22,800 research outputs found
Realizing the supersymmetric inverse seesaw model in the framework of R-parity violation
If, on one hand, the inverse seesaw is the paradigm of TeV scale seesaw
mechanism, on the other it is a challenge to find scenarios capable of
realizing it. In this work we propose a scenario, based on the framework of
R-parity violation, that realizes minimally the supersymmetric inverse seesaw
mechanism. In it the energy scale parameters involved in the mechanism are
recognized as the vacuum expectation values of the scalars that compose the
singlet superfields and . We develop also the scalar sector
of the model and show that the Higgs mass receives a new tree-level
contribution that, when combined with the standard contribution plus loop
correction, is capable of attaining GeV without resort to heavy stops.Comment: Minor modification of the text. Final version to be published in PL
Classical integrability of chiral and classical curves
In this letter, classical chiral is studied in the lightcone gauge
. The once integrated equation of motion for the current is shown to
be of the Lax form, which demonstrates an infinite number of conserved
quantities. Specializing to gauge group SU(2), we show that solutions to the
classical equations of motion can be identified with a very large class of
curves. We demonstrate this correspondence explicitly for two solutions. The
classical fermionic fields associated with these currents are then obtained.Comment: Final version to appear in Mod. Phys. Lett. A. A reference and two
footnotes added. 6 pages revte
Regression analysis with missing data and unknown colored noise: application to the MICROSCOPE space mission
The analysis of physical measurements often copes with highly correlated
noises and interruptions caused by outliers, saturation events or transmission
losses. We assess the impact of missing data on the performance of linear
regression analysis involving the fit of modeled or measured time series. We
show that data gaps can significantly alter the precision of the regression
parameter estimation in the presence of colored noise, due to the frequency
leakage of the noise power. We present a regression method which cancels this
effect and estimates the parameters of interest with a precision comparable to
the complete data case, even if the noise power spectral density (PSD) is not
known a priori. The method is based on an autoregressive (AR) fit of the noise,
which allows us to build an approximate generalized least squares estimator
approaching the minimal variance bound. The method, which can be applied to any
similar data processing, is tested on simulated measurements of the MICROSCOPE
space mission, whose goal is to test the Weak Equivalence Principle (WEP) with
a precision of . In this particular context the signal of interest is
the WEP violation signal expected to be found around a well defined frequency.
We test our method with different gap patterns and noise of known PSD and find
that the results agree with the mission requirements, decreasing the
uncertainty by a factor 60 with respect to ordinary least squares methods. We
show that it also provides a test of significance to assess the uncertainty of
the measurement.Comment: 12 pages, 4 figures, to be published in Phys. Rev.
Bounds on the Simplest Little Higgs Model Mass Spectrum Through Z Leptonic Decay
We derive the leptonic neutral current in the simplest little Higgs model and
compute the contribution of the model to the decay width . Using
the precision electroweak data we obtain a strong lower bound TeV
at 95% C.L. on the characteristic energy scale of the model. It results in a
lower bound for the new gauge bosons and as being
TeV and TeV, respectively.
We also present the allowed values of the which is the parameter
relating the two vacuum expectation values of the scalar triplets in the model,
and the parameter of a quadratic term, involving the triplets, necessary
to provide an acceptable mass range for the standard Higgs boson.Comment: New references added, 13 pages. Version to be publishe
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