A statistical investigation of the mass discrepancy-acceleration relation
Harry Desmond

TL;DR
This study uses the mass discrepancy-acceleration relation (MDAR) to test galaxy-halo models in LCDM, finding that while some features are reproduced, there are significant discrepancies in scatter, normalization, and galaxy-halo correlations.
Contribution
It provides a comprehensive statistical analysis of MDAR features and evaluates the consistency of LCDM-based galaxy-halo models with observational data.
Findings
AM reproduces the MDAR shape but overpredicts scatter.
Dark matter is too centrally concentrated in models.
Evidence suggests galaxy size and type correlate with halo properties.
Abstract
We use the mass discrepancy-acceleration relation (the correlation between the ratio of total-to-visible mass and acceleration in galaxies; MDAR) to test the galaxy-halo connection. We analyse the MDAR using a set of 16 statistics that quantify its four most important features: its shape, its scatter, the presence of a "characteristic acceleration scale," and the correlation of its residuals with other galaxy properties. We construct an empirical framework for the galaxy-halo connection in LCDM to generate predictions for these statistics, starting with conventional correlations (halo abundance matching; AM) and introducing more where required. Comparing to the SPARC data, we find that: 1) the approximate shape of the MDAR is readily reproduced by AM, and there is no evidence that the acceleration at which dark matter becomes negligible has less spread in the data than in AM mocks; 2)…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
