arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1507.05092astro-ph.CO
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未来大尺度结构调查中的干扰者偏差

Interloper bias in future large-scale structure surveys

Anthony R. Pullen, Christopher M. Hirata, Olivier Dore, Alvise Raccanelli

摘要:

下一代分光巡天将利用发射线星系作为示踪物,绘制可观测宇宙的大尺度结构。虽然每一次巡天都将用一条特定的发射线来绘制天空,但交错的发射线可以伪装成巡天在不同红移处的预期发射线。没有被移除的星系的干涉线会污染功率谱测量,混合各种红移的相关性并稀释真实信号。我们评估了功率谱污染的可能性,发现一个比0.2%更差的干扰者分数可能会使未来调查的功率谱测量偏差超过10%的统计误差,同时也会使功率谱推断产生偏差。我们还构建了一个预测宇宙学参数偏差的形式主义,证明了0.15%-0.3%的闯入者分数可能会使增长率偏差超过10%的误差,这可能会影响对即将到来的重力调查的约束。我们使用COSMOS模拟目录(CMC),与发射线重新缩放,以更好地再现最近的数据,预测潜在的闯入者分数的主焦点摄谱仪(PFS)和宽视场红外巡天望远镜(WFIRST)。我们发现,二次线识别,或确认星系红移找到相关的发射线,可以删除PFS的闯入者。对于WFIRST,我们使用CMC来预测WFIRST H $α$调查可以达到0.2%的目标,但需要灵敏的光学和近红外测光。对于WFIRST [OIII]调查,预测的闯入者比例达到百分之几,必须估计它们的影响并在统计上消除(例如,使用深度训练样本)。(节录)

英文摘要:

Next-generation spectroscopic surveys will map the large-scale structure of the observable universe, using emission line galaxies as tracers. While each survey will map the sky with a specific emission line, interloping emission lines can masquerade as the survey's intended emission line at different redshifts. Interloping lines from galaxies that are not removed can contaminate the power spectrum measurement, mixing correlations from various redshifts and diluting the true signal. We assess the potential for power spectrum contamination, finding that an interloper fraction worse than 0.2% could bias power spectrum measurements for future surveys by more than 10% of statistical errors, while also biasing power spectrum inferences. We also construct a formalism for predicting cosmological parameter bias, demonstrating that a 0.15%-0.3% interloper fraction could bias the growth rate by more than 10% of the error, which can affect constraints on gravity upcoming surveys. We use the COSMOS Mock Catalog (CMC), with the emission lines re-scaled to better reproduce recent data, to predict potential interloper fractions for the Prime Focus Spectrograph (PFS) and the Wide-Field InfraRed Survey Telescope (WFIRST). We find that secondary line identification, or confirming galaxy redshifts by finding correlated emission lines, can remove interlopers for PFS. For WFIRST, we use the CMC to predict that the 0.2% target can be reached for the WFIRST H$α$ survey, but sensitive optical and near-infrared photometry will be required. For the WFIRST [OIII] survey, the predicted interloper fractions reach several percent and their effects will have to be estimated and removed statistically (e.g. with deep training samples). (Abridged)

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