I am interested in how today's professional mathematicians view the Pythagorean theorem, in terms of how the theorem fits within the axiomatic framework of mathematics. I often come across textbooks that define length by the Pythagorean theorem, so that the theorem is in essence a definition or axiom. In more modern mathematics such as linear algebra, is the Pythagorean theorem generally just used as the definition of length? Is it more conventional today to treat the Pythagorean theorem as a definition (or axiom) rather than a theorem? Are there any modern proofs of the Pythagorean theorem that don't rely on Euclidean geometry (like a proof that utilizes linear algebra/the dot product, etc.)?
Where does the Pythagorean theorem "fit" within modern mathematics?
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0I have posed the following question, now a community wiki, What is Modern Mathematics? Is this an exact concept with a clear meaning? [http://math.stackexchange.com/questions/3447/what-is-modern-mathematics-is-this-an-exact-concept-with-a-clear-meaning – 2010-08-27
6 Answers
Length, in Euclidean geometry, is a relation, not a number. We say that two segments are of the same length if they are congruent to each other, and congruence is one of the undefined notions of Euclidean geometry. The Pythagorean theorem comes about as soon as you decide to map lengths to positive real numbers, and it does so because of how length and angles are related by the congruence and similarity axioms (e.g., how the Pythagorean theorem is proved).
Lengths, in vector spaces, can be anything that satisfies the axioms for a norm. But to have a Pythagorean theorem, you need a notion of perpendicularity of vectors, that is, an inner product, which exists only if the norm satisfies the parallelogram law. For example, the taxicab norm, which is given by $|(a,b)|=|a|+|b|$ does not come from an inner product and there is no Pythagorean theorem for that notion of length.
The natural question is why does the Pythagorean theorem in Euclidean geometry correspond to the Pythagorean theorem in a finite dimensional vector space over the reals with an inner product? (there is a theorem that states that in a finite-dimensional vector space there is only one inner product up to isomorphism, so we really can talk about THE Pythagorean theorem).
The answer is that the finite dimensional vector space over the reals with an inner product encodes the congruence and similarity axioms of Euclidean geometry. The basic exposition of (most of) this can be found in the first half of Chapter 2 of Emil Artin's wonderful book Geometric Algebra.
Take a geometry of points and lines for which the following statements are true:
- Any two points determine a line.
- Parallel postulate: for any point $p$ not on line $\ell_1$ there exists a unique line $\ell_2$ that passes through $p$ but doesn't intersect $\ell_1$.
- Non-triviality: there exist $3$ non-collinear points.
- Desargues' Theorem (the wiki article is horrible)
The first three statements allow you to define translations (transformations of the plane that send lines to parallel lines and have no fixed points), while the fourth allows you to a construct a field over which the space of translations is a $2$-dimensional vector space, and such that if you associate translations $OP$ and $OQ$ with $(0,1)$ and $(1,0)$, then any point $R$ has a translation $OR$ which can be written as $(a,b)$ with $a$ and $b$ in the field.
In this way, any affine Desarguesian plane (thing that satisfies statements 1, 2, 3 and 4) can be identified with a $2$-dimensional vector space over some field (and conversely any $2$-dimensional vector space over some field corresponds to an affine Desarguesian plane).
Alright. Now, Euclidean geometry satisfies Desargues' Theorem, so which field does it correspond to? Well, it turns out that the fact that the geometry is ordered (i.e., we have a notion of an ordering of points on a line) means that the field has to be ordered and thus is a subfield of the real numbers (this is where we need something like the continuity or Hilbert's completeness axiom which roughly state that things that should intersect do intersect, and imply that the base field is all of the real numbers).
Then the whole inner product shebang turns out to just be a codification of the various congruence axioms. The norm is given by choosing some vector to make a unit vector (segment) and then considering to which vector in the same direction other vectors (segments) are congruent to. The inner product is a matter of encoding the notion of angle between vectors as an inner product, i.e., as a function linear in both vectors, which essentially takes the notions of similarity, congruences and unit circles.
It turns out that you can do all of this in the reverse direction, and so the Euclidean plane really is a 2-d vector space over the reals with an inner product.
Addendum: a comment on symmetry groups that is too long to leave as a comment.
Every norm on a vector space has its own unit blob, that is, the set of vectors with norm less than one. Geometrically, blobs that correspond to a norm satisfy the following properties: they are convex, they are absorbing (every vector is a multiple of a vector in the blob), and they don't contain any lines through the origin. It is a theorem that any such blob corresponds to a norm.
As we know, the transformations of a vector space are linear transformations, which means that the symmetry group of an object in your vector space is going to consist of the linear transformations that bijectively send an object to itself. In other words, the group of symmetries of an object is the set of invertible linear transformations that fix that object.
Now, the blob of the Euclidean norm is the unit disk, and the unit circle is the boundary of the disk. The unit circle is the set of vectors with Euclidean norm $1$, and in general, the boundary of the unit blob for a norm will be the set of vectors with norm $1$. The group of symmetries of the boundary of the blob then will be the set of invertible linear transformations that send vectors with norm $1$ to vectors with norm $1$.
A slight caveat is that you don't want to consider just any old invertible linear transformations because when you add a norm to a vector space, you are in effect defining a topology, that is, a way to define continuity. As a result you want to work with continuous linear transformations. BUT! In a finite dimensional vector space, no matter what the norm, we have that every linear transformation is continuous.
What this means is that for any norm on, say the $2$-d vector space over the reals, the symmetry groups of the boundary of the unit blob are all invertible linear transformations of the same space. Hence, we can directly compare these groups to each other since they live in the same space (of invertible linear transformations of $\mathbb R^2$).
Example: the boundary of the unit blob for the Euclidean norm is the unit circle, i.e., all points such that $x^2 + y^2=1$. The boundary of the unit blob of the Taxicab norm is the unit diamond, i.e., all points such that $|x|+|y|=1$.
Now if you think about it, any linear transformation that sends the unit diamond to itself will also send the unit circle to itself. Hence, the symmetry group for the Euclidean norm contains the symmetry group for the Taxicab norm, and in fact it contains it properly since, for example, rotation by $45$ degrees fixes the circle, but doesn't fix the diamond.
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0(i keep forgetting the reflections, circle semi-direct Z/2Z?) – 2010-08-27
The Pythagorean theorem follows directly from the basic properties of the dot product: if $x \cdot v = 0$, then $(x + v) \cdot (x + v) = x \cdot x + v \cdot v$. There is not much to say about this proof from a modern point of view except that it does not depend on the finite-dimensionality of the underlying space, e.g. in Hilbert spaces it even generalizes to Parseval's identity. (Of course one then has to prove that dot products induce norms, but this is the standard Cauchy-Schwarz argument.)
I would like to interpret your title question more broadly. My impression is that mathematicians do not really think about the Pythagorean theorem directly (unless, perhaps, they are functional analysts!). Rather, following Klein's Erlangen philosophy, they think about the group of symmetries that the use of the Pythagorean theorem (really, dot products) implies. In the plane, this is the Euclidean group $\text{E}(2)$, in which sits the orthogonal group $\text{O}(2)$ of linear transformations preserving the dot product (rotations and reflections). The geometry determined by the Euclidean group is one where it makes sense to talk about lengths and angles and all the familiar tools of Euclidean geometry. There are other Lie groups which determine other types of geometries (the "non-Euclidean" ones).
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0@guest: as for the functional analyst comment, I just meant that functional analysts deal with Parseval's identity and other things that could be called infinite-dimensional generalizations of the Pythagorean theorem. – 2010-08-25
Based on the previous answers, I have come to the following (possible incomplete or incorrect) conclusion: It seems that the Pythagorean theorem can be dealt with in one of two ways, either it is taken as the definition of length/distance, or it is proved by invoking the technical definitions of an inner product space. However, proving Pythagoras via the definitions of an inner product space really just shifts the question to how one motivates these definitions (namely, why does one define the length of a vector to be the square root of its dot product with itself?). Thus, one can say that the Pythagorean theorem is generally taken to be the definition of length or distance, and the only thing left to do is motivate this definition; that is, show why the Euclidean norm is such a natural system for determining length. Qiaochu has alluded to the fact that the Euclidean norm is natural because of its large symmetry group, but I'd like someone to elaborate on this a bit if possible...
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0(the kinks are qualitative as places where the square doesn't have a tangent) – 2010-08-27
Perhaps these thoughts will shed some light on the discussion here. If one writes down a collection of axioms for Euclidean geometry, for example, Hilbert's axioms, the Pythagorean Theorem and discussion of a distance function do not explicitly appear.
http://www.beva.org/math323/asgn7/dec12b.htm#hilb
A model of Euclidean geometry consists of taking points as (x,y), ordered pairs of real numbers and lines as linear equations ax + by + c = 0, (a, b, c real numbers) using the Euclidean distance function as the way to find the distance between pairs of points.
However, if one takes points as (x, y) (ordered pairs of real numbers) and lines as linear equations ax + by + c = 0 but uses |a-b| + |c- d| as the distance between the two points (a,b) and (c,d) and measures angles as one does in the Euclidean plane one gets a geometry, often called the Taxicab Plane, which obeys all of the axioms of the Euclidean Plane except for the axiom dealing with the congruence of triangles.
Details can be found in Eugene Krause's book Taxicab Geometry.
The Pyhtagorean Theorem does not hold here.
For interesting subtleties, and lots about the taxicab plane, see Dawson's article available at this site:
You don't need inner product spaces to prove the Pythagorean theorem. If abc is a right triangle with hypotenuse c, arrange four copies of it into a square whose sides are of length $a + b$. Then calculate the area of the square two different ways and equate them.
$(a+b)^2$ = ${4*ab/2} + c^2$
Expand and simplify to get the Pythagorean theorem.
It all has to do with non-euclidean geometry. The basic idea is that the distance function, or to say the same thing as a professional mathematician, the "metric", is super important in geometry. You can have any kind of distance function you like, as long as it has three key properties (look them up). This is a pretty big subject, and it all goes back to the independence of Eulcid's 5th axiom on parallel lines.
The distance between two points depends on the curvature of the underlying space, that's the key idea.
It's not possible to prove that the distance between two points is given by the Pythagorean theorem; because the actual distance between two actual points is the domain of physics, not axiomatic mathematics. The best we can do in mathematics is define what we mean by distance (with a distance function), and since it's a definition, there's nothing to prove.
The story goes that Gauss realized Euclid's 5th postulate was independent because there are many geometries where it fails, e.g. on a circle or hyperboloid. But Gauss didn't want to just tell the world he had solved the oldest problem in math, so what he did was when Riemann came to him looking for a job as a professor, he told Riemann to list 3 possible topics to give a talk on as a sort of interview for the job. So Riemann wrote two topics down, but he couldn't think of a good third topic, and he put down "foundations of geometry" even though he hadn't thought very hard about it, just because he had some nice idea's which he had not fully formulated. And since Gauss already been thinking about that, he picked the foundations of geometry; and the rest is math history. Riemann went home and came up with a theory significantly beyond what Gauss had already known.
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0@guest: there is no reason to get all worked up trying to understand experimental physics (i.e. measuring length) in the light of axiomatic mathematics; this will only give you a headache =) It's natural to use pythag thrm to define (the word) length, because thats how lengths work in nature! It turns out that the pythag thrm is actually wrong (in experimental physics) for a subtle reason. However, if you can somehow measure just how "wrong" the pythag thrm is, then you have measured the strength of gravity in that part of space! – 2010-08-25