21,836 research outputs found

    Condensation of Eigen Microstate in Statistical Ensemble and Phase Transition

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    In a statistical ensemble with MM microstates, we introduce an M×MM \times M correlation matrix with the correlations between microstates as its elements. Using eigenvectors of the correlation matrix, we can define eigen microstates of the ensemble. The normalized eigenvalue by MM represents the weight factor in the ensemble of the corresponding eigen microstate. In the limit M→∞M \to \infty, weight factors go to zero in the ensemble without localization of microstate. The finite limit of weight factor when M→∞M \to \infty indicates a condensation of the corresponding eigen microstate. This indicates a phase transition with new phase characterized by the condensed eigen microstate. We propose a finite-size scaling relation of weight factors near critical point, which can be used to identify the phase transition and its universality class of general complex systems. The condensation of eigen microstate and the finite-size scaling relation of weight factors have been confirmed by the Monte Carlo data of one-dimensional and two-dimensional Ising models.Comment: 9 pages, 16 figures, accepted for publication in Sci. China-Phys. Mech. Astro

    f(R)f(R) gravity theories in the Palatini Formalism constrained from strong lensing

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    f(R)f(R) gravity, capable of driving the late-time acceleration of the universe, is emerging as a promising alternative to dark energy. Various f(R)f(R) gravity models have been intensively tested against probes of the expansion history, including type Ia supernovae (SNIa), the cosmic microwave background (CMB) and baryon acoustic oscillations (BAO). In this paper we propose to use the statistical lens sample from Sloan Digital Sky Survey Quasar Lens Search Data Release 3 (SQLS DR3) to constrain f(R)f(R) gravity models. This sample can probe the expansion history up to z∼2.2z\sim2.2, higher than what probed by current SNIa and BAO data. We adopt a typical parameterization of the form f(R)=R−αH02(−RH02)βf(R)=R-\alpha H^2_0(-\frac{R}{H^2_0})^\beta with α\alpha and β\beta constants. For β=0\beta=0 (Λ\LambdaCDM), we obtain the best-fit value of the parameter α=−4.193\alpha=-4.193, for which the 95% confidence interval that is [-4.633, -3.754]. This best-fit value of α\alpha corresponds to the matter density parameter Ωm0=0.301\Omega_{m0}=0.301, consistent with constraints from other probes. Allowing β\beta to be free, the best-fit parameters are (α,β)=(−3.777,0.06195)(\alpha, \beta)=(-3.777, 0.06195). Consequently, we give Ωm0=0.285\Omega_{m0}=0.285 and the deceleration parameter q0=−0.544q_0=-0.544. At the 95% confidence level, α\alpha and β\beta are constrained to [-4.67, -2.89] and [-0.078, 0.202] respectively. Clearly, given the currently limited sample size, we can only constrain β\beta within the accuracy of Δβ∼0.1\Delta\beta\sim 0.1 and thus can not distinguish between Λ\LambdaCDM and f(R)f(R) gravity with high significance, and actually, the former lies in the 68% confidence contour. We expect that the extension of the SQLS DR3 lens sample to the SDSS DR5 and SDSS-II will make constraints on the model more stringent.Comment: 10 pages, 7 figures. Accepted for publication in MNRA
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