Seeking particle dark matter in the TeV sky

Under the assumption that dark matter is made of new particles, annihilations of those are required to reproduce the correct dark matter abundance in the Universe. This process can occur in dense regions of our Galaxy such as the Galactic center, dwarf galaxies and other types of sub-haloes. High-energy gamma-rays are expected to be produced in dark matter particle collisions and could be detected by ground-based Cherenkov telescopes such as HESS, MAGIC and VERITAS. The main experimental challenges to get constraints on particle dark matter models are reviewed, making explicit the pros and cons that are inherent to this technique, together with the current results from running observatories. Main results concerning dark matter searches towards selected targets with Cherenkov telescopes are presented. Eventually, a focus is made on a new way to perform a search for Galactic subhaloes with such telescopes, based on wide-field surveys, as well as future prospects.Comment: 12 pages, 10 figures. To appear in the proceedings of the eleventh international symposium Frontiers of Fundamental Physic

On the Dark Matter Solutions to the Cosmic Ray Lepton Puzzle

Recent measurements of cosmic ray leptons by PAMELA, ATIC, HESS and Fermi revealed interesting excesses. Many authors suggested particle Dark Matter (DM) annihilations could be at the origin of these effects. In this paper, we critically assess this interpretation by reviewing some results questioning the naturalness and robustness of such an interpretation. Natural values for the DM particle parameters lead to a poor leptons production so that models often require signal enhancement effects that we constrain here. Considering DM annihilations are likely to produce antiprotons as well, we use the PAMELA antiproton to proton ratio measurements to constrain a possible exotic contribution. We also consider the possibility of an enhancement due to a nearby clump of DM. This scenario appears unlikely when compared to the state-of-the-art cosmological N-body simulations. We conclude that the bulk of the observed signals most likely has no link with DM and is rather a new, yet unconsidered source of background for searches in these channels.Comment: 8 pages, Proceedings of the Invisible Universe International Conference 2009, Pari

Decoherence and quantum trajectories

Decoherence is the process by which quantum systems interact and become correlated with their external environments; quantum trajectories are a powerful technique by which decohering systems can be resolved into stochastic evolutions, conditioned on different possible ``measurements'' of the environment. By calling on recently-developed tools from quantum information theory, we can analyze simplified models of decoherence, explicitly quantifying the flow of information and randomness between the system, the environment, and potential observers.Comment: 14 pages, Springer LNP LaTeX macros, 1 figure in encapsulated postscript format. To appear in proceedings of DICE 200

Cycle Connectivity and Automorphism Groups of Flag Domains

A flag domain $D$ is an open orbit of a real form $G_0$ in a flag manifold $Z=G/P$ of its complexification. If $D$ is holomorphically convex, then, since it is a product of a Hermitian symmetric space of bounded type and a compact flag manifold, ${Aut}(D)$ is easily described. If $D$ is not holomorphically convex, then in our previous work (American J. Math, 136, Nr.2 (2013) 291-310 (arXiv: 1003.5974)) it was shown that ${Aut}(D)$ is a Lie group whose connected component at the identity agrees with $G_0$ except possibly in situations which arise in Onishchik's list of flag manifolds where ${Aut}(Z)^0$ is larger than $G$. These exceptions are handled in detail here. In addition substantially simpler proofs of some of our previous work are given.Comment: To appear in Birkh\"auser Progress Reports "Current Developments and Retrospectives in Lie Theor

Spectral mixture analysis of EELS spectrum-images

Recent advances in detectors and computer science have enabled the acquisition and the processing of multidimensional datasets, in particular in the field of spectral imaging. Benefiting from these new developments, earth scientists try to recover the reflectance spectra of macroscopic materials (e.g., water, grass, mineral types...) present in an observed scene and to estimate their respective proportions in each mixed pixel of the acquired image. This task is usually referred to as spectral mixture analysis or spectral unmixing (SU). SU aims at decomposing the measured pixel spectrum into a collection of constituent spectra, called endmembers, and a set of corresponding fractions (abundances) that indicate the proportion of each endmember present in the pixel. Similarly, when processing spectrum-images, microscopists usually try to map elemental, physical and chemical state information of a given material. This paper reports how a SU algorithm dedicated to remote sensing hyperspectral images can be successfully applied to analyze spectrum-image resulting from electron energy-loss spectroscopy (EELS). SU generally overcomes standard limitations inherent to other multivariate statistical analysis methods, such as principal component analysis (PCA) or independent component analysis (ICA), that have been previously used to analyze EELS maps. Indeed, ICA and PCA may perform poorly for linear spectral mixture analysis due to the strong dependence between the abundances of the different materials. One example is presented here to demonstrate the potential of this technique for EELS analysis.Comment: Manuscript accepted for publication in Ultramicroscop