The Discrepancy in Galaxy Rotation Curves

Version 1

In this work we try a new approach for dealing with the discrepancy between observed galaxy rotation curves and theoretical predictions. This new approach does not involve any changes in the current fundamental laws of nature or the addition of dark halos. Rather, it is based on the following single assumption: the observed velocities presented in rotation curves are not given relative to the galaxies' local inertial frames. Another way of putting it down: fictitious forces, which arise in non-inertial frames, should be taken into account when constructing a theoretical rotation curve. It turns out that this single assumption is sufficient in order to establish a robust model for fitting rotation curves. Applying the new model on a sample of more than 30 galaxies provides very promising results.

The Effects of Inertial Forces on the Dynamics of Disk Galaxies

Version 2

When dealing with galactic dynamics, or more specifically, with galactic rotation curves, one basic assumption is always taken: the frame of reference relative to which the rotational velocities are given is assumed to be inertial. In other words,  fictitious forces are assumed to vanish relative to the observational frame of a given galaxy. It might be interesting, however, to explore the outcomes of dropping that assumption; that is, to search for signatures of non-inertial behavior in the observed data. In this work, we show that the very discrepancy in galaxy rotation curves could be attributed to non-inertial effects. We derive a model for spiral galaxies that takes into account the possible influence of fictitious forces and find that the additional terms in the new model, due to fictitious forces, closely resemble dark halo profiles. Following this result, we apply the new model to a wide sample of galaxies, spanning a large range of luminosities and radii. It turns out that the new model accurately reproduces the structures of the rotation curves and provides very good fittings to the data.