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I'm interested in understanding the usual inner product on functions spaces more deeply than I already do. That is, the inner product $\int f(t) \;g^*(t) \;dt$, where $f$ and $g$ are complex valued functions over whatever domain.

In my research so far, I've seen analogies drawn between this inner product, and how it is essentially like a dot product in $C^n$. For example, we have $(v_1, v_2, ..., v_n) \cdot (u_1, u_2, ..., u_n) = \sum_{i=1}^n v_i u_i ^ *$, and this is a bit like considering $f(x) g(x)^*$ for each $x$, and then integrating over the domain.

I find this (so far) unsatisfactory for a number of reasons. Firstly, it is not clear in what sense the image of each point in the domain represents a 'dimension' of the function space. Secondly, it isn't clear that what works in finite dimensions can naturally be extended to infinite dimensions. I understand that the above is only really meant to be an analogy rather than some proper argument, but I don't find analogies very helpful unless the situations actually are analogous.

Essentially, I would like to see a motivation for this inner product on function spaces. Why would somebody come up with it, if they had never seen it before? I know that $\sin(x)$ and $\cos(x)$ are orthogonal, but only because their inner product as above is zero. I'm convinced that, without recourse to this integral, there is still a sense in which $\sin(x)$ and $\cos(x)$ are orthogonal, which would have naturally led to the construction of this inner product. I'm interested in finding this out.

Would anyone be able to provide some insight towards what I've discussed here?

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  • $\begingroup$ A vector in $\mathbb R^n$ can be thought of as a function from $\{1,2,\ldots,n\}$ to $\mathbb R$. From this viewpoint, it seems quite natural to think of a function from $\mathbb R$ to $\mathbb R$ as being like a vector in $\mathbb R^n$. That's a neat idea, and if we try to push the analogy further we will end up defining the inner product of two continuous functions using the integral formula that you mentioned. $\endgroup$
    – littleO
    Jul 7, 2019 at 0:55
  • $\begingroup$ The norm induced by this inner product is a very natural way of measuring the "distance" between functions. $\endgroup$ Jul 7, 2019 at 17:15
  • $\begingroup$ See On the Origin and Early History of Functional Analysis by Jens Lindström (2008; see p. 33) AND The Development of function spaces with particular reference to their origins in integral equation theory by Michael Bernkopf (1966; see p. 17 and p. 63). $\endgroup$ Jul 7, 2019 at 17:27

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Your third paragraph rejects many of the usual analogies. Let me try another. The orthogonality of the functions $\sin nx$ and $\cos mx$ is precisely what allows you to expand a function as a Fourier series - a sum of sines and cosines with various amplitudes, just as you express an arbitrary vector in $n$-space as a linear combination of basis vectors.

Fourier came up with this idea in his study of partial differential equations, although he did not have our modern terminology to describe it.

The picture is even clearer for complex function space, where you use the exponentials $e^{inx}$ for $n \in \mathbb{Z}$ instead of the sines and cosines. (Euler's formula connects the two bases.)

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  • $\begingroup$ Thanks for your answer. Why, though, do we use the particular inner product that we use, and how did Fourier come up with this? I was thinking about this last night, in the context of the complex exponentials. If we consider $e^{inx}$ and $e^{imx}$ where $m \neq n$, then it's easy enough to see that the average angle between the vector from the origin to $e^{inx}$ and $e^{inx}$ is $\pi / 2$. I see that in this sense, we can say something about orthogonality. (I'll continue in the next comment). $\endgroup$
    – M. Whyte
    Jul 6, 2019 at 19:24
  • $\begingroup$ In particular, we can say that the angle between these two vectors is given by $\arccos\left(\cos(nx)\cos(mx) + \sin(nx)\sin(mx)\right)$, and than take the average of this function over a period, integrating and dividing by $2 \pi$. Would it follow that $\frac{1}{2\pi} \int_0^{2\pi} \arccos\left(Re(f)Re(g) + Im(f)Im(g)\right)$ suffices as an inner product between $f$ and $g$? $\endgroup$
    – M. Whyte
    Jul 6, 2019 at 19:29
  • $\begingroup$ I don't know what Fourier was thinking when he came up with his visionary idea. You can search the web for solve heat equation Fourier series. I don't think the idea of the angle as defined by the inner product is particularly useful. What matters is how the orthogonality lets you calculate the Fourier coefficients. $\endgroup$ Jul 6, 2019 at 19:32
  • $\begingroup$ @M.Whyte : Fourier did not come up with the orthogonality condition. Nor did he define an "inner product"; such an inner-product was not defined for another century. $\endgroup$ Jul 14, 2019 at 10:59
  • $\begingroup$ @M.Whyte I know he didn't call what he was doing orthogonality but he did know how to calculate Fourier coefficients. $\endgroup$ Jul 15, 2019 at 2:35
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The "orthogonality" of the trigonometric functions was discovered well before an inner product was defined. It was discovered in the process of trying to solve the wave equation for a thin wire. In 1750 Bernoulli proposed a general description of the motion of a thin wire stretched between $x=0$ and $x=a$ as a displacement from rest $u$ given by $$ u(x,t)=\sum_{n=1}^{\infty}a_n\sin\frac{n\pi x}{a}\cos\frac{n\pi c}{a}(t-\beta_n) $$ for suitable values of $a_n$ and $\beta_n$. (Here $c$ is a constant determined by properties of the wire or string.) In 1753 Euler noticed that, if Bernoulli's conjecture were to be true, then the condition at $t=0$ would imply that any "mechanical" function $f$ describing the initial displacement of the string on $[0,a]$ would necessarily have to be described as $$ f(x)=\frac{1}{2}a_0+ (a_1\cos\frac{\pi x}{a}+b_1\sin \frac{\pi x}{a})+(a_2\cos\frac{2\pi x}{a}+b_2\sin\frac{2\pi x}{a})+\cdots. $$ Euler's opinion was this could not happen for a general mechanical function $f$, and most Mathematicians agreed. Remarkably, Euler and Clairaut discovered what the coefficients would have to be in order to have such a representation of $f$; they discovered that if you select any two different functions from $$ 1,\cos\frac{\pi x}{a},\sin\frac{\pi x}{a},\cos\frac{2\pi x}{a},\sin\frac{2\pi x}{a},\cdots $$ and integrate their product over $[0,a]$, you would obtain $0$. So they reasoned that if $$ f(x) = a_0+a_1\cos\frac{\pi x}{a}+b_1\sin\frac{\pi x}{a}+a_2\cos\frac{2\pi x}{a}+b_2\sin\frac{2\pi x}{a}+\cdots, $$ then you could multiply by one of these functions, integrate over $[0,a]$ and determine the corresponding coefficient $a_n$ or $b_n$. This is where the idea of "orthogonality" of functions first arose. Euler and Clairaut discovered these remarkable relations. However, they did not believe that a general mechanical displacement function $f$ could be expressed in this way; they felt that such an expansion put a constraint on the type of function $f$ that could be used if one wanted to solve the wave equation using Bernoulli's method. Fourier believed that every mechanical function $f$ could be expanded in this way. Fourier was correct, and that's why the coefficients are named after Fourier, and not after Euler and Clairaut who actually discovered the relations and expressions for the coefficients.

Fourier continued to study PDEs and he discovered other such orthogonality relations. He showed that orthogonality of this type was far more common than one might think. And a great deal of effort was expended over the next century in trying to understand why orthogonal expansions of this type worked. This eventually led to a general framework proposed by John von Neumann and his advisor David Hilbert, now known as Hilbert space. This led to thinking of functions as points in an abstract space with geometry through an inner product. From this, the metric space arose, and then general topology. But it all started with the vibrating string and Fourier's study of separation of variables and general function expansions.

The most confounding part of this History is that it came before even the Cauchy-Schwarz inequality for finite-dimensional spaces. Orthogonality of functions and an integral inner came before the study of finite-dimensional inner products. Infinite-dimensional function expansions, eigenfunction expansions, and symmetric operators came before a general treatment of finite-dimensional inner product spaces. The most abstract settings were studied before their concrete finite-dimensional counterparts. The motivation for the finite-dimensional came from infinite-dimensional function spaces arising out of solving PDEs. So, looking for motivation for the infinite-dimensional from the finite-dimensional is backwards.

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