Independencies Induced from a Graphical Markov Model After Marginalization and Conditioning: The R Package ggm

We describe some functions in the R package ggm to derive from a given Markov model, represented by a directed acyclic graph, different types of graphs induced after marginalizing over and conditioning on some of the variables. The package has a few basic functions that find the essential graph, the induced concentration and covariance graphs, and several types of chain graphs implied by the directed acyclic graph (DAG) after grouping and reordering the variables. These functions can be useful to explore the impact of latent variables or of selection effects on a chosen data generating model.

A gauge approach to the "pseudogap" phenomenology of the spectral weight in high Tc cuprates

We assume the t-t'-J model to describe the CuO_2 planes of hole-doped cuprates and we adapt the spin-charge gauge approach, previously developed for the t-J model, to describe the holes in terms of a spinless fermion carrying the charge (holon) and a neutral boson carrying spin 1/2 (spinon), coupled by a slave-particle gauge field. In this framework we consider the effects of a finite density of incoherent holon pairs in the normal state. Below a crossover temperature, identified as the experimental "upper pseudogap", the scattering of the "quanta" of the phase of the holon-pair field against holons reproduces the phenomenology of Fermi arcs coexisting with gap in the antinodal region. We thus obtain a microscopic derivation of the main features of the hole spectra due to pseudogap. This result is obtained through a holon Green function which follows naturally from the formalism and analytically interpolates between a Fermi liquid-like and a d-wave superconductor behavior as the coherence length of the holon pair order parameter increases. By inserting the gauge coupling with the spinon we construct explicitly the hole Green function and calculate its spectral weight and the corresponding density of states. So we prove that the formation of holon pairs induces a depletion of states on the hole Fermi surface. We compare our results with ARPES and tunneling experimental data. In our approach the hole preserves a finite Fermi surface until the superconducting transition, where it reduces to four nodes. Therefore we propose that the gap seen in the normal phase of cuprates is due to the thermal broadening of the SC-like peaks masking the Fermi-liquid peak. The Fermi arcs then correspond to the region of the Fermi surface where the Fermi-liquid peak is unmasked.Comment: 10 figures, comments and references added, 2 figures change

Collective pairing of resonantly coupled microcavity polaritons

We consider the possible phases of microcavity polaritons tuned near a bipolariton Feshbach resonance. We show that, as well as the regular polariton superfluid phase, a "molecular" superfluid exists, with (quasi-)long-range order only for pairs of polaritons. We describe the experimental signatures of this state. Using variational approaches we find the phase diagram (critical temperature, density and exciton-photon detuning). Unlike ultracold atoms, the molecular superfluid is not inherently unstable, and our phase diagram suggests it is attainable in current experiments.Comment: paper (4 pages, 3 figures), Supplemental Material (7 pages, 8 figures

Chain graph models of multivariate regression type for categorical data

We discuss a class of chain graph models for categorical variables defined by what we call a multivariate regression chain graph Markov property. First, the set of local independencies of these models is shown to be Markov equivalent to those of a chain graph model recently defined in the literature. Next we provide a parametrization based on a sequence of generalized linear models with a multivariate logistic link function that captures all independence constraints in any chain graph model of this kind.Comment: Published in at http://dx.doi.org/10.3150/10-BEJ300 the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm

Matrix representations and independencies in directed acyclic graphs

For a directed acyclic graph, there are two known criteria to decide whether any specific conditional independence statement is implied for all distributions factorized according to the given graph. Both criteria are based on special types of path in graphs. They are called separation criteria because independence holds whenever the conditioning set is a separating set in a graph theoretical sense. We introduce and discuss an alternative approach using binary matrix representations of graphs in which zeros indicate independence statements. A matrix condition is shown to give a new path criterion for separation and to be equivalent to each of the previous two path criteria.Comment: Published in at http://dx.doi.org/10.1214/08-AOS594 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org