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The Luminous Convolution Model (LCM) demonstrates that it is possible topredict the rotation curves of spiral galaxies directly from estimates of theluminous matter. We consider two frame-dependent effects on the light observedfrom other galaxies: relative velocity and relative curvature. With one freeparameter, we predict the rotation curves of twenty-three (23) galaxiesrepresented in forty-two (42) data sets. Relative curvature effects rely uponknowledge of both the gravitational potential from luminous mass of theemitting galaxy and the receiving galaxy, and so each emitter galaxy iscompared to four (4) different Milky Way luminous mass models. On average inthis sample, the LCM is more successful than either dark matter or modifiedgravity models in fitting the observed rotation curve data.  Implications of LCM constraints on populations synthesis modeling arediscussed in this paper. This paper substantially expands the results inarXiv:1309.7370.

The Luminous Convolution Model as an alternative to dark matter in spiral galaxies