Bertone, G., Bozorgnia, N., Kim, J. S., Liem, S., McCabe, C., Otten, S., et al. (2018). Identifying WIMP dark matter from particle and astroparticle data. J. Cosmol. Astropart. Phys., 03(3), 026–42pp.
Abstract: One of the most promising strategies to identify the nature of dark matter consists in the search for new particles at accelerators and with so-called direct detection experiments. Working within the framework of simplified models, and making use of machine learning tools to speed up statistical inference, we address the question of what we can learn about dark matter from a detection at the LHC and a forthcoming direct detection experiment. We show that with a combination of accelerator and direct detection data, it is possible to identify newly discovered particles as dark matter, by reconstructing their relic density assuming they are weakly interacting massive particles (WIMPs) thermally produced in the early Universe, and demonstrating that it is consistent with the measured dark matter abundance. An inconsistency between these two quantities would instead point either towards additional physics in the dark sector, or towards a non-standard cosmology, with a thermal history substantially different from that of the standard cosmological model.
|
de Salas, P. F., Gariazzo, S., Laveder, M., Pastor, S., Pisanti, O., & Truong, N. (2018). Cosmological bounds on neutrino statistics. J. Cosmol. Astropart. Phys., 03(3), 050–18pp.
Abstract: We consider the phenomenological implications of the violation of the Pauli exclusion principle for neutrinos, focusing on cosmological observables such as the spectrum of Cosmic Microwave Background anisotropies, Baryon Acoustic Oscillations and the primordial abundances of light elements. Neutrinos that behave (at least partly) as bosonic particles have a modified equilibrium distribution function that implies a different influence on the evolution of the Universe that, in the case of massive neutrinos, can not be simply parametrized by a change in the effective number of neutrinos. Our results show that, despite the precision of the available cosmological data, only very weak bounds can be obtained on neutrino statistics, disfavouring a more bosonic behaviour at less than 2 sigma.
|
Villanueva-Domingo, P., Gariazzo, S., Gnedin, N. Y., & Mena, O. (2018). Was there an early reionization component in our universe? J. Cosmol. Astropart. Phys., 04(4), 024–17pp.
Abstract: A deep understanding of the epoch of reionization is still missing in our knowledge of the universe. While future probes will allow us to test the precise evolution of the free electron fraction from redshifts between z similar or equal to 6 and z similar or equal to 20, at present one could ask what kind of reionization processes are allowed by present cosmic microwave background temperature and polarization measurements. An early contribution to reionization could imply a departure from the standard picture where star formation determines the reionization onset. By considering a broad class of possible reionization parameterizations, we find that current data do not require an early reionization component in our universe and that only one marginal class of models, based on a particular realization of reionization, may point to that. In addition, the frequentist Akaike information criterion (AIC) provides strong evidence against alternative reionization histories, favoring the most simple reionization scenario, which describes reionization by means of only one (constant) reionization optical depth tau.
|
Ramirez, H., Passaglia, S., Motohashi, H., Hu, W., & Mena, O. (2018). Reconciling tensor and scalar observables in G-inflation. J. Cosmol. Astropart. Phys., 04(4), 039–20pp.
Abstract: The simple m(2)phi(2) potential as an inflationary model is coming under increasing tension with limits on the tensor-to-scalar ratio r and measurements of the scalar spectral index n(s). Cubic Galileon interactions in the context of the Horndeski action can potentially reconcile the observables. However, we show that this cannot be achieved with only a constant Galileon mass scale because the interactions turn off too slowly, leading also to gradient instabilities after inflation ends. Allowing for a more rapid transition can reconcile the observables but moderately breaks the slow-roll approximation leading to a relatively large and negative running of the tilt alpha(s) that can be of order n(s) – 1. We show that the observables on CMB and large scale structure scales can be predicted accurately using the optimized slow-roll approach instead of the traditional slow-roll expansion. Upper limits on vertical bar alpha(s)vertical bar place a lower bound of r greater than or similar to 0.005 and, conversely, a given r places a lower bound on vertical bar alpha(s)vertical bar, both of which are potentially observable with next generation CMB and large scale structure surveys.
|
Caron, S., Gomez-Vargas, G. A., Hendriks, L., & Ruiz de Austri, R. (2018). Analyzing gamma rays of the Galactic Center with deep learning. J. Cosmol. Astropart. Phys., 05(5), 058–24pp.
Abstract: We present the application of convolutional neural networks to a particular problem in gamma ray astronomy. Explicitly, we use this method to investigate the origin of an excess emission of GeV gamma rays in the direction of the Galactic Center, reported by several groups by analyzing Fermi-LAT data. Interpretations of this excess include gamma rays created by the annihilation of dark matter particles and gamma rays originating from a collection of unresolved point sources, such as millisecond pulsars. We train and test convolutional neural networks with simulated Fermi-LAT images based on point and diffuse emission models of the Galactic Center tuned to measured gamma ray data. Our new method allows precise measurements of the contribution and properties of an unresolved population of gamma ray point sources in the interstellar diffuse emission model. The current model predicts the fraction of unresolved point sources with an error of up to 10% and this is expected to decrease with future work.
|
