Constraining the halo-ISM connection through multi-transition carbon monoxide line-intensity mapping

Line-intensity mapping (LIM) surveys will characterise the cosmological large-scale structure of emissivity in a range of atomic and molecular spectral lines, but existing literature rarely considers whether these surveys can recover excitation properties of the tracer gas species, such as the carbon monoxide (CO) molecule. Combining basic empirical and physical assumptions with the off-the-shelf Radex radiative transfer code or a Gaussian process emulator of Radex outputs, we devise a basic dark matter halo model for CO emission by tying bulk CO properties to halo properties, exposing physical variables governing CO excitation as free parameters. The CO Mapping Array Project (COMAP) is working towards a multi-band survey programme to observe both CO(1-0) and CO(2-1) at $z\sim7$. We show that this programme, as well as a further 'Triple Deluxe' extension to higher frequencies covering CO(3-2), is fundamentally capable of successfully recovering the connection between halo mass and CO abundances, and constraining the molecular gas kinetic temperature and density within the star-forming interstellar medium in ways that single-transition CO LIM cannot. Given a fiducial thermal pressure of $\sim10^4$ K cm$^{-3}$ for molecular gas in halos of $\sim10^{10}\,M_\odot$, simulated multi-band COMAP surveys successfully recover the thermal pressure within 68% interval half-widths of 0.5--0.6 dex. Construction of multi-frequency LIM instrumentation to access multiple CO transitions is crucial in harnessing this capability, as part of a cosmic statistical probe of gas metallicity, dust chemistry, and other physical parameters in star-forming regions of the first galaxies and proto-galaxies out of reionisation.Comment: 26 pages + appendices and bibliography (37 pages total including title page); 10 figures, 6 tables; to be submitted to JCA

A test of the hierarchy of advertising effects via a panel data set on email advertising

Advertising changes the consumer. Through advertising exposures, a consumer becomes aware of the advertised product, becomes interested in it, develops a desire, and makes a purchase decision (the hierarchy of effects model). However, despite a wide use of email advertising by advertisers, how email advertising persuades and how it changes the consumer have not been studied. This dissertation focuses on the measurement of email advertising effectiveness based on the hierarchy of effects (awareness – interest – desire – action, AIDA) model which highlights each email advertising recipient’s journey towards a purchasing decision. This dissertation investigates the following research questions: which factors influence the open rate of email advertising (study 1); which factors influence the click rate of email advertising (study 2); and which factors influence the overall purchase behavior (study 3; or company sales). First, study 1 analyzes the factors that influence the open rate of email advertising and identifies five factors including subject line with price discount promotion, subject line stated in a loss frame, utilitarian product attribute, subject line describing a company’s social responsibility and socially responsible actions, and subject line describing holiday celebration that have positive impacts on the email recipient’s opening rate. Also, study 1 finds out that the short interval between email sendings decreases the open rate. Study 2 investigates the effects of email advertising body contents and finds that body contents with price discount promotion, body contents stated in a loss frame, and body contents describing seasonal appeal increase the recipient’s click rate when they open the email advertising. Finally, study 3 examines which factors influence the overall purchase behavior and finds that one factor, body contents with price discount promotion, increases most the purchase rate. This dissertation contributes to the understanding of the effects of email advertising on consumer behaviors. Notably, the three studies in this dissertation examining the factors that influence on the email advertising recipient’s opening, clicking, and purchasing actions contribute to empirical testing of the hierarchy model of advertising effects. The findings of this dissertation can also help advertisers and marketers strategically plan their advertising to achieve their goalAdvertisin

Characteristic Functions for Cosmological Cross-Correlations

We introduce a novel unbiased, cross-correlation estimator for the one-point statistics of cosmological random fields. One-point statistics are a useful tool for analysis of highly non-Gaussian density fields, while cross-correlations provide a powerful method for combining information from pairs of fields and separating them from noise and systematics. We derive a new Deconvolved Distribution Estimator that combines the useful properties of these two methods into one statistic. Using two example models of a toy Gaussian random field and a line intensity mapping survey, we demonstrate these properties quantitatively and show that the DDE can be used for inference. This new estimator can be applied to any pair of overlapping, non-Gaussian cosmological observations, including large-scale structure, the Sunyaev-Zeldovich effect, weak lensing, and many others.Comment: 13 pages, 13 figures, for submission to MNRA

The Early Universe was Dust-Rich and Extremely Hot

We investigate the dust properties and star-formation signature of galaxies in the early universe by stacking 111,227 objects in the recently released COSMOS catalogue on maps at wavelengths bracketing the peak of warmed dust emission. We find an elevated far-infrared luminosity density to redshift 10, indicating abundant dust in the early universe. We further find an increase of dust temperature with redshift, reaching ~ 119 +- 7 K at z ~ 9, suggesting either the presence of silicate rich dust originating from Population II stars, or sources of heating beyond simply young hot stars. Lastly, we try to understand how these objects have been missed in previous surveys, and how to design observations to target them. All code, links to the data, and instructions to reproduce this research in full is located at https://github.com/marcoviero/simstack3/

Cross-correlating Carbon Monoxide Line-intensity Maps with Spectroscopic and Photometric Galaxy Surveys

Line-intensity mapping (LIM or IM) is an emerging field of observational work, with strong potential to fit into a larger effort to probe large-scale structure and small-scale astrophysical phenomena using multiple complementary tracers. Taking full advantage of such complementarity means, in part, undertaking line-intensity surveys with galaxy surveys in mind. We consider the potential for detection of a cross-correlation signal between COMAP and blind surveys based on photometric redshifts (as in COSMOS) or based on spectroscopic data (as with the HETDEX survey of Lyman-$\alpha$ emitters). We find that obtaining $\sigma_z/(1+z)\lesssim0.003$ accuracy in redshifts and $\gtrsim10^{-4}$ sources per Mpc$^3$ with spectroscopic redshift determination should enable a CO-galaxy cross spectrum detection significance at least twice that of the CO auto spectrum. Either a future targeted spectroscopic survey or a blind survey like HETDEX may be able to meet both of these requirements.Comment: 19 pages + appendix (31 pages total), 16 figures, 6 tables; accepted for publication in Ap

Efficient calculation of a partial-derivative wavefield using reciprocity for seismic imaging and inversion

Linearized inversion of surface seismic data for a model of the earths subsurface requires estimating the sensitivity of the seismic response to perturbations in the earths subsurface. This sensitivity, or Jacobian, matrix is usually quite expensive to estimate for all but the simplest model parameterizations.We exploit the numerical structure of the finite-element method, modern sparse matrix technology, and source–receiver reciprocity to develop an algorithm that explicitly calculates the Jacobian matrix at only the cost of a forward model solution. Furthermore, we show that we can achieve improved subsurface images using only one inversion iteration through proper scaling of the image by a diagonal approximation of the Hessian matrix, as predicted by the classical Gauss-Newton method. Our method is applicable to the full suite of wave scattering problems amenable to finiteelement forward modeling.We demonstrate our method through some simple 2-D synthetic examples