论文标题
远红外光度红移：一种高度不确定企业的新方法
Far-Infrared Photometric Redshifts: A New Approach to a Highly Uncertain Enterprise
论文作者
论文摘要
我提出了一种新的方法，该方法是根据星系从毫米远红外通过毫米波长的尘埃发射的重新处理的星系发射的星系发射的新方法。在过去的十年中，已使用了远红外光度红移（“ fir- $ z $”），以获得高度模糊的星系的红移约束，这些星系在其他波长（如光学/近红外）上缺乏光度法。大多数文献FIR-Z拟合是通过$χ^2 $最小化对单个Galaxy的远红外模板光谱能分布（SED）进行的。使用单个星系模板或适度的模板集可能会导致对FIR- $ Z $的人为较低的不确定性估计，因为真实的星系在固有的灰尘SED中显示了广泛的范围。我使用观察到的星系SED分布（对于$ 0 <z <5 $的构成良好约束的样品）来激励通过称为MMPZ的毫米光度红移技术来激励新的远红外。 MMPZ算法断言星系很可能是从经验观察到的REST-FRAME峰值波长，$λ_{\ rm peak} $和总IR亮度的经验观察到的关系中得出的，L $ _ {\ rm ir} $;派生的光度红移解释了所推论的l $ _ {\ rm ir} $的SED的测量不确定性和内在变化，以及从$ z> 5 $的CMB加热。 The MMpz algorithm has a precision of $σ_{Δz/(1+z)}\approx0.3-0.4$, similar to single-template fits, while providing a more accurate estimate of the FIR-$z$ uncertainty with reduced chi-squared of order $\mathcal{O}(χ^2_ν)=1$, compared to alternative far-infrared photometric红移技术（带有$ \ Mathcal {o}（χ^2_ν）\ lot10-10^{3} $）。
I present a new approach at deriving far-infrared photometric redshifts for galaxies based on their reprocessed emission from dust at rest-frame far-infrared through millimeter wavelengths. Far-infrared photometric redshifts ("FIR-$z$") have been used over the past decade to derive redshift constraints for highly obscured galaxies that lack photometry at other wavelengths like the optical/near-infrared. Most literature FIR-z fits are performed through $χ^2$minimization to a single galaxy's far-infrared template spectral energy distribution (SED). The use of a single galaxy template, or modest set of templates, can lead to an artificially low uncertainty estimate on FIR-$z$'s because real galaxies display a wide range in intrinsic dust SEDs. I use the observed distribution of galaxy SEDs (for well-constrained samples across $0<z<5$) to motivate a new far-infrared through millimeter photometric redshift technique called MMpz. The MMpz algorithm asserts that galaxies are most likely drawn from the empirically observed relationship between rest-frame peak wavelength, $λ_{\rm peak}$, and total IR luminosity, L$_{\rm IR}$; the derived photometric redshift accounts for the measurement uncertainties and intrinsic variation in SEDs at the inferred L$_{\rm IR}$, as well as heating from the CMB at $z>5$. The MMpz algorithm has a precision of $σ_{Δz/(1+z)}\approx0.3-0.4$, similar to single-template fits, while providing a more accurate estimate of the FIR-$z$ uncertainty with reduced chi-squared of order $\mathcal{O}(χ^2_ν)=1$, compared to alternative far-infrared photometric redshift techniques (with $\mathcal{O}(χ^2_ν)\approx10-10^{3}$).
