EDGE-INFERNO:模拟暗矮星系中的每一颗可观测恒星及其对解析星测光测量的影响

Eric P. Andersson, Martin P. Rey, Andrew Pontzen, Corentin Cadiou, Oscar Agertz, Justin I. Read, Nicolas F. Martin
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摘要

由于观测仅限于最亮的恒星,对来自暗矮星系的数据的解释就变得非常具有挑战性。为了应对这一挑战,我们提出了一个重大改进方案,即进行放大宇宙学模拟,解析所有质量小于0.5美元的单个恒星的演化,从而明确跟踪所有可观测恒星的哈勃时间。我们第一次直接从宇宙学的初始条件出发,预测了4个微小矮星系(M_{star}大约10^5,\{\rm M}_{\odot}$)中可观测到的颜色-星震图和大约10万颗恒星的空间分布。在所有情况下,模拟都预示了具有多个分量的复杂光剖面,这意味着对结构参数的典型观测测量会使总V-bandmagnitudes(V-bandmagnitudes)看起来比模拟的估计值暗0.5个品位。此外,当只有少量($\lessapprox100$)恒星可被观测时,色-magnitude图的实测噪声会带来不确定性,这些不确定性与总magnitude、半光半径和平均铁丰度等测量中的群体散度相当。用完全自洽的质量增长、恒星形成和化学富集历史来估计这些不确定性,为更稳健地解释矮星系数据铺平了道路。
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EDGE-INFERNO: Simulating every observable star in faint dwarf galaxies and their consequences for resolved-star photometric surveys
Interpretation of data from faint dwarf galaxies is made challenging by observations limited to only the brightest stars. We present a major improvement to tackle this challenge by undertaking zoomed cosmological simulations that resolve the evolution of all individual stars more massive than $0.5\,{\rm M}_{\odot}$, thereby explicitly tracking all observable stars for the Hubble time. For the first time, we predict observable color-magnitude diagrams and the spatial distribution of $\approx 100,000$ stars within four faint ($M_{\star} \approx 10^5 \, \,{\rm M}_{\odot}$) dwarf galaxies directly from their cosmological initial conditions. In all cases, simulations predict complex light profiles with multiple components, implying that typical observational measures of structural parameters can make total V-band magnitudes appear up to 0.5 mag dimmer compared to estimates from simulations. Furthermore, when only small ($\lessapprox100$) numbers of stars are observable, shot noise from realizations of the color-magnitude diagram introduces uncertainties comparable to the population scatter in, e.g., total magnitude, half-light radius, and mean iron abundance measurements. Estimating these uncertainties with fully self-consistent mass growth, star formation and chemical enrichment histories paves the way for more robust interpretation of dwarf galaxy data.
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