arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 0907.3718cond-mat.stat-mechcond-mat.mes-hallcond-mat.softhep-th
收藏

自洽屏蔽近似下物理晶体膜的结构

The Structure of Physical Crystalline Membranes within the Self-Consistent Screening Approximation

Doron Gazit

摘要:

控制物理结晶膜的平坦相的长波长行为的反常指数在应用于1/d_C(d_C是余维)中的二级展开的自洽屏蔽近似(SCSA)内计算,扩展了Le Doussal和Radzihovsky的开创性工作[Phys. Rev. Lett. 69,1209(1992)]。特别地,发现弯曲刚度在长波长极限下代数硬化,指数η =0.789..用于提取弹性软化指数eta_u=0.422.并且粗糙度指数zeta=0.605.证明了标度关系eta_u=2- 2 eta在SCSA中适用于所有阶。此外,将SCSA应用到1/dC展开式中是必要的,因为在两个气泡水平下没有找到自洽方程的解,这是朴素的二阶展开式。令人惊讶的是,尽管物理膜的膨胀参数为1/d_C=1,但应用于二级膨胀的SCSA仅与一级膨胀略有偏离,仅使zeta增加0.016。这支持了物理结晶膜的SCSA的高质量,并改善了与这些系统的实验和数值模拟的比较。SCSA的预测适用于泊松比的一阶扩展被证明是准确的所有订单。

英文摘要:

The anomalous exponents governing the long wavelength behavior of the flat phase of physical crystalline membranes are calculated within a self-consistent screening approximation (SCSA) applied to second order expansion in 1/d_C (d_C is the co-dimension), extending the seminal work of Le Doussal and Radzihovsky [Phys. Rev. Lett. 69, 1209 (1992)]. In particular, the bending rigidity is found to harden algebraically in the long wavelength limit with an exponent eta=0.789..., which is used to extract the elasticity softening exponent eta_u=0.422..., and the roughness exponent zeta=0.605.... The scaling relation eta_u=2-2eta is proven to hold to all orders in SCSA. Further, applying the SCSA to an expansion in 1/d_C, is found to be essential, as no solution to the self-consistent equations is found in a two bubble level, which is the naive second order expansion. Surprisingly, even though the expansion parameter for physical membrane is 1/d_C=1, the SCSA applied to second order expansion deviates only slightly from the first order, increasing zeta by mere 0.016. This supports the high quality of the SCSA for physical crystalline membranes, as well as improves the comparison to experiments and numerical simulations of these systems. The prediction of SCSA applied to first order expansion for the Poisson ratio is shown to be exact to all orders.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑