Something that I've been thinking lately (motivated by the simple explanations given in crystallography, which I interpret as a complex phenomenon),

are there any references (books, papers) that would try to shine some light onto the philosophical question of:

why does nature seem to follow so simple human-conceived patterns?

By simple patterns one can think of e.g. trigonometry.

Obviously not interested in pseudoscience or religions, but rational and scientific explanations/speculations.

  • "On Growth and Form: The Complete Revised Edition" by D'Arcy Wentworth Thompson. A classic. Commented Aug 19, 2018 at 11:18
  • I think the kind of question you're after is often expressed in terms of the applicability of mathematics (why do maths apply to the world?) Maybe you'll find resources if you look for that kind of question in philosophy of mathematics Commented Aug 19, 2018 at 23:01
  • Google "the unreasonable effectiveness of mathematics", a famous Eugene Wigner quote, that has been widely discussed, e.g., en.wikipedia.org/wiki/…
    – user19423
    Commented Aug 20, 2018 at 13:41
  • This question implies an affirming-the-consequent fallacy: "we have conceived this patterns which are identical to how nature behaves, so nature is following such patterns". This is like answering why Newton seems to follow my ideas. The right question will be why do I agree with Newton, or why does the patterns we've conceived adjust perfectly to nature. And such question has been posted several times. Previous comments present the answer to such question, they don't answer why nature acts in consequence.
    – RodolfoAP
    Commented Aug 22, 2018 at 1:55

3 Answers 3


What is your definition of "seems to follow?"

One can argue that that appearance needs be nothing more than an illusion. Thus one can argue that nature seems to follow simple human-conceived patterns because the definition of the concept of following a pattern is a human-conceived pattern itself.

One such example of why this thinking is reasonable is the phrase "the devil is in the details." You mention that trigonometry is an example of a simple human-conceived pattern. However, current scientific evidence suggests it is anything but simple. General relativity suggests that space is warped, and trigonometry on any non-Euclidean space is far from simple. In fact, it's so wretchedly frustrating that we often are forced to rely on numeric solutions to solve problems.

If things only appear to be simple because we aren't seeing the details, then it is easy to argue that nature seems to follow those patterns simply because we are ignoring that which does not follow the patterns.


The same reason as why religions were created by early hominids: our brains are wired to recognize patterns.

Recognition of these patterns often meant the difference between survival and death. From an Evolutionary point-of-view, it was more likely to pass on genes for "false positive" patterns than "skeptical" patterns. After a few thousand generations, the pattern-seeking drive in our minds was augmented by language (i.e. abstraction) and basic understanding of geometry.

It's the same reason as why theists perceive nature to be designed, while in reality all of this is a consequence of natural selection.

  • Would you have references for the pattern recognition? References support your answer and give the reader some place to go for more information. Regarding pattern recognition I suspect it is not only theists but atheists seeing patterns and from there describing physical laws. Commented Aug 21, 2018 at 14:53
  • Sure: NIH Study.
    – Codosaur
    Commented Aug 21, 2018 at 15:14
  • Then you should add it with details in the answer. You can edit your answer by clicking the "edit" link. Others may edit your answer as well. Commented Aug 21, 2018 at 15:24
  • I made an edit to show you what is possible. You can see the versions by clicking on the "edited" link. You can even roll back my edit. Commented Aug 21, 2018 at 15:26

In the context of artificial neural networks, in this paper, two physicists and a mathematician attempt to show rigorously why "deep learning" techniques work so well to model our physical world.

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