arXiv subjects

J. Camacho

Publications and source records attributed to J. Camacho.

21 records · Page 2Linked to original sources

arXiv2007

The contribution of Oxygen-Neon white dwarfs to the MACHO content of the Galactic Halo

The interpretation of microlensing results towards the Large Magellanic Cloud (LMC) still remains controversial. White dwarfs have been proposed to explain these results and, hence, to contribute significantly to the mass budget of our Galaxy. However, several constraints on the role played by regular carbon-oxygen white dwarfs exist. Massivewhite dwarfs are thought to be made of a mixture of oxygen and neon. Correspondingly, their cooling rate is larger than those of typical carbon-oxygen white dwarfs and they fade to invisibility in short timescales. Consequently, they constitute a good candidate for explaining the microlensing results. Here, we examine in detail this hypothesis by using the most recent and up-to-date cooling tracks for massive white dwarfs and a Monte Carlo simulator which takes into account the most relevant Galactic inputs. We find that oxygen-neon white dwarfs cannot account for a substantial fraction of the microlensing depth towards the LMC, independently of the adopted initial mass function, although some microlensing events could be due to oxygen--neon white dwarfs. The white dwarf population contributes at most a 5% to the mass of the Galactic halo.

astro-ph↗

arXiv2004

Quantitative patterns in the structure of model and empirical food webs

We analyze the properties of model food webs and of fifteen community food webs from a variety of environments. We first perform a theoretical analysis of the niche model of Williams and Martinez. We derive analytical expressions for the distributions of species' number of prey, number of predators, and total number of trophic links and find that they follow universal functional forms. We also derive expressions for a number of other biologically relevant parameters, including the fraction of top, intermediate, basal, and cannibal species, the standard deviations of generality and vulnerability, the correlation coefficient between species' number of prey and number of predators, and assortativity. We show that our findings are robust under rather general conditions. We then use our analytical predictions as a guide to the analysis of fifteen of the most complete empirical food webs available. We uncover quantitative unifying patterns that describe the properties of the model food webs and most of the trophic webs considered. Our results support a strong new hypothesis that the empirical distributions of number of prey and number of predators follow universal functional forms that, without free parameters, match our analytical predictions. Further, we find that the empirically observed correlation coefficient, assortativity, and fraction of cannibal species are consistent with our analytical expressions and simulations of the niche model. Finally, we show that the average distance between nodes and the average clustering coefficient show a high degree of regularity for both the empirical data and simulations of the niche model. Our findings suggest that statistical physics concepts such as scaling and universality may be useful in the description of natural ecosystems.

q-bio.PE↗

arXiv2002

Robust Patterns in Food Web Structure

We analyze the properties of seven community food webs from a variety of environments--including freshwater, marine-freshwater interfaces and terrestrial environments. We uncover quantitative unifying patterns that describe the properties of the diverse trophic webs considered and suggest that statistical physics concepts such as scaling and universality may be useful in the description of ecosystems. Specifically, we find that several quantities characterizing these diverse food webs obey functional forms that are universal across the different environments considered. The empirical results are in remarkable agreement with the analytical solution of a recently proposed model for food webs.

cond-mat.dis-nn↗