Warm Dark Matter and Cosmic Reionization

Villanueva-Domingo, Pablo; Gnedin, Nickolay Y.; Mena, Olga

doi:10.3847/1538-4357/aa9ff5

Cited by 33 publications

(32 citation statements)

References 81 publications

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“…Previous works have studied the effect of non-CDM models on the 21-cm signal [22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39]. Those models typically suppress the matter power spectrum beyond some wavenumber k, delaying the onset of cosmic dawn.…”

Section: Introductionmentioning

confidence: 99%

Probing the small-scale matter power spectrum with large-scale 21-cm data

2020

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The distribution of matter fluctuations in our universe is key for understanding the nature of dark matter and the physics of the early cosmos. Different observables have been able to map this distribution at large scales, corresponding to wavenumbers k 10 Mpc −1 , but smaller scales remain much less constrained. In this work we study the sensitivity of upcoming measurements of the 21-cm line of neutral hydrogen to the small-scale matter power spectrum. The 21-cm line is a promising tracer of early stellar formation, which took place in small haloes (with masses M ∼ 10 6 − 10 8 M ), formed out of matter overdensities with wavenumbers as large as k ≈ 100 Mpc −1 . Here we forecast how well both the 21-cm global signal, and its fluctuations, could probe the matter power spectrum during cosmic dawn (z = 12−25). In both cases we find that the long-wavelength modes (with k 40 Mpc −1 ) are highly degenerate with astrophysical parameters, whereas the modes with k = (40 − 80) Mpc −1 are more readily observable. This is further illustrated in terms of the principal components of the matter power spectrum, which peak at k ∼ 50 Mpc −1 both for a typical experiment measuring the 21-cm global signal and its fluctuations. We find that, imposing broad priors on astrophysical parameters, a global-signal experiment can measure the amplitude of the matter power spectrum integrated over k = (40−80) Mpc −1 with a precision of tens of percent. A fluctuation experiment, on the other hand, can constrain the power spectrum to a similar accuracy over both the k = (40 − 60) Mpc −1 and (60 − 80) Mpc −1 ranges even without astrophysical priors. The constraints outlined in this work would be able to test the behavior of dark matter at the smallest scales yet measured, for instance probing warm-dark matter masses up to mWDM = 8 keV for the global signal and 14 keV for the 21-cm fluctuations. This could shed light on the nature of dark matter beyond the reach of other cosmic probes.

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Section: Introductionmentioning

confidence: 99%

Probing the small-scale matter power spectrum with large-scale 21-cm data

2020

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“…WDM predicts fewer low-mass galaxies than CDM, with a larger difference at high redshift. For our choice of warm candidate mass (3 keV), the relative difference between CDM and WDM is only a factor of a few stellar masses around 10 6 M (see also Villanueva-Domingo et al 2018), below what is currently observable (Bouwens et al 2015(Bouwens et al , 2017Ceverino et al 2017). On the other hand, our results are in agreement with Corasaniti et al (2017), who found a lower limit of 2 keV from analysis of the luminosity function.…”

Section: Stellar Mass Functionmentioning

confidence: 94%

“…Future observations and facilities might improve this limit (e.g. JWST ), but then a very careful understanding of the baryonic physics implemented in the simulations will be needed, as discussed in Villanueva-Domingo et al (2018).…”

Section: Stellar Mass Functionmentioning

confidence: 99%

“…Two studies employing semi-analytic methods to study WDM in the context of high redshift and reionization also find that with a dark matter scenario consistent with observational constraints the ionizing population is shifted to lower halo masses, but that distinguishing CDM and WDM with current observations would be difficult (Bose et al 2016;Dayal et al 2017). Furthermore, Villanueva-Domingo et al (2018) have used hydrodynamical simulations in a box of 20 h −1 Mpc to derive constraints on WDM from galaxy luminosity functions, the ionization history, and the Gunn-Peterson effect. They have concluded that while some effects are indeed present, until the modelling of baryonic effects (star formation and feedback mainly) are constrained better, any conclusions on the nature of dark matter derived from reionization observables remain model-dependent.…”

Section: Introductionmentioning

confidence: 99%

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Clues to the nature of dark matter from first galaxies

Stoychev

Dixon

Macciò

et al. 2019

Monthly Notices of the Royal Astronomical Society

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We use thirty-eight high-resolution simulations of galaxy formation between redshift 10 and 5 to study the impact of a 3 keV warm dark matter (WDM) candidate on the high-redshift Universe. We focus our attention on the stellar mass function and the global star formation rate and consider the consequences for reionization, namely the neutral hydrogen fraction evolution and the electron scattering optical depth. We find that three different effects contribute to differentiate warm and cold dark matter (CDM) predictions: WDM suppresses the number of haloes with mass less than few 10 9 M ; at a fixed halo mass, WDM produces fewer stars than CDM; and finally at halo masses below 10 9 M , WDM has a larger fraction of dark haloes than CDM post-reionization. These three effects combine to produce a lower stellar mass function in WDM for galaxies with stellar masses at and below 10 7 M . For z > 7, the global star formation density is lower by a factor of two in the WDM scenario, and for a fixed escape fraction, the fraction of neutral hydrogen is higher by 0.3 at z ∼ 6. This latter quantity can be partially reconciled with CDM and observations only by increasing the escape fraction from 23 per cent to 34 per cent. Overall, our study shows that galaxy formation simulations at high redshift are a key tool to differentiate between dark matter candidates given a model for baryonic physics.

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“…We also refer readers to Ref. [165][166][167][168][169][170][171][172][173][174][175][176][177][178][179] for hydrodynamical simulation results differentiating WDM and CDM in galaxy formation. We estimate the observed number of satellites above M = 10 8 h −1 M as N obs sat = 63 (11 classical dwarf galaxies and 3.5 × 15 ultra-faint dwarf galaxies).…”

Section: )mentioning

confidence: 99%

Fingerprint matching of beyond-WIMP dark matter: neural network approach

Bae

Jinno

Kamada

et al. 2020

J. Cosmol. Astropart. Phys.

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Galactic-scale structure is of particular interest since it provides important clues to dark matter properties and its observation is improving. Weakly interacting massive particles (WIMPs) behave as cold dark matter on galactic scales, while beyond-WIMP candidates suppress galactic-scale structure formation. Suppression in the linear matter power spectrum has been conventionally characterized by a single parameter, the thermal warm dark matter mass. On the other hand, the shape of suppression depends on the underlying mechanism. It is necessary to introduce multiple parameters to cover a wide range of beyond-WIMP models. Once multiple parameters are introduced, it becomes harder to share results from one side to the other. In this work, we propose adopting neural network technique to facilitate the communication between the two sides. To demonstrate how to work out in a concrete manner, we consider a simplified model of light feebly interacting massive particles. ♦1 We refer readers to Ref. [10] for a recent review of gravitational probes of DM properties. ♦2 Prominent examples are the missing satellite problem [13][14][15][16][17], core-cusp problem [18][19][20][21], and toobig-to-fail problem [22][23][24][25][26][27]. We refer readers to Ref.[28] for a recent review and further details. Stateof-the-art hydrodynamical simulations have been demonstrating that astrophysical processes also play an important role [29][30][31][32][33][34][35][36][37][38][39][40][41][42][43][44][45][46]. There have also been reports that small-scale issues persist even in state-of-the-art hydrodynamical simulations [47][48][49][50][51][52][53][54][55]. To our best knowledge, it is still controversial if astrophysical processes fully resolve the small-scale issues.One can work out each step independently by parametrizing the linear matter power spectrum. See the red flow in Fig. 1. A single parameter has been adopted conventionally: the thermal WDM mass m WDM . ♦3 On the other hand, a single parameter is not enough to cover a wide range of beyond-WIMP scenarios. For this purpose, Ref.[88] introduces the 3parameter ({α, β, γ}) characterization of the linear matter power spectrum. On one side, one (likely particle physicist) can construct a map of model parameters onto {α, β, γ}. On the other side, one (likely astrophysicist) can provide observational constraints on {α, β, γ}, as indeed done for the Lyman-α forest data in Ref. [89]. By combining results from the two sides, one can obtain observational constraints on a given beyond-WIMP scenario. Nevertheless, once multiple parameters are introduced, it becomes hard to share results from one side to the other.In this respect, we propose building ready-to-use networks: one maps model parameters onto {α, β, γ}; and another maps {α, β, γ} onto observables. One can use these networks to examine models without repeating the aforementioned time-consuming procedure. Ideally, it would be the most efficient if one obtained analytic maps, but in reality, it is hard to establish such analytic maps....

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Warm Dark Matter and Cosmic Reionization

Cited by 33 publications

References 81 publications

Probing the small-scale matter power spectrum with large-scale 21-cm data

Probing the small-scale matter power spectrum with large-scale 21-cm data

Clues to the nature of dark matter from first galaxies

Fingerprint matching of beyond-WIMP dark matter: neural network approach

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