Quasar H II Regions During Cosmic Reionization

Cosmic reionization progresses as HII regions form around sources of ionizing radiation. Their average size grows continuously until they percolate and complete reionization. We demonstrate how this typical growth can be calculated around the largest, biased sources of UV emission, such as quasars, by further developing an analytical model based on the excursion set formalism. This approach allows us to calculate the sizes and growth of the HII regions created by the progenitors of any dark matter halo of given mass and redshift with a minimum of free parameters. Statistical variations in the size of these pre-existing HII regions are an additional source of uncertainty in the determination of very high redshift quasar properties from their observed HII region sizes. We use this model to demonstrate that the transmission gaps seen in very high redshift quasars can be understood from the radiation of only their progenitors and associated clustered small galaxies. The fit sets a lower limit on the redshift of overlap at z = 5.8 +/- 0.1. This interpretation makes the transmission gaps independent of the age of the quasars observed. If this interpretation were correct it would raise the prospects of using radio interferometers currently under construction to detect the epoch of reionization.Comment: 6 pages, 3 figures, accepted by MNRAS, revised to match published versio

Towards the quantification of the semantic information encoded in written language

Written language is a complex communication signal capable of conveying information encoded in the form of ordered sequences of words. Beyond the local order ruled by grammar, semantic and thematic structures affect long-range patterns in word usage. Here, we show that a direct application of information theory quantifies the relationship between the statistical distribution of words and the semantic content of the text. We show that there is a characteristic scale, roughly around a few thousand words, which establishes the typical size of the most informative segments in written language. Moreover, we find that the words whose contributions to the overall information is larger, are the ones more closely associated with the main subjects and topics of the text. This scenario can be explained by a model of word usage that assumes that words are distributed along the text in domains of a characteristic size where their frequency is higher than elsewhere. Our conclusions are based on the analysis of a large database of written language, diverse in subjects and styles, and thus are likely to be applicable to general language sequences encoding complex information.Comment: 19 pages, 4 figure