Phase diagram and dynamic response functions of the Holstein-Hubbard model

We present the phase diagram and dynamical correlation functions for the Holstein-Hubbard model at half filling and at zero temperature. The calculations are based on the Dynamical Mean Field Theory. The effective impurity model is solved using Exact Diagonalization and the Numerical Renormalization Group. Excluding long-range order, we find three different paramagnetic phases, metallic, bipolaronic and Mott insulating, depending on the Hubbard interaction U and the electron-phonon coupling g. We present the behaviour of the one-electron spectral functions and phonon spectra close to the metal insulator transitions.Comment: contribution to the SCES04 conferenc

First- and Second Order Phase Transitions in the Holstein-Hubbard Model

We investigate metal-insulator transitions in the Holstein-Hubbard model as a function of the on-site electron-electron interaction U and the electron-phonon coupling g. We use several different numerical methods to calculate the phase diagram, the results of which are in excellent agreement. When the electron-electron interaction U is dominant the transition is to a Mott-insulator; when the electron-phonon interaction dominates, the transition is to a localised bipolaronic state. In the former case, the transition is always found to be second order. This is in contrast to the transition to the bipolaronic state, which is clearly first order for larger values of U. We also present results for the quasiparticle weight and the double-occupancy as function of U and g.Comment: 6 pages, 5 figure

Automatic Classification of Text Databases through Query Probing

Many text databases on the web are "hidden" behind search interfaces, and their documents are only accessible through querying. Search engines typically ignore the contents of such search-only databases. Recently, Yahoo-like directories have started to manually organize these databases into categories that users can browse to find these valuable resources. We propose a novel strategy to automate the classification of search-only text databases. Our technique starts by training a rule-based document classifier, and then uses the classifier's rules to generate probing queries. The queries are sent to the text databases, which are then classified based on the number of matches that they produce for each query. We report some initial exploratory experiments that show that our approach is promising to automatically characterize the contents of text databases accessible on the web.Comment: 7 pages, 1 figur

Dynamic response functions for the Holstein-Hubbard model

We present results on the dynamical correlation functions of the particle-hole symmetric Holstein-Hubbard model at zero temperature, calculated using the dynamical mean field theory which is solved by the numerical renormalization group method. We clarify the competing influences of the electron-electron and electron-phonon interactions particularity at the different metal to insulator transitions. The Coulomb repulsion is found to dominate the behaviour in large parts of the metallic regime. By suppressing charge fluctuations, it effectively decouples electrons from phonons. The phonon propagator shows a characteristic softening near the metal to bipolaronic transition but there is very little softening on the approach to the Mott transition.Comment: 13 pages, 19 figure

Do resources, justice administration practices and federalism have an impact on registered and sentenced crime prevalence?

This contribution, based on a statistical approach, undertakes to link data on resources (personnel and financial means) and the working of the administration of penal justice (prosecution, sentencing) taking into account the nationality of those prosecuted. In order to be able to distinguish prosecution and sentencing practices of judicial authorities and possible processes of discrimination, diverse sources have been used such as data from court administrations, public finances and police forces, collected by the Swiss Federal Statistical Office and the Swiss Federal administration of finances. The authors discuss discrimination in prosecution and sentencing between Swiss residents and foreigners taking into account localization and resources regarding personnel and public finances

The Grow-Shrink strategy for learning Markov network structures constrained by context-specific independences

Markov networks are models for compactly representing complex probability distributions. They are composed by a structure and a set of numerical weights. The structure qualitatively describes independences in the distribution, which can be exploited to factorize the distribution into a set of compact functions. A key application for learning structures from data is to automatically discover knowledge. In practice, structure learning algorithms focused on "knowledge discovery" present a limitation: they use a coarse-grained representation of the structure. As a result, this representation cannot describe context-specific independences. Very recently, an algorithm called CSPC was designed to overcome this limitation, but it has a high computational complexity. This work tries to mitigate this downside presenting CSGS, an algorithm that uses the Grow-Shrink strategy for reducing unnecessary computations. On an empirical evaluation, the structures learned by CSGS achieve competitive accuracies and lower computational complexity with respect to those obtained by CSPC.Comment: 12 pages, and 8 figures. This works was presented in IBERAMIA 201

A Continuation Method for Nash Equilibria in Structured Games

Structured game representations have recently attracted interest as models for multi-agent artificial intelligence scenarios, with rational behavior most commonly characterized by Nash equilibria. This paper presents efficient, exact algorithms for computing Nash equilibria in structured game representations, including both graphical games and multi-agent influence diagrams (MAIDs). The algorithms are derived from a continuation method for normal-form and extensive-form games due to Govindan and Wilson; they follow a trajectory through a space of perturbed games and their equilibria, exploiting game structure through fast computation of the Jacobian of the payoff function. They are theoretically guaranteed to find at least one equilibrium of the game, and may find more. Our approach provides the first efficient algorithm for computing exact equilibria in graphical games with arbitrary topology, and the first algorithm to exploit fine-grained structural properties of MAIDs. Experimental results are presented demonstrating the effectiveness of the algorithms and comparing them to predecessors. The running time of the graphical game algorithm is similar to, and often better than, the running time of previous approximate algorithms. The algorithm for MAIDs can effectively solve games that are much larger than those solvable by previous methods

ENDOTHELIAL DYSFUNCTION AUGMENTS MYOGENIC ARTERIOLAR CONSTRICTION IN HYPERTENSION

To elucidate the underlying reason or reasons for the increased peripheral resistance in hypertension, we investigated the pressure-diameter relation-the myogenic response-of isolated, cannulated arterioles (approximately 50 mu m) of cremaster muscle of 12-week-old Wistar-Kyoto (WKY) rats, spontaneously hypertensive rats (SHR), and normal Wistar (NW) rats. All arterioles constricted in response to step increases in perfusion pressure from 20 to 160 mm Hg. This constriction was, however, significantly enhanced from 60 to 160 mm Hg in arterioles of SHR compared with NW or WKY rats. For example, at 80 and 140 mm Hg, respectively, the normalized diameter (expressed as a percentage of the corresponding passive diameter of arterioles of SHR) was 11.8% and 27.6% (P<.05) less compared with those of WKY rats. Endothelium removal eliminated the enhanced pressure-induced tone in SHR. Similarly, indomethacin (10(-5) mol/L, sufficient to block prostaglandin synthesis) or SQ 29,548 (10(-6) mol/L), a thromboxane A(2)-prostaglandin H-2 receptor blocker that inhibited vasoconstriction to the thromboxane agonist U46619, attenuated the enhanced pressure-diameter curve and reversed the blunted dilation to arachidonic acid in SHR. In contrast, the thromboxane A(2) synthesis inhibitor CGS 13,080 (5x10(-6) mol/L) did not affect the increased pressure-induced tone or the reduced dilation to arachidonic acid in SHR. Thus, the present findings suggest that in early hypertension pressure-induced arteriolar constriction is increased. This seems to be due to an enhanced production of endothelium-derived constrictor factors, primarily prostaglandin H-2

Entropy/IP: Uncovering Structure in IPv6 Addresses

In this paper, we introduce Entropy/IP: a system that discovers Internet address structure based on analyses of a subset of IPv6 addresses known to be active, i.e., training data, gleaned by readily available passive and active means. The system is completely automated and employs a combination of information-theoretic and machine learning techniques to probabilistically model IPv6 addresses. We present results showing that our system is effective in exposing structural characteristics of portions of the IPv6 Internet address space populated by active client, service, and router addresses. In addition to visualizing the address structure for exploration, the system uses its models to generate candidate target addresses for scanning. For each of 15 evaluated datasets, we train on 1K addresses and generate 1M candidates for scanning. We achieve some success in 14 datasets, finding up to 40% of the generated addresses to be active. In 11 of these datasets, we find active network identifiers (e.g., /64 prefixes or `subnets') not seen in training. Thus, we provide the first evidence that it is practical to discover subnets and hosts by scanning probabilistically selected areas of the IPv6 address space not known to contain active hosts a priori.Comment: Paper presented at the ACM IMC 2016 in Santa Monica, USA (https://dl.acm.org/citation.cfm?id=2987445). Live Demo site available at http://www.entropy-ip.com