论文标题

使用可能的无可能推理测量低$ z $ igm的热和电离状态

Measuring the thermal and ionization state of the low-$z$ IGM using likelihood free inference

论文作者

Hu, Teng, Khaire, Vikram, Hennawi, Joseph F., Walther, Michael, Hiss, Hector, Alsing, Justin, Oñorbe, Jose, Lukic, Zarija, Davies, Frederick

论文摘要

我们提出了一种测量幂律温度密度关系的新方法$ t = t_0(ρ/ \barρ)^{γ-1} $和Igm的UV背景光电离心率$γ_{\ rm hi} $,基于voigt profile profile compotion to ly $ ly $α$ forest to dick y $ forest in dick y $ $ $ n $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ b。 $ n _ {\ rm hi} $。以前的工作表明,$ b $ - $ n _ {\ rm hi} $分布对IGM热量参数$ t_0 $和$γ$敏感,而我们的新推理算法也考虑到了分布的归一化,即,线密度d $ n $/d $/d $ d $ z $,并且可以证明是限制的。 $γ_ {\ rm hi} $。我们使用密度估计的可能性推理(DELFI)来模仿$ b $ - $ n _ {\ rm hi} $分布在624个NYX Nyx流体动力学模拟时以$ z = 0.1 $进行的IGM参数进行培训,我们将与我们结合使用高斯的量子。为了证明这种方法的疗效,我们生成了数百种逼真的模拟HST/COS数据集的实现,每个数据集包含34个类星体视线,并转发模拟噪声和分辨率以匹配真实数据。我们使用这种大型模拟集合来广泛测试我们的推论,并在经验上证明我们的后验分布是牢固的。我们的分析表明,通过将我们的新方法应用于$ z \ simeq 0.1 $的现有$α$森林光谱,人们可以以很高的精度测量IGM的热和电离状态($σ_ {\ log t_0} \ sim 0.08 $ dex,$ n $ dex,$ n $ nim $σ_γ\ sim 0.06 $} \ sim 0.07 $ dex)。

We present a new approach to measure the power-law temperature density relationship $T=T_0 (ρ/ \barρ)^{γ-1}$ and the UV background photoionization rate $Γ_{\rm HI}$ of the IGM based on the Voigt profile decomposition of the Ly$α$ forest into a set of discrete absorption lines with Doppler parameter $b$ and the neutral hydrogen column density $N_{\rm HI}$. Previous work demonstrated that the shape of the $b$-$N_{\rm HI}$ distribution is sensitive to the IGM thermal parameters $T_0$ and $γ$, whereas our new inference algorithm also takes into account the normalization of the distribution, i.e. the line-density d$N$/d$z$, and we demonstrate that precise constraints can also be obtained on $Γ_{\rm HI}$. We use density-estimation likelihood-free inference (DELFI) to emulate the dependence of the $b$-$N_{\rm HI}$ distribution on IGM parameters trained on an ensemble of 624 Nyx hydrodynamical simulations at $z = 0.1$, which we combine with a Gaussian process emulator of the normalization. To demonstrate the efficacy of this approach, we generate hundreds of realizations of realistic mock HST/COS datasets, each comprising 34 quasar sightlines, and forward model the noise and resolution to match the real data. We use this large ensemble of mocks to extensively test our inference and empirically demonstrate that our posterior distributions are robust. Our analysis shows that by applying our new approach to existing Ly$α$ forest spectra at $z\simeq 0.1$, one can measure the thermal and ionization state of the IGM with very high precision ($σ_{\log T_0} \sim 0.08$ dex, $σ_γ\sim 0.06$, and $σ_{\log Γ_{\rm HI}} \sim 0.07$ dex).

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