Extraction of the atmospheric neutrino fluxes from experimental event rate data

The precise knowledge of the atmospheric neutrino fluxes is a key ingredient in the interpretation of the results from any atmospheric neutrino experiment. In the standard atmospheric neutrino data analysis, these fluxes are theoretical inputs obtained from sophisticated numerical calculations. In this contribution we present an alternative approach to the determination of the atmospheric neutrino fluxes based on the direct extraction from the experimental data on neutrino event rates. The extraction is achieved by means of a combination of artificial neural networks as interpolants and Monte Carlo methods.Comment: 6 pages, 2 figs, to appear in the proceedings of the 2nd International Conference on Quantum Theories and Renormalization Group in Gravity and Cosmology, Barcelona, July 200

Neural network approach to parton distributions fitting

We will show an application of neural networks to extract information on the structure of hadrons. A Monte Carlo over experimental data is performed to correctly reproduce data errors and correlations. A neural network is then trained on each Monte Carlo replica via a genetic algorithm. Results on the proton and deuteron structure functions, and on the nonsinglet parton distribution will be shown.Comment: 4 pages, 5 eps figures. Talk given by Andrea Piccione at the "X International Workshop on Advanced Computing and Analysis Techniques in Physics Research", ACAT 2005, DESY-Zeuthen, Germany, 22-27 May 2005. Corrected fig.

Giant planets around two intermediate-mass evolved stars and confirmation of the planetary nature of HIP67851 c

Precision radial velocities are required to discover and characterize planets orbiting nearby stars. Optical and near infrared spectra that exhibit many hundreds of absorption lines can allow the m/s precision levels required for such work. However, this means that studies have generally focused on solar-type dwarf stars. After the main-sequence, intermediate-mass stars (former A-F stars) expand and rotate slower than their progenitors, thus thousands of narrow absorption lines appear in the optical region, permitting the search for planetary Doppler signals in the data for these types of stars. We present the discovery of two giant planets around the intermediate-mass evolved star HIP65891 and HIP107773. The best Keplerian fit to the HIP65891 and HIP107773 radial velocities leads to the following orbital parameters: P=1084.5 d; m$_b$sin$i$ = 6.0 M$_{jup}$; $e$=0.13 and P=144.3 d; m$_b$sin$i$ = 2.0 M$_{jup}$; $e$=0.09, respectively. In addition, we confirm the planetary nature of the outer object orbiting the giant star HIP67851. The orbital parameters of HIP67851c are: P=2131.8 d, m$_c$sin$i$ = 6.0 M$_{jup}$ and $e$=0.17. With masses of 2.5 M$_\odot$ and 2.4 M$_\odot$ HIP65891 and HIP107773 are two of the most massive stars known to host planets. Additionally, HIP67851 is one of five giant stars that are known to host a planetary system having a close-in planet ($a <$ 0.7 AU). Based on the evolutionary states of those five stars, we conclude that close-in planets do exist in multiple systems around subgiants and slightly evolved giants stars, but probably they are subsequently destroyed by the stellar envelope during the ascent of the red giant branch phase. As a consequence, planetary systems with close-in objects are not found around horizontal branch stars.Comment: Accepted for publication in A&

Neural network determination of parton distributions: the nonsinglet case

We provide a determination of the isotriplet quark distribution from available deep--inelastic data using neural networks. We give a general introduction to the neural network approach to parton distributions, which provides a solution to the problem of constructing a faithful and unbiased probability distribution of parton densities based on available experimental information. We discuss in detail the techniques which are necessary in order to construct a Monte Carlo representation of the data, to construct and evolve neural parton distributions, and to train them in such a way that the correct statistical features of the data are reproduced. We present the results of the application of this method to the determination of the nonsinglet quark distribution up to next--to--next--to--leading order, and compare them with those obtained using other approaches.Comment: 46 pages, 18 figures, LaTeX with JHEP3 clas

Intuïcions dels alumnes de secundària sobre la probabilitat. Una recerca sobre la influència del treball empíric en el cas d'un esdeveniment compost

En aquest article es presenta una investigació relacionada amb dos conceptes probabilístics, l'espai mostral i la probabilitat d'un esdeveniment compost, realitzada amb alumnes de 2n d'ESO. En el camp de la probabilitat és sabut que un ensenyament efectiu s'ha de fomentar en el coneixement previ per part dels professors de les intuïcions que presenten els alumnes. En aquest sentit, un dels objectius d'aquest treball és determinar i classificar les intuïcions dels alumnes en relació amb els dos conceptes esmentats. Aquesta tasca s'ha realitzat seguint els paràmetres següents: el conjunt d'estratègies desenvolupades, la comprensió de les situacions presentades i la naturalesa de les argumentacions en relació amb els diferents significats que pot prendre la probabilitat. Per a l'obtenció de les dades s'ha utilitzat una de les proves d'avaluació de les competències bàsiques aplicades pel Departament d'Educació en els anys 2006-2007. Paral·lelament, s'ha analitzat la influència del treball empíric en la formació i la modificació de les intuïcions dels alumnes. En aquest sentit, els resultats de la investigació assenyalen un camí a seguir per ajudar els estudiants a crear intuïcions correctes, i a la vegada mostren que certes intuïcions que poden interferir en aquest camí sovint són evitables amb l'ajut de l'experimentació.This paper presents an investigation with two probabilistic concepts, the sample space and the probability of a compound event, made with 13-14 years students. In the field of probability it is known that effective teaching should be preceded by research into the primary intuitive substrate of the relevant subject. In this sense, one of the objectives of this study is to determinate and classify the students intuitions about the two concepts mentioned above. This task was carried out according to the following parameters: the set of strategies developed, the understanding of the situations presented and the nature of the students arguments in relation to the different meanings of the concept of probability. To obtain the data, we used one of the basic skills test implemented by the Education Department in 2006-2007. Simultaneously, we analyzed the influence of empirical work in the formation and modification of the students intuitions. In this sense, the results of the investigation indicate a way forward to help students create correct intuitions showing, at the same time, that the existence of certain intuitions that can interfere in their way are often avoidable with the help of experimentation

Spin Coulomb drag in the two-dimensional electron liquid

We calculate the spin-drag transresistivity $\rho_{\uparrow \downarrow}(T)$ in a two-dimensional electron gas at temperature $T$ in the random phase approximation. In the low-temperature regime we show that, at variance with the three-dimensional low-temperature result [$\rho_{\uparrow\downarrow}(T) \sim T^2$], the spin transresistivity of a two-dimensional {\it spin unpolarized} electron gas has the form $\rho_{\uparrow\downarrow}(T) \sim T^2 \ln T$. In the spin-polarized case the familiar form $\rho_{\uparrow\downarrow}(T) =A T^2$ is recovered, but the constant of proportionality $A$ diverges logarithmically as the spin-polarization tends to zero. In the high-temperature regime we obtain $\rho_{\uparrow \downarrow}(T) = -(\hbar / e^2) (\pi^2 Ry^* /k_B T)$ (where $Ry^*$ is the effective Rydberg energy) {\it independent} of the density. Again, this differs from the three-dimensional result, which has a logarithmic dependence on the density. Two important differences between the spin-drag transresistivity and the ordinary Coulomb drag transresistivity are pointed out: (i) The $\ln T$ singularity at low temperature is smaller, in the Coulomb drag case, by a factor $e^{-4 k_Fd}$ where $k_F$ is the Fermi wave vector and $d$ is the separation between the layers. (ii) The collective mode contribution to the spin-drag transresistivity is negligible at all temperatures. Moreover the spin drag effect is, for comparable parameters, larger than the ordinary Coulomb drag effect.Comment: 6 figures; various changes; version accepted for publicatio