1,721,078 research outputs found
The Cosmic 21-cm Revolution Charting the first billion years of our universe
Full text linkThe redshifted 21-cm signal is set to transform astrophysical cosmology, bringing a historically data-starved field into the era of Big Data. Corresponding to the spin-flip transition of neutral hydrogen, the 21-cm line is sensitive to the temperature and ionization state of the cosmic gas, as well as to cosmological parameters. Crucially, with the development of new interferometers it will allow us to map out the first billion years of our universe, enabling us to learn about the properties of the unseen first generations of galaxies. Rapid progress is being made on both the observational and theoretical fronts, and important decisions on techniques and future direction are being made. The Cosmic 21-cm Revolution gathers contributions from current leaders in this fast-moving field, providing both an overview for graduate students and a reference point for current researchers
The spin-temperature dependence of the 21-cm-LAE cross-correlation
Full text linkCross-correlating 21 cm with known cosmic signals will be invaluable proof of the cosmic origin of the first 21-cm detections. As some of the widest fields available, comprising thousands of sources with reasonably known redshifts, narrow-band Lyman-α emitter (LAE) surveys are an obvious choice for such cross-correlation. Here, we revisit the 21-cm-LAE cross-correlation, relaxing the common assumption of reionization occurring in a pre-heated intergalactic medium (IGM). Using specifications from the Square Kilometre Array and the Subaru Hyper Supreme-Cam, we present new forecasts of the 21-cm-LAE cross-correlation function at z ∼7. We sample a broad parameter space of the mean IGM neutral fraction and spin temperature, (\barx-H small I,\barT-S). The sign of the cross-correlation roughly follows the sign of the 21-cm signal: Ionized regions that surround LAEs correspond to relative hot spots in the 21-cm signal when the neutral IGM is colder than the CMB, and relative cold spots when the neutral IGM is hotter than the CMB. The amplitude of the cross-correlation function generally increases with increasing\barx-H small I, following the increasing bias of the cosmic H ii regions. As is the case for 21 cm, the strongest cross signal occurs when the IGM is colder than the CMB, providing a large contrast between the neutral regions and the ionized regions, which host LAEs. We also vary the topology of reionization and the epoch of X-ray heating. The cross-correlation during the first half of reionization is sensitive to these topologies, and could thus be used to constrain them
Minimum size of 21-cm simulations
Full text linkCosmic 21cm interferometry is set to revolutionize our understanding of the Epoch of Reionization (EoR) and the Cosmic Dawn (CD). However, the signal has structure on a huge range of scales, requiring large simulation boxes to statistically capture the relevant fields. In this work, we quantify the minimum box size for simulating the power spectrum (PS) of the 21cm signal. We perform multiple realizations of the initial conditions, for a range of box sizes. We quantify convergence with respect to a simulation that is 1.1 Gpc on a side, with thermal noise computed for a 1000 h integration with SKA1-low. We find that simulations of box lengths 200–300 Mpc underestimate the large-scale power during the CD by ∼7–9 per cent on average. We conclude that box lengths of L ≳ 250 Mpc are needed to converge at the level of ≲1σ of the total noise
Constraints on warm dark matter from UV luminosity functions of high-z galaxies with Bayesian model comparison
Full text linkThe number density of small dark matter (DM) haloes hosting faint high-redshift galaxies is sensitive to the DM free-streaming properties. However, constraining these DM properties is complicated by degeneracies with the uncertain baryonic physics governing star formation. In this work, we use a flexible astrophysical model and a Bayesian inference framework to analyse ultraviolet (UV) luminosity functions (LFs) at z = 6-8. We vary the complexity of the astrophysical galaxy model (single versus double power law for the stellar-halo mass relation) as well as the matter power spectrum [cold DM versus thermal relic warm DM (WDM)], comparing their Bayesian evidences. Adopting a conservatively wide prior range for the WDM particle mass, we show that the UV LFs at z = 6-8 only weakly favour cold DM over WDM. We find that particle masses of ≤ 2 keV are rejected at a 95 per cent credible level in all models that have a WDM-like power spectrum cutoff. This bound should increase to ∼2.5 keV with the James Webb Space Telescope (JWST)
Combining high-z galaxy luminosity functions with Bayesian evidence
Full text linkGalaxy formation during the first billion years of our Universe remains a challenging problem at the forefront of astrophysical cosmology. Although these z ≧ 6 galaxies are likely responsible for the last major phase change of our Universe, the epoch of reionization (EoR), detailed studies are possible only for relatively rare, bright objects. Characterizing the fainter galaxies that are more representative of the population as a whole is currently done mainly through their non-ionizing UV luminosity function (LF). Observing the faint end of the UV LFs is nevertheless challenging, and current estimates can differ by orders of magnitude. Here we propose a methodology to combine disparate high-z UV LF estimates in a Bayesian framework: Bayesian Data-analysis Averaging (BDA). Using a flexible, physically motivated galaxy model, we compute the relative evidence of various z = 6 UV LFs within the magnitude range -20 ≤ MUV ≤ -15 which is common to the data sets. Our model, based primarily on power-law scalings of the halo mass function, naturally penalizes systematically jagged points as well as misestimated errors. We then use the relative evidence to weigh the posteriors obtained from disparate LF data sets during the EoR, 6 ≤ z ≤ 10. The resulting LF posteriors suggest that the star formation rate density (SFRD) integrated down to a UV magnitude of - 17 represent 60.9-09.6+11.3 per cent / 28.2-10.1+9.3 per cent / 5.7-4.7+4.5 per cent of the total SFRD at redshifts 6 / 10 / 15. The BDA framework we introduce enables galaxy models to leverage multiple, analogous LF estimates when constraining their free parameters
Machine learning astrophysics from 21 cm lightcones: Impact of network architectures and signal contamination
Full text linkImaging the cosmic 21 cm signal will map out the first billion years of our Universe. The resulting 3D lightcone (LC) will encode the properties of the unseen first galaxies and physical cosmology. Here, we build on previous work using neural networks (NNs) to infer astrophysical parameters directly from 21 cm LC images. We introduce recurrent neural networks (RNNs), capable of efficiently characterizing the evolution along the redshift axis of 21 cm LC images. Using a large database of simulated cosmic 21 cm LCs, we compare the relative performance in parameter estimation of different network architectures. These including two types of RNNs, which differ in their complexity, as well as a more traditional convolutional neural network (CNN). For the ideal case of no instrumental effects, our simplest and easiest to train RNN performs the best, with a mean squared parameter estimation error (MSE) that is lower by a factor of 2 compared with the other architectures studied here, and a factor of 8 lower than the previously-studied CNN. We also corrupt the cosmic signal by adding noise expected from a 1000 h integration with the Square Kilometre Array, as well as excising a foreground-contaminated 'horizon wedge'. Parameter prediction errors increase when the NNs are trained on these contaminated LC images, though recovery is still good even in the most pessimistic case (with R2 0.5-0.95). However, we find no notable differences in performance between network architectures on the contaminated images. We argue this is due to the size of our data set, highlighting the need for larger data sets and/or better data augmentation in order to maximize the potential of NNs in 21 cm parameter estimation
Hydrodynamic Response of the Intergalactic Medium to Reionization
Full text linkThe intergalactic medium is expected to clump on scales down to 104 V108 Me before the onset of reionization. The impact of these small-scale structures on reionization is poorly understood despite the modern understanding that gas clumpiness limits the growth of H II regions. We use a suite of radiation-hydrodynamics simulations that capture the ~104M Jeans mass of unheated gas to study density fluctuations during reionization. Our simulations track the complex ionization and hydrodynamical response of gas in the wake of ionization fronts. The clumping factor of ionized gas (proportional to the recombination rate) rises to a peak value of 5 V20 approximately ?t= 10 Myr after ionization front passage, depending on the incident intensity, redshift, and degree to which the gas had been preheated by the first X-ray sources. The clumping factor reaches its relaxed value of .3 by ?t=300 Myr. The mean free path of Lyman-limit photons evolves in unison, being up to several times shorter in unrelaxed, recently reionized regions compared to those that were reionized much earlier. Assessing the impact of this response on the global reionization process, we find that unrelaxed gaseous structures boost the total number of recombinations by .50% and lead to spatial fluctuations in the mean free path that persist appreciably for several hundred million years after the completion of reionization
Reionization and galaxy inference from the high-redshift Ly α forest
Full text linkThe transmission of Lyman α (Ly α) in the spectra of distant quasars depends on the density, temperature, and ionization state of the intergalactic medium. Therefore, high-redshift (z > 5) Ly α forests could be invaluable in studying the late stages of the epoch of reionization (EoR), as well as properties of the sources that drive it. Indeed, high-quality quasar spectra have now firmly established the existence of large-scale opacity fluctuations at z > 5, whose physical origins are still debated. Here, we introduce a Bayesian framework capable of constraining the EoR and galaxy properties by forward-modelling the high-z Ly α forest. Using priors from galaxy and cosmic microwave background observations, we demonstrate that the final overlap stages of the EoR (when >95 per cent of the volume was ionized) should occur at z < 5.6, in order to reproduce the large-scale opacity fluctuations seen in forest spectra. However, it is the combination of patchy reionization and the inhomogeneous ultraviolet background that produces the longest Gunn-Peterson troughs. Ly α forest observations tighten existing constraints on the characteristic ionizing escape fraction of galaxies, with the combined observations suggesting fesc ≈ 7+4-3} per cent, and disfavouring a strong evolution with the galaxy's halo (or stellar) mass
- …
