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

$f(R)$ gravity, capable of driving the late-time acceleration of the universe, is emerging as a promising alternative to dark energy. Various $f(R)$ 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 $f(R)$ gravity models. This sample can probe the expansion history up to $z\sim2.2$, higher than what probed by current SNIa and BAO data. We adopt a typical parameterization of the form $f(R)=R-\alpha H^2_0(-\frac{R}{H^2_0})^\beta$ with $\alpha$ and $\beta$ constants. For $\beta=0$ ($\Lambda$CDM), we obtain the best-fit value of the parameter $\alpha=-4.193$, for which the 95% confidence interval that is [-4.633, -3.754]. This best-fit value of $\alpha$ corresponds to the matter density parameter $\Omega_{m0}=0.301$, consistent with constraints from other probes. Allowing $\beta$ to be free, the best-fit parameters are $(\alpha, \beta)=(-3.777, 0.06195)$. Consequently, we give $\Omega_{m0}=0.285$ and the deceleration parameter $q_0=-0.544$. At the 95% confidence level, $\alpha$ and $\beta$ are constrained to [-4.67, -2.89] and [-0.078, 0.202] respectively. Clearly, given the currently limited sample size, we can only constrain $\beta$ within the accuracy of $\Delta\beta\sim 0.1$ and thus can not distinguish between $\Lambda$CDM and $f(R)$ 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

The Role of China in 2 Degree World: The Needs for Change in Energy System Planning

AbstractChina is taking the crucial role to fulfill the global 2-degree target, which is claimed that the global temperature should be kept below 2 degrees by 2100. China is now the top CO2 emitter in the world and has much potential in carbon mitigation, and is now on the stage of its 12th five years plan and facing the problem of energy system optimization.This paper presents an assessment of possible changes in energy system planning in China within a 2 degree world. Our study is based on China-ESPT, a bottom-up and technological based optimization model with rich technical details at sectorial levels, including industry, power generation, and transportation, residential and commercial sectors. Three scenarios are designed referring to three kinds of mitigation pathways to fulfill the global 2-degree target: Equal per capita cumulative principle (EPC), grandfather principle (GF), and contraction and convergence (CC). The results show us the effect of carbon mitigation pathway, and relevant changes for energy system infrastructure, it is possible to evaluate both mitigation policies and technology innovation. Besides, we also considered the total cost for the adjustment of energy system. This analysis offers good reference and strong support for China's policy design and optimization both in short term by year 2020 and long term by year 2050. Under the 2-degree global target scheme, China should find its own way to both meet the global target as a main role and make optimal and cost-effective adjustment for energy system via a sustainable development way