One Dimensional Kondo Lattice Model Studied by the Density Matrix Renormalization Group Method

Recent developments of the theoretical investigations on the one-dimensional Kondo lattice model by using the density matrix renormalization group (DMRG) method are discussed in this review. Short summaries are given for the zero-temperature DMRG, the finite-temperature DMRG, and also its application to dynamic quantities. Away from half-filling, the paramagnetic metallic state is shown to be a Tomonaga-Luttinger liquid with the large Fermi surface. For the large Fermi surface its size is determined by the sum of the densities of the conduction electrons and the localized spins. The correlation exponent K_rho of this metallic phase is smaller than 1/2. At half-filling the ground state is insulating. Excitation gaps are different depending on channels, the spin gap, the charge gap and the quasiparticle gap. Temperature dependence of the spin and charge susceptibilities and specific heat are discussed. Particularly interesting is the temperature dependence of various excitation spectra, which show unusual properties of the Kondo insulators.Comment: 18 pages, 23 Postscript figures, REVTe

Program transformations using temporal logic side conditions

This paper describes an approach to program optimisation based on transformations, where temporal logic is used to specify side conditions, and strategies are created which expand the repertoire of transformations and provide a suitable level of abstraction. We demonstrate the power of this approach by developing a set of optimisations using our transformation language and showing how the transformations can be converted into a form which makes it easier to apply them, while maintaining trust in the resulting optimising steps. The approach is illustrated through a transformational case study where we apply several optimisations to a small program

Upside-Down Preference Reversal: How to Override Ceteris-Paribus Preferences?

Specific preference statements may reverse general prefer-ence statements, thus constituting a change of attitude in par-ticular situations. We define a semantics of preference rever-sal by relaxing the popular ceteris-paribus principle. We char-acterize preference reversal as default reasoning and we link it to prioritized Pareto-optimization, which permits a natu-ral computation of preferred solutions. The resulting method simplifies elicitation, representation, and utilization of com-plex preference relations and may thus enable a more realistic preference handling in personalized decision support systems and in preference-based intelligent systems

Human behavior in Prisoner's Dilemma experiments suppresses network reciprocity

During the last few years, much research has been devoted to strategic interactions on complex networks. In this context, the Prisoner's Dilemma has become a paradigmatic model, and it has been established that imitative evolutionary dynamics lead to very different outcomes depending on the details of the network. We here report that when one takes into account the real behavior of people observed in the experiments, both at the mean-field level and on utterly different networks the observed level of cooperation is the same. We thus show that when human subjects interact in an heterogeneous mix including cooperators, defectors and moody conditional cooperators, the structure of the population does not promote or inhibit cooperation with respect to a well mixed population.Comment: 5 Pages including 4 figures. Submitted for publicatio

Accumbal Cholinergic Interneurons Differentially Influence Motivation Related to Satiety Signaling

Satiety, rather than all or none, can instead be viewed as a cumulative decrease in the drive to eat that develops over the course of a meal. The nucleus accumbens (NAc) is known to play a critical role in this type of value reappraisal, but the underlying circuits that influence such processes are unclear. Although NAc cholinergic interneurons (CINs) comprise only a small proportion of NAc neurons, their local impact on reward-based processes provides a candidate cell population for investigating the neural underpinnings of satiety. The present research therefore aimed to determine the role of NAc-CINs in motivation for food reinforcers in relation to satiety signaling. Through bidirectional control of CIN activity in mice, we show that when motivated by food restriction, increasing CIN activity led to a reduction in palatable food consumption while reducing CIN excitability enhanced food intake. These activity-dependent changes developed only late in the session and were unlikely to be driven by the innate reinforcer strength, suggesting that CIN modulation was instead impacting the cumulative change in motivation underlying satiety signaling. We propose that on a circuit level, an overall increase in inhibitory tone onto NAc output neurons played a role in the behavioral results, as activating NAc-CINs led to an inhibition of medium spiny neurons that was dependent on nicotinic receptor activation. Our results reveal an important role for NAc-CINs in controlling motivation for food intake and additionally provide a circuit-level framework for investigating the endogenous cholinergic circuits that signal satiety.Peer reviewe

The Computational Complexity of Generating Random Fractals

In this paper we examine a number of models that generate random fractals. The models are studied using the tools of computational complexity theory from the perspective of parallel computation. Diffusion limited aggregation and several widely used algorithms for equilibrating the Ising model are shown to be highly sequential; it is unlikely they can be simulated efficiently in parallel. This is in contrast to Mandelbrot percolation that can be simulated in constant parallel time. Our research helps shed light on the intrinsic complexity of these models relative to each other and to different growth processes that have been recently studied using complexity theory. In addition, the results may serve as a guide to simulation physics.Comment: 28 pages, LATEX, 8 Postscript figures available from [email protected]

Rough droplet model for spherical metal clusters

We study the thermally activated oscillations, or capillary waves, of a neutral metal cluster within the liquid drop model. These deformations correspond to a surface roughness which we characterize by a single parameter $\Delta$. We derive a simple analytic approximate expression determining $\Delta$ as a function of temperature and cluster size. We then estimate the induced effects on shell structure by means of a periodic orbit analysis and compare with recent data for shell energy of sodium clusters in the size range $50 < N < 250$. A small surface roughness $\Delta\simeq 0.6$ \AA~ is seen to give a reasonable account of the decrease of amplitude of the shell structure observed in experiment. Moreover -- contrary to usual Jahn-Teller type of deformations -- roughness correctly reproduces the shape of the shell energy in the domain of sizes considered in experiment.Comment: 20 pages, 4 figures, important modifications of the presentation, to appear in Phys. Rev.