A deep survey of the Large Magellanic Cloud at ∼ 0.1−100 TeV photon energies with the Cherenkov Telescope Array is planned. We assess the detection prospects based on a model for the emission of the galaxy, comprising the four known TeV emitters, mock populations of sources, and interstellar emission on galactic scales. We also assess the detectability of 30 Doradus and SN 1987A, and the constraints that can be derived on the nature of dark matter. The survey will allow for fine spectral studies of N 157B, N 132D, LMC P3, and 30 Doradus C, and half a dozen other sources should be revealed, mainly pulsar-powered objects. The remnant from SN 1987A could be detected if it produces cosmic-ray nuclei with a flat power-law spectrum at high energies, or with a steeper index 2.3 − 2.4 pending a flux increase by a factor > 3 − 4 over ∼ 2015 − 2035. Large-scale interstellar emission remains mostly out of reach of the survey if its > 10 GeV spectrum has a soft photon index ∼ 2.7, but degree-scale 0.1 − 10 TeV pion-decay emission could be detected if the cosmic-ray spectrum hardens above >100 GeV. The 30 Doradus star-forming region is detectable if acceleration efficiency is on the order of 1 − 10% of the mechanical luminosity and diffusion is suppressed by two orders of magnitude within < 100 pc. Finally, the survey could probe the canonical velocity-averaged cross section for self-annihilation of weakly interacting massive particles for cuspy Navarro-Frenk-White profiles.

The dynamics of expansion and large scale structure formation of the Universe are analyzed for models with dark energy in the form of a phantom scalar field which initially mimics a Λ-term and evolves slowly to the Big Rip singularity. The discussed model of dark energy has three parametersthe density and the equation of state parameter at the current epoch, Ω de and w0, and the asymptotic value of the equation of state parameter at a → ∞, c 2 a . Their best-fit values are determined jointly with all other cosmological parameters by the MCMC method using observational data on CMB anisotropies and polarization, SNe Ia luminosity distances, BAO measurements and more. Similar computations are carried out for ΛCDM and a quintessence scalar field model of dark energy. It is shown that the current data slightly prefer the phantom model, but the differences in the maximum likelihoods are not statistically significant. It is also shown that the phantom dark energy with monotonically increasing density in future will cause the decay of large scale linear matter density perturbations due to the gravitational domination of dark energy perturbations long before the Big Rip singularity.PACS numbers: 95.36.+x, 98.80.-k

The dynamics of expansion and large scale structure formation in the multicomponent Universe with dark energy modeled by the minimally coupled scalar field with generalized linear barotropic equation of state (EoS) are analyzed. It is shown that the past dynamics of expansion and future of the Universe -eternal accelerated expansion or turnaround and collapse -are completely defined by the current energy density of a scalar field and relation between its current and early EoS parameters. The clustering properties of such models of dark energy and their imprints in the power spectrum of matter density perturbations depend on the same relation and, additionally, on the "effective sound speed" of a scalar field, defined by its Lagrangian. It is concluded that such scalar fields with different values of these parameters are distinguishable in principle. This gives the possibility to constrain them by confronting the theoretical predictions with the corresponding observational data. For that we have used the 7-year WMAP data on CMB anisotropies, the Union2 dataset on Supernovae Ia and SDSS DR7 data on luminous red galaxies (LRG) space distribution. Using the Markov Chain Monte Carlo technique the marginalized posterior and mean likelihood distributions are computed for the scalar fields with two different Lagrangians: Klein-Gordon and Dirac-Born-Infeld ones. The properties of such scalar field models of dark energy with best fitting parameters and uncertainties of their determination are also analyzed in the paper. PACS numbers: 95.36.+x, 98.80.-k Keywords: cosmology: dark energy-scalar field-cosmic microwave background-large scale structure of Universe-cosmological parameters

AM CVn binaries consist of a WD accreting from a hydrogen-deficient star (or WD) companion (Warner, 1995;Solheim, 2010). In their formation history (Fig. 1.6 and Section 1.3.1.1), AM CVns form after at least one CE phase of their progenitor system. The current RLO is initiated, due to orbital damping caused by GW radiation, at orbital periods of typically 5−20 min (depending on the nature and the temperature of the companion star), and the mass-transfer rate is determined

We determine the best-fit values and confidence limits for dynamical dark energy parameters together with other cosmological parameters on the basis of different datasets which include WMAP9 or Planck-2013 results on CMB anisotropy, BAO distance ratios from recent galaxy surveys, magnitude-redshift relations for distant SNe Ia from SNLS3 and Union2.1 samples and the HST determination of the Hubble constant. We use a Markov Chain Monte Carlo routine to map out the likelihood in the multi-dimensional parameter space. We show that the most precise determination of cosmological parameters with the narrowest confidence limits is obtained for the Planck+HST+BAO+SNLS3 dataset. The best-fit values and 2σ confidence limits for cosmological parameters in this case are Ω de = 0.718 ± 0.022, w 0 = −1.15 +0.14 −0.16 , c 2 a = −1.15 +0.02 −0.46 , Ω b h 2 = 0.0220 ± 0.0005, Ω cdm h 2 = 0.121 ± 0.004, h = 0.713 ± 0.027, n s = 0.958 +0.014 −0.010 , A s = (2.215 +0.093 −0.101 ) cdot10 −9 , τ rei = 0.093 +0.022 −0.028 . For this dataset, the ΛCDM model is just outside the 2σ confidence region, while for the dataset WMAP9+HST+BAO+SNLS3 the ΛCDM model is only 1σ away from the best fit. The tension in the determination of some cosmological parameters on the basis of two CMB datasets WMAP9 and Planck-2013 is highlighted.