论文标题
$ n $ - 体仿真用于参数化的重力
$N$-body simulations for parametrised modified gravity
论文作者
论文摘要
我们提出$ \ texttt {mg-evolution} $，一个$ n $的体制代码，模拟宇宙学结构形成，以进行参数化的重力修改。它是由参数性线性理论的结合以及从修改的球形塌陷计算中推断出的深层非线性宇宙学方面的参数化构建的，该综合界面范围涵盖了已知筛选机制的范围。 We test $\texttt {MG-evolution}$, which runs at the speed of conventional $Λ$CDM simulations, against a suit of existing exact model-specific codes, encompassing linearised and chameleon $f(R)$ gravity as well as the normal branch of the Dvali-Gabadadz-Porrati braneworld model, hence covering both large-field value and large-derivative screening effects.我们比较了由盒子大小和模拟的分辨率设置的全范围的参数化和特定于模型的方法所产生的非线性功率谱，$ k =（0.05-2.5）$ 〜h/mpc，对于两个红移切片，$ z = 0 $ z = 1 $。我们发现，针对整个尺度范围的模型代码生成的所有功率光谱的所有功率光谱都降至一倍。 $ \ texttt {mg-evolution} $可用于对重力和深色能量的通用和准确的测试，并且在未来十年内越来越多的高精度宇宙学调查数据可用。
We present $\texttt{MG-evolution}$, an $N$-body code simulating the cosmological structure formation for parametrised modifications of gravity. It is built from the combination of parametrised linear theory with a parametrisation of the deeply nonlinear cosmological regime extrapolated from modified spherical collapse computations that cover the range of known screening mechanisms. We test $\texttt {MG-evolution}$, which runs at the speed of conventional $Λ$CDM simulations, against a suit of existing exact model-specific codes, encompassing linearised and chameleon $f(R)$ gravity as well as the normal branch of the Dvali-Gabadadz-Porrati braneworld model, hence covering both large-field value and large-derivative screening effects. We compare the nonlinear power spectra produced by the parametrised and model-specific approaches over the full range of scales set by the box size and resolution of our simulations, $k=(0.05-2.5)$~h/Mpc, and for two redshift slices, $z=0$ and $z=1$. We find sub-percent to one-percent level recovery of all the power spectra generated with the model-specific codes for the full range of scales. $\texttt {MG-evolution}$ can be used for generalised and accurate tests of gravity and dark energy with the increasing wealth of high-precision cosmological survey data becoming available over the next decade.
