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Ultra Luminous Infra-Red Galaxies (ULIRGs) -- gas-rich mergers harboring the most extreme star-forming conditions encountered in the local Universe -- are thought to re-enact the galaxy formation processes we are only barely able to glimpse in the distant Universe. Combining new single-dish molecular line observations of 12CO, 13CO, HCO+, HCN, and CS towards the two ULIRGs Arp220 and NGC6240 with existing data in the literature, we have compiled the most extensive molecular line data-sets to date of such galaxies. The data allow us to put strong constraints on the properties of the dense star forming gas in these two systems, and compare the relative usefulness of CS, HCN and HCO+ as tracers of dense gas. In addition, we have build molecular line templates based on our observations, and demonstrate that Herschel/HI-FI will be able to detect the high-J transitions of most of the above molecules in a large sample of ULIRGs out to z<=0.5, assuming Arp220 and NGC6240 are representative of the ULIRG population at these redshifts.
The learning rate is an information-theoretical quantity for bipartite Markov chains describing two coupled subsystems. It is defined as the rate at which transitions in the downstream subsystem tend to increase the mutual information between the two
We investigate the effects of multi-task learning using the recently introduced task of semantic tagging. We employ semantic tagging as an auxiliary task for three different NLP tasks: part-of-speech tagging, Universal Dependency parsing, and Natural
Learning problems form an important category of computational tasks that generalizes many of the computations researchers apply to large real-life data sets. We ask: what concept classes can be learned privately, namely, by an algorithm whose output
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The HI content of the Eridanus group of galaxies is studied using the GMRT observations and the HIPASS data. A significant HI deficiency up to a factor of 2-3 is observed in galaxies in the Eridanus group. The deficiency is found to be directly corre