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Register a new userProbing Ultra-light Axion Dark Matter from 21cm Tomography using Convolutional Neural Networks
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We present forecasts on the detectability of Ultra-light axion-like particles (ULAP) from future 21cm radio observations around the epoch of reionization (EoR). We show that the axion as the dominant dark matter component has a significant impact on the reionization history due to the suppression of small scale density perturbations in the early universe. This behavior depends strongly on the mass of the axion particle. Using numerical simulations of the brightness temperature field of neutral hydrogen over a large redshift range, we construct a suite of training data. This data is used to train a convolutional neural network that can build a connection between the spatial structures of the brightness temperature field and the input axion mass directly. We construct mock observations of the future Square Kilometer Array survey, SKA1-Low, and find that even in the presence of realistic noise and resolution constraints, the network is still able to predict the input axion mass. We find that the axion mass can be recovered over a wide mass range with a precision of approximately 20%, and as the whole DM contribution, the axion can be detected using SKA1-Low at 68% if the axion mass is $M_X<1.86 times10^{-20}$eV although this can decrease to $M_X<5.25 times10^{-21}$eV if we relax our assumptions on the astrophysical modeling by treating those astrophysical parameters as nuisance parameters.
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If the symmetry breaking inducing the axion occurs after the inflation, the large axion isocurvature perturbations can arise due to a different axion amplitude in each causally disconnected patch. This causes the enhancement of the small-scale density fluctuations which can significantly affect the evolution of structure formation. The epoch of the small halo formation becomes earlier and we estimate the abundance of those minihalos which can host the neutral hydrogen atoms to result in the 21cm fluctuation signals. We find that the future radio telescopes, such as the SKA, can put the axion mass bound of order $m_a gtrsim 10^{-13}$ eV for the simple temperature-independent axion mass model, and the bound can be extended to of order $m_a gtrsim 10^{-8}$eV for a temperature-dependent axion mass.
Ultra-Light Axion-like Particle (ULAP) is motivated as one of the solutions to the small scale problems in astrophysics. When such a scalar particle oscillates with an $mathcal{O}(1)$ amplitude in a potential shallower than quadratic, it can form a localized dense object, oscillon. Because of its longevity due to the approximate conservation of the adiabatic invariant, it can survive up to the recent universe as redshift $z sim mathcal{O}(10)$. The scale affected by these oscillons is determined by the ULAP mass $m$ and detectable by observations of 21cm line. In this paper, we examine the possibility to detect ULAP by 21cm line and find that the oscillon can enhance the signals of 21cm line observations when $m lesssim 10^{-19} {rm eV}$ and the fraction of ULAP to dark matter is much larger than $10^{-2}$ depending on the form of the potential.
Ultra-light hidden-photon dark matter produces an oscillating electric field in the early Universe plasma, which in turn induces an electric current in its ionized component whose dissipation results in heat transfer from the dark matter to the plasma. This will affect the global 21cm signal from the Dark Ages and Cosmic Dawn. In this work we focus on the latter, in light of the reported detection by the EDGES collaboration of an absorption signal at frequencies corresponding to redshift z~17. By measuring the 21cm global signal, a limit can be placed on the amount of gas heating, and thus the kinetic mixing strength $varepsilon$ between the hidden and ordinary photons can be constrained. Our inferred 21cm bounds on $varepsilon$ in the mass range $10^{-23},{rm eV}lesssim m_chilesssim10^{-13},{rm eV}$ are the strongest to date.
The polarization of Cosmic Microwave Background (CMB) photons is rotated as they pass through (ultralight-) axion string loops. Studying this birefringence can reveal valuable information about the axion-photon coupling and the structure of the string network. We develop an approximate analytic formalism and identify a kernel function that can be used to calculate the two-point correlation function for CMB birefringence induced by an arbitrary axion string network. Using this formalism, we evaluate the birefringence signal for some simple loop distributions (including scaling and network collapse). We find that the angular correlation function has a characteristic angular scale set by $theta_mathrm{min}$, which corresponds to the angular extent of the loops at the time of recombination. This results in a peak in the birefringence power spectrum around $ell_p sim 1/theta_mathrm{min}$. An additional scale, controlled by the axions mass, is introduced if the network collapses before today.
Active Galactic Nuclei (AGN) and star-forming galaxies are leading candidates for being the luminous sources that reionized our Universe. Next-generation 21cm surveys are promising to break degeneracies between a broad range of reionization models, hence revealing the nature of the source population. While many current efforts are focused on a measurement of the 21cm power spectrum, some surveys will also image the 21cm field during reionization. This provides further information with which to determine the nature of reionizing sources. We create a Convolutional Neural Network (CNN) that is efficiently able to distinguish between 21cm maps that are produced by AGN versus galaxies scenarios with an accuracy of 92-100%, depending on redshift and neutral fraction range. An exception to this is when our Universe is highly ionized, since the source models give near-identical 21cm maps in that case. When adding thermal noise from typical 21cm experiments, the classification accuracy depends strongly on the effectiveness of foreground removal. Our results show that if foregrounds can be removed reasonably well, SKA, HERA and LOFAR should be able to discriminate between source models with greater accuracy at a fixed redshift. Only future SKA 21cm surveys are promising to break the degeneracies in the power spectral analysis.
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