Optimized Neural Networks to Search for Higgs Boson Production at the Tevatron

An optimal choice of proper kinematical variables is one of the main steps in using neural networks (NN) in high energy physics. Our method of the variable selection is based on the analysis of a structure of Feynman diagrams (singularities and spin correlations) contributing to the signal and background processes. An application of this method to the Higgs boson search at the Tevatron leads to an improvement in the NN efficiency by a factor of 1.5-2 in comparison to previous NN studies.Comment: 4 pages, 4 figures, partially presented in proceedings of ACAT'02 conferenc

The Advantage of Foraging Myopically

We study the dynamics of a \emph{myopic} forager that randomly wanders on a lattice in which each site contains one unit of food. Upon encountering a food-containing site, the forager eats all the food at this site with probability $p<1$; otherwise, the food is left undisturbed. When the forager eats, it can wander $\mathcal{S}$ additional steps without food before starving to death. When the forager does not eat, either by not detecting food on a full site or by encountering an empty site, the forager goes hungry and comes one time unit closer to starvation. As the forager wanders, a multiply connected spatial region where food has been consumed---a desert---is created. The forager lifetime depends non-monotonically on its degree of myopia $p$, and at the optimal myopia $p=p^*(\mathcal{S})$, the forager lives much longer than a normal forager that always eats when it encounters food. This optimal lifetime grows as $\mathcal{S}^2/\ln\mathcal{S}$ in one dimension and faster than a power law in $\mathcal{S}$ in two and higher dimensions.Comment: 10 pages, 1o figure

Densification and Structural Transitions in Networks that Grow by Node Copying

We introduce a growing network model---the copying model---in which a new node attaches to a randomly selected target node and, in addition, independently to each of the neighbors of the target with copying probability $p$. When $p<\frac{1}{2}$, this algorithm generates sparse networks, in which the average node degree is finite. A power-law degree distribution also arises, with a non-universal exponent whose value is determined by a transcendental equation in $p$. In the sparse regime, the network is "normal", e.g., the relative fluctuations in the number of links are asymptotically negligible. For $p\geq \frac{1}{2}$, the emergent networks are dense (the average degree increases with the number of nodes $N$) and they exhibit intriguing structural behaviors. In particular, the $N$-dependence of the number of $m$-cliques (complete subgraphs of $m$ nodes) undergoes $m-1$ transitions from normal to progressively more anomalous behavior at a $m$-dependent critical values of $p$. Different realizations of the network, which start from the same initial state, exhibit macroscopic fluctuations in the thermodynamic limit---absence of self averaging. When linking to second neighbors of the target node can occur, the number of links asymptotically grows as $N^2$ as $N\to\infty$, so that the network is effectively complete as $N\to \infty$.Comment: 15 pages, 12 figure

Glassy Dielectric Response in Tb_2NiMnO_6 Double Perovskite with Similarities to a Griffiths Phase

Frequency-dependent and temperature-dependent dielectric measurements are performed on double perovskite Tb$_2$NiMnO$_6$. The real ($\epsilon_1$) and imaginary ($\epsilon_2$) parts of dielectric permittivity show three plateaus suggesting dielectric relaxation originating from bulk, grain boundaries and the sample-electrode interfaces respectively. The temperature and frequency variation of $\epsilon_1$ and $\epsilon_2$ are successfully simulated by a $RC$ circuit model. The complex plane of impedance, $Z'$-$Z"$, is simulated using a series network with a resistor $R$ and a constant phase element. Through the analysis of frequency-dependent dielectric constant using modified-Debye model, different relaxation regimes are identified. Temperature dependence of dc conductivity also presents a clear change in slope at, $T^*$. Interestingly, $T^*$ compares with the temperature at which an anomaly occurs in the phonon modes and the Griffiths temperature for this compound. The components $R$ and $C$ corresponding to the bulk and the parameter $\alpha$ from modified-Debye fit tend support to this hypothesis. Though these results cannot be interpreted as magnetoelectric coupling, the relationship between lattice and magnetism is marked.Comment: Accepted in Europhysics Letter

Relevance of cosmic gamma rays to the mass of gas in the galaxy

The bulk of the diffuse gamma-ray flux comes from cosmic ray interactions in the interstellar medium. A knowledge of the large scale spatial distribution of the Galactic gamma-rays and the cosmic rays enables the distribution of the target gas to be examined. An approach of this type is used here to estimate the total mass of the molecular gas in the galaxy. It is shown to be much less than that previously derived, viz., approximately 6 x 10 to the 8th power solar masses within the solar radius as against approximately 3 x 10 to the 9th power based on 2.6 mm CO measurements