1,761 research outputs found
Superconductivity in a magnetically ordered background
Borocarbide compounds with the formula RNi2B2C show interesting
superconducting and magnetic properties and the coexistence of the two
phenomena. BCS theory is extended to systems with underlying commensurate
magnetic order. In the case of helical phases the technique may be extended to
any Q-vector and there exists a well defined limit for incommensurate values.
The way magnetic order influences superconductivity depends crucially on the
details of both the magnetic structure and the electron bands, but some
qualitative criteria may be given. As an example we give a brief analysis of
the compound HoNi2B2C.Comment: 3 pages, 1 figure, proceedings to the conference "Anomalous Complex
Superconductors", Crete 199
Gravitational clustering in N-body simulations
In this talk we discuss some of the main theoretical problems in the
understanding of the statistical properties of gravity. By means of N-body
simulations we approach the problem of understanding the r\^ole of gravity in
the clustering of a finite set of N-interacting particles which samples a
portion of an infinite system. Through the use of the conditional average
density, we study the evolution of the clustering for the system putting in
evidence some interesting and not yet understood features of the process.Comment: 5 pages, 1 figur
Clustering in N-Body gravitating systems
Self-gravitating systems have acquired growing interest in statistical
mechanics, due to the peculiarities of the 1/r potential. Indeed, the usual
approach of statistical mechanics cannot be applied to a system of many point
particles interacting with the Newtonian potential, because of (i) the long
range nature of the 1/r potential and of (ii) the divergence at the origin. We
study numerically the evolutionary behavior of self-gravitating systems with
periodical boundary conditions, starting from simple initial conditions. We do
not consider in the simulations additional effects as the (cosmological) metric
expansion and/or sophisticated initial conditions, since we are interested
whether and how gravity by itself can produce clustered structures. We are able
to identify well defined correlation properties during the evolution of the
system, which seem to show a well defined thermodynamic limit, as opposed to
the properties of the ``equilibrium state''.
Gravity-induced clustering also shows interesting self-similar
characteristics.Comment: 6 pages, 5 figures. To be published on Physica
Theoretical model for the superconducting and magnetically ordered borocarbides
We present a theory of superconductivity in presence of a general magnetic
structure in a form suitable for the description of complex magnetic phases
encountered in borocarbides. The theory, complemented with some details of the
band structure and with the magnetic phase diagram, may explain the nearly
reentrant behaviour and the anisotropy of the upper critical field of HoNi2B2C.
The onset of the helical magnetic order depresses superconductivity via the
reduction of the interaction between phonons and electrons caused by the
formation of magnetic Bloch states. At mean field level, no additional
suppression of superconductivity is introduced by the incommensurability of the
helical phase.Comment: 8 pages, 2 figures. Published version, one important reference adde
Estimation of Signal to Noise Ratio for Unsupervised Hyperspectral Images
Hyperspectral sensors have become a standard technology used in the techniques of observation by
satellite and aerial platform for observing the terrestrial ecosystem with particular interest in the
detection and identification of minerals, vegetation, materials and artificial environments. The detection
of real materials depends on the coverage spectral resolution and signal to noise ratio of the spectrometer itself,
as well as the density of the material and the absorption characteristics for the material in the region of
wavelength measured. The signal to noise ratio in particular is one of the parameters that need to be estimated
to establish the quality of images acquired by these systems.
In this contribution a method to estimate the Signal to Noise Ratio (SNR) for unsupervised hyperspectral images
has been investigated.
The method uses the computation of local means and local standard deviations of small homogeneous blocks
in order to define respectively the average signal and the mean noise of the images. If the noise may be
considered mainly addictive the local standard deviation may be considered as the mean noise of image. This
method uses all the spatial information contained in the image scene giving a representative SNR of entire image.
The technique has been engineered in IDL environment and applied to hyperspectral data of HYPER-SIMGA
sensor, developed in the frame of AIRFIRE Project for wildfire detection by airborne remote sensing data.
The SNR results point out that HYPER-SIMGA SWIR images are quite noisy and the spectral range that has to
be taken into account for data analysis is from 1000 to 1700 nm
Study on the presence and perception of coypu (Myocastor coypus Molina, 1782) in three areas of Lazio region (Italy)
Adriani, S., Bonanni, M., Amici, A
Is the Italian strategy to face the problem of stray dogs sustainable? A case study of two small municipalities in central Italy
Adriani, S., Bonanni, M., Amici, A
- …