What One Can Learn From the Cloud Condensation Nuclei (CCN) Size Distributions as Monitored by the BEO Moussala?

In this proceeding we report initial studies into the big data set acquired by the Cloud Condensation Nuclei (CCN) counter of the Basic Environmental Observatory (BEO) Moussala over the whole 2016 year at a frequency of 1 Hz. First, we attempt to reveal correlations between the results for CCN number concentrations on the timescale of a whole year (2016) as averaged over 12 month periods with the meteorological parameters for the same period and with the same time step. Then, we zoom into these data and repeat the study on the timescale of a month for two months from 2016, January and July, with a day time step. For the same two months we show the CCN size distributions averaged over day periods. Finally, we arrive at our main result: typical, in terms of maximal and minimal number concentrations, CCN size distributions for chosen hours, one hour for each month of the year, hence 24 distributions in total. These data show a steady pattern of peaks and valleys independent of the concrete number concentration which moves up and down the number concentrations (y-axis) without significant shifts along the sizes (x-axis).Comment: 6 pages, 4 figure, The 10th Jubilee Conference of the Balkan Physical Union (BPU10), 26-30 August, Sofia, Bulgari

A design and a code invariant under the simple group Co3

Mathematics;mathematics

On affine designs and Hadamard designs with line spreads

Rahilly [10] described a construction that relates any Hadamard design H on 4 m −1 points with a line spread to an affine design having the same parameters as the classical design of points and hyperplanes in AG(m, 4). Here it is proved that the affine design is the classical design of points and hyperplanes in AG(m, 4) if, and only if, H is the classical design of points and hyperplanes in P G(2m−1, 2) and the line spread is of a special type. Computational results about line spreads in P G(5, 2) are given. One of the affine designs obtained has the same 2-rank as the design of points and planes in AG(3, 4), and provides a counter-example to a conjecture o

Investigation of Pygmy Dipole Resonances in the Tin Region

The evolution of the low-energy electromagnetic dipole response with the neutron excess is investigated along the Sn isotopic chain within an approach incorporating Hartree-Fock-Bogoljubov (HFB) and multi-phonon Quasiparticle-Phonon-Model (QPM) theory. General aspects of the relationship of nuclear skins and dipole sum rules are discussed. Neutron and proton transition densities serve to identify the Pygmy Dipole Resonance (PDR) as a generic mode of excitation. The PDR is distinct from the GDR by its own characteristic pattern given by a mixture of isoscalar and isovector components. Results for the $^{100}$Sn-$^{132}$Sn isotopes and the several N=82 isotones are presented. In the heavy Sn-isotopes the PDR excitations are closely related to the thickness of the neutron skin. Approaching $^{100}$Sn a gradual change from a neutron to a proton skin is found and the character of the PDR is changed correspondingly. A delicate balance between Coulomb and strong interaction effects is found. The fragmentation of the PDR strength in $^{124}$Sn is investigated by multi-phonon calculations. Recent measurements of the dipole response in $^{130,132}$Sn are well reproduced.Comment: 41 pages, 10 figures, PR

Modelling crystallization: When the normal growth velocity depends on the supersaturation

The crystallization proceeds by the advance of the crystal faces into the disordered phase at the expense of the supersaturation which is not sustained in our model. Using a conservation constraint for the transformation ratio and a kinetic law, we derive a general equation for the rate of transformation. It is integrated for the six combinations of the three spatial dimensions D = 1, 2, 3 and the two canonical values of the growth order (1 and 2). The same equation with growth order 1 is obtained when taking only the linear term from the Taylor's expansion around 0 transformation of the model of Johnson-Mehl-Avrami-Kolmogorov(JMAK). We verify our model by fitting it with JMAK. We start the validation of our model in 2D with published results.Comment: 30 pages, 13 figures, 53 reference