On galactic scales, ranging from 1 kpc to 100 kpc, the need for a significant amount of dark matter comes from theoretical models that were developed to explain the observed rotation curves in disk galaxies by introducing a non-visible mass component. The standard model hypothesizes that DM has distinct properties from luminous matter (LM), but it’s not the only one that can explain the observations.

Recently, a new model called the Dark Matter Disk (DMD) model was introduced. It considers the possibility that DM is confined to galactic disks, just like LM.

This model is inspired by evidence suggesting a correlation between DM and the distribution of neutral hydrogen gas (HI) in disk galaxies. This correlation was first noted by Albert Bosma in the 1980s (Astron. J., 86, 1791, 1981) and later confirmed by numerous other studies (e.g., Sylos Labini et al., Mon. Not. R. Astron. Soc., 527, 2697, 2024, and references therein). Neutral hydrogen, which is observed from the emission of the 21cm line, is much more widespread in the disk than the stellar component. The DMD model assumes that wherever there is an HI atom, it emits the 21cm line. This form of DM could potentially consist of cold ordinary (baryonic) matter. For example, cold hydrogen clouds (at temperatures below 15 Kelvin) do not emit the 21cm line and are therefore almost invisible to electromagnetic detection.

In summary, the key points are the hypothesis that DM is traced by HI (whose density decreases more slowly with the radius compared to the stellar component) and the fact that the gravitational potential of a disk is more intense than that of a spherical distribution. This allows it to provide the same contribution to the circular velocity with a smaller mass. The constraints on the geometric distribution of the DM component are therefore crucial for distinguishing between the standard halo model and the DMD model.

It is possible to observationally distinguish between a galaxy with a large mass in a spherical halo and one with a smaller mass confined to a disk by analyzing generalized rotation curves, not only in the galactic plane but also outside of it. This analysis provides new information about the geometry of DM, as the flattened disk of the DMD model significantly influences vertical accelerations, unlike the symmetric spherical halo model, which has negligible gravitational effects out of the plane.

Another way to differentiate between a disk and a spherical distribution is to analyze the effects of strong gravitational lensing. Although high-resolution observations of strong gravitational lensing on galactic scales are not yet available, a detailed numerical investigation of theoretical models is necessary to study the role of mass distribution geometry in future gravitational lensing observations.

The European Space Agency’s Gaia satellite, launched in 2013, has revolutionized our understanding of the Milky Way (MW). Its precision has enabled a detailed mapping of the galaxy, covering up to ~20 kpc with high accuracy. To date, Gaia has released three datasets (2016, 2018, 2022), with two more planned for 2025-2026 and 2030, and has allowed for precise measurement of the MW’s rotation curve.

The CREF group has developed a statistical method that, based on the plausible assumption that observational errors are Gaussian, allows us to reach distances where the signal-to-noise ratio is around one. All these different determinations have consistently shown a decline in the rotation curve up to 30 kpc, contrary to previous measurements that found a flat profile. The best fits between theoretical mass models and the data (see the following figure) show that a DMD (Dark Matter Disk) model agrees better than a spherical halo model.

The analysis of the MW’s rotation curves outside the galactic plane also suggests that the DMD model fits the data better. The method will be further tested with new Gaia mission data, which will provide a better understanding of the spatial extent of coherent, large-amplitude motions in all velocity components, already detected in previous data releases.

Finally, Gaia will improve our understanding of the MW’s outer regions through more detailed sampling of halo stars and globular clusters. These objects, which are expected to show an almost isotropic velocity dispersion, could reveal deviations from equilibrium caused by tidal effects or other phenomena. Quantifying the spatial anisotropies in velocity distribution will help validate equilibrium hypotheses or discover out-of-equilibrium dynamics. Gaia will also enable detailed studies of nearby galaxies such as M31, M33, and the Magellanic Clouds, providing 6D samples of their stellar distributions. These data, analyzed using our deconvolution method, represent a bridge between kinematic studies based on precise stellar observations and those derived from HI line-of-sight velocity maps.

The formulation of the DMD model was developed through a careful study of high-resolution HI velocity and dispersion maps of nearby galaxies, provided by two important surveys: (i) The HI Nearby Galaxy Survey (THINGS), which includes 34 nearby galaxies with a wide range of morphologies and luminosities, and (ii) The LITTLE THINGS survey, which focuses on small, faint galaxies, complementing THINGS.

Other recent and ongoing surveys will be useful for further developing this research line.

Planned Milestones

M1. Milky Way (MW) Velocity Field

The analysis of the Milky Way’s velocity field will provide valuable information about the rotation curve and its dependence on the vertical height from the galactic plane. Detailed studies on the velocity distribution across the galactic disk will allow us to link spatial structures, such as spiral arms and satellites, to galactic kinematics and dynamics. Advanced data will enable the study of halo stars, globular clusters, and satellite galaxies within a range of 30–200 kpc, refining our understanding of galactic dynamics and interactions within the Local Group. These investigations will offer a comprehensive view of the Milky Way’s kinematics and dynamics.

M2. Velocity Fields of External Galaxies

The mapping of external galaxy velocity fields, using two-dimensional measurements of radial and transverse velocity components obtained with our developed method, will reveal the relationship between kinematics and spatial structures, such as spiral arms, satellites, etc. This approach will allow us to constrain the inflow and outflow of neutral hydrogen in the outer regions of galaxies. By analyzing the interaction between dark matter (DM) and baryonic matter (BM), we will address fundamental questions, such as the formation of spiral arms and the distribution of matter, providing new perspectives on the formation and evolution of galaxies.

M3. Geometry of Dark Matter Distribution on a Galactic Scale

Through the analysis of the geometry of the dark matter (DM) distribution, particularly using the rotation curves of the Milky Way and external galaxies, this research will impose strict constraints on galactic mass models. By comparing the standard halo model with the dark matter disk (DMD) model, it will be possible to determine which one aligns better with observational data. Understanding the role of DM in shaping the structure and dynamics of galaxies will help clarify its nature (e.g., baryonic or non-baryonic) and refine models of galaxy formation.

M4. Modeling Strong Gravitational Lensing

Disk galaxies are ideal laboratories for testing competing dark matter (DM) models or alternative theories of gravity, as they allow for rigorously constraining the symmetries of their mass distribution. Another task focuses on investigating DM in disk galaxies through strong gravitational lensing observations. Although these observations are still ongoing, it is essential to develop simulations of disk galaxies as strong gravitational lenses, varying the mass fractions of DM within the Einstein radius. These simulations will allow for a detailed evaluation of how sensitive gravitational lensing data are to the masses of a galaxy’s different components and the geometry of the DM distribution.