The Luminous Convolution Model as an alternative to dark matter in
  spiral galaxies
  The Luminous Convolution Model (LCM) demonstrates that it is possible to
predict the rotation curves of spiral galaxies directly from estimates of the
luminous matter. We consider two frame-dependent effects on the light observed
from other galaxies: relative velocity and relative curvature. With one free
parameter, we predict the rotation curves of twenty-three (23) galaxies
represented in forty-two (42) data sets. Relative curvature effects rely upon
knowledge of both the gravitational potential from luminous mass of the
emitting galaxy and the receiving galaxy, and so each emitter galaxy is
compared to four (4) different Milky Way luminous mass models. On average in
this sample, the LCM is more successful than either dark matter or modified
gravity models in fitting the observed rotation curve data.
  Implications of LCM constraints on populations synthesis modeling are
discussed in this paper. This paper substantially expands the results in
arXiv:1309.7370.
