Testing multiflavored ultralight dark matter models with SPARC

We perform maximum likelihood estimates for single and double flavor ultralight dark matter (ULDM) models using the Spitzer Photometry and Accurate Rotation Curves database. These estimates are compared to maximum likelihood estimates for several commonly used cold dark matter (CDM) models. By comparing various CDM models we find, in agreement with previous studies, that the Burkert and Einasto models tend to perform better than other commonly used CDM models. We focus on comparisons between the Einasto and ULDM models and analyze cases for which the ULDM particle masses are fixed or free to vary. For each of these analyses, we perform fits assuming the soliton and halo density profiles are summed together or matched at a given radius. Letting the particle masses vary and assuming the summed models, we find a negligible preference for any particular range of particle masses within 10-25 eV <= m <= 10-19 eV. For the matched models, we find that almost all galaxies prefer particle masses in the range 10-23 eV < m < 10-20 eV. For both double flavor models we find that most galaxies prefer approximately equal particle masses. Fixing the particle masses, we find the best fit results for the particle mass m = 10-20.5 eV, assuming the single flavor models, and m1 = 10-20.5 eV, m2 = 10-20.2 eV, assuming the double flavor, matched model.

Automated summary

By comparing maximum likelihood estimates for different cold dark matter (CDM) models, this study finds that the Burkert and Einasto models perform better than other commonly used CDM models. For ultralight dark matter (ULDM) models, most galaxies prefer particle masses in the range of 10-23 eV < m < 10-20 eV. In double flavor models, galaxies tend to prefer approximately equal particle masses.