A notion of graph likelihood and an infinite monkey theorem

We play with a graph-theoretic analogue of the folklore infinite monkey theorem. We define a notion of graph likelihood as the probability that a given graph is constructed by a monkey in a number of time steps equal to the number of vertices. We present an algorithm to compute this graph invariant and closed formulas for some infinite classes. We have to leave the computational complexity of the likelihood as an open problem.Comment: 6 pages, 1 EPS figur

Modifications in the Spectrum of Primordial Gravitational Waves Induced by Instantonic Fluctuations

Vacuum to vacuum instantonic transitions modify the power spectrum of primordial gravitational waves. We evaluate the new form of the power spectrum for ordinary gravity as well as the parity violation induced in the spectrum by a modification of General Relativity known as Holst term and we outline the possible experimental consequences.Comment: V1: 8 pages. V2: 8 pages, some points clarified, typos corrected, some references added, final result unchanged. V3: 8 pages, title changed, presentation improved, discussion of phenomenological consequences added, comments very welcome. V4: Discussion further improved, comments very very welcom

Bias Reduction of Long Memory Parameter Estimators via the Pre-filtered Sieve Bootstrap

This paper investigates the use of bootstrap-based bias correction of semi-parametric estimators of the long memory parameter in fractionally integrated processes. The re-sampling method involves the application of the sieve bootstrap to data pre-filtered by a preliminary semi-parametric estimate of the long memory parameter. Theoretical justification for using the bootstrap techniques to bias adjust log-periodogram and semi-parametric local Whittle estimators of the memory parameter is provided. Simulation evidence comparing the performance of the bootstrap bias correction with analytical bias correction techniques is also presented. The bootstrap method is shown to produce notable bias reductions, in particular when applied to an estimator for which analytical adjustments have already been used. The empirical coverage of confidence intervals based on the bias-adjusted estimators is very close to the nominal, for a reasonably large sample size, more so than for the comparable analytically adjusted estimators. The precision of inferences (as measured by interval length) is also greater when the bootstrap is used to bias correct rather than analytical adjustments.Comment: 38 page

Towards a mesoscopic model of water-like fluids with hydrodynamic interactions

We present a mesoscopic lattice model for non-ideal fluid flows with directional interactions, mimicking the effects of hydrogen-bonds in water. The model supports a rich and complex structural dynamics of the orientational order parameter, and exhibits the formation of disordered domains whose size and shape depend on the relative strength of directional order and thermal diffusivity. By letting the directional forces carry an inverse density dependence, the model is able to display a correlation between ordered domains and low density regions, reflecting the idea of water as a denser liquid in the disordered state than in the ordered one

Updating constraint preconditioners for KKT systems in quadratic programming via low-rank corrections

This work focuses on the iterative solution of sequences of KKT linear systems arising in interior point methods applied to large convex quadratic programming problems. This task is the computational core of the interior point procedure and an efficient preconditioning strategy is crucial for the efficiency of the overall method. Constraint preconditioners are very effective in this context; nevertheless, their computation may be very expensive for large-scale problems, and resorting to approximations of them may be convenient. Here we propose a procedure for building inexact constraint preconditioners by updating a "seed" constraint preconditioner computed for a KKT matrix at a previous interior point iteration. These updates are obtained through low-rank corrections of the Schur complement of the (1,1) block of the seed preconditioner. The updated preconditioners are analyzed both theoretically and computationally. The results obtained show that our updating procedure, coupled with an adaptive strategy for determining whether to reinitialize or update the preconditioner, can enhance the performance of interior point methods on large problems.Comment: 22 page

Peccei--Quinn mechanism in gravity and the nature of the Barbero--Immirzi parameter

A general argument provides the motivation to consider the Barbero--Immirzi parameter as a field. The specific form of the geometrical effective action allows to relate the value of the Barbero--Immirzi parameter to other quantum ambiguities through the analog of the Peccei--Quinn mechanism.Comment: Accepted for publication on Phys. Rev. Let