Abstract Line intensity mapping (LIM) proposes to efficiently observe distant faint galaxies and map the matter density field at high redshift.Building upon the formalism in a companion paper,we first highlight the degeneracies between cosmology and astrophysics in LIM.We discuss what can be constrained from measurements of the mean intensity and redshift-space power spectra.With a sufficient spectral resolution, the large-scale redshift-space distortions of the 2-halo term can be measured, helping to break the degeneracy between bias and mean intensity.With a higher spectral resolution, measuring the small-scale redshift-space distortions disentangles the 1-halo and shot noise terms.Cross-correlations with external galaxy catalogs or lensing surveys further break degeneracies.We derive requirements for experiments similar to SPHEREx, HETDEX, CDIM, COMAP and CONCERTO.We then revisit the question of the optimality of the LIM observables, compared to galaxy detection, for astrophysics and cosmology.We use a matched filter to compute the luminosity detection threshold for individual sources.We show that LIM contains information about galaxies too faint to detect, in the high-noise or high-confusion regimes.We quantify the sparsity and clustering bias of the detected sources and compare them to LIM, showing in which cases LIM is a better tracer of the matter density.We extend previous work by answering these questions as a function of Fourier scale, including for the first time the effect of cosmic variance, pixel-to-pixel correlations, luminosity-dependent clustering bias and redshift-space distortions.
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Multi-tracer intensity mapping: cross-correlations, line noise & decorrelation
Abstract Line intensity mapping (LIM) is a rapidly emerging technique for constraining cosmology and galaxy formation using multi-frequency, low angular resolution maps.Many LIM applications crucially rely on cross-correlations of two line intensity maps, or of intensity maps with galaxy surveys or galaxy/CMB lensing.We present a consistent halo model to predict all these cross-correlations and enable joint analyses, in 3D redshift-space and for 2D projected maps.We extend the conditional luminosity function formalism to the multi-line case, to consistently account for correlated scatter between multiple galaxy line luminosities.This allows us to model the scale-dependent decorrelation between two line intensity maps,a key input for foreground rejection and for approaches that estimate auto-spectra from cross-spectra.This also enables LIM cross-correlations to reveal astrophysical properties of the interstellar medium inacessible with LIM auto-spectra.We expose the different sources of luminosity scatter or “line noise” in LIM, and clarify their effects on the 1-halo and galaxy shot noise terms.In particular, we show that the effective number density of halos can in some cases exceed that of galaxies, counterintuitively.Using observational and simulation input, we implement this halo model for the Hα, [Oiii], Lyman-α, CO and [Cii] lines.We encourage observers and simulators to measure galaxy luminosity correlation coefficients for pairs of lines whenever possible.Our code is publicly available at https://github.com/EmmanuelSchaan/HaloGen/tree/LIM .In a companion paper, we use this halo model formalism and codeto highlight the degeneracies between cosmology and astrophysics in LIM, and to compare the LIM observables to galaxy detection for a number of surveys.
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- Award ID(s):
- 1713791
- NSF-PAR ID:
- 10322132
- Date Published:
- Journal Name:
- Journal of Cosmology and Astroparticle Physics
- Volume:
- 2021
- Issue:
- 05
- ISSN:
- 1475-7516
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Submillimeter emission lines produced by the interstellar medium (ISM) are strong tracers of star formation and are some of the main targets of line intensity mapping (LIM) surveys. In this work we present an empirical multiline emission model that simultaneously covers the mean, scatter, and correlations of [C ii ], CO J = 1–0 to J = 5–4, and [C i ] lines in the redshift range 1 ≤ z ≤ 9. We assume that the galaxy ISM line emission luminosity versus halo mass relations can be described by double power laws with redshift-dependent lognormal scatter. The model parameters are then derived by fitting to the state-of-the-art semianalytic simulation results that have successfully reproduced multiple submillimeter line observations at 0 ≤ z ≲ 6. We cross-check the line emission statistics predicted by the semianalytic simulation and our empirical model, finding that at z ≥ 1 our model reproduces the simulated line intensities with fractional error less than about 10%. The fractional difference is less than 25% for the power spectra. Grounded on physically motivated and self-consistent galaxy simulations, this computationally efficient model will be helpful in forecasting ISM emission-line statistics for upcoming LIM surveys.more » « less
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Abstract The epoch of reionization (EoR) offers a unique window into the dawn of galaxy formation, through which high-redshift galaxies can be studied by observations of both themselves and their impact on the intergalactic medium. Line intensity mapping (LIM) promises to explore cosmic reionization and its driving sources by measuring intensity fluctuations of emission lines tracing the cosmic gas in varying phases. Using LIMFAST, a novel seminumerical tool designed to self-consistently simulate LIM signals of multiple EoR probes, we investigate how building blocks of galaxy formation and evolution theory, such as feedback-regulated star formation and chemical enrichment, might be studied with multitracer LIM during the EoR. On galaxy scales, we show that the star formation law and the feedback associated with star formation can be indicated by both the shape and redshift evolution of LIM power spectra. For a baseline model of metal production that traces star formation, we find that lines highly sensitive to metallicity are generally better probes of galaxy formation models. On larger scales, we demonstrate that inferring ionized bubble sizes from cross-correlations between tracers of ionized and neutral gas requires a detailed understanding of the astrophysics that shape the line luminosity–halo mass relation. Despite various modeling and observational challenges, wide-area, multitracer LIM surveys will provide important high-redshift tests for the fundamentals of galaxy formation theory, especially the interplay between star formation and feedback by accessing statistically the entire low-mass population of galaxies as ideal laboratories, complementary to upcoming surveys of individual sources by new-generation telescopes.
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ABSTRACT Line-intensity mapping (LIM) is an emerging technique to probe the large-scale structure of the Universe. By targeting the integrated intensity of specific spectral lines, it captures the emission from all sources and is sensitive to the astrophysical processes that drive galaxy evolution. Relating these processes to the underlying distribution of matter introduces observational and theoretical challenges, such as observational contamination and highly non-Gaussian fields, which motivate the use of simulations to better characterize the signal. In this work we present skyline , a computational framework to generate realistic mock LIM observations that include observational features and foreground contamination, as well as a variety of self-consistent tracer catalogues. We apply our framework to generate realizations of LIM maps from the multidark planck 2 simulations coupled to the universemachine galaxy formation model. We showcase the potential of our scheme by exploring the voxel intensity distribution and the power spectrum of emission lines such as 21 cm, CO, [C ii], and Lyman-α, their mutual cross-correlations, and cross-correlations with galaxy clustering. We additionally present cross-correlations between LIM and submillimetre extragalactic tracers of large-scale structure such as the cosmic infrared background and the thermal Sunyaev-Zel’dovich effect, as well as quantify the impact of galactic foregrounds, line interlopers, and instrument noise on LIM observations. These simulated products will be crucial in quantifying the true information content of LIM surveys and their cross-correlations in the coming decade, and to develop strategies to overcome the impact of contaminants and maximize the scientific return from LIM experiments.
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Abstract The abundance of cold molecular gas plays a crucial role in models of galaxy evolution. While deep spectroscopic surveys of CO emission lines have been a primary tool for measuring this abundance, the difficulty of these observations has motivated alternative approaches to studying molecular gas content. One technique, line intensity mapping, seeks to constrain the average molecular gas properties of large samples of individually undetectable galaxies through the CO brightness power spectrum. Here we present constraints on the cross-power spectrum between CO intensity maps and optical galaxy catalogs. This cross-measurement allows us to check for systematic problems in CO intensity mapping data, and validate the data analysis used for the auto-power spectrum measurement of the CO Power Spectrum Survey. We place a 2
σ upper limit on the band-averaged CO-galaxy cross-power ofP ×< 540μ K h−3Mpc3. Our measurement favors a nonzero 〈T CO〉 at around 90% confidence and gives an upper limit on the mean molecular gas density atz ∼ 2.6 of 7.7 × 108M ⊙Mpc−3. We forecast the expected cross-power spectrum by applying a number of literature prescriptions for the CO luminosity–halo mass relation to a suite of mock light cones. Under the most optimistic forecasts, the cross-spectrum could be detected with only moderate extensions of the data used here, while more conservative models could be detected with a factor of 10 increase in sensitivity. Ongoing CO intensity mapping experiments will target fields allowing for extensive cross-correlation analysis and should reach the sensitivity required to detect the cross-spectrum signal.
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1088/1475-7516/2021/05/068
