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There was/is nothing magic about epicycles. Epicycles was part of a model which described the movement of the planets. Now we have better and more precise model

by olavk 9y ago

There was/is nothing magic about epicycles. Epicycles was part of a model which described the movement of the planets. Now we have better and more precise model, but that does not mean epicycles was "magic". There is nothing magic about the the word "dark matter" either. Yes indeed it describe a phenomen we don't understand, this does not mean it is magic.

TillE 9y ago
Epicycles were wrong. They were an incorrect theory attempting to fit the math.
- yorwba 9y ago
  Using epicycles just means to decompose the motion into its Fourier series. It may not be the most elegant description, but its not wrong per se, either.
  - JadeNB 9y ago
    > Using epicycles just means to decompose the motion into its Fourier series. It may not be the most elegant description, but its not wrong per se, either. One issue here is that (as I understand the history) epicycles were not originally proposed in the context of "just add them until you've got something that looks right"; it was proposed that, occasionally, one needed to add one epicycle. After a while it was found that even this didn't work, and we needed sometimes to add another. I forget whether the theory collapsed before instances were found where we'd need a third. This, I think, is 'wrong' in the sense of physics: if your model is constantly scrambling to catch up with newly acquired data, then it has no predictive, and hence little scientific, value. Further, the very ability of epicycles constantly to scramble to catch up—the ability of trigonometric polynomials to approximate continuous functions arbitrarily well over arbitrary bounded intervals, as you mention—is also a mark against them: a scientific theory that is so general that it could be tuned to predict anything can, in fact, for that reason actually predict nothing.
    - olavk 9y ago
      Epicycles were added to make the model better fit the observations. There is nothing wrong or unscientific about this. It is just like new planets are added to the model of the solar system when new planets are observed.
      - JadeNB 9y ago
        > There is nothing wrong or unscientific about this. To be sure, there is nothing wrong with changing your model in response to data—what would be wrong would be the opposite. What I was calling 'wrong' was two things: (1) a model that can only be tuned post hoc to observations (that is, it's always being changed to fit them, and never predicting new ones); and (2) a model that is so flexible that it can be tuned to fit any observations (again, because it will never have the ability to predict future observations).
        olavk 9y ago
        The predictions by the system is the movements of the planets in the sky. The Ptolemaic system with epicycles actually did this pretty well, considering the available data. It is just that as better observations and better calculations became available, the model have to be more precise which required more epicycles. I don't really get the thing about "too flexible". According to Wikipedia there is apparently some myths floating around regarding the science history of epicycles, but I assure there is nothing magical about them - at least they are not any more magical than Newtonian mechanics.
        JadeNB 9y ago
        > I don't really get the thing about "too flexible". According to Wikipedia there is apparently some myths floating around regarding the science history of epicycles, but I assure there is nothing magical about them - at least they are not any more magical than Newtonian mechanics. I think we may be talking at cross purposes here, but I wanted to give it another shot. I do not think that there is anything magical about epicycles, and my objection to them is scientific; it has nothing to do with their history. My claim is that a scientific tool is valid science only to the extent that it has predictive power. If your model has so many parameters that, by setting them to appropriate values, you can fit any outcome, then (absent some other data telling you which values of the parameters to use) you'll never actually predict anything, only scramble setting them to 'post-dict' existing observations—which is, effectively, useless. (For example, any finite collection of observations can be 'post-dicted' by a high-degree polynomial, and we can accommodate more observations simply by increasing the degree of the interpolating polynomial. This is not magical, and mathematically totally sound; but its very flexibility means that it is scientifically useless, because there's no reason to believe that our perfect fit to the `n` values we've seen so far says anything about the (`n + 1`)st value we'll see next.)
- douche 9y ago
  This should not be downvoted

by olavk 9y ago

TillE 9y ago

Epicycles were wrong. They were an incorrect theory attempting to fit the math.

yorwba 9y ago
Using epicycles just means to decompose the motion into its Fourier series. It may not be the most elegant description, but its not wrong per se, either.
- JadeNB 9y ago
  > Using epicycles just means to decompose the motion into its Fourier series. It may not be the most elegant description, but its not wrong per se, either. One issue here is that (as I understand the history) epicycles were not originally proposed in the context of "just add them until you've got something that looks right"; it was proposed that, occasionally, one needed to add one epicycle. After a while it was found that even this didn't work, and we needed sometimes to add another. I forget whether the theory collapsed before instances were found where we'd need a third. This, I think, is 'wrong' in the sense of physics: if your model is constantly scrambling to catch up with newly acquired data, then it has no predictive, and hence little scientific, value. Further, the very ability of epicycles constantly to scramble to catch up—the ability of trigonometric polynomials to approximate continuous functions arbitrarily well over arbitrary bounded intervals, as you mention—is also a mark against them: a scientific theory that is so general that it could be tuned to predict anything can, in fact, for that reason actually predict nothing.
  - olavk 9y ago
    Epicycles were added to make the model better fit the observations. There is nothing wrong or unscientific about this. It is just like new planets are added to the model of the solar system when new planets are observed.
    - JadeNB 9y ago
      > There is nothing wrong or unscientific about this. To be sure, there is nothing wrong with changing your model in response to data—what would be wrong would be the opposite. What I was calling 'wrong' was two things: (1) a model that can only be tuned post hoc to observations (that is, it's always being changed to fit them, and never predicting new ones); and (2) a model that is so flexible that it can be tuned to fit any observations (again, because it will never have the ability to predict future observations).
      - olavk 9y ago
        The predictions by the system is the movements of the planets in the sky. The Ptolemaic system with epicycles actually did this pretty well, considering the available data. It is just that as better observations and better calculations became available, the model have to be more precise which required more epicycles. I don't really get the thing about "too flexible". According to Wikipedia there is apparently some myths floating around regarding the science history of epicycles, but I assure there is nothing magical about them - at least they are not any more magical than Newtonian mechanics.
        JadeNB 9y ago
        > I don't really get the thing about "too flexible". According to Wikipedia there is apparently some myths floating around regarding the science history of epicycles, but I assure there is nothing magical about them - at least they are not any more magical than Newtonian mechanics. I think we may be talking at cross purposes here, but I wanted to give it another shot. I do not think that there is anything magical about epicycles, and my objection to them is scientific; it has nothing to do with their history. My claim is that a scientific tool is valid science only to the extent that it has predictive power. If your model has so many parameters that, by setting them to appropriate values, you can fit any outcome, then (absent some other data telling you which values of the parameters to use) you'll never actually predict anything, only scramble setting them to 'post-dict' existing observations—which is, effectively, useless. (For example, any finite collection of observations can be 'post-dicted' by a high-degree polynomial, and we can accommodate more observations simply by increasing the degree of the interpolating polynomial. This is not magical, and mathematically totally sound; but its very flexibility means that it is scientifically useless, because there's no reason to believe that our perfect fit to the `n` values we've seen so far says anything about the (`n + 1`)st value we'll see next.)
douche 9y ago
This should not be downvoted