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Register a new userCosmic antiprotons as a probe for supersymmetric dark matter?
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The flux of cosmic ray antiprotons from neutralino annihilations in the galactic halo is computed for a large sample of models in the MSSM (the Minimal Supersymmetric extension of the Standard Model). We also revisit the problem of estimating the background of low-energy cosmic ray induced secondary antiprotons, taking into account their subsequent interactions (and energy loss) and the presence of nuclei in the interstellar matter. We consider a two-zone diffusion model, with and without a galactic wind. We find that, given the uncertainties in the background predictions, there is no need for a primary (exotic) component to explain present data. However, allowing for a signal by playing with the uncertainties in the background estimate, we discuss the characteristic features of the supersymmetric models which give a satisfactory description of the data. We point out that in some cases the optimal kinetic energy to search for a signal from supersymmetric dark matter is above several GeV, rather than the traditional sub-GeV region. The large astrophysical uncertainties involved do not, one the other hand, allow the exclusion of any of the MSSM models we consider, on the basis of data. We present besides numerical results also convenient parameterizations of the antiproton yields of all `basic two-body final states. We also give examples of the yield and differential energy spectrum for a set of supersymmetric models with high rates. We also remark that it is difficult to put a limit on the antiproton lifetime from present measurements, since the injection of antiprotons from neutralino annihilation can compensate the loss from decay.
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Cosmic-ray antiprotons are a powerful tool for astroparticle physics. While the bulk of measured antiprotons is consistent with a secondary origin, the precise data of the AMS-02 experiment provides us with encouraging prospects to search for a subdominant primary component, e.g. from dark matter. In this brief review, we discuss recent limits on heavy dark matter as well as a tentative signal from annihilation of dark matter with a mass $lesssim 100$ GeV. We emphasize the special role of systematic errors that can affect the signal. In particular, we discuss recent progress in the modeling of secondary production cross sections and correlated errors in the AMS-02 data, the dominant ones originating from uncertainties in the cross sections for cosmic-ray absorption in the detector.
Global fits of primary and secondary cosmic-ray (CR) fluxes measured by AMS-02 have great potential to study CR propagation models and search for exotic sources of antimatter such as annihilating dark matter (DM). Previous studies of AMS-02 antiprotons revealed a possible hint for a DM signal which, however, could be affected by systematic uncertainties. To test the robustness of such a DM signal, in this work we systematically study two important sources of uncertainties: the antiproton production cross sections needed to calculate the source spectra of secondary antiprotons and the potential correlations in the experimental data, so far not provided by the AMS-02 Collaboration. To investigate the impact of cross-section uncertainties we perform global fits of CR spectra including a covariance matrix determined from nuclear cross-section measurements. As an alternative approach, we perform a joint fit to both the CR and cross-section data. The two methods agree and show that cross-section uncertainties have a small effect on the CR fits and on the significance of a potential DM signal, which we find to be at the level of $3sigma$. Correlations in the data can have a much larger impact. To illustrate this effect, we determine possible benchmark models for the correlations in a data-driven method. The inclusion of correlations strongly improves the constraints on the propagation model and, furthermore, enhances the significance of the DM signal up to above $5sigma$. Our analysis demonstrates the importance of providing the covariance of the experimental data, which is needed to fully exploit their potential.
Terascale supersymmetry has the potential to provide a natural explanation of the dominant dark matter component of the standard lambda-CDM cosmology. However once we impose the constraints on minimal supersymmetry parameters from current particle physics data, a satisfactory dark matter abundance is no longer prima facie natural. This Neutralino Tuning Problem could be a hint of nonstandard cosmology during and/or after the Terascale era. To quantify this possibility, we introduce an alternative cosmological benchmark based upon a simple model of quintessential inflation. This benchmark has no free parameters, so for a given supersymmetry model it allows an unambiguous prediction of the dark matter relic density. As a example, we scan over the parameter space of the CMSSM, comparing the neutralino relic density predictions with the bounds from WMAP. We find that the WMAP--allowed regions of the CMSSM are an order of magnitude larger if we use the alternative cosmological benchmark, as opposed to lambda-CDM. Initial results from the CERN Large Hadron Collider will distinguish between the two allowed regions.
Antiprotons are regarded as a powerful probe for Dark Matter (DM) indirect detection and indeed current data from PAMELA have been shown to lead to stringent constraints. However, in order to exploit their constraining/discovery power properly, great attention must be put into effects (linked to their propagation in the Galaxy) which may be perceived as subleading but actually prove to be quite relevant. We revisit the computation of the astrophysical background and of the DM antiproton fluxes fully including the effects of: diffusive reacceleration, energy losses including tertiary component and solar modulation (in a force field approximation). Using the updated proton and helium fluxes just released by the AMS experiment we reevaluate the secondary astrophysical antiproton to proton ratio and its uncertainties, and compare it with the ratio preliminarly reported by AMS. We find no unambiguous evidence for a significant excess with respect to expectations. Yet, some preference for a flatter energy dependence of the diffusion coefficient (with respect to the {sc Med} benchmark often used in the literature) starts to emerge. Finally, we provide a first assessment of the room left for exotic components such as Galactic Dark Matter annihilation, deriving new stringent constraints.
The interpretation of data from indirect detection experiments searching for dark matter annihilations requires computationally expensive simulations of cosmic-ray propagation. In this work we present a new method based on Recurrent Neural Networks that significantly accelerates simulations of secondary and dark matter Galactic cosmic ray antiprotons while achieving excellent accuracy. This approach allows for an efficient profiling or marginalisation over the nuisance parameters of a cosmic ray propagation model in order to perform parameter scans for a wide range of dark matter models. We identify importance sampling as particularly suitable for ensuring that the network is only evaluated in well-trained parameter regions. We present resulting constraints using the most recent AMS-02 antiproton data on several models of Weakly Interacting Massive Particles. The fully trained networks are released as DarkRayNet together with this work and achieve a speed-up of the runtime by at least two orders of magnitude compared to conventional approaches.
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