Single-hole properties in the tt-JJ and strong-coupling models

We report numerical results for the single-hole properties in the $t$-$J$ model and the strong-coupling approximation to the Hubbard model in two dimensions. Using the hopping basis with over $10^6$ states we discuss (for an infinite system) the bandwidth, the leading Fourier coefficients in the dispersion, the band masses, and the spin-spin correlations near the hole. We compare our results with those obtained by other methods. The band minimum is found to be at ($\pi/2,\pi/2$) for the $t$-$J$ model for $0.1 \leq t/J \leq 10$, and for the strong-coupling model for $1 \leq t/J \leq 10$. The bandwidth in both models is approximately $2J$ at large $t/J$, in rough agreement with loop-expansion results but in disagreement with other results. The strong-coupling bandwidth for t/J\agt6 can be obtained from the $t$-$J$ model by treating the three-site terms in first-order perturbation theory. The dispersion along the magnetic zone face is flat, giving a large parallel/perpendicular band mass ratio.Comment: 1 RevTeX file with epsf directives to include 8 .eps figures 8 figure files encoded using uufile

Unlearning in feed-forward multi-nets

Multi-nets promise an improved performance over monolithic neural networks by virtue of their distributed implementation. Modular neural networks are multi-nets based on an judicious assembly of functionally different parts. This can be viewed as again a monolithic network, but with more complex neurons (the neural modules). Therefore they will share the same learning problems, notably the unlearning effect. In this paper we will look more closely into the reasons for unlearning and discuss how this can be applied to detect novelties.</p