5,676 research outputs found
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
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
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
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
Growing Graphs with Hyperedge Replacement Graph Grammars
Discovering the underlying structures present in large real world graphs is a
fundamental scientific problem. In this paper we show that a graph's clique
tree can be used to extract a hyperedge replacement grammar. If we store an
ordering from the extraction process, the extracted graph grammar is guaranteed
to generate an isomorphic copy of the original graph. Or, a stochastic
application of the graph grammar rules can be used to quickly create random
graphs. In experiments on large real world networks, we show that random
graphs, generated from extracted graph grammars, exhibit a wide range of
properties that are very similar to the original graphs. In addition to graph
properties like degree or eigenvector centrality, what a graph "looks like"
ultimately depends on small details in local graph substructures that are
difficult to define at a global level. We show that our generative graph model
is able to preserve these local substructures when generating new graphs and
performs well on new and difficult tests of model robustness.Comment: 18 pages, 19 figures, accepted to CIKM 2016 in Indianapolis, I
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
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