large strong
phase around and may play an important role in producing large CP
violation for decays; and (d) for and decays, the newly known NLO annihilation correction can produce
only a very small enhancement to their branching ratios, less than in
magnitude, and therefore we could not interpret the well-known -puzzle
by the inclusion of this NLO correction to the factorizable annihilation
diagrams.Comment: 26 pages, 12 figures, 1 Table; Minor correction
Algebraic higher symmetry and categorical symmetry -- a holographic and entanglement view of symmetry
We introduce the notion of algebraic higher symmetry, which generalizes
higher symmetry and is beyond higher group. We show that an algebraic higher
symmetry in a bosonic system in -dimensional space is characterized and
classified by a local fusion -category. We find another way to describe
algebraic higher symmetry by restricting to symmetric sub Hilbert space where
symmetry transformations all become trivial. In this case, algebraic higher
symmetry can be fully characterized by a non-invertible gravitational anomaly
(i.e. an topological order in one higher dimension). Thus we also refer to
non-invertible gravitational anomaly as categorical symmetry to stress its
connection to symmetry. This provides a holographic and entanglement view of
symmetries. For a system with a categorical symmetry, its gapped state must
spontaneously break part (not all) of the symmetry, and the state with the full
symmetry must be gapless. Using such a holographic point of view, we obtain (1)
the gauging of the algebraic higher symmetry; (2) the classification of
anomalies for an algebraic higher symmetry; (3) the equivalence between classes
of systems, with different (potentially anomalous) algebraic higher symmetries
or different sets of low energy excitations, as long as they have the same
categorical symmetry; (4) the classification of gapped liquid phases for
bosonic/fermionic systems with a categorical symmetry, as gapped boundaries of
a topological order in one higher dimension (that corresponds to the
categorical symmetry). This classification includes symmetry protected trivial
(SPT) orders and symmetry enriched topological (SET) orders with an algebraic
higher symmetry.Comment: 61 pages, 31 figure
Harmonic Suppressed Dual Resonance Decoupling Network With Near Zero Insertion Loss for Patch Antenna Arrays
Learning to Purification for Unsupervised Person Re-identification
Unsupervised person re-identification is a challenging and promising task in
computer vision. Nowadays unsupervised person re-identification methods have
achieved great progress by training with pseudo labels. However, how to purify
feature and label noise is less explicitly studied in the unsupervised manner.
To purify the feature, we take into account two types of additional features
from different local views to enrich the feature representation. The proposed
multi-view features are carefully integrated into our cluster contrast learning
to leverage more discriminative cues that the global feature easily ignored and
biased. To purify the label noise, we propose to take advantage of the
knowledge of teacher model in an offline scheme. Specifically, we first train a
teacher model from noisy pseudo labels, and then use the teacher model to guide
the learning of our student model. In our setting, the student model could
converge fast with the supervision of the teacher model thus reduce the
interference of noisy labels as the teacher model greatly suffered. After
carefully handling the noise and bias in the feature learning, our purification
modules are proven to be very effective for unsupervised person
re-identification. Extensive experiments on three popular person
re-identification datasets demonstrate the superiority of our method.
Especially, our approach achieves a state-of-the-art accuracy 85.8\% @mAP and
94.5\% @Rank-1 on the challenging Market-1501 benchmark with ResNet-50 under
the fully unsupervised setting. The code will be released
Optical Fiber Harsh Environment Sensors
Various optical fiber harsh environment sensors were reported, including the miniaturized inline Fabry-Perot interferometer sensor by femtosecond laser micromachining, the long period fiber grating sensor and the inline core-cladding mode interferometer by CO2 laser irradiations
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