The MultiDark Database: Release of the Bolshoi and MultiDark Cosmological Simulations

We present the online MultiDark Database – a Virtual Observatory-oriented, relational database for hosting various cosmological simulations. The data is accessible via an SQL (Structured Query Language) query interface, which also allows users to directly pose scientific questions, as shown in a number of examples in this paper. Further examples for the usage of the database are given in its extensive online documentation (www.multidark.org). The database is based on the same technology as the Millennium Database, a fact that will greatly facilitate the usage of both suites of cosmological simulations. The first release of the MultiDark Database hosts two 8.6 billion particle cosmological N-body simulations: the Bolshoi (250/h Mpc simulation box, 1/h kpc resolution) and MultiDark Run1 simulation (MDR1, or BigBolshoi, 1000/h Mpc simulation box, 7/h kpc resolution). The extraction methods for halos/subhalos from the raw simulation data, and how this data is structured in the database are explained in this paper. With the first data release, users get full access to halo/subhalo catalogs, various profiles of the halos at redshifts z=0-15, and raw dark matter data for one time-step of the Bolshoi and four time-steps of the MultiDark simulation. Later releases will also include galaxy mock catalogs and additional merging trees for both simulations as well as new large volume simulations with high resolution. This project is further proof of the viability to store and present complex data using relational database technology. We encourage other simulators to publish their results in a similar manner.

💡 Research Summary

The paper presents the MultiDark Database, an online relational database that hosts the results of two state‑of‑the‑art cosmological N‑body simulations: Bolshoi and MultiDark Run 1 (MDR1). Both simulations contain roughly 8.6 billion dark‑matter particles, but differ in volume and resolution—Bolshoi covers a 250 h⁻¹ Mpc cube with 1 h⁻¹ kpc force resolution, while MDR1 spans a 1 Gpc h⁻¹ cube with 7 h⁻¹ kpc resolution. The simulations adopt ΛCDM parameters consistent with WMAP5/7 (Ω_m≈0.27, Ω_Λ≈0.73, σ₈≈0.82).

The database adopts the same technology stack as the Millennium Database (Microsoft SQL Server, T‑SQL, and the Spatial3D library), enabling seamless cross‑database analyses. Data are organized into relational tables with unique identifiers (fofId, bdmId) that link halos, subhalos, particles, and derived profiles. Indexes on common query fields (mass, coordinates, identifiers) and spatial indexing dramatically improve performance for large‑scale queries.

Two halo‑finding algorithms are provided: the Bound Density Maximum (BDM) finder, which supplies two definitions of halo radius—BDMV (virial overdensity Δ_vir(z)) and BDMW (Δ=200 ρ_crit)—and the Friends‑of‑Friends (FOF) finder, which groups particles using a linking length of 0.2 times the mean inter‑particle separation. Both catalogs contain 23 physical properties per halo, including position, velocity, various mass measures, concentration, spin, and substructure information. The FOF catalog also includes a particle‑to‑group mapping table, allowing users to retrieve the raw particle list for any halo.

Access to the data is provided through a web portal (www.multidark.org). Registered users can submit arbitrary SQL queries via an interactive form, visualize results with VOPlot, and download outputs in CSV or VOTable formats. For large result sets, a scripted interface (wget.multidark.org/MyDB) enables batch retrieval and integration with tools such as TOPCAT or IDL. A public “miniMDR1” instance offers a 100 h⁻¹ Mpc sub‑volume for trial queries without registration.

The initial data release includes full halo/subhalo catalogs, radial profiles for redshifts z = 0–15, and limited raw particle snapshots (one Bolshoi snapshot and four MDR1 snapshots). Future releases will add galaxy mock catalogs, BDM‑based merger trees, additional time‑steps, and new large‑volume, high‑resolution simulations. By demonstrating that multi‑terabyte cosmological datasets can be efficiently stored, queried, and disseminated via a relational database, the authors encourage other simulation groups to adopt similar open‑access strategies, thereby fostering broader collaboration between theoretical and observational cosmology.