scholarly journals Extracting H i astrophysics from interferometric Intensity Mapping

2021 ◽  
Author(s):  
Zhaoting Chen ◽  
Laura Wolz ◽  
Marta Spinelli ◽  
Steven G Murray
Keyword(s):  
Galaxy Formation ◽  
Shot Noise ◽  
Large Scale ◽  
Neutral Hydrogen ◽  
Mass Function ◽  
Small Scale ◽  
Number Density ◽  
Model Framework ◽  
Intensity Mapping ◽  
Cent Level

Abstract We present a new halo model of neutral hydrogen (H i) calibrated to galaxy formation simulations at redshifts z ∼ 0.1 and z ∼ 1.0 which we employ to investigate the constraining power of interferometric H i Intensity Mapping on H i astrophysics. We demonstrate that constraints on the small-scale H i power spectrum can break the degeneracy between the H i density $\Omega _{\rm H\, \rm \small {I}}$ and the H i bias $b_{\rm H\, \rm \small {I}}$. For z ∼ 0.1, we forecast that an accurate measurement of $\Omega _{\rm H\, \rm \small {I}}$ up to 6 per cent level precision and the large scale H i bias $b_{\rm H\, \rm \small {I}}^0$ up to 1 per cent level precision can be achieved using Square Kilometre Array (SKA) pathfinder data from MeerKAT and ASKAP. We also propose a new description of the H i shot noise in the halo model framework in which a scatter of the relation between the H i mass of galaxies and their host halo mass is taken into account. Furthermore, given the number density of H i galaxies above a certain H i mass threshold, future surveys will also be able to constrain the H i Mass Function using only the H i shot noise. This will lead to constraints at the 10 per cent level using the standard Schechter function. This technique will potentially provide a new way of measuring the H i Mass Function, independent from existing methods. We predict that the SKA will be able to further improve the low redshift constraints by a factor of three, as well as pioneering measurements of H i astrophysics at higher redshifts.

scholarly journals The atomic hydrogen content of the post-reionization Universe

2020 ◽  
Vol 493 (4) ◽  
pp. 5434-5455 ◽  
Author(s):  
Marta Spinelli ◽  
Anna Zoldan ◽  
Gabriella De Lucia ◽  
Lizhi Xie ◽  
Matteo Viel
Keyword(s):  
Galaxy Formation ◽  
Shot Noise ◽  
Atomic Hydrogen ◽  
Mass Function ◽  
Limiting Factor ◽  
History Plays ◽  
Local Universe ◽  
Intensity Mapping ◽  
The One ◽  
Halo Occupation Distribution

ABSTRACT We present a comprehensive analysis of atomic hydrogen (H i) properties using a semi-analytical model of galaxy formation and N-body simulations covering a large cosmological volume at high resolution. We examine the H i mass function and the H i density, characterizing both their redshift evolution and their dependence on hosting halo mass. We analyse the H i content of dark matter haloes in the local Universe and up to redshift z = 5, discussing the contribution of different galaxy properties. We find that different assembly history plays a crucial role in the scatter of this relation. We propose new fitting functions useful for constructing mock H i maps with halo occupation distribution techniques. We investigate the H i clustering properties relevant for future 21 cm intensity mapping (IM) experiments, including the H i bias and the shot-noise level. The H i bias increases with redshift and it is roughly flat on the largest scales probed. The scale dependence is found at progressively larger scales with increasing redshift, apart from a dip feature at z = 0. The shot-noise values are consistent with the ones inferred by independent studies, confirming that shot noise will not be a limiting factor for IM experiments. We detail the contribution from various galaxy properties on the H i power spectrum and their relation to the halo bias. We find that H i poor satellite galaxies play an important role at the scales of the one-halo term. Finally, we present the 21 cm signal in redshift space, a fundamental prediction to be tested against data from future radio telescopes such as Square Kilometre Array.

scholarly journals Mapping large-scale-structure evolution over cosmic times

2021 ◽  
Author(s):  
Marta B. Silva ◽  
Ely D. Kovetz ◽  
Garrett K. Keating ◽  
Azadeh Moradinezhad Dizgah ◽  
Matthieu Bethermin ◽  
...  
Keyword(s):  
Galaxy Formation ◽  
Large Scale ◽  
High Redshift ◽  
Formation Rate ◽  
Far Infrared ◽  
Large Scale Structure ◽  
Scale Structure ◽  
Structure Evolution ◽  
Intensity Mapping ◽  
Wide Range

AbstractThis paper outlines the science case for line-intensity mapping with a space-borne instrument targeting the sub-millimeter (microwaves) to the far-infrared (FIR) wavelength range. Our goal is to observe and characterize the large-scale structure in the Universe from present times to the high redshift Epoch of Reionization. This is essential to constrain the cosmology of our Universe and form a better understanding of various mechanisms that drive galaxy formation and evolution. The proposed frequency range would make it possible to probe important metal cooling lines such as [CII] up to very high redshift as well as a large number of rotational lines of the CO molecule. These can be used to trace molecular gas and dust evolution and constrain the buildup in both the cosmic star formation rate density and the cosmic infrared background (CIB). Moreover, surveys at the highest frequencies will detect FIR lines which are used as diagnostics of galaxies and AGN. Tomography of these lines over a wide redshift range will enable invaluable measurements of the cosmic expansion history at epochs inaccessible to other methods, competitive constraints on the parameters of the standard model of cosmology, and numerous tests of dark matter, dark energy, modified gravity and inflation. To reach these goals, large-scale structure must be mapped over a wide range in frequency to trace its time evolution and the surveyed area needs to be very large to beat cosmic variance. Only a space-borne mission can properly meet these requirements.

scholarly journals The impact of stellar feedback on high-z galaxy populations

2015 ◽  
Vol 11 (S319) ◽  
pp. 26-26
Author(s):  
Michaela Hirschmann ◽  
Gabriella De Lucia
Keyword(s):  
Star Formation ◽  
Galaxy Formation ◽  
Large Scale ◽  
Mass Function ◽  
Chemical Enrichment ◽  
Stellar Feedback ◽  
Feedback Scheme ◽  
Galaxy Populations ◽  
Improved Model ◽  
The Impact

AbstractOne major deficiency of state-of-the-art galaxy formation models consists in their inability of capturing the observed galaxy downsizing trend significantly over-estimating the number density of low-mass galaxies, in particular at high redshifts. Employing an enhanced galaxy formation model with a full chemical enrichment scheme (DeLucia et al., 2014), we present an improved model for stellar feedback (based on parametrizations from cosmological zoom simulations), in which strong gas outflows occur due to bursty star formation at high z, while star formation is mainly “quiescent” not causing any significant outflows anymore at low z. Due to the stronger gas outflows at high z, early star formation is strongly delayed towards later times. This helps to sufficiently detach the evolution of galaxy growth from the hiearchical dark matter assembly resulting in a fairly good agreement with the evolution of the observed stellar mass function (SMF, see Fig. 1). With our new feedback scheme, we can also successfully reproduce many other observational constraints, such as the metallicity content, the cold gas fractions or the quiescent galaxy fractions at both low and high redshifts. The resulting new-generation galaxy catalogues (Hirschmann et al., in prep) based on that model are expected to significantly contribute to the interpretation of current and up-coming large-scale surveys (HST, JWST, Euclid). This will, in turn, provide a rapid verification and refinement of our modeling.

scholarly journals Voronoi volume function: a new probe of cosmology and galaxy evolution

2020 ◽  
Vol 495 (3) ◽  
pp. 3233-3251 ◽  
Author(s):  
Aseem Paranjape ◽  
Shadab Alam
Keyword(s):  
Dark Matter ◽  
Galaxy Evolution ◽  
Large Scale ◽  
Cold Dark Matter ◽  
Voronoi Tessellation ◽  
Small Scale ◽  
Summary Statistics ◽  
Number Density ◽  
Volume Function ◽  
Space Effects

ABSTRACT We study the Voronoi volume function (VVF) – the distribution of cell volumes (or inverse local number density) in the Voronoi tessellation of any set of cosmological tracers (galaxies/haloes). We show that the shape of the VVF of biased tracers responds sensitively to physical properties such as halo mass, large-scale environment, substructure, and redshift-space effects, making this a hitherto unexplored probe of both primordial cosmology and galaxy evolution. Using convenient summary statistics – the width, median, and a low percentile of the VVF as functions of average tracer number density – we explore these effects for tracer populations in a suite of N-body simulations of a range of dark matter models. Our summary statistics sensitively probe primordial features such as small-scale oscillations in the initial matter power spectrum (as arise in models involving collisional effects in the dark sector), while being largely insensitive to a truncation of initial power (as in warm dark matter models). For vanilla cold dark matter (CDM) cosmologies, the summary statistics display strong evolution and redshift-space effects, and are also sensitive to cosmological parameter values for realistic tracer samples. Comparing the VVF of galaxies in the Galaxies & Mass Assembly (GAMA) survey with that of abundance-matched CDM (sub)haloes tentatively reveals environmental effects in GAMA beyond halo mass (modulo unmodelled satellite properties). Our exploratory analysis thus paves the way for using the VVF as a new probe of galaxy evolution physics as well as the nature of dark matter and dark energy.

scholarly journals Deep learning for intensity mapping observations: component extraction

2020 ◽  
Vol 496 (1) ◽  
pp. L54-L58 ◽  
Author(s):  
Kana Moriwaki ◽  
Nina Filippova ◽  
Masato Shirasaki ◽  
Naoki Yoshida
Keyword(s):  
Deep Learning ◽  
Galaxy Formation ◽  
Large Scale ◽  
Generative Adversarial Networks ◽  
Intensity Mapping ◽  
Adversarial Networks ◽  
Galaxy Formation And Evolution ◽  
Formation And Evolution ◽  
Emission Line Galaxies ◽  
Two Populations

ABSTRACT Line intensity mapping (LIM) is an emerging observational method to study the large-scale structure of the Universe and its evolution. LIM does not resolve individual sources but probes the fluctuations of integrated line emissions. A serious limitation with LIM is that contributions of different emission lines from sources at different redshifts are all confused at an observed wavelength. We propose a deep learning application to solve this problem. We use conditional generative adversarial networks to extract designated information from LIM. We consider a simple case with two populations of emission-line galaxies; H $\rm \alpha$ emitting galaxies at $z$ = 1.3 are confused with [O iii] emitters at $z$ = 2.0 in a single observed waveband at 1.5 $\mu{\textrm m}$. Our networks trained with 30 000 mock observation maps are able to extract the total intensity and the spatial distribution of H $\rm \alpha$ emitting galaxies at $z$ = 1.3. The intensity peaks are successfully located with 74 per cent precision. The precision increases to 91 per cent when we combine five networks. The mean intensity and the power spectrum are reconstructed with an accuracy of ∼10 per cent. The extracted galaxy distributions at a wider range of redshift can be used for studies on cosmology and on galaxy formation and evolution.

scholarly journals Magnification and evolution biases in large-scale structure surveys

2021 ◽  
Vol 2021 (12) ◽  
pp. 009
Author(s):  
Roy Maartens ◽  
José Fonseca ◽  
Stefano Camera ◽  
Sheean Jolicoeur ◽  
Jan-Albert Viljoen ◽  
...  
Keyword(s):  
Luminosity Function ◽  
Large Scale ◽  
Near Infrared ◽  
Physical Change ◽  
Number Density ◽  
Galaxy Surveys ◽  
Intensity Mapping ◽  
The Galaxy ◽  
Infrared Wavelengths ◽  
Derivatives Of

Abstract Measurements of galaxy clustering in upcoming surveys such as those planned for the Euclid and Roman satellites, and the SKA Observatory, will be sensitive to distortions from lensing magnification and Doppler effects, beyond the standard redshift-space distortions. The amplitude of these contributions depends sensitively on magnification bias and evolution bias in the galaxy number density. Magnification bias quantifies the change in the observed number of galaxies gained or lost by lensing magnification, while evolution bias quantifies the physical change in the galaxy number density relative to the conserved case. These biases are given by derivatives of the number density, and consequently are very sensitive to the form of the luminosity function. We give a careful derivation of the magnification and evolution biases, clarifying a number of results in the literature. We then examine the biases for a variety of surveys, encompassing galaxy surveys and line intensity mapping at radio and optical/near-infrared wavelengths.

scholarly journals Cosmology with stacked cluster weak lensing and cluster–galaxy cross-correlations

2019 ◽  
Vol 491 (3) ◽  
pp. 3061-3081 ◽  
Author(s):  
Andrés N Salcedo ◽  
Benjamin D Wibking ◽  
David H Weinberg ◽  
Hao-Yi Wu ◽  
Douglas Ferrer ◽  
...  
Keyword(s):  
Large Scale ◽  
Cross Correlation ◽  
Nuisance Parameter ◽  
Mass Function ◽  
Weak Lensing ◽  
Small Scale ◽  
Density Parameter ◽  
Cluster Galaxy ◽  
Dark Energy Survey ◽  
Galaxy Population

ABSTRACT Cluster weak lensing is a sensitive probe of cosmology, particularly the amplitude of matter clustering σ8 and matter density parameter Ωm. The main nuisance parameter in a cluster weak lensing cosmological analysis is the scatter between the true halo mass and the relevant cluster observable, denoted $\sigma _{\ln M_\mathrm{ c}}$. We show that combining the cluster weak lensing observable ΔΣ with the projected cluster–galaxy cross-correlation function wp,cg and galaxy autocorrelation function wp,gg can break the degeneracy between σ8 and $\sigma _{\ln M_\mathrm{ c}}$ to achieve tight, per cent-level constraints on σ8. Using a grid of cosmological N-body simulations, we compute derivatives of ΔΣ, wp,cg, and wp,gg with respect to σ8, Ωm, $\sigma _{\ln M_\mathrm{ c}}$, and halo occupation distribution (HOD) parameters describing the galaxy population. We also compute covariance matrices motivated by the properties of the Dark Energy Survey cluster and weak lensing survey and the BOSS CMASS galaxy redshift survey. For our fiducial scenario combining ΔΣ, wp,cg, and wp,gg measured over 0.3−30.0 h−1 Mpc, for clusters at z = 0.35−0.55 above a mass threshold Mc ≈ 2 × 1014 h−1 M⊙, we forecast a $1.4{{\ \rm per\ cent}}$ constraint on σ8 while marginalizing over $\sigma _{\ln M_\mathrm{ c}}$ and all HOD parameters. Reducing the mass threshold to 1 × 1014 h−1 M⊙ and adding a z = 0.15−0.35 redshift bin sharpens this constraint to $0.8{{\ \rm per\ cent}}$. The small-scale (rp < 3.0 h−1 Mpc) ‘mass function’ and large-scale (rp > 3.0 h−1 Mpc) ‘halo-mass cross-correlation’ regimes of ΔΣ have comparable constraining power, allowing internal consistency tests from such an analysis.

scholarly journals Luminosity Bias. II. The Cosmic Web of the First Stars

2013 ◽  
Vol 30 ◽  
Author(s):  
R. Barkana
Keyword(s):  
Dark Matter ◽  
Galaxy Formation ◽  
Relative Velocity ◽  
Large Scale ◽  
Neutral Hydrogen ◽  
Unique Form ◽  
Velocity Difference ◽  
First Stars ◽  
Formation And Evolution ◽  
The Universe

AbstractUnderstanding the formation and evolution of the first stars and galaxies represents one of the most exciting frontiers in astronomy. Since the universe was filled with neutral hydrogen at early times, the most promising method for observing the epoch of the first stars is using the prominent 21-cm spectral line of the hydrogen atom. Current observational efforts are focused on the reionisation era (cosmic age t ~ 500 Myr), with earlier times considered much more challenging. However, the next frontier of even earlier galaxy formation (t ~ 200 Myr) is emerging as a promising observational target. This is made possible by a recently noticed effect of a significant relative velocity between the baryons and dark matter at early times. The velocity difference suppresses star formation, causing a unique form of early luminosity bias. The spatial variation of this suppression enhances large-scale clustering and produces a prominent cosmic web on 100 comoving Mpc scales in the 21-cm intensity distribution. This structure makes it much more feasible for radio astronomers to detect these early stars, and should drive a new focus on this era, which is rich with little-explored astrophysics.

scholarly journals The Evolution of Dispersion Spectra and the Evaluation of Model Differences in an Ensemble Estimation of Error Statistics for a Limited-Area Analysis

2006 ◽  
Vol 134 (11) ◽  
pp. 3456-3478 ◽  
Author(s):  
Simona Ecaterina Ştefănescu ◽  
Loïk Berre ◽  
Margarida Belo Pereira
Keyword(s):  
Large Scale ◽  
Model Error ◽  
Small Scale ◽  
Limited Area ◽  
Error Statistics ◽  
Model Framework ◽  
Cold Starting ◽  
Estimation Of Error ◽  
Ensemble Estimation ◽  
Perfect Model

Abstract An ensemble of limited-area forecasts has been obtained by integrating the Aire Limitée Adaptation Dynamique Développement International (ALADIN) limited-area model, in cold-starting mode, from an ensemble of Action de Recherche Petite Echelle Grande Echelle (ARPEGE) global analyses and forecasts. This permits error covariances of the ALADIN 6-h forecast and of the ARPEGE analysis to be estimated. These two fields may be combined in a future ALADIN analysis. The evolution of dispersion spectra is first studied in a perfect model framework. The ARPEGE analysis reduces the large-scale dispersion of the ARPEGE background by extracting some information from observations. Then, the digital filter initialization reduces the small-scale dispersion by removing the noise caused by interpolation of the ARPEGE analysis onto the ALADIN grid. Finally, the ALADIN 6-h forecast strongly increases the small-scale dispersion, in accordance with its ability to represent small-scale processes. Some model error contributions are then studied. The variances of the differences between the ALADIN and ARPEGE forecasts, which are started from the same ARPEGE analysis, are of smaller scale than are the ALADIN and ARPEGE perfect model dispersions. The small-scale part of these ARPEGE–ALADIN model differences is shown to correspond to structures that are represented by ALADIN and not by ARPEGE. Therefore, this part may be added to the ARPEGE analysis dispersion. The residual large-scale part is more ambiguous, but it may be added to the ALADIN dispersion; this may reflect some effects of the coupling inaccuracies, and strengthen (in a future ALADIN analysis) the use of the large-scale information from the ARPEGE analysis.

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