6,266 research outputs found

    Pressures for Asymptotically Sub-additive Potentials Under a Mistake Function

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    This paper defines the pressure for asymptotically subadditive potentials under a mistake function, including the measuretheoretical and the topological versions. Using the advanced techniques of ergodic theory and topological dynamics, we reveals a variational principle for the new defined topological pressure without any additional conditions on the potentials and the compact metric space.Comment: 13page

    Image Forgery Localization Based on Multi-Scale Convolutional Neural Networks

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    In this paper, we propose to utilize Convolutional Neural Networks (CNNs) and the segmentation-based multi-scale analysis to locate tampered areas in digital images. First, to deal with color input sliding windows of different scales, a unified CNN architecture is designed. Then, we elaborately design the training procedures of CNNs on sampled training patches. With a set of robust multi-scale tampering detectors based on CNNs, complementary tampering possibility maps can be generated. Last but not least, a segmentation-based method is proposed to fuse the maps and generate the final decision map. By exploiting the benefits of both the small-scale and large-scale analyses, the segmentation-based multi-scale analysis can lead to a performance leap in forgery localization of CNNs. Numerous experiments are conducted to demonstrate the effectiveness and efficiency of our method.Comment: 7 pages, 6 figure

    Assessing the effect of lens mass model in cosmological application with updated galaxy-scale strong gravitational lensing sample

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    By comparing the dynamical and lensing masses of early-type lens galaxies, one can constrain both the cosmological parameters and the density profiles of galaxies. We explore the constraining power on cosmological parameters and the effect of the lens mass model in this method with 161 galaxy-scale strong lensing systems, which is currently the largest sample with both high resolution imaging and stellar dynamical data. We assume a power-law mass model for the lenses, and consider three different parameterizations for γ\gamma (i.e., the slope of the total mass density profile) to include the effect of the dependence of γ\gamma on redshift and surface mass density. When treating δ\delta (i.e., the slope of the luminosity density profile) as a universal parameter for all lens galaxies, we find the limits on the cosmological parameter Ωm\Omega_m are quite weak and biased, and also heavily dependent on the lens mass model in the scenarios of parameterizing γ\gamma with three different forms. When treating δ\delta as an observable for each lens, the unbiased estimate of Ωm\Omega_m can be obtained only in the scenario of including the dependence of γ\gamma on both the redshift and the surface mass density, that is Ωm=0.381−0.154+0.185\Omega_m = 0.381^{+0.185}_{-0.154} at 68\% confidence level in the framework of a flat Λ\LambdaCDM model. We conclude that the significant dependencies of γ\gamma on both the redshift and the surface mass density, as well as the intrinsic scatter of δ\delta among the lenses, need to be properly taken into account in this method.Comment: Accepted for publication in MNRAS; 17 pages, 5 figures, 2 table

    Determining the luminosity function of Swift long gamma-ray bursts with pseudo-redshifts

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    The determination of luminosity function (LF) of gamma-ray bursts (GRBs) is of an important role for the cosmological applications of the GRBs, which is however hindered seriously by some selection effects due to redshift measurements. In order to avoid these selection effects, we suggest to calculate pseudo-redshifts for Swift GRBs according to the empirical L-E_p relationship. Here, such a L−EpL-E_p relationship is determined by reconciling the distributions of pseudo- and real redshifts of redshift-known GRBs. The values of E_p taken from Butler's GRB catalog are estimated with Bayesian statistics rather than observed. Using the GRB sample with pseudo-redshifts of a relatively large number, we fit the redshift-resolved luminosity distributions of the GRBs with a broken-power-law LF. The fitting results suggest that the LF could evolve with redshift by a redshift-dependent break luminosity, e.g., L_b=1.2\times10^{51}(1+z)^2\rm erg s^{-1}. The low- and high-luminosity indices are constrained to 0.8 and 2.0, respectively. It is found that the proportional coefficient between GRB event rate and star formation rate should correspondingly decrease with increasing redshifts.Comment: 5 pages, 5 figures, accepted for publication in ApJ
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