Public Data Access Overview / Data Specifications
公共数据访问概述 / 数据规范

This page contains a comprehensive description of the simulation snapshots, group catalogs, merger trees, and supplementary data sets. Differences and additions in TNG with respect to the original Illustris public data release are noted: aspects which have changed, or which are new in TNG, are marked in blue, while those marked in green are identical to Illustris.
本页包含对模拟快照、群组目录、合并树及补充数据集的全面描述。TNG 相较于原始 Illustris 公共数据发布的不同之处和新增内容均已标注：TNG 中已更改或新增的部分以蓝色标记，与 Illustris 相同的部分则以绿色标记。

Table of Contents  目录

• 1. Snapshots  1. 快照
• Organization  组织
• Contents  目录
• PartType0 (Gas)
• PartType1 (DM)
• PartType3 (Tracers)
• PartType4 (Stars)  PartType4（恒星）
• PartType5 (BHs)
• Subboxes
• 2. Group Catalogs  2. 群组目录
• FoF Halos
• Subfind Subhalos (Galaxies)
  Subfind 子晕（星系）
• 3. Important Additional Files
  3. 重要附加文件
• Offsets
• The "simulation.hdf5" File
  “simulation.hdf5”文件
• 4. Merger Trees
• SubLink
• LHaloTree
• 5. Supplementary Data Catalogs
  5. 补充数据目录
• (a) Tracer Tracks
• (b) Star Formation Rates
  (b) 恒星形成率
• (c) Stellar Circularities, Angular Momenta, Axis Ratios
  (c) 恒星圆度、角动量、轴比
• (d) Subhalo Matching Between Runs
  (d) 运行之间的子晕匹配
• (e) Stellar Projected Sizes
  (e) 恒星投影尺寸
• (f) Blackhole Mergers and Details
  (f) 黑洞合并与详细信息
• (g) Stellar Assembly  (g) 恒星组装
• (h) Subbox Subhalo List
  (h) 子盒子子晕列表
• (i) Molecular and atomic hydrogen (HI+H2) galaxy contents
  (i) 分子氢和原子氢 (HI+H2) 星系含量
• (j) Barred Galaxies Properties and Evolution
  (j) 棒旋星系属性与演化
• (k) SDSS ugriz and UVJ Photometry/Colors with Dust
  (k) SDSS ugriz 和 UVJ 光度/颜色（含尘埃）
• (l) SKIRT Synthetic Images and Optical Morphologies
  (l) SKIRT 合成图像和光学形态
• (m) Disk Galaxy Kinematic Decompositions
  (m) 盘状星系运动学分解
• (n) L-Galaxies Semi-Analytical Model
  (n) L-Galaxies 半解析模型
• (o) Lensing Profiles
• (p) Aperture Masses (Total and Stellar)
  (p) 孔径质量（总质量和恒星质量）
• (q) Halo Structure
• (r) Galaxy Morphologies (Deep Learning)
• (s) Cosmic Web Distances (Disperse)
  (s) 宇宙网距离（Disperse）
• (t) Galaxy Morphologies (Kinematic) and Bar Properties
  (t) 星系形态（动力学）和棒状结构属性
• (u) LEGA-C/VIMOS Mock Optical Spectra
  (u) LEGA-C/VIMOS 模拟光学光谱
• (v) JWST-CEERS Mock Galaxy Imaging
  (v) JWST-CEERS 模拟星系成像
• (w) Multi-band (UV to submm) Photometry and SEDs
  (w) 多波段（紫外到亚毫米）光度测量和 SEDs
• (x) Globular Clusters  (x) 球状星团
• (y) Merger History  (y) 合并历史
• (z) MaNGIA Mock MANGA IFU Cubes
  (z) MaNGIA 模拟 MANGA IFU 立方体
• (1) TNG50 Milky Way+Andromeda (MW/M31)-like Galaxies
  (1) TNG50 银河系+仙女座星系（MW/M31）类星系
• (2) HVC-like Cosmological Cloud Catalog
• (3) Zooniverse Cosmological Jellyfish
• (4) iMaNGA Mock MANGA IFU Datacubes
  (4) iMaNGA Mock MANGA IFU 数据立方体
• (5) Synthetic Stellar Light Images with HSC-SSP Realism
  (5) 合成恒星光图像，具有 HSC-SSP 真实感
• (6) Nearest Neighbors  (6) 最近邻
• (7) TNG50-Skirt Atlas

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1. Snapshots

Organization  组织

There are 100 snapshots stored for every run. These include all particles/cells in the whole volume. The complete snapshot listings, spacings and redshifts can be found in the API. Note that, unlike in Illustris, TNG contains two different types of snapshots: 'full' and 'mini'. While both encompass the entire volume, 'mini' snapshots only have a subset of particle fields available (detailed below). In TNG twenty snapshots are full, while the remaining 80 are mini. The 20 full snapshots are:
每次运行存储了 100 个快照。这些快照包括整个体积中的所有粒子/单元格。完整的快照列表、间隔和红移可以在 API 中找到。请注意，与 Illustris 不同，TNG 包含两种不同类型的快照：“完整”和“迷你”。虽然两者都涵盖了整个体积，但“迷你”快照仅提供粒子字段的子集（详见下文）。在 TNG 中，20 个快照是完整的，其余 80 个是迷你的。20 个完整快照是：

Every snapshot is stored in a series of "chunks", i.e. more manageable, smaller-size files. The number of chunks per snapshots is different for the different runs:
每个快照存储在一系列“块”中，即更易于管理的小文件。不同运行的每个快照的块数不同：

Note that the snapshot data is not organized according to spatial position. Rather, particles within the snapshot files are sorted according to their group/subgroup memberships, according to the FoF or Subfind algorithms. Within each particle type, the sort order is: GroupNumber, SubgroupNumber, BindingEnergy, where particles belonging to the group but not to any of its subgroups ("fuzz") are included after the last subgroup. The following figure provides a schematic view of the particle organization within a snapshot, for one particle type. Note that the truncation of a snapshot in chunks is arbitrary, thus halos may happen to be stored across multiple, subsequent chunks. Similarly, the different particle types of a halo can be stored in different sets of chunks.
请注意，快照数据并不是根据空间位置组织的。相反，快照文件中的粒子根据它们的群组/子群组成员关系，按照 FoF 或 Subfind 算法进行排序。在每种粒子类型内，排序顺序为：GroupNumber、SubgroupNumber、BindingEnergy，其中属于群组但不属于任何子群组的粒子（“fuzz”）包含在最后一个子群组之后。下图提供了快照中粒子组织的示意图，针对一种粒子类型。请注意，快照的分块截断是任意的，因此晕可能恰好存储在多个连续的分块中。同样，一个晕的不同粒子类型可以存储在不同的分块集合中。

Caption. Schematic diagram of the organization of particle/cell data within the snapshots for a single particle type. Within a type, particle order is determined by a global sort of the following fields in this order: FoF group number, Subfind subhalo number, binding energy, nearest FoF group number. This implies that FOF halos are contiguous, although they can span file chunks. Subfind subhalos are only contiguous within a single group, being separated between groups by an "inner fuzz" of all FOF particles not bound to any subhalo. Here Nc$N_c$ indicates the number of file chunks, nF$n_F$ the number of FOF groups, and NS,j$N_{S,j}$ the number of subhalos in jth$j^{\mathrm{t}\mathrm{h}}$ FoF group.
标题：单粒子类型快照中粒子/单元格数据组织的示意图。在类型内，粒子顺序由以下字段的全局排序决定：FoF 组号、Subfind 子晕号、结合能、最近的 FoF 组号。这意味着 FoF 晕是连续的，尽管它们可以跨越文件块。Subfind 子晕仅在单个组内是连续的，在组之间由所有未绑定到任何子晕的 FoF 粒子的“内部模糊”分隔。这里 Nc$N_c$ 表示文件块的数量， nF$n_F$ 表示 FoF 组的数量， NS,j$N_{S,j}$ 表示 jth$j^{\mathrm{t}\mathrm{h}}$ FoF 组中子晕的数量。

Contents  目录

Every HDF5 snapshot contains several groups: "Header", "Parameters", "Configuration", and five "PartTypeX" groups, for the following particle types (the DM only runs have a single PartType1 group):
每个 HDF5 快照包含多个组："Header"、"Parameters"、"Configuration"，以及五个"PartTypeX"组，对应以下粒子类型（仅含暗物质的运行中只有一个 PartType1 组）：

• PartType0 - GAS
• PartType1 - DM
• PartType2 - (unused)  PartType2 - (未使用)
• PartType3 - TRACERS
• PartType4 - STARS & WIND PARTICLES
  PartType4 - 恒星与风粒子
• PartType5 - BLACK HOLES

The most important fields of the Header group are given in the following table.
Header 组中最重要的字段在以下表格中给出。

The Parameters and Configuration provide the complete set of parameter file options and run-time configuration options used to run TNG. That is, they encode the fiducial "TNG Galaxy Formation Model". Many will clearly map to Table 1 of Pillepich et al. (2018a), while others deal with more numerical/technical options. In the future, together with the release of the TNG initial conditions and the TNG code base of AREPO, this will enable any of the TNG simulations to be reproduced.
Parameters 和 Configuration 提供了用于运行 TNG 的完整参数文件选项和运行时配置选项。也就是说，它们编码了基准的 "TNG 星系形成模型"。其中许多选项将清晰地映射到 Pillepich 等人 (2018a) 的表 1，而其他选项则涉及更多的数值/技术选项。未来，随着 TNG 初始条件和 AREPO 的 TNG 代码库的发布，这将使得任何 TNG 模拟都能够被复现。

The complete snapshot field listings of the PartTypeX groups, including dimensions, units and descriptions, are given for all the particles types in the following large table. Rows in blue are new or different in some way with respect to original Illustris, while those in green are unchanged.
完整的 PartTypeX 组的快照字段列表，包括维度、单位和描述，在下面的大表格中为所有粒子类型提供。蓝色行表示与原始 Illustris 相比是新的或有所不同的，而绿色行则表示未更改。

The general unit system is kpc/h$\mathrm{k}\mathrm{p}\mathrm{c}/h$ for lengths, 1010M⊙/h${10}^{10}{\mathrm{M}}_{\odot }/h$ for masses, km/s$\mathrm{k}\mathrm{m}/\mathrm{s}$ for velocities. The frequently occurring (1010M⊙/h)/(0.978Gyr/h)$({10}^{10}{\mathrm{M}}_{\odot }/h)/(0.978\mathrm{G}\mathrm{y}\mathrm{r}/h)$ represents mass-over-time in this unit system, and multiplying by 10.22 converts to M⊙/yr${\mathrm{M}}_{\odot }/\mathrm{y}\mathrm{r}$. Comoving quantities can be converted in the corresponding physical ones by multiplying for the appropriate power of the scale factor a$a$. For instance, to convert a length in physical units it is sufficient to multiply it by a$a$, volumes need a factor a3$a^3$, densities a−3$a^{-3}$ and so on. Note that at redshift z=0$z=0$ the scale factor is a=1$a=1$, so that the numerical values of comoving quantities are the same as their physical counterparts.
一般单位系统中，长度单位为 kpc/h$\mathrm{k}\mathrm{p}\mathrm{c}/h$ ，质量单位为 1010M⊙/h${10}^{10}{\mathrm{M}}_{\odot }/h$ ，速度单位为 km/s$\mathrm{k}\mathrm{m}/\mathrm{s}$ 。在此单位系统中，经常出现的 (1010M⊙/h)/(0.978Gyr/h)$({10}^{10}{\mathrm{M}}_{\odot }/h)/(0.978\mathrm{G}\mathrm{y}\mathrm{r}/h)$ 表示质量随时间的变化，乘以 10.22 可转换为 M⊙/yr${\mathrm{M}}_{\odot }/\mathrm{y}\mathrm{r}$ 。通过乘以适当的比例因子 a$a$ 的幂次，可以将共动量转换为相应的物理量。例如，要将长度转换为物理单位，只需将其乘以 a$a$ ，体积需要乘以 a3$a^3$ ，密度需要乘以 a−3$a^{-3}$ ，依此类推。请注意，在红移 z=0$z=0$ 时，比例因子为 a=1$a=1$ ，因此共动量的数值与其物理对应量相同。

Tagged Metals  标记金属

(*) The units of all the entries of GFM_MetalsTagged, except for NSNS, are the same as GFM_Metals: dimensionless mass ratios. If you sum up all the elements of GFM_Metals heavier than Helium, you recover the sum of the three tags SNIa+SNII+AGB. Likewise, the Fe entry of GFM_Metals roughly equals the sum of FeSNIa+FeSNII, modulo the small amount of iron consumed (i.e. negative contribution) by AGB winds. The particular fields are:
(*) GFM_MetalsTagged 的所有条目（NSNS 除外）的单位与 GFM_Metals 相同：无量纲质量比。如果你将 GFM_Metals 中比氦重的所有元素相加，你将得到 SNIa+SNII+AGB 这三个标签的总和。同样，GFM_Metals 中的 Fe 条目大致等于 FeSNIa+FeSNII 的总和，减去 AGB 风消耗的少量铁（即负贡献）。具体字段为：

• SNIa (0): The total metals ejected by Type Ia supernovae.
  SNIa (0): Ia 型超新星喷射出的总金属量。
• SNII (1): The total metals ejected by Type II supernovae.
  SNII (1): II 型超新星喷射出的总金属量。
• AGB (2): the total metals ejected by stellar winds, which is dominated by AGB stars.
  AGB (2): 由恒星风喷射出的总金属量，主要由 AGB 星主导。
• NSNS (3): the total mass ejected from NS-NS merger events, which are modeled stochastically (i.e. no fractional events) with a DTD scheme similar to that used for SNIa, except with a different τ$\tau$ value. Note that the units of NSNS are arbitrary. To obtain physical values in units of solar masses, this field must be multiplied by (MyPreferred_NSNS_MassPerEvent/NSNS_MassPerEvent), where MyPreferred_NSNS_MassPerEvent is the amount of mass ejected per NS-NS merger preferred for analysis (e.g. Shen+ 2015 uses here a value of 0.05M⊙$0.05M_{\odot }$), and NSNS_MassPerEvent is the value we have set for the simulation, which varies by run. In particular, it is 0.05 for TNG100* and 5000.0 for TNG300* and TNG50*.
  NSNS (3): 从 NS-NS 合并事件中抛出的总质量，这些事件以类似于 SNIa 的 DTD 方案进行随机建模（即没有分数事件），但具有不同的 τ$\tau$ 值。请注意，NSNS 的单位是任意的。要获得以太阳质量为单位的物理值，必须将此字段乘以(MyPreferred_NSNS_MassPerEvent/NSNS_MassPerEvent)，其中 MyPreferred_NSNS_MassPerEvent 是每次 NS-NS 合并中抛出的质量，用于分析（例如 Shen+ 2015 在此处使用 0.05M⊙$0.05M_{\odot }$ ），而 NSNS_MassPerEvent 是我们为模拟设置的值，因运行而异。特别是，TNG100*的值为 0.05，TNG300*和 TNG50*的值为 5000.0。
• FeSNIa (4): The total iron ejected by Type Ia supernovae alone.
  FeSNIa (4): 仅由 Ia 型超新星喷射出的总铁量。
• FeSNII (5): The total iron ejected by Type II supernovae alone.
  FeSNII (5): 仅由 II 型超新星喷射出的总铁量。

(^) Although the two shock finder fields exist in subboxes, they are not updated for each subbox output, but only occasionally, so in general one should NOT use these two fields in subbox snapshots.
尽管两个 shock finder 字段存在于 subboxes 中，但它们并不会为每个 subbox 输出更新，而只是偶尔更新，因此通常不应在 subbox 快照中使用这两个字段。

Subboxes

Separate "subbox" cutouts exist for each baryonic run. These are spatial cutouts of fixed comoving size and fixed comoving coordinates, and the primary benefit is that their time resolution is significantly better than that of the main snapshots. This may be useful for some types of analysis or particular science questions, or for making movies. There are two subboxes for TNG100 (corresponding to the original Illustris subboxes #0 and #2, the latter increased in size), and three subboxes for TNG50 and TNG300. Two notes of caution: first, the time spacing of the subboxes is not uniform in scale factor or redshift, but scales with the time integration hierarchy of the simulation, and is thus variable, with some discrete factor of two jumps at several points during the simulations. Second, the subboxes, unlike the full box, are not periodic.
每个重子运行都有独立的“子盒”截取。这些是固定共动大小和固定共动坐标的空间截取，其主要优势是它们的时间分辨率显著优于主快照。这对于某些类型的分析或特定的科学问题，或者制作电影可能很有用。TNG100 有两个子盒（对应于原始 Illustris 的子盒#0 和#2，后者尺寸有所增加），TNG50 和 TNG300 各有三个子盒。需要注意两点：首先，子盒的时间间隔在尺度因子或红移上并不均匀，而是与模拟的时间积分层次成比例，因此是可变的，在模拟过程中某些点会出现离散的倍数跳跃。其次，与完整盒子不同，子盒不是周期性的。

The subboxes sample different areas of the large boxes, roughly described by the environment column in the following table. The particle fields are all identical to the main snapshots. However, the ordering differs. In particular, particles/cells in the subboxes are not ordered according to their group membership, as no group catalogs are available for these cutouts.
子盒子对大盒子的不同区域进行采样，大致由下表中的环境列描述。粒子字段与主快照完全相同。然而，排序方式不同。特别是，子盒子中的粒子/单元没有按照它们的群组成员关系进行排序，因为这些截取部分没有可用的群组目录。

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2. Group Catalogs

There is one group catalog associated with each snapshot, which includes both FoF and Subfind objects. The group files are split into a small number of sub-files, just as with the raw snapshots. In TNG, these files are called "fof_subhalo_tab_*", whereas in original Illustris they were called "groups_*" (they are otherwise essentially identical). Every HDF5 group catalog contains the following groups: Header, Group, Subhalo. The IDs of the member particles of each group/subgroup are not stored in the group catalog files. Rather, particles/cells in the snapshot files are ordered according to group membership.
每个快照都关联一个群组目录，其中包括 FoF 和 Subfind 对象。群组文件被分成少量子文件，与原始快照相同。在 TNG 中，这些文件被称为“fof_subhalo_tab_*”，而在原始 Illustris 中它们被称为“groups_*”（除此之外它们基本完全相同）。每个 HDF5 群组目录包含以下组：Header、Group、Subhalo。每个群组/子群的成员粒子 ID 不存储在群组目录文件中。相反，快照文件中的粒子/单元格按照群组成员资格排序。

In order to reduce confusion, we adopt the following terminology when referring to different types of objects:
为了减少混淆，我们在提及不同类型的对象时采用以下术语：

• "Group", "FoF Group", and "FoF Halo" all refer to halos.
  "Group"、"FoF Group"和"FoF Halo"均指代 halos。
• "Subgroup", "Subhalo", and "Subfind Group" all refer to subhalos.
  “Subgroup”、“Subhalo”和“Subfind Group”均指代子晕。
• The first (most massive) subgroup of each halo is the "Primary Subgroup" or "Central Subgroup".
  每个晕圈中的第一个（质量最大）子群是“Primary Subgroup”或“Central Subgroup”。
• All other following subgroups within the same halo are "Secondary Subgroups", or "Satellite Subgroups".
  同一光环内的所有其他后续子群均为“次级子群”或“卫星子群”。

FoF Halos

The Group fields are derived with a standard friends-of-friends (FoF) algorithm with linking length b=0.2$b=0.2$. The FoF algorithm is run on the dark matter particles, and the other types (gas, stars, BHs) are attached to the same groups as their nearest DM particle. The fields for the FoF halo catalog are described in the following table (all fields are float32 unless otherwise specified):
Group 字段是通过标准的 friends-of-friends (FoF)算法生成的，链接长度为 b=0.2$b=0.2$ 。FoF 算法在暗物质粒子上运行，其他类型（气体、恒星、黑洞）则附加到与其最近的 DM 粒子相同的组中。FoF 晕目录的字段如下表所述（除非另有说明，所有字段均为 float32）：

Subfind Subhalos (Galaxies)
Subfind 子晕（星系）

The Subhalo fields are derived with the Subfind algorithm, with modifications to add additional baryonic properties to each subhalo entry. Descriptions of all fields in this subhalo catalog are given in the following table. Note that for all mass calculations by type, wind phase cells are counted as gas.
Subhalo 字段是通过 Subfind 算法导出的，并进行了修改，为每个 subhalo 条目添加了额外的重子属性。以下表格中给出了此 subhalo 目录中所有字段的描述。请注意，对于所有按类型计算的质量，风相单元被视为气体。

Note: all quantities restricted to some fraction (0.5, 1.0, or 2.0) of the stellar half mass radius are by definition zero if there are no stars in subhalo.
注意：如果子晕中没有恒星，则所有限制在恒星半质量半径的某个分数（0.5、1.0 或 2.0）内的量按定义为零。

Header

The following table describes the Header group of each groupcat file:
下表描述了每个 groupcat 文件的 Header 组：

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3. Important Additional Files
3. 重要附加文件

Offsets

The "offsets" files are simply helpers which facilitate rapid loading of data. If you want to use the helper scripts for working with the actual data files (snapshots or group catalogs) on your local machine, then it is required that you download the offset file(s) for the snapshot(s) you are interested in working with.
“offsets”文件只是辅助工具，便于快速加载数据。如果您想在本地机器上使用辅助脚本来处理实际的数据文件（快照或组目录），则需要下载您感兴趣的快照的 offset 文件。

If you only work with the web-based tools and API (e.g. only analyze particle-level data using cutouts), then downloading offset files is not required.
如果您仅使用基于 Web 的工具和 API（例如仅使用 cutouts 分析粒子级数据），则无需下载 offset 文件。

Note that in Illustris, offsets were embedded inside the group catalog files for convenience. In TNG however, we have kept offsets as a separate HDF5 file (one per snapshot), which need to be downloaded as required. Most simply, you can think of offsets as describing where in the group catalog files to find a specific halo/subhalo, and where in the snapshot files to find the start of the particles of a given halo/subhalo.
请注意，在 Illustris 中，为了方便起见，偏移量被嵌入到了群组目录文件中。然而在 TNG 中，我们将偏移量保留为单独的 HDF5 文件（每个快照一个），需要时下载即可。最简单地说，你可以将偏移量理解为描述在群组目录文件中找到特定光环/子光环的位置，以及在快照文件中找到给定光环/子光环粒子起始位置的信息。

The following table describes the fields in each offsets file.
下表描述了每个 offsets 文件中的字段。

The "simulation.hdf5" File
"simulation.hdf5" 文件

Each run has a single file available called simulation.hdf5 which is purely optional, for convenience, and not required by any of the helper scripts or examples. Its purpose is to encapsulate all data of an entire simulation into a single file. They can be downloaded on each simulation page.
每次运行都有一个名为 simulation.hdf5 的单一文件，这完全是可选的，为了方便起见，任何辅助脚本或示例都不需要它。其目的是将整个模拟的所有数据封装到一个文件中。它们可以在每个模拟页面上下载。

To accomplish this, we make advantage of a new feature of the HDF5 library called "virtual datasets". You can think of a virtual dataset as a collection of symbolic links to one or more datasets in other HDF5 file(s), where these symlinks can refer to subsets of a dataset, in either the source or target of the link. The simulation.hdf5 is thus a large collection of "links", which refer to other files which actually contain data. In order to use it, you must therefore also download the necessary files (e.g. of snapshots, group catalogs, or supplementary data catalogs).
为了实现这一点，我们利用了 HDF5 库的一个新功能，称为“虚拟数据集”。你可以将虚拟数据集视为指向其他 HDF5 文件中一个或多个数据集的符号链接集合，这些符号链接可以引用数据集的子集，无论是在链接的源还是目标中。因此，simulation.hdf5 是一个“链接”的大集合，这些链接指向实际包含数据的其他文件。为了使用它，你必须下载必要的文件（例如快照、群组目录或补充数据目录）。

What does it let us do? First of all, no more file chunks! The fact that a snapshot or group catalog is split over multiple files is no longer relevant. Loading becomes very simple:
它让我们能做什么？首先，不再有文件块！快照或群组目录被分割成多个文件的事实不再相关。加载变得非常简单：

where gas_cell_mass then contains the masses of every gas cell in the entire z=0 snapshot, while subhalo_size_stars contains the stellar half mass radii of all the subhalos in the z=0 group catalog. The simulation.hdf5 also makes loading the particles of a given halo or subhalo trivial:
其中， gas_cell_mass 包含整个 z=0 快照中每个气体单元的质量，而 subhalo_size_stars 则包含 z=0 组目录中所有子晕的恒星半质量半径。simulation.hdf5 还使得加载给定晕或子晕的粒子变得非常简单：

where dm_positions would then contain the dark matter coordinates of every DM particle belonging to halo index 400 of the given simulation.
其中 dm_positions 将包含给定模拟中属于晕指数 400 的每个暗物质粒子的暗物质坐标。

Finally, supplementary data catalogs (either those we provide, or similar computations you have run yourself) can be virtually inserted at any time as datasets in snapshots or group catalogs. This provides a nice, clean way to organize post-processing computations which result in value-added values for halos, subhalos, or individual particles/cells. You can then load such catalogs with the same scripts (and same syntax) as 'original' snapshot/group catalog fields.
最后，补充数据目录（无论是我们提供的，还是您自己运行的类似计算）可以随时作为数据集虚拟插入到快照或组目录中。这为组织后处理计算提供了一种简洁、清晰的方式，这些计算会为晕、子晕或单个粒子/细胞生成增值值。然后，您可以使用与“原始”快照/组目录字段相同的脚本（和相同的语法）加载此类目录。

There are two requirements to use a simulation.hdf5 file:
使用 simulation.hdf5 文件有两个要求：

• Actual data files must be organized exactly as suggested and described in the example scripts tutorial (i.e., an "output" directory containing a "snapdir_099" subdirectory and a "group_099" subdirectory, along with a "postprocessing" directory containing, among others, an "offsets" subdirectory).
  实际数据文件必须严格按照示例脚本教程中的建议和描述进行组织（即，一个包含“snapdir_099”子目录和“group_099”子目录的“output”目录，以及一个包含“offsets”子目录等的“postprocessing”目录）。
• HDF5 virtual datasets are a new feature, only supported by HDF5 version 1.10.x and later. This is not presently the default version installed on most clusters, which still use 1.8.x. You may have to install a newer version yourself, or request that your system administrator do so. Note! Files created with advanced features of the new HDF5 library series are not backwards compatible. The old 1.8.x series of HDF5 reaches end of life in 2019, so it is a good idea regardless to migrate. In Python, you will also need a fairly new version of h5py (e.g. 2.9.x).
  HDF5 虚拟数据集是一项新功能，仅由 HDF5 1.10.x 及更高版本支持。目前大多数集群上安装的默认版本仍然是 1.8.x。您可能需要自行安装较新的版本，或请求系统管理员进行安装。注意！使用新 HDF5 库系列的高级功能创建的文件不向后兼容。旧的 1.8.x 系列 HDF5 在 2019 年已结束生命周期，因此无论如何迁移都是一个好主意。在 Python 中，您还需要一个较新版本的 h5py（例如 2.9.x）。

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4. Merger Trees

Merger trees have been created for the various Illustris simulations using SubLink (Rodriguez-Gomez+ 2015) and LHaloTree (Springel+ 2005). The LHaloTree are essentially identical to the primary trees of the Millennium and Aquarius simulations, but in HDF5 format. Merger tree formats in TNG are identical to Illustris, with additional fields from the group catalogs also present. In the population average sense the different merger trees give similar results. In more detail, the exact merger history or mass assembly history for any given halo may differ. For any given science goal, one type of tree may be more or less useful, and users are free to use whichever they prefer. These codes are all included in the Sussing Merger Trees comparison project (Srisawat+ 2013).
针对各种 Illustris 模拟，已使用 SubLink（Rodriguez-Gomez+ 2015）和 LHaloTree（Springel+ 2005）创建了合并树。LHaloTree 与 Millennium 和 Aquarius 模拟的主树基本相同，但采用 HDF5 格式。TNG 中的合并树格式与 Illustris 相同，并包含来自群组目录的额外字段。在总体平均意义上，不同的合并树给出相似的结果。更详细地说，对于任何给定的晕，确切的合并历史或质量组装历史可能有所不同。对于任何特定的科学目标，一种类型的树可能或多或少有用，用户可以自由选择他们喜欢的类型。这些代码都包含在 Sussing 合并树比较项目（Srisawat+ 2013）中。

The following figure shows a schematic of the structure of both the SubLink and LHaloTree merger trees. It is not necessary to understand the complete details of the trees to practically use them. In particular, the only critical links are the 'descendant' (black), 'first progenitor' (green), and 'next progenitor' (red) associations. These are shown for all tree nodes in the diagram. For their exact definitions, see the tables below. Walking back in time following along the main (most massive) progenitor branch consists of following the first progenitor links until they end (value equals -1). Similarly, walking forward in time along the descendants branch consists of following the descendant links until they end (value equals -1), which typically occurs at z=0$z=0$. The full progenitor history, and not just the main branch, requires following both the first and next progenitor links. In this way the user can identify all subhalos at a previous snapshot which have a common descendant. Examples of walking the tree are provided in the example scripts.
下图展示了 SubLink 和 LHaloTree 合并树结构的示意图。在实际使用中，无需完全理解这些树的全部细节。特别是，唯一关键的联系是“后代”（黑色）、“第一祖先”（绿色）和“下一祖先”（红色）关联。图中展示了所有树节点的这些关联。有关它们的精确定义，请参见下表。沿着主（最庞大）祖先分支回溯时间，就是跟随第一祖先链接直到它们结束（值等于-1）。同样，沿着后代分支向前追溯时间，就是跟随后代链接直到它们结束（值等于-1），这通常发生在 z=0$z=0$ 。完整的祖先历史，而不仅仅是主分支，需要同时跟随第一和下一祖先链接。通过这种方式，用户可以识别在先前快照中具有共同后代的所有子晕。在示例脚本中提供了遍历树的示例。

Caption. Schematic diagram of the merger tree structure for both SubLink and LHaloTree. Both algorithms connect subhalos across different snapshots in the simulation. Rows indicate discrete snapshots, with time increasing downwards towards redshift zero (the horizontal axis is arbitrary). Green circles represent subhalos (the nodes of the merger tree), while beige boxes indicate the grouping of the subhalos into their parent FoF groups. The most important links are for the descendant (black), first progenitor (green), and next progenitor (red), which are shown for all subhalos. The root descendant (purple), last progenitor (blue), and main leaf progenitor (orange) links exist only for the SubLink trees, and for simplicity these last three link types are shown only for subhalos 5, 7, and 19 (darker striped circles).
标题。SubLink 和 LHaloTree 的合并树结构示意图。两种算法在模拟中连接不同快照下的子晕。行表示离散的快照，时间向下递增，朝向红移零（水平轴是任意的）。绿色圆圈代表子晕（合并树的节点），而米色框表示将子晕分组到其父 FoF 组中。最重要的链接是后代（黑色）、第一前身（绿色）和下一个前身（红色），这些链接显示在所有子晕上。根后代（紫色）、最后前身（蓝色）和主叶前身（橙色）链接仅存在于 SubLink 树中，为简单起见，最后三种链接类型仅显示在子晕 5、7 和 19 上（较深的条纹圆圈）。

The number inside each circle from the figure is the unique ID (within the whole simulation) of the corresponding subhalo, which is assigned in a depth-first fashion. Numbering also indicates the on-disk storage ordering for the SubLink trees, which adopt the approach of Lemson+ (2006). For example, the main progenitor branch (from 5-7 in the example) and the full progenitor tree (from 5-13 in the example) are both contiguous subsets of each merger tree field, whose location and size can be calculated using these links. The ordering within a single tree in the LHaloTree is not guaranteed to follow this scheme.
图中每个圆圈内的数字是对应子晕在整个模拟中的唯一 ID，该 ID 以深度优先的方式分配。编号还表示 SubLink 树的磁盘存储顺序，该顺序采用了 Lemson+（2006）的方法。例如，主要祖先分支（示例中为 5-7）和完整祖先树（示例中为 5-13）都是每个合并树字段的连续子集，其位置和大小可以使用这些链接计算得出。LHaloTree 中单个树的顺序不保证遵循此方案。

The 'root descendant' (purple), 'last progenitor' (blue), and 'main leaf progenitor' (orange) links exist only for the SubLink trees. For simplicity, these last three link types are shown only for nodes 5, 7, and 19 (darker striped circles). Using these links is optional, but allows efficient extraction of main progenitor branches, subtrees (i.e., the set containing a subhalo and "all" its progenitors), "forward" descendant branches, and other subsets of the tree. For their full definitions, see the following table.
'root descendant'（紫色）、'last progenitor'（蓝色）和'main leaf progenitor'（橙色）链接仅存在于 SubLink 树中。为简化起见，最后这三种链接类型仅显示在节点 5、7 和 19（较深的条纹圆圈）上。使用这些链接是可选的，但它们可以高效地提取主要祖先分支、子树（即包含一个子晕及其“所有”祖先的集合）、“向前”后代分支以及树的其他子集。有关它们的完整定义，请参见下表。

Each subhalo spans a "subtree" consisting of the subhalo itself and all its progenitors. As an example, the subhalos belonging to the subtree of subhalo 5 are shown in darker green in the figure. Other subhalos not belonging to this subtree are shown in lighter green, and their links are indicated with dashed arrows. In the SubLink trees, the subtree of any subhalo can be extracted easily using the 'last progenitor' pointer. As shown in the figure, since subhalo 13 is the 'last progenitor' of subhalo 5, the subtree of subhalo 5 consists of all subhalos with IDs between 5 and 13. Similarly, the main progenitor branch of any subhalo can be retrieved efficiently using the 'main leaf progenitor' link.
每个子晕跨越一个“子树”，由子晕本身及其所有前身组成。例如，图中属于子晕 5 的子树中的子晕以深绿色显示。不属于该子树的其他子晕以浅绿色显示，并用虚线箭头表示它们的链接。在 SubLink 树中，任何子晕的子树都可以使用“最后一个前身”指针轻松提取。如图所示，由于子晕 13 是子晕 5 的“最后一个前身”，子晕 5 的子树由 ID 在 5 到 13 之间的所有子晕组成。同样，任何子晕的主前身分支都可以使用“主叶前身”链接高效地检索。

Both SubLink and LHaloTree contain the links 'first subhalo in FoF group' (light brown dotted arrow) and 'next subhalo in FoF group' (dark brown dotted arrow), which connect subhalos that belong to the same FoF group. The FoF groups do not play a direct role in the construction of the merger tree. However, in SubLink, subhalos that belong to the same FoF group are also considered to be part of the same tree. As a result, two otherwise independent trees (based on the progenitor and descendant links) are considered to be the same tree if they are "connected" by a FoF group. This is exemplified in the figure by the FoF group containing subhalos 12, 16, and 20. This FoF group acts as a bridge between the left and right trees.
SubLink 和 LHaloTree 都包含“FoF 组中的第一个子晕”（浅棕色虚线箭头）和“FoF 组中的下一个子晕”（深棕色虚线箭头）的链接，这些链接连接属于同一 FoF 组的子晕。FoF 组在构建合并树中并不直接起作用。然而，在 SubLink 中，属于同一 FoF 组的子晕也被视为同一棵树的一部分。因此，如果两个原本独立的树（基于祖先和后代链接）通过 FoF 组“连接”在一起，它们就被视为同一棵树。这在图中通过包含子晕 12、16 和 20 的 FoF 组得到了例证。这个 FoF 组充当了左右树之间的桥梁。

SubLink

The SubLink algorithm constructs merger trees at the subhalo level. A unique descendant is assigned to each subhalo in three steps (see Rodriguez-Gomez+ 2015). First, descendant candidates are identified for each subhalo as those subhalos in the following snapshot that have common particles with the subhalo in question. Second, each of the descendant candidates is given a score based on a merit function that takes into account the binding energy rank of each particle. Third, the unique descendant of the subhalo in question is the descendant candidate with the highest score. Sometimes the halo finder does not detect a small subhalo that is passing through a larger structure, because the density contrast is not high enough. {\sc SubLink} deals with this issue by allowing some subhalos to skip a snapshot when finding a descendant. Once all descendant connections have been made, the main progenitor of each subhalo is defined as the one with the "most massive history" behind it.
SubLink 算法在子晕级别构建合并树。每个子晕的唯一后代通过三个步骤分配（参见 Rodriguez-Gomez+ 2015）。首先，为每个子晕识别后代候选者，这些候选者是在后续快照中与当前子晕有共同粒子的子晕。其次，根据一个考虑每个粒子结合能排名的评分函数为每个后代候选者打分。第三，当前子晕的唯一后代是得分最高的后代候选者。有时，晕查找器无法检测到穿过较大结构的小子晕，因为密度对比不够高。{\sc SubLink}通过允许一些子晕在寻找后代时跳过快照来解决这个问题。一旦所有后代连接建立完毕，每个子晕的主要前身被定义为具有“最庞大历史”的那个。

Note that this merger tree comes in two varieties: "dark-matter based" and "baryonic based". The dark-matter based tree is the fiducial choice, and has been publicly released as "SubLink". The baryonic based tree is called "SubLink_gal" and has not been publicly released for simplicity, although it is available upon request. While the two will largely give identical results, depending on scientific application, one might be more useful than the other.
请注意，此合并树有两种类型：“基于暗物质”和“基于重子物质”。基于暗物质的树是基准选择，已作为“SubLink”公开发布。基于重子物质的树称为“SubLink_gal”，为简化起见尚未公开发布，但可根据请求提供。虽然两者在大多数情况下会给出相同的结果，但根据科学应用的不同，其中一种可能比另一种更有用。

The SubLink merger tree is one large data structure split across several sequential HDF5 files named tree_extended.[fileNum].hdf5, where [fileNum] goes from e.g. 0 to 9 for the Illustris-1 run. These files store the data on a per tree basis, and therefore are completely independent from each other. More specifically, any two subhalos that are connected by any of the pointers described in the SubLink table are guaranteed to belong to the same tree, and, therefore, their data is found in the same file. The following table lists the fields which are present in each file.
SubLink 合并树是一个大型数据结构，分布在多个连续的 HDF5 文件中，文件名为 tree_extended.[fileNum].hdf5 ，其中 [fileNum] 在 Illustris-1 运行中从 0 到 9。这些文件按树存储数据，因此彼此完全独立。更具体地说，任何通过 SubLink 表中描述的指针连接的两个子晕都保证属于同一棵树，因此它们的数据位于同一文件中。下表列出了每个文件中存在的字段。

LHaloTree

The LHaloTree algorithm is virtually identical to that used for the Millennium simulation, constructing trees based on subhalos instead of main halos, described fully in the supplementary information of Springel+ (2005). In short, to determine the appropriate descendant, the unique IDs that label each particle are tracked between outputs. For a given halo, the algorithm finds all halos in the subsequent output that contain some of its particles. These are then counted in a weighted fashion, giving higher weight to particles that are more tightly bound in the halo under consideration, and the one with the highest count is selected as the descendant. In this way, preference is given to tracking the fate of the inner parts of a structure, which may survive for a long time upon infall into a bigger halo, even though much of the mass in the outer parts can be quickly stripped. To allow for the possibility that halos may temporarily disappear for one snapshot, the process is repeated for Snapshot n to Snapshot n+2. If either there is a descendant found in Snapshot n+2$n+2$ but none found in Snapshot n+1, or, if the descendant in Snapshot n+1 has several direct progenitors and the descendant in Snapshot n+2 has only one, then a link is made that skips the intervening snapshot.
LHaloTree 算法与用于 Millennium 模拟的算法几乎相同，基于子晕而非主晕构建树，Springel+（2005）的补充信息中对此进行了详细描述。简而言之，为了确定合适的后代，算法在输出之间跟踪标记每个粒子的唯一 ID。对于给定的晕，算法会在后续输出中找到包含其部分粒子的所有晕。然后以加权方式对这些晕进行计数，给予在所考虑晕中更紧密束缚的粒子更高的权重，并选择计数最高的晕作为后代。通过这种方式，优先跟踪结构内部部分的命运，这些部分在落入更大晕后可能存活很长时间，尽管外部部分的大部分质量可能会迅速被剥离。为了允许晕可能暂时在某一快照中消失的情况，该过程会从 Snapshot n 重复到 Snapshot n+2。 如果在 Snapshot n+2$n+2$ 中找到了后代，但在 Snapshot n+1 中未找到，或者如果在 Snapshot n+1 中的后代有多个直接祖先，而在 Snapshot n+2 中的后代只有一个，则会创建一个跳过中间快照的链接。

The LHaloTree merger tree is one large data structure split across several HDF5 files named trees_sf1_99.[chunkNum].hdf5, where [chunkNum] goes from e.g. 0 to 511 for the Illustris-1 run. Within each file there are a number of groups named TreeX, where X is an integer which simply increases from zero to the number of tree groups in that file chunk. Note that a given TreeX group may contain subhalos spanning different FoF groups as well as snapshots, and to efficiently locate a specific subhalo at a specific snapshot (e.g z=0) the offsets can be used. The pair (SubhaloNumber,SnapNum) provides the indexing into the Subfind group catalog. The five other indices for each entry in a TreeX group (e.g. Descendant) index into that same group in the tree file. The following tables describe the fields. First, the Header group:
LHaloTree 合并树是一个大型数据结构，分布在多个名为 trees_sf1_99.[chunkNum].hdf5 的 HDF5 文件中，其中[chunkNum]从例如 0 到 511（对于 Illustris-1 运行）。在每个文件中，有多个名为 TreeX 的组，其中 X 是一个整数，从零增加到该文件块中的树组数量。请注意，给定的 TreeX 组可能包含跨越不同 FoF 组和快照的子晕，为了高效定位特定快照（例如 z=0）下的特定子晕，可以使用偏移量。对 (SubhaloNumber,SnapNum) 提供了对 Subfind 组目录的索引。TreeX 组中每个条目的其他五个索引（例如 Descendant ）索引到树文件中的同一组。下表描述了字段。首先是 Header 组：

TreeX Groups:

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5. Supplementary Data Catalogs
5. 补充数据目录

"Supplementary" or "post-processing" catalogs have been created by various members of the TNG team, extended collaboration, and general public. They typically contain valuable (and often computationally expensive) calculations, which are released here in the hope that they will accelerate the science and productivity of all users of the TNG data. Most often, they are catalogs of physical quantities calculated for halos or subhalos, at one or more snapshots. Each will have a somewhat different structure, so one should carefully read the provided documentation. To use any of these catalogs, one should download the respective HDF5 file(s) and directly load them using e.g. h5py.
"补充"或"后处理"目录已由 TNG 团队的各个成员、扩展合作者以及公众创建。它们通常包含有价值（且通常计算成本高昂）的计算结果，发布在此处是希望它们能加速所有 TNG 数据用户的科学研究和生产力。最常见的是，它们是在一个或多个快照下为 halo 或 subhalo 计算的物理量目录。每个目录的结构会有所不同，因此应仔细阅读提供的文档。要使用这些目录中的任何一个，应下载相应的 HDF5 文件，并直接使用例如 h5py 加载它们。

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(a) Tracer Tracks

The Monte Carlo tracer particles can be difficult to work with, and this dataset aims to enable some simple use cases. In particular, a number of catalogs are available, each of which contains information on all the tracers in the simulation which are contained within (all) FoF halos at redshift zero. Tracers have been re-arranged into "group order", such that you can quickly load the tracers which belong to a given subhalo or halo. Further, their evolution through time has been saved, and these "tracks" through time are immediately available, such that one does not need to load previous snapshots.
Monte Carlo 示踪粒子可能难以处理，而此数据集旨在支持一些简单的用例。特别是，提供了多个目录，每个目录都包含模拟中所有位于红移零处（所有）FoF 晕内的示踪粒子的信息。示踪粒子已被重新排列为“组顺序”，以便您可以快速加载属于给定子晕或晕的示踪粒子。此外，它们随时间演化的过程已被保存，这些“轨迹”可以立即使用，因此无需加载先前的快照。

A series of files with the common base "tr_all_groups_99_*" indicating that each contains information on all the tracers in the simulation which are contained within FoF halos at snapshot 99 (z=0). The 'meta' file contains the IDs of the tracers (and their parents), which are ordered according to their halo/subhalo membership, exactly following the group-ordering of the particles in the snapshots. Therefore, the order of the ParentIDs list is the same as those IDs appear in the snapshots (although with possible omissions or duplications if a parent has no, or multiple, tracers). The 'meta' file also contains the lengths and offsets, for both halos and subhalos (in exact analogy to GroupLenType, SubhaloLenType, offsets/Group/SnapByType, and offsets/Subhalo/SnapByType). This allows the child tracers of any halo or subhalo (at z=0) to be selected.
一系列以共同基础“tr_all_groups_99_*”命名的文件，表示每个文件都包含模拟中所有追踪器的信息，这些追踪器位于快照 99（z=0）时的 FoF 晕中。'meta'文件包含追踪器（及其父级）的 ID，这些 ID 根据其晕/子晕成员关系排序，完全遵循快照中粒子的群组排序。因此，ParentIDs 列表的顺序与这些 ID 在快照中出现的顺序相同（尽管如果父级没有追踪器或有多个追踪器，可能会出现遗漏或重复）。'meta'文件还包含晕和子晕的长度和偏移量（与 GroupLenType、SubhaloLenType、offsets/Group/SnapByType 和 offsets/Subhalo/SnapByType 完全类似）。这使得可以选择任何晕或子晕（在 z=0 时）的子追踪器。

Note that tracers are stored separately by parent type (at z=0), either gas, stars (pt4), or bhs.
请注意，tracers 按父类型（在 z=0 时）单独存储，包括 gas、stars (pt4) 或 bhs。

All other 'data' files (e.g. temp, pos, ...) contain the evolutionary tracks of this property, for the identical set of tracers through time, recorded for all snapshots which contain tracers. For TNG100 these are the 20 full snapshots, while for TNG50 and TNG300 these are all 100 snapshots.
所有其他“数据”文件（例如 temp、pos 等）包含该属性的演化轨迹，针对相同的一组示踪物随时间变化，记录在所有包含示踪物的快照中。对于 TNG100，这些是 20 个完整快照，而对于 TNG50 和 TNG300，这些是所有 100 个快照。

For example, the temperature history of the third tracer of Halo=10 in a BH parent is (python indexing convention pseudocode):
例如，Halo=10 的第三个示踪剂在 BH 父级中的温度历史记录为（python 索引约定伪代码）：

while the evolution of distance from the halo center, in units of the virial radius, of all tracers in Subhalo=20 in star parents is given by:
而 Subhalo=20 中所有恒星母体的示踪物距晕中心距离的演化，以维里半径为单位，由下式给出：

If you want all tracers in a halo/subhalo regardless of their z=0 parent type, then you must extract and combine the three types. If you want a subset of tracers of a given halo/subhalo at z=0 (e.g. only those in some radial shell), you must intersect the set of these IDs with the subset of meta.hdf5/ParentIDs for that halo/subhalo (or equivalently, with the entirety of meta.hdf5/ParentIDs, the only penalty being speed) and use the resulting indices.
如果你想要一个晕/子晕中的所有追踪器，无论它们的 z=0 父类型是什么，那么你必须提取并组合这三种类型。如果你想要一个给定晕/子晕在 z=0 时的追踪器子集（例如，仅在某些径向壳中的那些），你必须将这些 ID 集合与该晕/子晕的 meta.hdf5/ParentIDs 子集相交（或者等效地，与 meta.hdf5/ParentIDs 的全部相交，唯一的代价是速度），并使用生成的索引。

For complete definitions of each value, see the following table and Nelson+ (2019b) where they were first used and presented. Citation to this paper is requested if you use these data catalogs. For more information and examples related to the Monte Carlo tracer particles, see Genel+ (2013), Nelson+ (2013), and Nelson+ (2015).
有关每个值的完整定义，请参见下表以及首次使用和展示这些值的 Nelson+ (2019b)。如果您使用这些数据目录，请引用该论文。有关蒙特卡洛示踪粒子的更多信息和示例，请参见 Genel+ (2013)、Nelson+ (2013)和 Nelson+ (2015)。

Simulation and snapshot coverage:
模拟和快照覆盖范围：

• Currently available for the 3 resolution levels of TNG100: TNG100-1, TNG100-2, TNG100-3.
  目前可用于 TNG100 的 3 个分辨率级别：TNG100-1、TNG100-2、TNG100-3。
• All tracers in all parent types (gas cells, stars, and black holes), in all FoF halos at z=0$z=0$.
  所有父类型（气体单元、恒星和黑洞）中的所有示踪物，在所有 FoF 晕中，在 z=0$z=0$ 。
• For each, time tracks have twenty entries, corresponding to the twenty "full" snapshots in TNG100.
  对于每一个，时间轨迹都有二十个条目，对应于 TNG100 中的二十个“完整”快照。

The contents of the 'meta' file are:
'meta' 文件的内容是：

For the data files, all values which are computed with respect to evolving halo properties use the Sublink tree. Tracers are associated with the central subhalo of the FoF halo they belong to at z=0, and the main progenitor branch (MPB) of that subhalo is used backwards in time. If the MPB is untracked at a snapshot, these values (rad_rvir,vrad,angmom) are set to NaN at that snapshot. Values with respect to the subhalo center use SubhaloPos (maximally bound particle position), while those with respect to the subhalo velocity uses the mass-weighted mean velocity of all star particles in the subhalo (if the subhalo has no stars, these values are then recorded as NaN).

The structure of the data files is:

Important note! These files are very large. For TNG100, the one-dimensional data files (e.g. temp, entr, vrad) are ~300 GB each. Therefore, functionality has been added to the data access API to enable the retrieval of tracer tracks on a per-halo or per-subhalo basis. In particular, an API request for a halo/subhalo cutout, of particles/cells from the snapshot can specity tracer_tracks as the 'particle type', together with any of the dataset names above (namely, TracerIDs, ParentIDs, temp, entr, and so on). For example, whereas a normal cutout request for the positions of all gas cells of halo ID 1000 in TNG100-1 at redshift zero would be:

https://www.tng-project.org/api/TNG100-1/snapshots/99/halos/1000/cutout.hdf5?gas=Coordinates

A cutout request for the temperature tracks of all the tracers belonging to that halo would be:

https://www.tng-project.org/api/TNG100-1/snapshots/99/halos/1000/cutout.hdf5?tracer_tracks=temp

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(b) Star Formation Rates

A catalog of time-averaged, rather than instantaneous, star formation rates of galaxies. To do so the SFRs are derived the stellar particles actually produced across different time spans, using their initial mass at birth. This is in contrast to all values in the group/subhalo catalogs, which are instantaneous values (measured from the gas cells). The time-averaged methodology, across a given period of Myr or Gyr, better reflects the values obtained via various observational tracers. For complete definitions on the calculation of each value, see the following table, Donnari+ (2019), and Pillepich+ (2019) where they were first presented. Citation to these two papers is requested if you use these data catalogs.

Simulation and snapshot coverage:

• Available for all baryonic simulations: TNG50-1, TNG50-2, TNG50-3, TNG50-4, TNG100-1, TNG100-2, TNG100-3, TNG300-1, TNG300-2, TNG300-3, Illustris-1, Illustris-2, Illustris-3.
• All snapshots/redshifts.
• Restricted to subhalos with a reasonable number of stellar particles (>~ 100).

For all measurements, time intervals {X} exist for X = 10, 50, 100, 200, 1000 (Myr).

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(c) Stellar Circularities, Angular Momenta, Axis Ratios

A catalog of circularities, angular momenta and axis ratios of the stellar component of galaxies. For complete definitions on the calculation of each value, see the following table and Genel+ (2015), where they were first presented. Citation to that paper is requested if you use these data catalogs.

The first four quantities are calculated after alignment with the angular momentum vector of the stars within 10 times the stellar half-mass radius, and measure the quantities inside that radius. The Circ* fields are based on the distribution of the circularity parameter ϵ$ϵ$. First the system is rotated such that the z-axis is aligned with the angular momentum vector as described above. Then, for every stellar particle with specific angular momentum Jz$J_z$ we calculate ϵ=JzJ(E)$ϵ=\frac{J_z}{J(E)}$ where J(E)$J(E)$ is the maximum angular momentum of the stellar particles at positions between 50 before and 50 after the particle in question in a list where the stellar particles are sorted by their binding energy (=Ugrav+v2$=U_{\mathrm{g}\mathrm{r}\mathrm{a}\mathrm{v}}+v^2$).

Simulation and snapshot coverage:

• Available for all baryonic simulations: TNG50-1, TNG50-2, TNG50-3, TNG50-4, TNG100-1, TNG100-2, TNG100-3, TNG300-1, TNG300-2, TNG300-3, Illustris-1 (all snapshots/redshifts).
• Restricted to subhalos with stellar mass M⋆>3.4×108M⊙$M^{\star }>3.4\times {10}^8{M}_{\odot }$ (TNG50/TNG100/Illustris) or M⋆>1010M⊙$M^{\star }>{10}^{10}{M}_{\odot }$ (TNG300), measured within the usual twice stellar half mass radius, and at least 100 stars.

Note: For original Illustris (only), the "SpecificAngMom" and "Circ*" fields are available for snapshots 13 through 135, while the "*MassTensor*" fields are available for snapshots 38 through 135.

Note: In addition to the values measured within 10RE$10R_E$, the "SpecificAngMom" and "Circ*" fields are also computed including all stars in the subhalo. These are available as the _allstars datasets.

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(d) Subhalo Matching Between Runs

The possibility exists to cross-match subhalos between:

• (i) matched baryonic and dark matter only runs (e.g. TNG100-1 and TNG100-1-Dark) runs, at the same resolution.
• (ii) two baryonic realizations of the same box at different resolutions (e.g. TNG100-1 and TNG100-2)
• (iii) two simulations of the same box with different physical models (e.g. TNG100-1 and Illustris-1)

All baryonic runs have complete matching catalogs to their dark matter only counterparts, the first option (i) above.

These are data products from: Rodriguez-Gomez+ (2015; for SubLink), and Nelson+ (2015; for LHaloTree). Citation to these papers is requested if you use this data.

Simulation and snapshot coverage:

• All baryonic runs at all resolutions, all snapshots, all subhalos:
• TNG50-1, TNG50-2, TNG50-3, TNG50-4.
• TNG100-1, TNG100-2, TNG100-3.
• TNG300-1, TNG300-2, TNG300-3.

Data format: a single file subhalo_matching_to_dark.hdf5 for each simulation. Each contains one hundred groups named Snapshot_N. Within each group are two arrays, each with the same size, equal to the number of subhalos at the corresponding snapshot. The two arrays provide the results of two different matching algorithms, and should for the most part provide the same answer. Each array gives integer indices, whose value is the corresponding index of the matched subhalo in the DM only run. If no suitable match exists, a value of -1 is present for that subhalo index.

• The first array SubhaloIndexDark_LHaloTree is based on the LHaloTree matching algorithm. The matching is bidirectional, i.e. TNG <-> DMO. In each case, the best subhalo candidate is chosen as that with the largest number of matching DM particles (α=0$\alpha =0$). Only if the candidate in each direction agrees (bijective), then these matches are saved.
• The second array SubhaloIndexDark_SubLink is based on the SubLink weighting algorithm. The direction of the matching is TNG -> DMO, i.e. for each subhalo in the baryonic physics box a best match is found in the DMO run.

The second two types (ii) and (iii) of matching catalogs (between different resolution levels, and between TNG100 and original Illustris), will be available soon.

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(e) Stellar Projected Sizes

A catalog of stellar "sizes", mostly half-light radii, all in 2D projection. For more details of the modeling see Genel+ (2018), where they were first presented. Citation to that paper is requested if you use these data catalogs.

Simulation and snapshot coverage:

• Available for all baryonic simulations: TNG50-1, TNG100-1 and TNG300-1.
• Eight snapshots: z=0, 0.5, 1.0, 1.5, 2.0, 3.0, 4.0, 5.0.
• Restricted to subhalos with stellar mass M⋆>3×108M⊙$M^{\star }>3\times {10}^8{M}_{\odot }$ measured within the usual twice stellar half mass radius, and at least 100 stars.

There is one file for every snapshot, containing a single dataset /Rhalf/, which is a 10 x 5 x Nsubs shaped array. Namely, for each subhalo there are 10x5 different values of half-something radii, as follows:

• Along the dimension of length 10, the values correspond to different somethings, in order, as follows: half-mass, half-star-formation-rate, half-light in the 8 bands of the “stellar photometrics”, namely U, B, V, K, g, r, i, z. Note that the impact of dust attenuation/scattering is not taken into account.
• Along the dimension of length 5, the values correspond to projections along various lines of sight, in order, as follows: face-on, largest edge-on, smallest edge-on, random edge-on, box z-axis, where:
• The face-on direction is set according to the moment of inertia tensor of the star-formation distribution within 2R1/2,⋆$2R_{1/2,\star }$ (unless there are fewer than 50 star-forming cells, in which case it is according to the moment of inertia tensor of the stellar mass distribution within R1/2,⋆$R_{1/2,\star }$.
• All three edge-on directions are from lines of sights that are perpendicular to the face-on direction. The largest and smallest edge-on directions mean the particular such lines of sight that produce the largest/smallest, respectively, projected radii for the star-formation distribution within 2R1/2,⋆$2R_{1/2,\star }$. The random edge-on direction is indeed at a random line of sight within the "edge-on plane".
• For a "random" angle, choose the projection along the box z-axis, which is of course "random" with respect to each and every individual galaxy, since there is no preferred direction to the simulation.

All units are physical kpc.

Note: a value of -1 indicates that the subhalo falls outside of the selection described above, and no data is available for this object.

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(f) Blackhole Mergers and Details

This catalog is comprised of two data sets: 'mergers' and 'details'. The mergers file contains a record of each BH-BH merger in the simulation. The details file contain properties of each BH at significantly higher time resolution than the snapshots. In both cases the information is extracted from output files separate from the snapshots, and so represents additional data which is otherwise not available from the snapshots alone. Here we distinguish the two BHs which participate in the merger as 'in' and 'out' BH. The difference, which during the simulation is chosen randomly by the code, is which BH ID number persists along with the remnant after the merger. The 'out' BH survives after the merger, increased in mass by that of the 'in' BH--which no longer exists after the merger event.

There exists one blackhole_mergers.hdf5 and one blackhole_details.hdf5 per baryonic run. All datasets corresponding to physical values are in code units, with masses in units of 1010M⊙/h${10}^{10}{M}_{\odot }/h$, mass accretion rates in units of 10.22M⊙/yr$10.22M_{\odot }/\mathrm{y}\mathrm{r}$, gas densities in units of (1010M⊙/h)/(ckpc/h)3$({10}^{10}{M}_{\odot }/h)/(\mathrm{c}\mathrm{k}\mathrm{p}\mathrm{c}/\mathrm{h}{)}^3$, and gas sound speeds in units of km/s$\mathrm{k}\mathrm{m}/\mathrm{s}$. They were generated with the illustris_blackholes code. Citation recommmended to Kelley et al. (2016) and Blecha et al. (2016) as appropriate.

Simulation and snapshot coverage:

• Available for all TNG baryonic runs, as well as all original Illustris baryonic runs.
• Black hole mergers: TNG50-1, TNG50-2, TNG50-3, TNG50-4, TNG100-1, TNG100-2, TNG100-3, TNG300-1, TNG300-2, TNG300-3.
• Black hole details: TNG50-1, TNG50-2, TNG50-3, TNG50-4, TNG100-1, TNG100-2, TNG100-3, TNG300-1, TNG300-2, TNG300-3.
• IMPORTANT NOTE: For both the mergers and details files, there are a few small missing data gaps. In general these files are fragile and may contain inconsistencies. In TNG100-1, this includes redshift periods [0.96 - 0.98], [1.18 - 1.20], [1.27 - 1.40], [2.06 - 2.48]. For Illustris-1, data is missing in the redshift range from approximately z = 0.14 to z = 0.38, where roughly half of the BH data is missing, except at the higher-z end of the range, where nearly all of the mergers are missing around snapshots 110-111. All other runs are unaffected. This information was lost to data corruption and cannot be recovered, and appropriate care should be taken in analysis of this data.

Blackhole mergers:

Blackhole details:

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(g) Stellar Assembly

This large catalog contains information about the stellar assembly of all galaxies across all snapshots, focusing on in situ vs. ex situ stellar mass growth, the contribution from star formation before or after infall, the role of major and/or minor mergers and flyby encounters. There exists one stellar_assembly.hdf5 file per baryonic run. All datasets are masses, and are given in code units, that is, 1010M⊙/h${10}^{10}{M}_{\odot }/h$. There is one group per snapshot, and within each group, all datasets have the same size, corresponding to exactly one entry per Subfind subhalo. Citation recommmended to Rodriguez-Gomez et al. (2015), Rodriguez-Gomez et al. (2016a), and/or Rodriguez-Gomez et al. (2016b) as appropriate. Further information and usage examples are available in these same papers.

Simulation and snapshot coverage:

• Available for all baryonic simulations:
• TNG50-1, TNG50-2, TNG50-3, TNG50-4, TNG100-1, TNG100-2, TNG100-3, TNG300-1, TNG300-2, TNG300-3, Illustris-1, Illustris-2, Illustris-3, and TNG-Cluster.
• All snapshots and redshifts (in one file).
• All subhalos with nonzero stellar mass.

The 'galaxy' quantities above should satisfy the following invariants (up to rounding errors):

• StellarMassInSitu + StellarMassExSitu == StellarMassTotal
• StellarMassBeforeInfall + StellarMassAfterInfall + StellarMassFormedOutsideGalaxies == StellarMassExSitu
• StellarMassFromCompletedMergers + StellarMassFromOngoingMergers + StellarMassFromFlybys + StellarMassFormedOutsideGalaxies == StellarMassExSitu

The above descriptions make reference to two values computed for every star particle in the simulation, derived as follows (see references for more details):

• AccretionOrigin: A value which can take the following integer values: 0, 1, and 2 for ex situ stellar particles that were accreted from completed mergers (i.e., when the subhalo in which the stellar particle formed has already merged with the current subhalo), ongoing mergers (i.e., when the subhalo in which the stellar particle formed has not yet merged with the current subhalo, but will do so at a later snapshot in the simulation), and flybys (i.e., when the subhalo in which the stellar particle formed has not merged with the current subhalo, and will not do so at any future snapshot in the simulation), respectively; and -1 if not applicable (i.e., if the particle was formed in situ or if it was formed outside of any subhalo). NOTE: towards the end of the simulation, it becomes impossible to distinguish a flyby from an ongoing merger. Therefore, cases (1) and (2) are usually considered as being part of the same category: "stripped from surviving galaxies".
• MergerMassRatio: The stellar mass ratio of the merger in which a given ex-situ stellar particle was accreted (if applicable). The mass ratio is measured at the time when the secondary progenitor reaches its maximum stellar mass. NOTE: this quantity was calculated also in the case of flybys, without a merger actually happening.

A small caveat: the "subhalo switching" problem" can result in some galaxies having (spurious) ex situ fractions very close to 1 (say, if a satellite suddenly becomes a central, then most of its newly assigned mass will appear as ex situ). The number of galaxies this affects is negligible, but still noticeable in e.g. a scatter plot.

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(h) Subbox Subhalo List

This catalog describes the time-evolving intersection of the subhalos/merger trees with the subboxes. Allows the selection of objects of interest, which can then be traced at high time resolution using the snapshots of a given subbox. This enables science requiring high time resolution, and also visualizations of galaxy-scale evolution. This data was created in Nelson+ (2019b) and citation to that work is requested if you use this supplementary catalog.

Simulation and snapshot coverage:

• Available for all subboxes of all TNG baryonic runs (see download page for a given run for links).

Each simulation contains one file per subbox named subbox{N}_{snap}.hdf5, corresponding to subbox number {N} and the subhalo selection of all {nSubhalosFullSnap} at snapshot {snap} of the full box. Each contains the following fields:

Note that {nSubhalos} corresponds to the subset of subhalos which are ever inside the subbox. The 'SubLink' merger tree is used for all MPBs.

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(i) Molecular and atomic hydrogen (HI+H2) galaxy contents

This catalog contains post-processed modeling of atomic (HI) and molecular (H2) hydrogen, on a per subhalo (i.e. per galaxy) basis. The total mass of each component is available, as well as pre-computed radial profiles. Note that all results sum, by construction, over the gas cells gravitationally bound to each subhalo only. Citation recommmended to Diemer et al. (2018) and Diemer et al. (2019) as appropriate.

Simulation and snapshot coverage:

• Available for: TNG50-1, TNG100-1, TNG100-2, TNG300-1, and Illustris-1.
• For each, redshifts: z=0, z=0.5, z=1, z=1.5, and z=2 (five snapshots per run).

In many of the datasets, the placeholder {model}_{type} appears. Here, {model} refers to a model for the HI/H2 transition, and can be one of:

• L08 - Leroy et al. 2008
• GK11 - Gnedin & Kravtsov 2011
• K13 - Krumholz 2013
• GD14 - Gnedin & Draine 2014
• S14 - Sternberg et al. 2014

Each model was computed on a cell-by-cell basis (the "volumetric" method, {type} = vol) and in 2D projection (the "map" method, {type} = map). For the L08 model, the cell-by-cell method was found to be unphysical and the L08_vol data are not included in the release for that reason.

Due to the fundamentally different nature of the volumetric and projected calculations, the radial profiles are provided in three versions, denoted as {proj} below. Profiles of projected quantities can only be expressed in projected, 2D radii (they carry the suffix {proj} = map in the profile names listed below). The profiles of volumetric quantities are given in two versions, namely as a 3D profile (suffix {proj} = 3d) and projected onto the same plane as the maps from which projected quantities were generated (suffix {proj} = 2d). When integrating the profiles to get total quantities, one should multiply the suffix {proj} = map and suffix {proj} = 2d profiles with the bin area and the suffix {proj} = 3d profiles with the bin volume. When multiplying the profiles with each other (for example, to obtain the total HI or H2 mass profiles), one should always multiply profiles of the same projection type.

The galaxy selection was designed to be complete both in stellar and in gas mass, i.e., a galaxy needs to either exceed the minimum stellar OR the minimum gas mass. For the original Illustris and TNG100, those limits were both set to 2×108M⊙$2\times {10}^8{M}_{\odot }$. Please note that this is a rather aggressive limit, including galaxies that are resolved by only a few hundred particles. Depending on the application, it may well be wise to make more conservative mass cuts. For TNG300, the stellar mass cut is 5×1010M⊙$5\times {10}^{10}{M}_{\odot }$, the gas mass cut is 5×109M⊙$5\times {10}^9{M}_{\odot }$. The stellar mass cut was chosen to be relatively high to reduce the otherwise very large dataset, and because that stellar mass range is well covered by TNG100.

In the listings below, Ngal denotes the number of subhalos (galaxies) in the file, and Nbin the number of radial bins for the profiles.

In addition, the config/ group contains a number of metadata attributes giving details of the analysis procedure:

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(j) Barred Galaxies Properties and Evolution

Three catalogs are available which describe the existence, and properties, of galatic bars. They are from Rosas-Guevara+ (2020), Zhao+ (2020), and Lu+ (2024), respectively. Each is described below.

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The first catalog contains the properties of galaxy bars, and their evolution in time, of the disk galaxy sample analyzed in Rosas-Guevara+ (2020), to which citation is requested if you use this data.

Simulation and snapshot coverage:

• Available for: TNG100-1, redshift zero.
• Computed only for massive disk galaxies, defined as those with stellar mass M^* > 10^10.4 Msun, and with stellar (D/T + B/T) > 0.7, as determined by the kinematic circularity decomposition method of Genel+15.
• There are 270 galaxies which satisfy these criteria.

The first dimension of each array corresponds to a particular galaxy, and the second dimension to the 100 time snapshots. Each bar-related property is therefore given along the main progenitor branch of each galaxy. The only exception is the Bartype field with a length equal to the number of galaxies at z=0. In general, values equal to NaN mean that the calculation was not performed at this particular snapshot, and thus should be ignored. The available fields are:

This catalog was extended to the TNG50-1 simulation, as analyzed in Rosas-Guevara+ (2022), to which citation is requested if you use this data.

Simulation and snapshot coverage:

• Available for: TNG50-1 (six snapshots), z=0, 0.5, 1, 2, 3, 4.
• Computed only for massive disk galaxies, defined as those with stellar mass M^* > 10^10.0 Msun, and with stellar (D/T + B/T) > 1/2.
• There are 1062 galaxies (across all snapshots) which satisfy these criteria.

The available fields are:

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The second catalog contains measurements of bar properties of the galaxy sample analyzed in Zhao+ (2020), to which citation is requested if you use this data.

Simulation and snapshot coverage:

• Available for: TNG100-1, redshift zero.
• Relatively high-mass, disk galaxies only, defined as those with stellar mass M⋆>1010Msun$M_{\star }>{10}^{10}{\mathrm{M}}_{\mathrm{s}\mathrm{u}\mathrm{n}}$ (within 30 kpc), and with the κ_rot parameter >= 0.5, measuring the fraction of kinetic energy in ordered rotation, as defined by Sales+10.
• There are 1179 galaxies which satisfy this criterion.

The available fields are:

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The third catalog contains measurements of bar properties of the galaxy sample analyzed in Lu+ (2024), to which citation is requested if you use this data.

Simulation and snapshot coverage:

• Available for: TNG50-1, snaps 50 to 99, as well as for TNG100-1, snaps 40 to 99.
• Relatively high-mass, disk galaxies only, defined as those with stellar mass M⋆$M_{\star }$ from 1010.0${10}^{10.0}$ to 1011.1${10}^{11.1}$ (for TNG50-1), and 1010.4${10}^{10.4}$ to 1011.1${10}^{11.1}$ (for TNG100-1), in \rm{M}_{\rm sun}$ (within 30 kpc), and with the κ_rot parameter >= 0.5, measuring the fraction of kinetic energy in ordered rotation, as defined by Sales+10. These disk galaxies are selected at z=0$z=0$, and then the evolution and formation history of their bars is traced backwards.
• There are 1707 galaxies in TNG100-1 and 615 galaxies in TNG50-1.
• This data is introduced in Lu, Du, & Debattista (2024) where the authors investigate the factors affecting the presence of bars.

The available fields are:

The value of X is X = 1.4 for TNG100-1, and X = 1.4 or X = 0.6 for TNG50-1, meaning that the inner boundary of the ellipse fitting is X.

Note: if untracked at the snapshot or failed to fit, the corresponding value is -1.

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(k) SDSS ugriz and UVJ Photometry/Colors with Dust

This catalog contains synthetic stellar photometry (i.e. colors) including the effects of dust obscuration. These correspond to the fiducial dust model of Nelson+ (2018a) (i.e. Model C), to which citation is requested if you use this data. Two separate catalogs are available: one for SDSS ugriz (rest-frame) bands, and one for UVJ (rest-frame). The latter was used in the analysis of Donnari+ (2019).

For SDSS ugriz: Simulation and snapshot coverage:

• Available for: TNG100-1.
• Available for: TNG300-1.
• For each, redshifts: z=0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.7, 1.0, 1.5, 2.0, 3.0 (one file per snapshot).
• All subhalos.

For UVJ: Simulation and snapshot coverage:

• Available for: TNG100-1.
• Available for: TNG300-1.
• For each, redshifts: z=0, 0.75, 1.0, 1.75, 2.0, 2.2 (one file per snapshot).
• All subhalos.

In the single HDF5 file per snapshot, there are two datasets: subhaloIDs gives the list of subhalo indices which have been computed (this is redundant, and this array equals [0,1,2,...,nSubhalos-1] exactly.), and either Subhalo_StellarPhot_p07c_cf00dust_res_conv_ns1_rad30pkpc with a shape of [nSubhalos,8,12] (for ugriz), or Subhalo_StellarPhot_UVJ_p07c_cf00dust_res_conv_z_30pkpc with a shape of [nSubhalos,3] (for UVJ).

The dimensions 8 or 3 corresponds to photometric bands, in order: sdss_u, sdss_g, sdss_r, sdss_i, sdss_z, wfc_acs_f606w, des_y, jwst_f150w or u, v, 2mass_j. Note that the wfc, des, and jwst bands were for testing only and should not be used. The high redshift SDSS files have only 5 photometric bands saved, which are (in order): sdss_u, sdss_g, sdss_r, sdss_i, sdss_z.

For the SDSS ugriz catalogs, the dimension 12 corresponds to twelve different projection directions (i.e. observer view angles), since the dust attenuation mode is view-dependent. In general, one can simply take the first entry for each subhalo, or a random entry for each subhalo. For the UVJ catalogs, only one projection direction is computed (along the z-axis of the box).

The units of these datasets are always AB magnitudes, and the bands are always rest-frame. Check carefully if the magnitudes are apparent (usually the case), or absolute (e.g. at z=0). Only stars within a 3D radial aperture of 30 physical kpc are included.

Additional information is available in the header attributes of the HDF5 file.

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(l) SKIRT Synthetic Images and Optical Morphologies

This catalog contains synthetic images and the corresponding morphological measurements, including Gini-M20, CAS and MID statistics, as well as 2D Sersic fits. The full description of the synthetic images and measurements can be found in Rodriguez-Gomez+ (2019), to which citation is requested if you use this data. Full details are not repeated, for which the user is directed to the paper.

Synthetic images and measurements are available separately for: "pogs" and "sdss", designed to match Pan-STARRS and SDSS, respectively.

Simulation and snapshot coverage:

• Available for: TNG50-1, TNG100-1, and Illustris-1.
• For each, redshifts: z=0, z=0.05.
• Restricted to subhalos with (total) stellar mass M^* > 10^9.5 solar masses.

There are two ways to download this data.

• The entire dataset (for one survey/snapshot combination) can be downloaded as a single tar file (above).
• The FITS and PNG images can be downloaded separately for each subhalo for which they are available through the API, similar to the original Illustris FITS files. For example, /api/TNG100-1/snapshots/99/subhalos/397866/skirt/broadband_sdss.fits downloads the broadband FITS file matched to the SDSS survey, for the central subhalo of FoF group #500 in TNG100-1 at redshift zero.

In the single tar collection, the files "morphs_i.hdf5" and "morphs_g.hdf5" (and "morphs_r.hdf5" for SDSS only) contain statmorph morphological measurements in the observed i-band, g-band, (and r-band), respectively (using Pan-STARRS or SDSS filter curves, depending on the dataset), and "subfind_ids.txt" contains the associated subhalo IDs. For a description of the measurements, see Section 4 of Rodriguez-Gomez+ (2019). In general, only morphological measurements with flag == 0 are reliable. If interested in parameters derived from the Sérsic fits, then flag_sersic == 0 should be imposed as well. In addition, only measurements with S/N > 2.5 (included in the catalog as sn_per_pixel) should be trusted. See Section 5 of the paper, for more details.

The idealized synthetic images themselves are available in FITS format. The dimensions of each image are NxNx4, where N is the number of pixels in each dimension and the 4 layers correspond to the observed g,r,i,z broadband filters of Pan-STARRS or SDSS. Note that the SDSS z-band data should be used with caution (they are reasonable for morphologies, but not for magnitudes and colors), since the long-wavelength tail of the SDSS z filter curve extends beyond the wavelength range of the SKIRT runs (clipped at 0.95 microns in the rest frame).

These synthetic broadband images are "idealized", meaning that some realism may need to be added before analyzing them. Most importantly, they should be convolved with an adequate PSF (for most purposes, a 2D Gaussian with the same FWHM as the observations should suffice) and background shot noise should be added. In general, Gaussian noise with sigma_sky ~ 1/20 (1/10) for Pan-STARRS (SDSS) represents a good compromise between observational realism and detection strength. Note that the image units are electrons/s/pixel. For more details, see Section 3.4 of the paper.

In addition to the FITS files, PNG images are also available. These are analogous to Fig. 4 of Rodriguez-Gomez+ (2019), such that different panels show different morphological diagnostics. These figures can be used to quickly inspect the morphology of a given galaxy.

Notes: The z=0 images and measurements were created by assuming that the galaxies are actually located at z=0.0485 (this determines the pixel scale, etc.). Galaxy sizes (e.g. "rhalf", "sersic_rhalf", "rpetro", "rmax") are given in pixels. To convert to simulation units (ckpc/h), note that the scale of each pixel at z=0.0485 corresponds to 0.174 ckpc/h for Pan-STARRS and 0.276 ckpc/h for SDSS.

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2022 addition: KiDS Survey Mock Images. A new, third set of images were generated with the same procedure as in Rodriguez-Gomez et al. (2019), except that:

1. the field-of-view is fixed for all images (does not scale with galaxy size), and
2. neighboring galaxies (from the same FoF group) were included.

The image settings are consistent with the Kilo-Degree Survey (KiDS). In particular, each FITS file has 4 layers corresponding to OmegaCAM g,r,i,z filters.

Simulation and snapshot coverage:

• Available for: TNG50-1.
• Redshift: z=0.0337 (snapshot 96) only.
• Restricted to subhalos with (total) stellar mass M^* > 10^8.0 solar masses.

There are three projections for each galaxy (xy, yz, zx). The pixel scale: 0.2 arcsec/pixel, corresponding to 138.9 pc (physical) per pixel at z = 0.0337. The dimensions of each image are 240x240 pixels (33.34 kpc per side). Note that the most massive galaxies may extend beyond the FoV.

The image units are ADU/s, just like in the real survey, and the zeropoint is zero, i.e. mag = -2.5 * log10(data). The images are "idealized", i.e. they have not been convolved with a PSF and they do not include background or shot noise. See Section 2.4 from Guzmán-Ortega et al. (2022) for information on how to apply realism. Complete details are available in that paper, to which citation is requested if you use this dataset.

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(m) Disk Galaxy Kinematic Decompositions

This catalog contains mass fractions of galactic disk structures which have been kinematically identified and decomposed by applying the "auto-GMM" (Gaussian mixture model) technique. The full description of the synthetic images and measurements can be found in Du+ (2019) and Du+ (2020), to which citation is requested if you use this data.

Simulation and snapshot coverage:

• Available for: TNG100-1, redshift zero and TNG50-1, redshift zero only.
• Computed only for massive "disk galaxies", defined as those subhalos with a high relative fraction of their kinetic energy in ordered rotation (K_rot > 0.5, measured within 30 kpc), and high stellar mass (M^* > 10¹⁰ Msun for TNG100-1, and M^* > 10⁹ Msun for TNG50-1).
• There are 3931 subhalos in TNG100-1 (2831 in TNG50-1) which satisfy this criterion.

The classification 1 (cls1) decomposes each galaxy into a cold disk, warm disk, bugle, and halo. The classification 2 (cls2) isolates an additional structure with moderate rotation, but compact morphology, namely the disky bulge that is the counterpart of the so-called pseudo bulge in observations (see Du et al. 2020). The supplementary catalog file has the following fields:

Here {method} can have the values class1,class2, corresponding to the two classification techniques, and {aperture} can have the values 1re,3re,allstars, corresponding to using stars within 1 times r_e, 3 times r_e, or in the entire subhalo (where r_e is the 3D stellar half-mass radius).

Associated PNG or PDF images, showing the decomposed structures, can be downloaded here: PNG .tar.gz image set, or PDF .tar.gz image set. These archives contain the following directories:

• "total_level": images of all stars.
• "SD_level": images of the spheroidal and disky structures.
• "structures_level_cls1/2": images of the kinematic structures defined in Du+2020. cls1 and cls2 correspond to classifications 1 and 2, respectively.
• "components_level_cls1/2": images of the multiple Gaussian components from the auto-GMM, that correspond to sub-structures.

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(n) L-Galaxies Semi-Analytical Model

This catalog contains the results of the L-Galaxies semi-analytical model run on the TNG simulation volumes. Specifically, of the latest public version of this model, as described in Henriques+2015 (H15). The SAM itself is run on the merger trees of the dark matter only analog boxes of TNG100-1 and TNG300-1.

This catalog was produced in Ayromlou+ (2020), where these results were first presented, and to which citation is requested if you use this data.

Simulation and snapshot coverage:

• Available for: TNG100-1.
• Available for: TNG300-1.
• All snapshots, and all (L-Galaxies) galaxies, covering all TNG subhalos.

The outcome of L-Galaxies is a population of galaxies which reside within the halos and subhalos of TNG100-1-Dark or TNG300-1-Dark, respectively. These have been cross-matched to the subhalos of the baryonic TNG100-1 and TNG300-1 runs (as well as the subhalos in the corresponding -Dark runs). As a result, the galaxy properties predicted by L-Galaxies can be directly compared with those in TNG, on an object by object basis.

There is one HDF5 file per TNG snapshot, with the following datasets in the /Galaxy/ group:

Dataset	Shape	Units	Description
Type	N	-	Indicates whether the galaxy is a "central" (at the center of its FOF group, type=0), a "satellite" (within its own subhalo but not at the center of its FOF group, type=1), or an "orphan" (a satellite that has lost its subhalo, type=2).
SubhaloIndex_TNG	N	-	The unique subhalo index hosting this galaxy in the IllustrisTNG (baryonic) simulation. This value shall be used to match the galaxy to an object in the IllustrisTNG simulation. The value is -1 if there is no match for this subhalo in the IllustrisTNG.
SubhaloIndex_TNG-Dark	N	-	The subhalo index hosting this galaxy in the IllustrisTNG dark matter only (IllustrisTNG-Dark) simulation. This value shall be used to match the galaxy to an object in the IllustrisTNG-Dark simulation. The value is -1 if there is no match for this subhalo in the IllustrisTNG-Dark.
Central_M_Crit200	N	1010M⊙/h${10}^{10}{\mathrm{M}}_{\odot }/\mathrm{h}$	The virial mass (as defined by m_crit200) of the FOF group the galaxy resides in.
Central_R_Crit200	N	ckpc/h$\mathrm{c}\mathrm{k}\mathrm{p}\mathrm{c}/\mathrm{h}$	The virial radius (as defined by r_crit200) of the FOF group the galaxy resides in.
DistanceToCentralGal	N,3	ckpc/h$\mathrm{c}\mathrm{k}\mathrm{p}\mathrm{c}/\mathrm{h}$	The distance (along each dimension separately) between this galaxy and the galaxy at the centre of the FoF group.
Pos	N,3	ckpc/h$\mathrm{c}\mathrm{k}\mathrm{p}\mathrm{c}/\mathrm{h}$	Spatial (x,y,z) position of the galaxy. For Type == 0 and Type == 1 galaxies, this corresponds to the position of the hosting subhalo, while for Type == 2 galaxies this is set by the semi-analytic treatment for infalling satellite orbits.
Vel	N,3	km/s$\mathrm{k}\mathrm{m}/\mathrm{s}$	Spatial velocity of the galaxy.
SuhaloLen	N	-	Number of particles associated with the subhalo hosting this galaxy.
M_Crit200	N	1010M⊙/h${10}^{10}{\mathrm{M}}_{\odot }/\mathrm{h}$	Virial mass (as defined by m_crit200) of the subhalo this galaxy was in when it was last a type 0 galaxy. I.e. current virial mass for type 0 galaxies, and infall virial mass for type 1,2 galaxies.
R_Crit200	N	ckpc/h$\mathrm{c}\mathrm{k}\mathrm{p}\mathrm{c}/\mathrm{h}$	Virial radius (as defined by r_crit200) of the subhalo this galaxy was in when it was last a type 0 galaxy. I.e. current virial radius for type 0 galaxies, infall virial radius for type 1,2 galaxies.
Vvir	N	km/s$\mathrm{k}\mathrm{m}/\mathrm{s}$	Virial velocity of the subhalo this galaxy was in when it was last a type 0 galaxy. I.e. current virial velocity for type 0 galaxies, infall virial velocity for type 1,2 galaxies.
Vmax	N	km/s$\mathrm{k}\mathrm{m}/\mathrm{s}$	Maximum rotational velocity of the subhalo of this galaxy. This property continues to be updated even after the galaxy becomes a type 1.
ColdGasSpin	N,3	(kpc/h)(km/s)$(\mathrm{k}\mathrm{p}\mathrm{c}/\mathrm{h})(\mathrm{k}\mathrm{m}/\mathrm{s})$	The spin of the cold gas disc.
StellarDiskSpin	N,3	(kpc/h)(km/s)$(\mathrm{k}\mathrm{p}\mathrm{c}/\mathrm{h})(\mathrm{k}\mathrm{m}/\mathrm{s})$	The spin of the stellar disc.
InfallVmax	N	km/s$\mathrm{k}\mathrm{m}/\mathrm{s}$	Maximum rotational velocity of the suhalo of this galaxy at the time of infall (same as Vmax for type 0 galaxies).
InfallVmaxPeak	N	km/s$\mathrm{k}\mathrm{m}/\mathrm{s}$	Maximum past rotational velocity of the subhalo of this galaxy.
InfallSnap	N	-	Most recent (largest) snapnum at which this galaxy's type changed from 0 to 1 or 2.
InfallHotGasMass	N	1010M⊙/h${10}^{10}{\mathrm{M}}_{\odot }/\mathrm{h}$	Mass in hot gas at the time of infall (same as hotGas for type 0 galaxies).
HotGasRadius	N	ckpc/h$\mathrm{c}\mathrm{k}\mathrm{p}\mathrm{c}/\mathrm{h}$	Radius out to which hot gas extends: Rvir for type 0; 0 for type 2; maximum radius out to which hot gas is not stripped for type 1.
OriMergTime	N	yr$\mathrm{y}\mathrm{r}$	Estimated dynamical friction time (in years) when the merger clock was set. Only calculated for type 2 galaxies.
MergTime	N	yr$\mathrm{y}\mathrm{r}$	Estimated remaining merging time (in years). OriMergeTime - time since the merger clock is set. Only calculated for type 2 galaxies.
ColdGasMass	N	1010M⊙/h${10}^{10}{\mathrm{M}}_{\odot }/\mathrm{h}$	Mass in the cold gas disc.
StellarMass	N	1010M⊙/h${10}^{10}{\mathrm{M}}_{\odot }/\mathrm{h}$	Total mass in stars in the disc and the bulge together.
StellarDiskMass	N	1010M⊙/h${10}^{10}{\mathrm{M}}_{\odot }/\mathrm{h}$	Mass of stars in the disk.
StellarBulgeMass	N	1010M⊙/h${10}^{10}{\mathrm{M}}_{\odot }/\mathrm{h}$	Mass of stars in the bulge.
HotGasMass	N	1010M⊙/h${10}^{10}{\mathrm{M}}_{\odot }/\mathrm{h}$	Mass in hot gas.
EjectedMass	N	1010M⊙/h${10}^{10}{\mathrm{M}}_{\odot }/\mathrm{h}$	Mass in the ejected gas component.
BlackHoleMass	N	1010M⊙/h${10}^{10}{\mathrm{M}}_{\odot }/\mathrm{h}$	Mass of the central black hole.
HaloStellarMass	N	1010M⊙/h${10}^{10}{\mathrm{M}}_{\odot }/\mathrm{h}$	Mass in intra-cluster (ICL) stars.
MetalsColdGasMass	N	1010M⊙/h${10}^{10}{\mathrm{M}}_{\odot }/\mathrm{h}$	Mass in metals in the cold gas disk.
MetalsStellarMass	N	1010M⊙/h${10}^{10}{\mathrm{M}}_{\odot }/\mathrm{h}$	Mass in metals in stars in the disk and the bulge together.
MetalsBulgeMass	N	1010M⊙/h${10}^{10}{\mathrm{M}}_{\odot }/\mathrm{h}$	Mass in metals in stars in the bulge.
MetalsDiskMass	N	1010M⊙/h${10}^{10}{\mathrm{M}}_{\odot }/\mathrm{h}$	Mass in metals in stars in the disk.
MetalsHotGasMass	N	1010M⊙/h${10}^{10}{\mathrm{M}}_{\odot }/\mathrm{h}$	Mass in metals in hot gas.
MetalsEjectedMass	N	1010M⊙/h${10}^{10}{\mathrm{M}}_{\odot }/\mathrm{h}$	Mass in metals in the ejected mass component.
MetalsHaloStellarMass	N	1010M⊙/h${10}^{10}{\mathrm{M}}_{\odot }/\mathrm{h}$	Mass in metals in intra-cluster (ICL) stars.
PrimordialAccretionRate	N	M⊙/yr${\mathrm{M}}_{\odot }/\mathrm{y}\mathrm{r}$	Accretion rate of primordial gas.
CoolingRadius	N	ckpc/h$\mathrm{c}\mathrm{k}\mathrm{p}\mathrm{c}/\mathrm{h}$	The radius within which the cooling time scale is shorter than the dynamical timescale.
CoolingRate	N	M⊙/yr${\mathrm{M}}_{\odot }/\mathrm{y}\mathrm{r}$	Cooling rate of hot halo gas.
coolingRate_beforeAGN	N	M⊙/yr${\mathrm{M}}_{\odot }/\mathrm{y}\mathrm{r}$	Cooling rate of hot halo gas, if there had been no AGN feedback.
QuasarAccretionRate	N	M⊙/yr${\mathrm{M}}_{\odot }/\mathrm{y}\mathrm{r}$	Rate at which cold gas is accreted into the central black hole in the quasar mode.
RadioAccretionRate	N	M⊙/yr${\mathrm{M}}_{\odot }/\mathrm{y}\mathrm{r}$	Rate at which hot gas is accreted into the central black hole in the radio mode.
StarFormationRate	N	M⊙/yr${\mathrm{M}}_{\odot }/\mathrm{y}\mathrm{r}$	Star formation rate.
StarFormationRateBulge	N	M⊙/yr${\mathrm{M}}_{\odot }/\mathrm{y}\mathrm{r}$	Star formation rate in bulge.
XrayLum	N	log10(erg/sec)${\log }_{10}(\mathrm{e}\mathrm{r}\mathrm{g}/\mathrm{s}\mathrm{e}\mathrm{c})$	X-Ray luminosity of the hot halo gas.
BulgeSize	N	ckpc/h$\mathrm{c}\mathrm{k}\mathrm{p}\mathrm{c}/\mathrm{h}$	Half mass radius of galaxy bulge.
StellarDiskRadius	N	ckpc/h$\mathrm{c}\mathrm{k}\mathrm{p}\mathrm{c}/\mathrm{h}$	Size of the stellar disk, 3x the scale length.
GasDiskRadius	N	ckpc/h$\mathrm{c}\mathrm{k}\mathrm{p}\mathrm{c}/\mathrm{h}$	Size of the cold gas disk.
CosInclination	N	deg$\mathrm{d}\mathrm{e}\mathrm{g}$	Inclination of the galaxy. Derived from the angle between the total and z-axis stellar spins of the galaxy.
DisruptionOn	N	-	Disruption history flag. If 0: galaxy merged onto merger center; 1: galaxy was disrupted before merging onto its descendant, matter went into ICM of merger center.
MergeOn	N	-	Current merger state of the galaxy. If 0: merger clock not set yet; 1: type 1 galaxy with baryon mass > halo mass, separate dynamical friction time calculated; 2: this galaxy is type 2 and will merge into the merger center in the next snapshot; 3: this galaxy is type 1 and will merge into the central galaxy of the main halo in the next snapshot.
MagDust	N,20	mag$\mathrm{m}\mathrm{a}\mathrm{g}$	Rest-frame absolute magnitudes of the galaxy stellar light (dust extinction included). Description of the 20 bands are given below.
Mag	N,20	mag$\mathrm{m}\mathrm{a}\mathrm{g}$	Rest-frame absolute magnitudes of the galaxy stellar light. Description of 20 bands are given below.
MagBulge	N,20	mag$\mathrm{m}\mathrm{a}\mathrm{g}$	Rest-frame absolute magnitudes of the stellar light of the galaxy bulge. Description of the 20 bands are given below.
MassWeightedAge	N	109yr${10}^9\mathrm{y}\mathrm{r}$	The age of this galaxy, weighted by mass of its components.

Note: For all units, ckpc stands for kpc length scale in comoving units. Multiply by the scale factor a=1/(1+z)$a=1/(1+z)$ to convert to physical units. Additional information is available in the header attributes of the HDF5 file.

For each of the three Mag* datasets, all magnitudes are rest-frame, absolute (AB). The twenty entires correspond to (in order):

Entry	Band
0	Johnson-Bessel U filter (λ=0.36μm$\lambda =0.36\mu \mathrm{m}$).
1	Johnson-Bessel B filter (λ=0.435μm$\lambda =0.435\mu \mathrm{m}$).
2	Johnson-Bessel V filter (λ=0.55μm$\lambda =0.55\mu \mathrm{m}$).
3	Cousins Rc filter (λ=0.64μm$\lambda =0.64\mu \mathrm{m}$).
4	Cousins Ic filter (λ=0.79μm$\lambda =0.79\mu \mathrm{m}$).
5	VISTA Z filter (λ=0.88μm$\lambda =0.88\mu \mathrm{m}$).
6	VISTA Y filter (λ=1.02μm$\lambda =1.02\mu \mathrm{m}$).
7	VISTA/2MASS J filter (λ=1.26μm$\lambda =1.26\mu \mathrm{m}$).
8	VISTA/2MASS H filter (λ=1.60μm$\lambda =1.60\mu \mathrm{m}$).
9	Johnson-Bessel K (λ=2.22μm$\lambda =2.22\mu \mathrm{m}$) filter.
10	VISTA/2MASS Ks (λ=2.16μm$\lambda =2.16\mu \mathrm{m}$) filter.
11	IRAC 3.6μm$\mu \mathrm{m}$ filter.
12	IRAC 4.5μm$\mu \mathrm{m}$ filter.
13	IRAC 5.8μm$\mu \mathrm{m}$ filter.
14	IRAC 8.0μm$\mu \mathrm{m}$ filter.
15	SDSS u filter (λ=0.355μm$\lambda =0.355\mu \mathrm{m}$).
16	SDSS g filter (λ=0.469μm$\lambda =0.469\mu \mathrm{m}$).
17	SDSS r filter (λ=0.617μm$\lambda =0.617\mu \mathrm{m}$).
18	SDSS i filter (λ=0.748μm$\lambda =0.748\mu \mathrm{m}$).
19	SDSS z filter (λ=0.893μm$\lambda =0.893\mu \mathrm{m}$).

As an example, the following (python) code shows how this L-Galaxies catalog can be matched and compared to TNG galaxies from the group catalogs:

The resulting array mstar_matched has the same size as mstar_tng (which should be loaded from the TNG subhalo catalog at this snapshot, e.g. SubhaloMassInRadType[i,4]), and the value mstar_matched[i] can be compared directly to mstar_tng[i].

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(o) Lensing Profiles

This catalog contains lensing profiles of halos/subhalos, as described in Renneby+20 to which citation is requested if you use this data.

Simulation and snapshot coverage:

• Available for: TNG100-1, TNG100-1-Dark, TNG300-1, TNG300-1-Dark.
• Redshift zero (snapshot 99) only, all subhalos above a stellar mass limit (see below).

Lensing profiles have been computed for all galaxies with M⋆≥108.2h−2M⊙$M_{\star }\ge {10}^{8.2}{h}^{-2}{M}_{\odot }$ in the baryonic runs, and their matched gravity-only counterparts in the dark matter only runs. In total there are profiles for 417,535 galaxies for TNG300-1 and 334,606 matched substructures in TNG300-1-DMO (matching rate of ~80%). For TNG100 there are 35,270 galaxies in TNG100-1 and 27,088 galaxies in TNG100-1-DMO (~77% matched). The DMO matches are made with the LHaloTree-algorithm.

We have measured the signal radially for field projections along the x, y and z axes in 40 log10-equidistant bins between 30 kpc/h and 3 Mpc/h, and have separate "core terms" where we store all particle/cell counts below 30 kpc/h.

There is one HDF5 file per simulation/snapshot, with the following datasets:

Group/Dataset	Shape/Dimensions	Units	Description
/Header/	-	Msun/h	Group contains one attribute: MPart, which gives the (constant) dark matter particle mass for this simulation.
/ParticleCountCylinderGeometry/	-	ckpc/h	Group contains three attributes: MaxRad, MinRad, and NRadialBins, which give the shell binning configuration (note: comoving).
/ProjectedParticleShells/{DM,Gas,SMBHs,StarsAndWinds}CoreProjectedAlong{X,Y,Z}	Nsubhalos	varies	Counts of particles/cells in the "core", i.e. at distances smaller than the innermost bin (30 kpc/h). Note that for DM alone (!) we store unweighted counts, so these must be multiplied by the MPart attribute of the Header group in order to yield units of mass. All other components {Gas, SMBHs, StarsAndWinds} are already in mass units. For each of the three projection directions X,Y,Z.
/ProjectedParticleShells/{DM,Gas,SMBHs,StarsAndWinds}CountsRadialShellsProjectedAlong{X,Y,Z}	Nsubhalos,40	varies	Counts of particles/cells in each of the 40 radial shells (see above). Note that for DM alone (!) we store unweighted counts, so these must be multiplied by the MPart attribute of the Header group in order to yield units of mass. All other components {Gas, SMBHs, StarsAndWinds} are already in mass units. For each of the three projection directions X,Y,Z.
/Subgroups/SubhaloIDs	Nsubhalos	-	The Subfind/subhalo IDs contained in the catalog.
/Subgroups/LBGInProjectionAlong{X,Y,Z}	Nsubhalos	-	Indication if the subhalo is a "locally brightest galaxy" (LBG), i.e. if it is the brightest galaxy in the r-band (with dust extinction applied) within a cylinder of radius 1 pMpc and LOS distance < 1000 km/s in redshift at z=0. A galaxy/subhalo has its proper ID written out if it is an LBG, and -1 otherwise for the x, y and z projections. Note: the same galaxy can be an LBG or not depending on the projection axis X,Y,Z. Note: Only available in the TNG300-1 file.

Finally, we provide a supplementary .zip file for download. It contains several items:

• an example selection for TNG300 in ”tng300_example_selection_galaxies_mstar_10p11_10p11p2_Msun.hdf5” and an example compute script in ”compute_delta_sigma_signal_example_script.py”.
• Lensing profiles columnated in .txt-files where the first column holds the radius r [h^-1 Mpc], the second column the model Delta Sigma [h M_sun pc^-2], the third column the upper bootstrapped 95 % model Delta Sigma [h M_sun pc^-2], and the fourth column the lower bootstrapped 95 % model Delta Sigma [h M_sun pc^-2]. They are stored in folders referring to the reference of the dataset we are attempting to model.
• Baryonic deformations of the lensing profiles are stored in subdirectories ”BaryonicEffects” for the van Uitert+16 and Velliscig+17 datasets. Note that we use matched subhaloes only and restrict ourselves to centrals.
• The corresponding SAM-profiles are found in subdirectories for the different datasets under the folder ”SAMs”. The title of the file holds the parameter settings the model was run on. Note that the Guo+11 model parameter values for the Henriques+15 model is referred to as ”guo11”, whereas the original Guo+11 model is referred to as ”guo11_makefile_switch”.

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(p) Aperture Masses (Total and Stellar)

Measurements of 3D total and stellar masses within physical apertures, accounting for the resolution elements that are gravitationally bound to a subhalo according to the SUBFIND algorithm within 100 (physical) kpc, 30 pkpc, 10 pkpc, and 5 pkpc. For complete definitions on the calculation of each value, see the following table and Engler+ (2021a) where they were first presented. Citation to this paper is requested if you use these data catalogs.

Simulation and snapshot coverage:

• Available for all TNG baryonic simulations: TNG50-1, TNG50-2, TNG50-3, TNG50-4, TNG100-1, TNG100-2, TNG100-3, TNG300-1, TNG300-2, TNG300-3.
• All full snapshots between z=0 and z=1.5 (i.e. 99, 91, 84, 78, 72, 67, 59, 50, 40).
• Restricted to subhalos with at least one star (for TNG50 and TNG100), or at least 1000 stars (for TNG300).

Note: these are original values directly from the simulation. No "resolution rescalings" have been applied.

For all measurements, apertures {X} exist for X = 5, 10, 30, 100 (pkpc).

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(q) Halo Structure

Measurements of halo structural properties such as concentrations, shapes, formation times, and so on. All are computed using the dark matter particles that both (i) belong to the central/primary Subfind subhalo, and; (ii) are within R200c of the halo. For complete definitions of each value, see the following table and Anbajagane+ (2021) where they were presented. Citation to this paper is requested if you use these data catalogs.

Simulation and snapshot coverage:

• Available for the highest resolution run of each TNG box, both baryonic and dark-matter only: TNG50-1, TNG100-1, TNG300-1, TNG50-1-Dark, TNG100-1-Dark, TNG300-1-Dark.
• All twenty full snapshots (i.e. z=0,0.1,0.2,0.3,0.4,0.5,0.7,1.0,1.5,2,3,4,5,6,7,8,9,10,11,12$z=0,0.1,0.2,0.3,0.4,0.5,0.7,1.0,1.5,2,3,4,5,6,7,8,9,10,11,12$).
• Restricted to halos with total masses greater than 108.8M⊙${10}^{8.8}{M}_{\odot }$ (for TNG50), 109.8M⊙${10}^{9.8}{M}_{\odot }$ (for TNG100), and 1010.8M⊙${10}^{10.8}{M}_{\odot }$ (for TNG300).

Note: one file per snapshot. Be careful to use only entries with GroupFlag == 1.

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(r) Galaxy Morphologies (Deep Learning)

Probabilities that galaxies have certain visual-like morphologies, as determined by a machine learning algorithm. In the case of TNG50, classifications are provided at high redshift and are CANDELS-like, i.e. based on synthetic H-band galaxy images at CANDELS depth and resolution. In the case of TNG100, classifications are provided at low redshift, and are SDSS-like, based on synthetic r-band galaxy images with SDSS resolution and noise characteristics. For complete definitions on the calculation of each value, see the following table, Huertas-Company+ (2019), and Varma+ (2021), where they were first presented and used. Citation to these papers is requested if you use these data catalogs.

Simulation and snapshot coverage:

• Available for TNG50-1 (z=0.5, 1, 1.5, 2, 2.5, 3), and TNG100-1 (z=0, 0.05).
• Restricted to subhalos with M⋆>109M⊙$M_{\star }>{10}^9{M}_{\odot }$ (for TNG50 classifications), or M⋆>109.5M⊙$M_{\star }>{10}^{9.5}{M}_{\odot }$ (for TNG100, i.e. 12,468 galaxies at z=0.05).

For TNG100 (SDSS-like):

For TNG50 (CANDELS-like):

Note: a Snapshot_N group exists for the above-mentioned snapshots (two for TNG100-1, six for TNG50-1).

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(s) Cosmic Web Distances (Disperse)

A post-processing identification of the topology of the cosmic web, using the DisPerSE code. This method provides an automatic identification of topological structures such as peaks, voids, walls, and in particular filaments. To do so, DisPerSE uses a set of discrete points (e.g. galaxies) to estimate a density field, and then identify the cosmic web. By definition critical points in this density field are nodes, and the unique integral lines between them are filaments: every filament starts and ends at a node, and saddle points are minima along the filaments.

For this catalog, the points used to define the cosmic web are galaxies. Specifically, subhalos with a minimum stellar mass of 108.5M⊙h−1${10}^{8.5}{M}_{\odot }{\mathrm{h}}^{-1}$, which is designed to be roughly comparable to what you might be able to recover from an observational galaxy survey. The only other parameter of DisPerSE is the "persistence", which defines the robustness of each pair of critical points, in terms of the peak relative to background. For this catalog a persistence of σ=4$\sigma =4$ has been chosen.

The physical properties presented in this catalog are cosmic web distances, between subhalos in the simulation and the nearest cosmic web structures of a given type. This allows for the identification, for example, of galaxies as a function of distance away from the centers of filaments, void galaxies, and so on.

For more details, see the DisPerSE paper Sousbie (2011). This catalog was developed as part of the work of Duckworth+ (2020a) and Duckworth+ (2020b). Citation to these three papers is suggested if you use these data catalogs. The codes to run DisPerSE on TNG and to derive quantities of interest are available on github.

Simulation and snapshot coverage:

• Available for the highest resolution run of TNG100 and TNG300 currently: TNG100-1, TNG300-1.
• Several full snapshots between redshift two and zero (i.e. z=0,0.1,0.2,0.3,0.5,1.0,1.5,2$z=0,0.1,0.2,0.3,0.5,1.0,1.5,2$).
• All subhalos.

Note: in the above, N_subhalos always refers to the number of subhalos in the group catalog at a particular snapshot. All distances are in code units.

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(t) Galaxy Morphologies (Kinematic) and Bar Properties

This catalog contains (i) kinematic decompositions of the stars of galaxies into different morphological components, and (ii) bar properties. Galaxies are decomposed in five morpho/kinematical components, namely a thin/cold disc, a thick/warm disc, a pseudo-bulge, a bulge and a halo, after an analysis of the stellar kinematics with the MORDOR code. In addition, a detailed catalogue of stellar bars is given, along with bar properties, based on a fourier analysis of the galactic stellar surface density. For complete definitions on the calculation of each value, see Zana+ (2022), where they were first presented and used. Citation to this paper is requested if you use these data catalogs.

Simulation and snapshot coverage:

• Available for TNG50-1 (all redshifts).
• Restricted to subhalos with M⋆≳109M⊙$M_{\star }\gtrsim {10}^9{M}_{\odot }$ (corresponding to a minimum of 104${10}^4$ star particles).

This catalogue is one file per simulation, containing many groups Snapshot_N, one per snapshot. The following datasets are included:

Note: for TNG50-1, the available snapshot numbers N range from 6 to 99.

Note: if no bar structure is found, the related entries are set equal to -1.

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(u) LEGA-C/VIMOS Mock Optical Spectra

This catalog contains mock (i.e. synthetic) optical spectra of galaxies at intermediate redshift, designed to match the instrumental properties and setup of the LEGA-C Survey. This spectroscopic survey obtained deep, high-resolution spectra of thousands of galaxies with M⋆>1010M⊙$M_{\star }>{10}^{10}{\mathrm{M}}_{\odot }$ from z=0.6$z=0.6$ to z=1$z=1$, using the VLT/VIMOS multi-object slit spectograph.

These synthetic spectra have been designed to cover TNG galaxies over the same redshift and mass ranges, such that LEGA-C matched samples can be constructed. The spectra have been created to exactly mimic the instrumental and survey characteristics, such as spectral resolution, noise, seeing, and so on. Each extends over a rest-frame wavelength range of ∼3700$\sim 3700$ Angstrom to ∼5200$\sim 5200$ Angstrom. For every TNG galaxy, 10 realizations are provided, by matching to 10 different random LEGA-C galaxies of similar mass. In addition, the original 'idealized' spectra are also included, one per TNG galaxy.

Complete details on the methodology are presented in Wu+ (2021), where they were first analyzed. Citation to that paper, as well as to Nelson+ (2018) where the mock spectra construction was developed, is requested if you use this data catalog.

Simulation and snapshot coverage:

• Available for TNG100-1 (five snapshots, z=0.6, 0.7, 0.8, 0.9, and 1.0).
• Restricted to subhalos with 1010.3<M⋆/M⊙<1011.5${10}^{10.3}<M_{\star }/{\mathrm{M}}_{\odot }<{10}^{11.5}$ (stellar masses measured within 30 pkpc).

This catalogue is one single file, containing five groups named Snapshot_N, one per snapshot. The following datasets are included in each snapshot group:

Note: for TNG100-1, the available snapshot numbers N are 50, 53, 56, 59, and 63. The corresponding values of {N_gal} are 3058, 3223, 3371, 3503, and 3624.

Note: the dimension of size 10 in the above datasets corresponds to 10 realizations of mock spectra for each TNG galaxy (see paper for details).

Note: For all spectra, {N_wave} is a constant 6166 wavelength points.

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(v) JWST-CEERS Mock Galaxy Imaging

This catalog contains synthetic images for JWST-like NIRCam and MIRI observations of high-redshift galaxies. The full description of the synthetic images and measurements can be found in Costantin+ (2022), to which citation is requested if you use this data. For full details, please see the paper.

Simulation and snapshot coverage:

• Available for: TNG50-1.
• Redshifts: z=3, z=4, z=5, and z=6.
• Restricted to subhalos with stellar mass M⋆/M⊙>109.0$M_{\star }/{\mathrm{M}}_{\odot }>{10}^{9.0}$ as well as total half-mass radius Rhalf≳1arcsec$R_{\mathrm{h}\mathrm{a}\mathrm{l}\mathrm{f}}\gtrsim 1\mathrm{a}\mathrm{r}\mathrm{c}\mathrm{s}\mathrm{e}\mathrm{c}$.
• For each galaxy, there are 20 view configurations (5 inclinations: i=[0, 45, 90, 135, 180], and 4 azimuths: a=[0, 90, 180, 270]).

Each dataset (for one instrument configuration and redshift) can be downloaded as a single tar.gz file (below).

• NIRCam SW: 0.031 arcsec/px: z=3, z=4, z=5, z=6
• NIRCam LW: 0.063 arcsec/px: z=3, z=4, z=5, z=6
• MIRI: 0.110 arcsec/px: z=3, z=4, z=5, z=6
• Highly-resolved "ideal" TNG50 0.010 arcsec/px: z=3, z=4, z=5, z=6

As an additional dataset, simulated imaging data suited for CEERS observations (F200W and F356W filters) are provided. The instrumental noise effects of JWST/NIRCam were simulated using the mirage tool (v2.2.1). Data simulated with mirage were run through the JWST calibration pipeline (v1.4.6), mimicking the data reduction strategy to be used for in-flight data, and are provided at nominal and half-nominal angular resolution (see detailed information). Morphological catalogs based on Costantin+2023 are also provided (coming soon).

• NIRCam F200W (0.031 arcsec/px and 0.015 arcsec/px): z=3, z=4, z=5, z=6
• NIRCam F356W (0.063 arcsec/px and 0.030 arcsec/px): z=3, z=4, z=5, z=6

The synthetic images are available as datacubes in FITS format. Each dataset contains the same 4 redshift bins (galaxies from four simulation snapshots). The ‘EXTn’ keyword in the main header can be used to identify the different filters available (n=1-12 for NIRCam SW, n=1-15 for NIRCam LW, n=1-9 for MIRI, and n=1-36 for the resolved TNG50 version). Catalogs containing the main properties of each synthetic image are also available.

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(w) Multi-band (UV to submm) Photometry and SEDs

This catalog contains mock (i.e. synthetic) multi-wavelength photometry and spectral energy distributions (SEDs), across a broad wavelength range, from the UV to the submillimeter. These are highly realistic values, obtained with the SKIRT dust radiative transfer code, and with a calibration against DustPedia data. These band magnitudes/fluxes and SEDs are available for TNG50 galaxies at low redshift: z=0$z=0$ and z=0.1$z=0.1$ in particular.

Complete details on the methodology are presented in Trčka+ (2022) and Gebek+ (2024), where they were created and first analyzed. Citation to these two papers is requested if you use this data catalog.

Simulation and snapshot coverage:

• Available for TNG50-1, TNG50-2, and TNG100-1 (in all cases, for two snapshots, z=0.0 and z=0.1).
• Restricted to subhalos with M⋆>108M⊙$M_{\star }>{10}^8{\mathrm{M}}_{\odot }$ for TNG50 (or M⋆>108.5M⊙$M_{\star }>{10}^{8.5}{\mathrm{M}}_{\odot }$ for TNG100), stellar masses measured within twice the stellar half mass radius.
• This corresponds to 7375 (5669) [30712] galaxies at z=0$z=0$ and 7302 (5665) [30364] galaxies at z=0.1$z=0.1$ for TNG50-1 (TNG50-2) [TNG100-1].

This catalogue is one single file per simulation, containing groups named Snapshot_N, one per snapshot. The following datasets are included for each snapshot:

Note: {N_apertures} is always 4, and these correspond to (in order): 10 kpc, 30 kpc, twice the stellar half mass radius, and five times the stellar half mass radius. (Also listed in the HDF5 attributes).

Note: {N_orientations} is always 3, and these correspond to (in order): edge-on, face-on, and random. (Also listed in the HDF5 attributes).

Note: {N_bands} is always 53, and these correspond to (in order): GALEX_FUV, GALEX_NUV, SDSS_u, SDSS_g, SDSS_r, SDSS_i, SDSS_z, TwoMASS_J, TwoMASS_H, TwoMASS_Ks, UKIDSS_Z, UKIDSS_Y, UKIDSS_J, UKIDSS_H, UKIDSS_K, Johnson_U, Johnson_B, Johnson_V, Johnson_R, Johnson_I, Johnson_J, Johnson_M, WISE_W1, WISE_W2, WISE_W3, WISE_W4, IRAS_12, IRAS_25, IRAS_60, IRAS_100, IRAC_I1, IRAC_I2, IRAC_I3, IRAC_I4, MIPS_24, MIPS_70, MIPS_160, PACS_70, PACS_100, PACS_160, SPIRE_250, SPIRE_350, SPIRE_500, SCUBA2_450, SCUBA2_850, ALMA_10, ALMA_9, ALMA_8, ALMA_7, ALMA_6, PLANCK_857, PLANCK_545, PLANCK_353. (Also listed in the HDF5 attributes). For the values at redshift zero, all instruments were placed at a distance of 20 Mpc.

Note: {N_wave} is always 387, and the values are given by the SEDs_wave dataset.

Finally, we provide a supplementary .zip file for download. This contains: (i) a Jupyter notebook which shows examples of loading and exploring the data, and (ii) the SKIRT .ski configuration file used to perform the radiative transfer runs.

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(x) Globular Clusters

This catalog contains a dataset of globular clusters for high-mass halos. The existence, and properties, of globular clusters (GCs) has been inferred in post-processing with a 'tagging' technique. At the time when a galaxy infalls (i.e. accretes) into a more massive host, its GC population is created. Each GC is attached to (i.e. represented by) a single dark matter particle, which sets its subsequent gravitational dynamics and location.

Complete details on the methodology and physical modeling assumptions are presented in Doppel+ (2020), where this GC catalog was created and first analyzed. Citation to that paper is requested if you use this data. Additional details are available in Ramos+ (2015), Ramos-Almendares+ (2018), and Ramos-Almendares+ (2020), which describe previous versions and the evolution of the GC tagging model.

This catalog specifically contains the "realistic GCs" from Doppel+ (2020), which is one realization of the GC population, subsampled from a larger ensemble of candidate GC populations. It has been designed to roughly reproduce realistic GC properties at redshift zero. Additional realizations, as well as the entire set of GC candidates, can be made available upon request.

Simulation and snapshot coverage:

• Available for TNG50-1, redshift zero (snapshot 99).
• Restricted to halos with M200c>5×1012M⊙$M_{200c}>5\times {10}^{12}{\mathrm{M}}_{\odot }$. More specifically, GCs are present within subhalos with stellar masses M⋆≥106M⊙$M_{\star }\ge {10}^6{\mathrm{M}}_{\odot }$ at z=0$z=0$ which have additionally reached a maximum stellar mass of at least 5×106M⊙$5\times {10}^6{\mathrm{M}}_{\odot }$ in their lifetime, and had at least 100 dark matter particles and non-zero stellar mass at infall.
• This corresponds to the subhalos of 39 massive host halos at z=0$z=0$, and a total of 196,606 GCs.

This catalogue is one file, which includes the following datasets:

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(y) Merger History

Catalogs containing information and statistics about the merging history of all subhalos (i.e. galaxies), across all time. Here mergers are split into three categories: major (stellar mass ratio > 1/4), minor (stellar mass ratio between 1/10 and 1/4), and all (any stellar mass ratio) mergers. The mass ratio is always based on the stellar masses of the two merging galaxies at the time when the secondary reached its maximum stellar mass.

To avoid spurious flyby and re-merger events, mergers are only included when both galaxies can be tracked back to a time when each of them belonged to a different FoF group. Furthermore, to clean the mergers from events released to non-cosmological subhalos (i.e. "clumps"), a cleaning procedure has been applied as follows. First, all subhalos with SubhaloFlag == False are ignored. Second, the secondary is ignored if it did not exist for more than 2 snapshots.

For complete definitions on the calculation of each value, see the following table, Rodriguez-Gomez (2017), and Eisert et al. (2022). Citation to these two papers is requested if you use these data catalogs.

Simulation and snapshot coverage:

• Available for all TNG baryonic runs: TNG50-1, TNG50-2, TNG50-3, TNG50-4, TNG100-1, TNG100-2, TNG100-3, TNG300-1, TNG300-2, TNG300-3, and TNG-Cluster.
• All snapshots: one HDF5 file per snapshot.
• All subhalos.

Major mergers (stellar mass ratio > 1/4), minor mergers (1/10 < stellar mass ratio < 1/4), and all mergers (any stellar mass ratio):

Note: in all cases above, {time} can be any of six options: "Last250Myr", "Last500Myr", "LastGyr", "SinceRedshiftOne", and "SinceRedshiftTwo".

Note: if a snapshot number is undefined, i.e. there is no major merger for SnapNumLastMajorMerger, the value is set to -1.

There are also additional merger statistics that attempt to quantify the cumulative effects of all the mergers that a galaxy has ever had. These are plausibly more meaningful quantities than the "standard" merger statistics described above (e.g. the time since the last major merger, etc.). As usual, the properties of the secondary progenitor (as well as the merger mass ratio) are measured at the time when it reached its maximum stellar mass, while the time of the merger corresponds to the snapshot in which the two merger tree branches join. As shown in Rodriguez-Gomez et al. (2017), these quantities are strongly correlated with the fraction of accreted stars in a galaxy. Available quantities are:

Finally, there are additional merger statistics, with analog meanings as above, unless otherwise stated:

Note: in all cases above, {time} can be any of four options: "Last2Gyr", "Last5Gyr", "Last8Gyr", and "SinceRedshift5".

Finally, in the case of TNG50-1 catalogs (only), each file contains an additional group named "WithConstraint". In this group, a second version of all the above datasets can be found, where an additional constraint has been applied to secondaries. Specifically, secondaries are ignored if there were not more than 50 stellar particles in at least one snapshot in its lifetime. These merger statistics exclude very small galaxies, and may be useful. They reproduce the published results of Eisert+ (2022) and Sotillo-Ramos+ (2022).

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(z) MaNGIA Mock MANGA IFU Cubes

This catalog contains 10,000 MaNGA-like (IFU datacube) mocks from TNG50 galaxies for stellar population analysis. To enable a statistical comparison with the observations, the sample of simulated galaxies has been chosen to match the MaNGA selection criterion based on stellar mass, radius and redshift. The mock datacubes emulate the instrumental characteristics of the observed survey, and have been analyzed with the same tools to extract stellar populations properties. The final products are comparable the latest release of the analysis performed with pyPipe3D on the MaNGA survey (Sánchez+ 2022).

The full description of the sample, mock procedure, and data products can be found in Sarmiento+ (2023), to which citation is requested if you use this data.

The cubes where produced using the SSP template MaStar_CB19.slog_1_5 (Sánchez+ 2022) assuming a dust screen model and later analyzed with pyPipe3D. The code to produce the mocks is based on Ibarra-Medel+ (2019). For this work, we use an updated version of this code, available here.

Simulation and snapshot coverage:

• Available for: TNG50-1.
• Sample: Selection of 10,000 galaxies from TNG50-1 snapshots 87 through 98 (inclusive), chosen to match MaNGA properties.

Bulk download of the mocks, for all galaxies, is available. They can be downloaded as two tar.gz files:

• MaNGIA_catalog.fits (1 MB)- list of the 10,000 TNG50 galaxies used to produce the mocks (and the corresponding snapshots).
• MaNGIA_maps.tar.gz (35 GB) - stacked 2D property maps (stellar mass, stellar kinematics, intrinsic and assigned ages and metallicities) derived directly from the simulation with the same spatial resolution as the cube mocks. Also includes the relevant pyPipe3D outputs: stellar absorption indices, "SFH", and "SSP". The SFH extension contains the recovered weights of the linear combination of stellar populations, while the SSP extension has the main parameters derived from the analysis of the stellar populations (LW and MW ages, metallicities, dust attenuation and stellar kinematics properties).
• MaNGIA_rss.tar.gz (345 GB) - row-stacked spectra. Files containing the list of emulated fiber spectra corresponding to each galaxy. The 3D-datacubes can be re-built from the row-stacked spectra (RSS) files using the provided code.

In the "maps" and "rss" .tar.gz files, there are one or more .fits files per subhalo. They are named with the format ""TNG50-{snap}-{subhaloID}-{view}-{numfibers}.fits" where {snap} is the snapshot number, {subhaloID} is the Subhalo ID, {view} is an integer from 0-5 (see paper), and {numfibers} is the number of fibers in the bundle (19, 37, 61, 91, or 127, see paper). Note: the majority of subhalos are only viewed once, so they have only one corresponding .fits file with {view} == 0.

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(1) TNG50 Milky Way+Andromeda (MW/M31)-like Galaxies

The TNG50 Milky Way + Andromeda sample, as presented in Pillepich+ (2023), contains detailed information and special snapshot cutouts for 198 MW/M31-like galaxies. Three data products are available: (i) a catalog of the sample, including many physical properties of each MW/M31-like galaxy, (ii) a catalog of the satellite galaxies surrounding each MW/M31-like central, and (iii) individual snapshot cutouts of the stars, dark matter, gas, and supermassive black holes which reside in, and around, each galaxy, at z=0$z=0$ as well as following the main progenitor for all redshifts up to z=7$z=7$.

See the TNG50 Milky Way+Andromeda Sample and Data Release page.

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(2) HVC-like Cosmological Cloud Catalog

This is the Cosmological Cloud Catalog (CCC), a library of physical properties of cool clouds in the circumgalactic medium of Milky Way-like galaxies from TNG50. These objects are possible High Velocity Cloud (HVC) and/or Intemediate Velocity Cloud (IVC) analogs. For complete definitions on the calculation of each value, see the following table and Ramesh+ (2023b), where they were first presented. Citation to that paper is requested if you use this catalog.

These clouds can be visualized in the Ramesh+ (2023b) Infinite Gallery.

Simulation and snapshot coverage:

• Available for TNG50-1 at z=0 (snapshot 99).
• Restricted to a subset of 132 galaxies from the MW/M31-like sample, corresponding to those with 1010.5M⊙<M⋆<1010.9M⊙${10}^{10.5}{\mathrm{M}}_{\odot }<{\mathrm{M}}^{\star }<{10}^{10.9}{\mathrm{M}}_{\odot }$.

The single HDF5 file consists of various datasets. Each dataset is an array of length 119895, and each entry corresponds to a single cloud. Clouds here are defined as contigous sets of Voronoi cells that are cold (T≤104.5K$T\le {10}^{4.5}\mathrm{K}$). Refer to Ramesh+(2023b) for more details. The "Interface" fields refer to the immediate shell of gas cells surrounding each cloud, i.e. the closest/transition region. The "Background" fields refer to the shell of gas cells surrounding the interface, i.e. a more distant/background region. See this website for more information.

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(3) Zooniverse Cosmological Jellyfish

This catalog contains the complete results of the Citizen Science Project Cosmological Jellyfish on Zooniverse.org. In this project a large number of satellite galaxies were visually inspected to determine if they exhibit jellyfish-like morphological features, namely: extended tails of gas consistent with ram pressure stripping (RPS). The catalog includes the merged results of both Phase 1 (June 2021) and Phase 2 (August-December 2021). It contains two sets of scores: the 'raw' scores, based on the votes of at least 20 Inspectors (all scores receive equal weights), and the 'adjusted' scores, found after implementing the Inspector-weighting scheme described in Zinger et al. (2023).

There are three parts to this catalog: "flags and scores", "viewing angle comparison", and "branches". The first two come from Zinger et al. (2023), while the last comes from Rohr et al. (2023). Citation to these two papers is requested if you use this data. In addition, please include the following statement in the Acknowledgements: "This publication uses data generated via the \href{https://www.zooniverse.org/}{Zooniverse.org} platform, development of which is funded by generous support, including a Global Impact Award from Google, and by a grant from the Alfred P. Sloan Foundation."

Simulation and snapshot coverage:

• Available for the highest resolution runs of TNG100 and TNG50 currently: TNG100-1, TNG50-1.
• Only satellites were inspected.
• Satellite stellar mass: M∗>108.3M⊙${\mathrm{M}}_{\ast }>{10}^{8.3}{\mathrm{M}}_{\odot }$ (TNG50) or M∗>109.5M⊙${\mathrm{M}}_{\ast }>{10}^{9.5}{\mathrm{M}}_{\odot }$ (TNG100).
• Satellite gas fraction: fgas>0.01$f_{\mathrm{g}\mathrm{a}\mathrm{s}}>0.01$.
• Snapshots: all full snapshots up to z=2$z=2$ (i.e. 33, 40, 50, 69, 67, 72, 78, 84, 91, 99), plus all snapshots up to z=0.5$z=0.5$ for TNG50 only (i.e. 68-98 inclusive).

Flags and scores: in the catalog file there is a unique group labeled Snapshot_NNN for each snapshot number. It contains a number of datasets, each has a size equal to the number of inspected satellites at that snapshot:

Viewing angle comparison: in the catalog file there are two groups named Snapshot_NNN_ViewingAngle for snapshots 67 and 99 only. Here we chose a subset of objects (8762) for which we generated images from a preferred vantage point for jellyfish identification, such that the velocity vector is in the plane of the image. These images were presented for classification as separate objects so as not to introduce any bias to the classification process. The results of this experiment -- based on images from preferred instead of random directions -- are available in these groups. Both contain a number of datasets, each has a size equal to the number of inspected satellites at that snapshot:

Branches: the evolutionary tracks or branches of the galaxies inspected as part of the Zooniverse Cosmological Jellyfish project. While there are 53610 and 28094 inspected galaxy images for TNG50 and TNG100, many of these galaxies were inspected at different instances of cosmic time, resulting in 5023 and 9052 unique galaxy branches in TNG50 and TNG100, respectively. We store information about these galaxies for all snapshots, from snapshot 99 to 0 (in the same order as the merger trees). A given galaxy may not exist in the merger trees (for this catalog Sublink_gal) at every snapshot. In these cases, all fields except for SnapNum have a value -1. Each dataset has two dimensions: the first corresponds to the branch number (of size 5023 or 9052), while the second always has a size of 100, corresponding to the 100 snapshots:

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(4) iMaNGA Mock MANGA IFU Datacubes

This catalog contains ~1,000 mock IFU datacubes recreating SDSS-IV/MaNGA-like observations. The galaxies are drawn from TNG50, selected to mimic the MaNGA-Primary sample selection. The IFU cubes are in .fits format. They are created using the MaStar stellar population models, plus Mappings-III models for young star-forming regions, using the SKIRT dust radiative transfer code.

The full description of the sample, mock procedure, and data products can be found in Nanni+ (2023), to which citation is requested if you use this data.

Simulation and snapshot coverage:

• Available for: TNG50-1.
• Sample: Selection of ~1,000 galaxies from TNG50-1 snapshots 88 through 98 (inclusive), chosen to match MaNGA properties.

The mock datacubes can be individually downloaded for each subhalo for which they are available. The API page for each (included) subhalo gives the download path, and the full list of available subhalos and the iMaNGA downloads are also available below.

• iMaNGA Datacubes - (~10 MB to ~3 GB each) list of the TNG50-1 galaxies available, each with a link to download the .fits mock IFU datacube.
• iMaNGA_catalog.hdf5 (1 MB) - catalog with additional information, including sample IDs (see table below).
• iMaNGA_catalog.fits (1 MB) - same catalog, also available in .fits format (see table below).
• iMaNGA_VAC.fits (11 GB) - value-added catalog (VAC) in .fits format (see second table below).

The contents of the iMaNGA VAC are:

Note: For HDU12, 10 is the maximum number of SSPs combined by Firefly in the fitting process.

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(5) Synthetic Stellar Light Images with HSC-SSP Realism

This catalog contains synthetic near-UV/optical/near-IR images made using dust radiative transfer post-processing with SKIRT. The images include dust radiative transfer, and have been 'injected' into real Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP, Aihara+ 2022) backgrounds.

The full description of the sample, mock procedure, and data products can be found in Bottrell+ (2023). Citation to that work, as well as to Eisert+ (in prep) is requested if you use this data.

Simulation and snapshot coverage:

• Available for: TNG50-1 and TNG100-1.
• Redshifts: 0.1≤z≤0.4$0.1\le z\le 0.4$ (snapshots 72-91).
• Subhalos: total subhalo stellar masses M⋆≥109M⊙${\mathrm{M}}_{\star }\ge {10}^9{\mathrm{M}}_{\odot }$ for TNG50-1; M⋆≥1010M⊙${\mathrm{M}}_{\star }\ge {10}^{10}{\mathrm{M}}_{\odot }$ for TNG100-1, excluding SubhaloFlag=0 objects.
• Cameras: 4 viewing angles v0-v3 (tetrahedron; where v3 is the box z-axis).

The catalog includes images in noise-free, high-resolution format (idealized) and statistical injections into the HSC-SSP 3rd public data release wide layer (pdr3_wide). All images for a given galaxy / camera angle are contained in a FITS file with comprehensive headers detailing information about the images.

Idealized images:

• Filters: CLAUDS u-band; CFHT MegaCam r-band; HSC grizy-bands.
• FoV size: 50-500 kpc (see Bottrell+)
• Pixel scale: 100 pc

Survey-realistic images:

• Filters: HSC-SSP grizy-bands.
• FoV size: 50-500 kpc (see Bottrell+)
• Pixel scale: 0.167 arcseconds
• Survey extras: HSC-SSP variance maps, mask images, and PSF reconstructions

The FITS files can be downloaded separately for each subhalo for which they are available through the API. For example,

• TNG50-1 FITS Files (~10 MB to ~1 GB each) - list of the TNG50-1 galaxies available, each with a link to download the .fits mock.
• TNG100-1 FITS Files (~10 MB to ~1 GB each) - list of the TNG100-1 galaxies available, each with a link to download the .fits mock.
• /api/TNG100-1/snapshots/91/subhalos/388890/skirt/skirt_images_hsc_idealized_v0.fits downloads the idealized mock (v0) for the central subhalo of FoF #600 in TNG100-1 at z=0.1$z=0.1$.
• /api/TNG50-1/snapshots/91/subhalos/503737/skirt/skirt_images_hsc_realistic_v3.fits downloads the hsc_realistic mock (v3) for the central subhalo of FoF #200 in TNG50-1 at z=0.1$z=0.1$.

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(6) Nearest Neighbors

A catalog of the nearest neighbours of galaxies. The catalog is constructed by measuring Euclidean distances between the galaxies in the simulation box with stellar masses above a minimum threshold. The minimum stellar mass threshold for the nearest neighbours (Mnn∗,min$M_{\ast ,\mathrm{m}\mathrm{i}\mathrm{n}}^{\mathrm{n}\mathrm{n}}$) depends on the resolution of the simulation run, with Mnn∗,min=107 M⊙$M_{\ast ,\mathrm{m}\mathrm{i}\mathrm{n}}^{\mathrm{n}\mathrm{n}}={10}^7{\mathrm{M}}_{\odot }$ for TNG50-1, Mnn∗,min=108.2 M⊙$M_{\ast ,\mathrm{m}\mathrm{i}\mathrm{n}}^{\mathrm{n}\mathrm{n}}={10}^{8.2}{\mathrm{M}}_{\odot }$ for TNG100-1 and Mnn∗,min=109.1 M⊙$M_{\ast ,\mathrm{m}\mathrm{i}\mathrm{n}}^{\mathrm{n}\mathrm{n}}={10}^{9.1}{\mathrm{M}}_{\odot }$ for TNG300-1. For each galaxy, the catalogue stores information about its ten nearest neighbours within 15 Mpc and the total number of neighbours within a fixed spherical aperture centred on the target galaxy. For further information, see Flores-Freitas+ (2024). Citation to that paper is requested if you use these data catalogs.

In the datasets, the placeholders {i} and {r} appears. Here, {i} refers to the index of the i$i$-th neighbour, and can be any integer from 1 to 10. While {r} refers to the radius (in Mpc) of the spherical aperture used to count galaxies around a target galaxy, and can be the integers 1, 2 or 5.

Simulation and snapshot coverage:

• Available for: TNG50-1, TNG100-1, TNG300-1 (all snapshots/redshifts).
• Restricted to subhalos with stellar mass M∗≥107 M⊙$M_{\ast }\ge {10}^7{\mathrm{M}}_{\odot }$ in TNG50-1, M∗>108.2 M⊙$M_{\ast }>{10}^{8.2}{\mathrm{M}}_{\odot }$ in TNG100-1 and M∗≥109.1 M⊙$M_{\ast }\ge {10}^{9.1}{\mathrm{M}}_{\odot }$ in TNG300-1.

Note: The stellar masses (M∗$M_{\ast }$) refered above are measured within the usual twice stellar half mass radius. Note: Only subhalos of cosmological origin (subhalo_flag=1) are considered as neighbours or target galaxies.
注意：上述提到的恒星质量（ M∗$M_{\ast }$ ）是在通常的两倍恒星半质量半径内测量的。注意：只有宇宙学起源的子晕（ subhalo_flag=1 ）被视为邻近或目标星系。

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(7) TNG50-SKIRT Atlas

A database of images in 18 UV to near-infrared broadband filters. The images were generated with the SKIRT radiative transfer code and account for different stellar populations and absorption and scattering by interstellar dust. The images have a high spatial resolution (100 pc) and a wide field of view (160 kpc). Each galaxy is observed from 5 observing positions, spread on the unit sphere in optimal arrangement. In addition to the dust-obscured images, we also release dust-free images and physical parameter property maps with matching characteristics. For full details, see Baes et al. (2024). Additional images in the Euclid bands are also generated; they are presented in Kovacic et al. (in prep). Citations to these papers are appreciated if you use these images.

Simulation and snapshot coverage:

• Available for: TNG50-1 at z=0 only (the link lists all available files for download).
• Restricted to the 1154 subhalos with (total) stellar mass M^* > 10^9.8 solar masses.

There are two datasets:

• A simple text-file catalog containing the subhalo IDs, and a few basic properties, for the sample.
• The individual FITS files, available as one .tar.gz file per subhalo, available through the API (10MB to 2GB each).
• For example, /api/TNG50-1/snapshots/99/subhalos/503987/skirt/skirt_atlas.tar.gz downloads the images for the central subhalo of HaloID 150 in TNG50-1 at z=0$z=0$.

The synthetic images are available in FITS format, one file per band. All FITS for a given subhalo are combined into one .tar.gz file for download. The dimensions of each image are 1600x1600 pixels. These images are 'idealized', i.e. they do not contain instrumental effects such as PSF smoothing or noise. This must be added by the user, if desired.

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(8) ... coming soon?