arXivDaily arXiv每日学术速递 周一至周五更新
arXiv周末暂无论文更新,休息一下吧,周末愉快~~
arXiv 1607.02768astro-ph.CO
收藏

关联信息熵和质量方差度量偏差和非高斯性

Relating information entropy and mass variance to measure bias and non-Gaussianity

Biswajit Pandey

摘要:

我们将信息熵和质量方差的任何分布的制度的小波动。我们使用一组不同的均匀和非均匀分布的蒙特卡罗模拟来验证这种关系,并在一组宇宙学N体模拟中检验它。我们发现,这种关系是在很好的协议与模拟,是独立的数密度和分布的性质。我们表明,信息熵和质量方差之间的关系可以用来确定大尺度上的线性偏差和检测的签名的非高斯星系分布在小尺度上。

英文摘要:

We relate the information entropy and the mass variance of any distribution in the regime of small fluctuations. We use a set of Monte Carlo simulations of different homogeneous and inhomogeneous distributions to verify the relation and also test it in a set of cosmological N-body simulations. We find that the relation is in excellent agreement with the simulations and is independent of number density and the nature of the distributions. We show that the relation between information entropy and mass variance can be used to determine the linear bias on large scales and detect the signatures of non-Gaussianity on small scales in galaxy distributions.

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。

↑