The splashback radius
Traditionally, halo radii have been defined based on the spherical overdensity criterion where the halo radius encloses some overdensity with respect to the critical or mean density of the universe, leading to definitions such as R200c, R200m, and Rvir. There are, however, a number of issues with these definitions: the halo mass and radius undergo pseudo-evolution, a significant number of satellites orbit outside the virial radius (e.g., Wetzel et al. 2014), and infalling subhalos begin to get stripped far outside Rvir (Behroozi et al. 2014).
To remedy these issues, we have proposed the splashback radius (Rsp) as a physically motivated definition of the halo boundary (Diemer & Kravtsov 2014, Adhikari et al. 2014, More et al. 2015). Rsp is the radius where particles reach the apocenter of their first orbit. The theoretical motivation for this definition is provided by the self-similar spherical infall model (Fillmore & Goldreich 1984, Bertschinger 1985): in spherical symmetry, this radius cleanly separates infalling material from matter orbiting in the halo, and by definition includes the orbits of all satellites in the halo (see figure).
In perfect spherical symmetry, the splashback radius would be marked by a caustic, an infinitely sharp drop in density. This feature is smoothed out in realistic halos but we detected it in stacked density profiles in simulations. While conventional definitions depend only on the static density profile, the location of Rsp depends on the mass accretion rate because a rapidly growing potential well reduces the apocenters of particles’ orbits. Overall, Rsp is significantly larger than spherical overdensity radii, roughly between about 1 and 2.5 Rvir. This is illustrated in the figure below: the left panel shows a slowly accreting halo where Rsp is significantly larger than R200m, the right panel shows a quickly accreting halo where Rsp is slightly smaller than R200m.
While the location of the density caustic is obvious in the above examples, identifying it in individual halos is non-trivial due to non-sphericity, sub-structure, and the complex nature of orbits in LCDM halos. We have presented two algorithms for measuring Rsp. The first, SHELLFISH, finds sharp drops in the 3D density field around halos and fits their locations with non-spherical shells (Mansfield et al. 2017). The second, SPARTA, analyzes the orbits of individual particles and assigns the halo a splashback radius based on the distribution of the orbit apocenters (Diemer 2017). The figure below shows the classical virial radii (orange) of halos with at least 1000 particles in a simulation, the white circles show the splashback radii identified by SPARTA.
Observationally, the splashback radius has been detected in the density profiles of satellite galaxies around stacked clusters as well as in weak lensing (see references below). Initially, these observations found slightly lower splashback radii than expected from simulations but this difference has likely been tracked to projection effects and systematics in the cluster selection.
Most recently, we have provided publicly available halo catalogs and merger trees for the Erebos N-body simulations that contain both conventional and splashback masses and radii, as well as subhalo relations for each definition. The relationship between spherical overdensity and splashback radii has also been summarized in a fitting function that is included in the Colossus python code.
Literature on the splashback radius
In the following list, I will try to give an overview of particularly relevant, splashback-related publications. They are crudely split into theoretical and observational work and sorted chronologically within those groups. Pre-prints are marked as (pp). This list is probably incomplete, out of date, or biased by my particular view of the topic. If you feel that I missed or mischaracterized any papers, please let me know!
Simulations and theoretical modeling
- Diemer & Kravtsov 2014 (first detection of density drop in cosmological simulations)
- Adhikari et al. 2014 (theoretical explanation of density drop as caustic at first apocenter)
- More et al. 2015 (proposal as radius definition and relation to spherical overdensity radii and masses)
- Shi 2016a (splashback in the spherical collapse model with dark energy)
- Shi 2016b (relative location of accretion shocks and splashback radii)
- Mansfield et al. 2017 (the SHELLFISH algorithm to determine non-spherical splashback shells)
- Diemer 2017 (the SPARTA algorithm to determine the splashback radius)
- Diemer et al. 2017 (fitting function for Rsp-R200m relation and dependence on mass, accretion rate etc.)
- Busch & White 2017 (projection effects and other issues in splashback observations)
- Okumura et al. 2018 (splashback in non-isotropic and momentum correlations)
- Fong et al. 2018 (observability of the steepening feature with weak lensing)
- Adhikari et al. 2018 (dependence of Rsp on dark energy and modified gravity)
- Contigiani et al. 2019 (the splashback radius in symmetron gravity)
- Sunayama & More 2019 (update on projection effects in splashback measurements)
- Mansfield & Kravtsov 2020 (assembly bias when taking splashback into account)
- Sugiura et al. 2020 (phase space, splashback, and self-similar modeling)
- Deason et al. 2020a (connection between splashback radius and the stellar halo in galaxies)
- Banerjee et al. 2020 (the splashback radius in self-interacting dark matter models)
- Xhakaj et al. 2020 (comparison of measurement techniques and forecasts for future surveys)
- Diemer 2020a (catalogs and merger trees with splashback radii and masses)
- Diemer 2020b (splashback mass functions and their remarkable universality)
- Deason et al. 2021 (connection between splashback radius and the stellar halo in clusters)
- Aung et al. 2021a (the phase-space structure of halos around the splashback radius)
- Diemer 2021 (subhalo and flyby fractions as defined by SO and splashback radii)
- O’Neil et al. 2021 (splashback signatures in DM, gas, and galaxies in IllustrisTNG)
- Contigiani et al. 2021 (splashback in hydro simulations of galaxy clusters)
- Ryu & Lee 2021 (excursion-set modeling of the splashback mass function)
- Zhang et al. 2021 (evolution of splashback and shock radii in mergers)
- Aung et al. 2021b (connection between splashback and accretion shocks in clusters)
- Dacunha et al. 2022 (splashback as a probe for galaxy evolution in clusters)
- O’Neil et al. 2022 (impact of galaxy selection in satellite profiles)
- Diemer 2022 (density profiles I: the shape of the splashback feature from orbiting particles)
- Ryu & Lee 2022 (splashback mass function in cosmologies with massive neutrinos)
- Wang et al. 2022 (splashback features in anisotropic density profiles)
- Diemer 2023 (density profiles II: new fitting function for profiles and splashback feature)
- Genina et al. 2023 (stellar and DM splashback from individually resolved satellites)
- Shin & Diemer 2023 (correlation between Rsp, halo properties, and mass accretion history)
- Zhang et al. 2023 (impact of the splashback feature on weak lensing measurements)
- Towler et al. 2024 (splashback-like features in DM, X-ray, and SZ profiles in FLAMINGO)
- Mpetha et al. 2024 (forecasts for accuracy of Rsp-based cosmological inference)
- Lebeau et al. 2024 (pp) (baryonic and DM profiles in constrained simulation of Virgo)
- O’Shea et al. 2024 (pp) (investigation of dynamical friction effects on Rsp)
- Haggar et al. 2024 (pp) (measuring cosmology from Rsp)
Observations of splashback
- Tully 2015 (tentative detection of a drop in galaxy density around the Coma cluster)
- Patej & Loeb 2016 (tentative detection in individual SDSS clusters)
- More et al. 2016 (first significant detection of splashback radius in stacked galaxy clusters in SDSS)
- Adhikari et al. 2016 (observation of dynamical friction from the steepening feature in clusters)
- Umetsu & Diemer 2017 (attempt to discover splashback in weak lensing in CLASH clusters)
- Baxter et al. 2017 (detection in DES clusters)
- Nishizawa et al. 2018 (detection in HSC survey)
- Chang et al. 2018 (detection in galaxy profiles and lensing in DES clusters)
- Zürcher & More 2019 (detection in SZ-selected clusters from Planck in Pan-STARRS data)
- Contigiani et al. 2019 (lensing analysis in CCCP clusters)
- Shin et al. 2019 (detection in SZ-selected clusters from ACT and SPT in DES data)
- Murata et al. 2020 (detection in HSC survey and modeling of selection/projection effects)
- Tomooka et al. 2020 (detecting cluster edges in phase space)
- Bianconi et al. 2021 (first detection in spectroscopically confirmed cluster member profiles)
- Gonzalez et al. 2021 (possible detection of splashback in ICL of individual cluster)
- Shin et al. 2021 (updated analysis with ACT year 5 clusters and DES year 3 galaxies)
- Adhikari et al. 2021 (using the splashback signals of galaxy samples as a dynamical clock)
- Kopylova & Kopylov 2022 (attempt to measure Rsp for individual clusters from galaxies)
- Contigiani et al. 2023 (splashback and lensing constraints on cluster masses and MG)
- Rana et al. 2023 (splashback radius from eROSITA X-ray selected clusters)
- Giocoli et al. 2024 (pp) (splashback radius from KIDS lensing across redshift and mass)
- Xu et al. 2024 (pp) (measurement of Rsp in DECALS down to low masses)
Related work
- Fillmore & Goldreich 1984 (spherical collapse model in Einstein-de Sitter universe)
- Bertschinger 1985 (spherical collapse model in Einstein-de Sitter universe)
- Lithwick & Dalal 2011 (non-spherical collapse model)
- Vogelsberger et al. 2011 (non-spherical collapse model with focus on outer caustic radius)
- Lau et al. 2015 (effect of accretion rate on baryonic profiles in clusters)
- Zu et al. 2017 (projection effects in optically selected clusters)
- Walker et al. 2019 (review: the physics of galaxy cluster outskirts)
- O’Donnell et al. 2021 (observing the connection between accretion and star formation)
- Fong & Han 2021 (halo boundary based on bias profiles)
- Wagoner & Rozo 2021 (dynamical cluster edges as a cosmological observable)
- Garcia et al. 2021 (redefinition of the halo boundary based on correlation functions)
- Anbajagane et al. 2022 (comparing possible measurements of accretion shocks to Rsp)
- Shi 2023 (spherical collapse model from iterative mean field approach)
- Enomoto et al. 2024 (dissecting the orbital structure of halos)