Cosmology from Quantum Information

We describe inflation in terms of a time dependent quantum density matrix with time playing the role of a stochastic variable. Using a quasi-de Sitter model we compute the corresponding quantum Fisher information function as the second derivative of the relative entanglement entropy for the density matrix at two different times. Employing standard quantum estimation theory we evaluate the minimal variance of quantum scalar fluctuations that reproduces the power spectrum and the corresponding tilt in the slow roll limit. The Jeffreys prior associated with such Fisher information can be used to define the probabilities on the set of initial conditions defined by the slow roll parameter $\epsilon$ and the initial Shannon information.Comment: extended discussion in general and in particular for fluctuation curvature power spectrum and citations adde

Stereo visual odometry by combining points and lines

Poster presented at ICVSS2016: international Computer Vision Summer SchoolMost approaches to stereo visual odometry reconstruct the motion based on the tracking of point features along a sequence of images. However, in low-textured scenes it is often difficult to encounter a large set of point features, or it may happen that they are not well distributed over the image, so that the behavior of these algorithms deteriorates. This paper proposes a probabilistic approach to stereo visual odometry based on the combination of both point and line segment that works robustly in a wide variety of scenarios. The camera motion is recovered through non-linear minimization of the projection errors of both point and line segment features. The method, of course, is computationally more expensive that using only one type of feature, but still can run in real-time on a standard computer and provides interesting advantages, including a straightforward integration into any probabilistic framework commonly employed in mobile robotics.Universidad de Málag

Robust Stereo Visual Odometry through a Probabilistic Combination of Points and Line Segments

Most approaches to stereo visual odometry reconstruct the motion based on the tracking of point features along a sequence of images. However, in low-textured scenes it is often difficult to encounter a large set of point features, or it may happen that they are not well distributed over the image, so that the behavior of these algorithms deteriorates. This paper proposes a probabilistic approach to stereo visual odometry based on the combination of both point and line segment that works robustly in a wide variety of scenarios. The camera motion is recovered through non-linear minimization of the projection errors of both point and line segment features. In order to effectively combine both types of features, their associated errors are weighted according to their covariance matrices, computed from the propagation of Gaussian distribution errors in the sensor measurements. The method, of course, is computationally more expensive that using only one type of feature, but still can run in real-time on a standard computer and provides interesting advantages, including a straightforward integration into any probabilistic framework commonly employed in mobile robotics.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Project "PROMOVE: Advances in mobile robotics for promoting independent life of elders", funded by the Spanish Government and the "European Regional Development Fund ERDF" under contract DPI2014-55826-R

Initial conditions for inflation and the energy scale of SUSY-breaking from the (nearly) gaussian sky

We show how general initial conditions for small field inflation can be obtained in multi-field models. This is provided by non-linear angular friction terms in the inflaton that provide a phase of non-slow-roll inflation before the slow-roll inflation phase. This in turn provides a natural mechanism to star small-field slow-roll at nearly zero velocity for arbitrary initial conditions. We also show that there is a relation between the scale of SUSY breaking sqrt (f) and the amount of non-gaussian fluctuations generated by the inflaton. In particular, we show that in the local non-gaussian shape there exists the relation sqrt (f) = 10^{13} GeV sqrt (f_NL). With current observational limits from Planck, and adopting the minimum amount of non-gaussian fluctuations allowed by single-field inflation, this provides a very tight constraint for the SUSY breaking energy scale sqrt (f) = 3-7 x 10^{13} GeV at 95% confidence. Further limits, or detection, from next year's Planck polarisation data will further tighten this constraint by a factor of two. We highlight that the key to our approach is to identify the inflaton with the scalar component of the goldstino superfield. This superfield is universal and implements the dynamics of SUSY breaking as well as superconformal breaking.Comment: Invited talk at the BW2013 meetin

Geometric-based Line Segment Tracking for HDR Stereo Sequences

In this work, we propose a purely geometrical approach for the robust matching of line segments for challenging stereo streams with severe illumination changes or High Dynamic Range (HDR) environments. To that purpose, we exploit the univocal nature of the matching problem, i.e. every observation must be corresponded with a single feature or not corresponded at all. We state the problem as a sparse, convex, `1-minimization of the matching vector regularized by the geometric constraints. This formulation allows for the robust tracking of line segments along sequences where traditional appearance-based matching techniques tend to fail due to dynamic changes in illumination conditions. Moreover, the proposed matching algorithm also results in a considerable speed-up of previous state of the art techniques making it suitable for real-time applications such as Visual Odometry (VO). This, of course, comes at expense of a slightly lower number of matches in comparison with appearance based methods, and also limits its application to continuous video sequences, as it is rather constrained to small pose increments between consecutive frames.We validate the claimed advantages by first evaluating the matching performance in challenging video sequences, and then testing the method in a benchmarked point and line based VO algorithm.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.This work has been supported by the Spanish Government (project DPI2017-84827-R and grant BES-2015-071606) and by the Andalucian Government (project TEP2012-530)

Social Pressure in Networks Induces Public Good Provision

I develop a dynamic model with forward looking agents, and show that social pressure is effective in generating provision in a public good game: after a small group of agents start contributing to the public good, other agents decide to contribute as well due to a fear of being punished, and this generates contagion in the network. In contrast to earlier models in the literature, contagion happens fast, as part of the best response of fully rational individuals. The network topology has implications for whether contagion starts and the extent to which it spreads. I find conditions under which an agent decides to be the first to contribute in order to generate contagion in the network, as well as conditions for contribution due to a self-fulfilling fear of social pressure.I gratefully acknowledge financial support from the Bank of Spain and Fundación Rafael del Pino during my PhD, when this research project was initiated

Resistance to Change of Ethanol Self-Administration: Effects of Naltrexone and Extinction

Drug self-administration has proven to be an adequate model for assessing variables that contribute to the maintenance of drug taking. The present experiment was concerned with the persistence of drug self-administration, a defining characteristic of drug dependence and abuse. Findings from studies of the resistance to change of food-maintained responding may contribute to a better understanding of the persistence of drug abuse and dependence. Using an animal model of alcohol self-administration, this study evaluated the effects of rate of reinforcement on the persistence of ethanol self-administration in rats in the face of behavioral (i.e., extinction) and pharmacological (i.e., naltrexone) disruptors. Four experimentally naive Long Evans rats were trained to respond for a 10% (vol/vol) ethanol solution on a multiple variable-interval (VI) 15-s VI 45-s schedule of reinforcement. Baseline response rates were higher in the component that provided higher rates of ethanol delivery. Consistent with behavioral momentum theory, responding was more resistant to extinction in the component with higher rates of ethanol delivery. Conversely, disruption with naltrexone (1.0, 3.0, 10.0 mg/kg, s.c.), injected one hour before the session, resulted in no differential resistance to change of responding. The results are interpreted in terms of the effect of naltrexone on the incentive-motivational properties of the stimulus context

Accurate Stereo Visual Odometry with Gamma Distributions

Point-based stereo visual odometry systems typically estimate the camera motion by minimizing a cost function of the projection residuals between consecutive frames. Under some mild assumptions, such minimization is equivalent to maximizing the probability of the measured residuals given a certain pose change, for which a suitable model of the error distribution (sensor model) becomes of capital importance in order to obtain accurate results. This paper proposes a robust probabilistic model for projection errors, based on real world data. For that, we argue that projection distances follow Gamma distributions, and hence, the introduction of these models in a probabilistic formulation of the motion estimation process increases both precision and accuracy. Our approach has been validated through a series of experiments with both synthetic and real data, revealing an improvement in accuracy while not increasing the computational burden.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Project "PROMOVE: Advances in mobile robotics for promoting independent life of elders", funded by the Spanish Government and the "European Regional Development Fund ERDF" under contract DPI2014-55826-R