Marcus Marci’s Investigations of the Prism and their Relation to Newton’s Theory of Color [1932c

Abstract

The Prague doctor and naturalist Marcus Marci1 has been frequently cited as a predecessor of Newton in establishing the physical theory of color; he recognized namely that (1) different refractions uniquely correspond to the different colored rays produced by a prism; (2) the monochromatic rays so defined maintain their color unchanged under further refraction: two propositions which in fact form an essential part of the Newtonian theory of color. Now, naturally, this last assertion is correct as far as it goes; however I would not take it as proper to hold Marci up as Newton’s predecessor merely on the basis of this fact. For, completely apart from the question of whether or not Newton was acquainted with Marci’s arguments, the history of physics should not be comprehended as a mere chronological stringing together of isolated discoveries, but rather the main emphasis should be placed on the logical connections between the individual steps which contribute to the development of a physical theory. In order to judge whether, from this standpoint, a given theory can be designated as a predecessor of another, more complete, theory, the following question must above all be decided: Does an extension and modification, in keeping with their meaning, of the essential categories suffice for arriving at the second theory from the first; or is a complete rejection of the basic concept of the first theory required? Only in the first case could one speak of an historical connection. In this sense, for example, Galileian mechanics would be a predecessor of Newtonian mechanics and this latter in turn a predecessor of Einsteinian mechanics; or the older quantum theory would also be a forerunner of modern quantum mechanics.KeywordsColored LightLogical ConnectionNewtonian TheoryCrystal BallSpectral ColorThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.