Reddening and extinction estimates with APOGEE data

The reddening (reddeningAllStars.csv.zip) and extinction (extinctionsAllStars.csv.zip) estimates provided below were derived as part of Yu et al. (2026). For comprehensive details regarding the methodology, please refer to the original paper. Data are provided for the following 39 passbands: Photometric System Passband Column name used in the catalogs Gaia G, BP, RP gaiag, gaiabp, gaiarp Pan-STARRS g, r, i, z, y panstarrsps1g, panstarrsps1r, panstarrsps1i, panstarrsps1z, panstarrsps1y SDSS u, g, r, i, z sdssu, sdssg, sdssr, sdssi, sdssz APASS B, V, g, r, i apassb, apassv, apassg, apassr, apassi Johnson–Kron–Cousins U, B, V, R, I U, B, V, R, I SkyMapper v, g, r, i, z skymapperv, skymapperg, skymapperr, skymapperi, skymapperz Stromgren v, b, y stromgrenv, stromgrenb, stromgreny HST F435W, F606W, F814W hstf435w, hstf606w, hstf814w 2MASS J, H, Ks twomassj, twomassh, twomassk ALLWISE W1, W2 wisew1, wisew2 If specific reddening values for a color are not directly available in reddeningAllStars.csv.zip, they can be derived using a linear combination of other available colors. For example, E(B−V) is not listed directly in this catalogue but can be derived from E(B−RP)−E(V−RP) (please find the passband names in the table above). For your convenience, we have provided a python script (catalog_explorer.py) to quickly calculate E(B−V) and its associated uncertainty through error propagation. Note on Negative Values: Reddening values may be negative for a small fraction of stars. Users can utilize the associated uncertainties (e.g., 3σ clipping) to manage or remove these negative values. # ensure that your explorer.py and reddeningAllStarsFinal.csv are in the current directory. from explorer import get_reddening # to obtain E(B-V), run the code below df = get_reddening(band1="B", band2="V") # to obtain E(BP-RP), run this code (check the filter names from the table above) df = get_reddening(band1="gaiabp", band2="gaiarp") # to obtain E(V-J), run this code df = get_reddening(band1="V", band2="twomassj") Although one can calculate E(B-V) from A(B) and A(V), where A(B) and A(V) can be accessed from extinctionsAllStars.csv.zip, this method is not as robust as the method of using a combination of reddenings in different colors. This is becuase in our work, we have to made assumptions to convert reddening to extinction, and this assumption can introduce a small uncertainty (~3% level). While E(B−V) can be calculated using A(B) and A(V) from extinctionsAllStars.csv.zip, this approach is less robust than using a linear combination of reddenings in different colors. This is because our process for converting reddening to extinction requires certain assumptions, which may introduce a small uncertainty (at the ~3% level for most stars). In addition, the table reddeningAllStarsFinal.csv.zip includes the Gaia DR3 source_id , stellar parameters from APOGEE DR19 (reported as weighted averages when multiple entries are available for a given star), distances from Bailer-Jones et al. (2021) based on Gaia EDR3 (r_med_photogeo preferred if available, otherwise r_med_geo), and metadata describing the origin of the colours—either directly obtained from photometric surveys or synthesised from Gaia BP/RP spectra. For convinience, the table table1.csv is also provided here as well. It contains the same data as Table 1 in the paper.Feel free to reach out to Jie Yu ([e-mail]), if you have any questions.下述提供的红化（reddeningAllStars.csv.zip）与消光（extinctionsAllStars.csv.zip）估算值源自Yu等人（2026）的研究。如需了解方法学的完整细节，请参阅原文。本数据集涵盖以下39个测光通带： | 测光系统（Photometric System） | 通带名称（Passband） | 目录列名（Column name used in the catalogs） | | --- | --- | --- | | Gaia | G、BP、RP | gaiag、gaiabp、gaiarp | | Pan-STARRS | g、r、i、z、y | panstarrsps1g、panstarrsps1r、panstarrsps1i、panstarrsps1z、panstarrsps1y | | SDSS | u、g、r、i、z | sdssu、sdssg、sdssr、sdssi、sdssz | | APASS | B、V、g、r、i | apassb、apassv、apassg、apassr、apassi | | Johnson–Kron–Cousins | U、B、V、R、I | U、B、V、R、I | | SkyMapper | v、g、r、i、z | skymapperv、skymapperg、skymapperr、skymapperi、skymapperz | | Stromgren | v、b、y | stromgrenv、stromgrenb、stromgreny | | HST | F435W、F606W、F814W | hstf435w、hstf606w、hstf814w | | 2MASS | J、H、Ks | twomassj、twomassh、twomassk | | ALLWISE | W1、W2 | wisew1、wisew2 | 若reddeningAllStars.csv.zip中未直接提供某色指数的红化值，可通过其他可用色指数的线性组合推导得到。例如，本目录未直接列出E(B−V)，但可通过E(B−RP)−E(V−RP)推导得到（通带名称详见上表）。为方便使用者，我们提供了Python脚本（catalog_explorer.py），可通过误差传播快速计算E(B−V)及其对应不确定度。 关于负值说明：少量恒星的红化值可能为负值。使用者可利用相关不确定度（如3σ截断）处理或剔除这些负值。 python # 确保explorer.py与reddeningAllStarsFinal.csv位于当前工作目录下 from explorer import get_reddening # 获取E(B-V)，运行如下代码 df = get_reddening(band1="B", band2="V") # 获取E(BP-RP)，请根据上表核对滤光片名称 df = get_reddening(band1="gaiabp", band2="gaiarp") # 获取E(V-J)，运行如下代码 df = get_reddening(band1="V", band2="twomassj") 尽管可通过extinctionsAllStars.csv.zip中的A(B)与A(V)计算E(B-V)，但该方法不如使用不同色指数红化值线性组合的方法稳健。这是因为在本研究中，我们需通过假设将红化值转换为消光值，该假设会引入约3%量级的小不确定度。 虽然可通过extinctionsAllStars.csv.zip中的A(B)与A(V)计算E(B-V)，但该方法的稳健性仍不及利用不同色指数红化值线性组合的方案。究其原因，本研究在将红化值转换为消光值时需引入若干假设，这会为多数恒星带来约3%量级的微小不确定度。 此外，reddeningAllStarsFinal.csv.zip表格中包含Gaia DR3的source_id、来自APOGEE DR19的恒星参数（若某颗恒星存在多个条目，则以加权平均值报告）、基于Gaia EDR3的Bailer-Jones等人（2021）距离测量结果（优先使用r_med_photogeo，若不可用则使用r_med_geo），以及描述色指数来源的元数据——色指数可直接源自测光巡天，或由Gaia BP/RP光谱合成得到。 为方便使用者，我们同时提供了table1.csv，其内容与论文中的表1完全一致。若有任何疑问，可联系Jie Yu（[e-mail]）。