Probing Cosmic Reionization and Molecular Gas Growth with TIME

Line intensity mapping (LIM) provides a unique and powerful means to probe cosmic structures by measuring the aggregate line emission from all galaxies across redshift. The method is complementary to conventional galaxy redshift surveys that are object-based and demand exquisite point-source sensitivity. The Tomographic Ionized-carbon Mapping Experiment (TIME) will measure the star formation rate (SFR) during cosmic reionization by observing the redshifted [CII] 158$\mu$m line ($6 \lesssim z \lesssim 9$) in the LIM regime. TIME will simultaneously study the abundance of molecular gas during the era of peak star formation by observing the rotational CO lines emitted by galaxies at $0.5 \lesssim z \lesssim 2$. We present the modeling framework that predicts the constraining power of TIME on a number of observables, including the line luminosity function, and the auto- and cross-correlation power spectra, including synergies with external galaxy tracers. Based on an optimized survey strategy and fiducial model parameters informed by existing observations, we forecast constraints on physical quantities relevant to reionization and galaxy evolution, such as the escape fraction of ionizing photons during reionization, the faint-end slope of the galaxy luminosity function at high redshift, and the cosmic molecular gas density at cosmic noon. We discuss how these constraints can advance our understanding of cosmological galaxy evolution at the two distinct cosmic epochs for TIME, starting in 2021, and how they could be improved in future phases of the experiment.Comment: 30 pages, 18 figures, accepted for publication in Ap

The multifurcating skyline plot

A variety of methods based on coalescent theory have been developed to infer demographic history from gene sequences sampled from natural populations. The ‘skyline plot’ and related approaches are commonly employed as flexible prior distributions for phylogenetic trees in the Bayesian analysis of pathogen gene sequences. In this work we extend the classic and generalized skyline plot methods to phylogenies that contain one or more multifurcations (i.e. hard polytomies). We use the theory of Λ-coalescents (specifically, Beta(2-α,α)-coalescents) to develop the ‘multifurcating skyline plot’, which estimates a piecewise constant function of effective population size through time, conditional on a time-scaled multifurcating phylogeny. We implement a smoothing procedure and extend the method to serially sampled (heterochronous) data, but we do not address here the problem of estimating trees with multifurcations from gene sequence alignments. We validate our estimator on simulated data using maximum likelihood and find that parameters of the Beta(2-α,α) -coalescent process can be estimated accurately. Furthermore, we apply the multifurcating skyline plot to simulated trees generated by tracking transmissions in an individual-based model of epidemic superspreading. We find that high levels of superspreading are consistent with the high-variance assumptions underlying Λ-coalescents and that the estimated parameters of the Λ-coalescent model contain information about the degree of superspreading

Spatial dynamics and control of a crop pathogen with mixed-mode transmission

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