Domain walls in supersymmetric QCD

We consider domain walls that appear in supersymmetric SU(N) with one massive flavour. In particular, for N > 3 we explicitly construct the elementary domain wall that interpolates between two contiguous vacua. We show that these solutions are BPS saturated for any value of the mass of the matter fields. We also comment on their large N limit and their relevance for supersymmetric gluodynamics.Comment: 4 pages, 1 figure, uses latex with hep99 class files. Presented at the International Europhysics Conference in High Energy Physics, Tampere (Finland) 15-21 July 199

Generations of orthogonal surface coordinates

Two generation methods were developed for three dimensional flows where the computational domain normal to the surface is small. With this restriction the coordinate system requires orthogonality only at the body surface. The first method uses the orthogonal condition in finite-difference form to determine the surface coordinates with the metric coefficients and curvature of the coordinate lines calculated numerically. The second method obtains analytical expressions for the metric coefficients and for the curvature of the coordinate lines

Modified Renormalization Strategy for Sandpile Models

Following the Renormalization Group scheme recently developed by Pietronero {\it et al}, we introduce a simplifying strategy for the renormalization of the relaxation dynamics of sandpile models. In our scheme, five sub-cells at a generic scale $b$ form the renormalized cell at the next larger scale. Now the fixed point has a unique nonzero dynamical component that allows for a great simplification in the computation of the critical exponent $z$. The values obtained are in good agreement with both numerical and theoretical results previously reported.Comment: APS style, 9 pages and 3 figures. To be published in Phys. Rev.

Finite size scaling of the bayesian perceptron

We study numerically the properties of the bayesian perceptron through a gradient descent on the optimal cost function. The theoretical distribution of stabilities is deduced. It predicts that the optimal generalizer lies close to the boundary of the space of (error-free) solutions. The numerical simulations are in good agreement with the theoretical distribution. The extrapolation of the generalization error to infinite input space size agrees with the theoretical results. Finite size corrections are negative and exhibit two different scaling regimes, depending on the training set size. The variance of the generalization error vanishes for $N \rightarrow \infty$ confirming the property of self-averaging.Comment: RevTeX, 7 pages, 7 figures, submitted to Phys. Rev.