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This answer here details that an inner product can be defined for a vector space defined over any ordered field.

However , not every such field is complete ( Consider a vector space over $\mathbb{Q}$).

However this would mean that $\lVert{.}\rVert$ isn't defined at all points. For instance if $\langle v ,v \rangle=2$ for some $v \in V$. Then $\lvert \lvert v\rvert \rvert$, isn't defined anymore.

However, the inner product axioms don't necessitate the existence of a norm.

I therefore suspect that you can have an inner product space without a norm

Am I right in my hypothesis, if not , why not?

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    $\begingroup$ Every inner product space induces a norm, called its canonical norm, defined by $\lVert x\rVert=\langle x,x\rangle$. In your example, may be you should say $\forall v\in\Bbb{Q}$, $\langle v,v\rangle\ne2$ $\endgroup$ Commented yesterday
  • $\begingroup$ @JCQ, doesn't the canonical norm assume the completeness of the field though? $\endgroup$ Commented yesterday
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    $\begingroup$ A norm doesn't have to "hit" every single possible positive real number length to be a norm. $\endgroup$ Commented yesterday
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    $\begingroup$ @mathforever No, it can't be discrete. There is no norm, for instance, that only yields natural numbers. It has to be dense, because you can always scale vectors, and those scalars are dense. But the range of possible vector norms, while dense, doesn't have to be complete. $\endgroup$ Commented yesterday
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    $\begingroup$ The field $\mathbb{Q}^2$ is a vector space over $\mathbb{Q}$ and has the usual inner product. We would usually also say $\mathbb{Q}^2$ has a norm, defined in the usual way. This works because nothing in the definition of a norm absolutely requires the values of the norm to be contained in the field of scalars of the vector space. $\endgroup$ Commented yesterday

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Short answer: yes, your hypothesis is correct.

You can have a positive-definite inner product taking values in an ordered field $F$ without the induced norm $\|v\| = \sqrt{\langle v,v\rangle}$ existing inside $F$ . The usual passage from inner product to norm needs square roots of positive field elements; if those square roots are not in the field (e.g. $F = \mathbb Q$), the norm does not lie in $F$.

Let $F = \mathbb Q$ and $V=\mathbb Q$ as a $1$-dimensional vector space over $F$.

The function

$$\langle x , y\rangle = 2xy \in \mathbb Q$$

is bilinear, symmetric and $\langle x,x \rangle = 2 x^2 > 0$ for $x \neq 0$. So it is an inner product over $\mathbb Q$.

But for $v=1$ we have

$$\langle 1, 1 \rangle = 2,$$

and $\sqrt{2} \not\in \mathbb Q$. Hence no $\mathbb Q$-valued norm $\|v\| = \sqrt{\langle v,v \rangle}$ exists.

Many algebraic consequences of an inner product still hold over any ordered field: for instance the Cauchy–Schwarz inequality

$$\langle u, v\rangle^2 \le \langle u,u \rangle \langle v, v \rangle$$

can be proved algebraically (consider $\langle u-tv, u-tv\rangle$ as a quadratic in $t$. That inequality lives entirely in $F$.

Let $u, v\in V$. Consider the polynomial in $ t\in F$,

$$f(t) := \langle u-tv, u-tv \rangle = \langle u, u\rangle - 2t\langle u,v\rangle + t^2\langle v,v\rangle.$$

Since $\langle w, w \rangle\ \geq 0$ for all $w$, we have $f(t) \ge 0$ for every $t\in F$. For a quadratic $at^2+bt+c$ with $a>0$ to be nonnegative for all $t$ in an ordered field, its discriminant must be $\leq 0$. Here the discriminant is

$$\Delta = (-2\langle u,v\rangle)^2 - 4\langle v, v\rangle \langle u, u \rangle = 4\big(\langle u,v\rangle^2 - \langle u, u\rangle \langle v,v \rangle \big).$$

Nonpositivity of $\Delta$ gives

$$\langle u, v\rangle^2 - \langle u,u\rangle\langle v, v\rangle \le 0,$$

which is exactly Cauchy-Schwarz

$$\langle u,v\rangle^2 \le \langle u,u\rangle\langle v,v\rangle.$$

Everything in this argument uses only ordered-field inequalities and arithmetic. No square roots.

But to derive the triangle inequality $\|u + v \| \le \|u\| + \|v\|$ you need to take square roots.

If $F$ has the property that every positive element of $F$ has a square root in $F$, then the induced norm $\|v\| = \sqrt{\langle v, v \rangle}$ is well-defined in $F$ and all the usual metric/topological consequences follow.

There are two workarounds I can think of:

  1. You can always view $F$ as a subfield of a larger ordered field (e.g. embed $\mathbb Q \hookrightarrow \mathbb R$) and then take square roots there.
  2. Or treat $\langle v, v\rangle$ as a positive definite quadratic form on $V$ rather than as a norm-valued function (explained further down, below).

There are some things that work fine, apart from Cauchy-Schwarz. For example, you can orthogonalize just fine without square roots.

Given a finite set of linearly independent vectors $v_1,\dots,v_n$ in $V$, the usual Gram–Schmidt formulas

$$u_1 = v_1, \qquad u_k = v_k - \displaystyle\sum_{j=1}^{k-1} \frac{\langle v_k, u_j\rangle}{\langle u_j, u_j\rangle} u_j$$

produce vectors $u_1, \dots, u_n$ that are pairwise orthogonal. The only field operations used are addition, subtraction, multiplication and division by the nonzero $\langle u_j, u_j \rangle$.

What you cannot do inside $F$ is normalize these $u_j$ to unit length $\tilde u_j = u_j/\|u_j\|$, because $\|u_j\| = \sqrt{\langle u_j, u_j\rangle}$ may not lie in $F$.

Polarization and the paralellogram law also holds. Define $q(v) := \langle v, v \rangle$. For fields $\operatorname{char} F \neq 2$, the polarization identity holds:

$$\langle u, v\rangle = \frac{1}{2} \big(q(u+v) - q(u) - q(v) \big).$$

The parallelogram identity

$$\langle u+v ,u+v \rangle + \langle u-v, u-v \rangle = 2 \langle u, u\rangle + 2 \langle v, v\rangle$$

is also purely algebraic and holds in any field with $\operatorname{char} F \neq 2 $.

But specifying the quadratic form $q$ is equivalent to specifying the inner product (over fields of characteristic $\neq 2$). Thus an inner-product structure is the same data as a positive-definite quadratic form, and that makes many algebraic manipulations possible without referring to any square root operations.

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  • $\begingroup$ A very good point about normalization failing if you can't take square roots in the underlying field. Even if you define the norm as taking values in $\mathbb R$ (or $\mathbb C$), there simply isn't any unit vector in $\mathbb Q^2$ that would be parallel to $(1, 1)$. $\endgroup$ Commented 6 hours ago
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According to the usual definition, as given, for instance, in Topological Vector Spaces, Distributions and Kernels, p112 by François Treves, an inner product is a positive definite sesquilinear form. It is thus, by definition, a mapping $\ \langle\ \cdot\,,\,\cdot\ \rangle:V\times V\rightarrow\mathbb{C}\ $ which satisfies the conditions specified by the definition of those concepts. While those definitions presuppose that the field over which $\ V\ $ is a vector space must be a subfield $\ \mathbb{F}\ $ of $\ \mathbb{C}\ ,$ they do not require an inner product to have $\ \mathbb{F}\ $ as a codomain. Since $\ \langle v,v\rangle\ $ is a non-negative real number for any $\ v\in V\ $, the norm, $\ \|v\|\stackrel{\text{def}}{=}\sqrt{\langle v,v\rangle}\ ,$ is always well-defined. Whether $\ \|v\|\in\mathbb{F}\ $ or not is irrelevant.

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Well, the Wikipedia definition is:

In mathematics, an inner product space ... is a real vector space or a complex vector space with an operation called an inner product ...

(emphasis mine)

So you can always take the necessary square roots to define a norm.

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  • $\begingroup$ That is true, But I'm interested specifically when the field isn't $\mathbb{R}$ or $\mathbb{C}$. But as I've been told, the norm need not map onto the field over which the inner product is defined, so it works out $\endgroup$ Commented yesterday
  • $\begingroup$ Then you should call it an "almost inner product space". Although based on your other comments it seems like you were concerned about the inner product not assuming every possible value, as opposed to not having enough square roots. So I guess this answer responds to your question as posted, but not your underlying worry. $\endgroup$ Commented yesterday
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Given an inner product $\langle \phantom v \mid \phantom v\rangle$, there is always the canonical norm $\|v\| =\sqrt{ \langle v \mid v\rangle}$. This will fulfill all axioms of a norm. Note that while the result of a norm is always a non-negative real number, there is no requirement that each positive real number is the norm of some vector, so non-completeness is not an issue.

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  • $\begingroup$ One requirement for a norm is to be absolutely homogeneous: $\|\lambda v\| = |\lambda| \cdot \|v\| $. But that is not the case for $\|v\| = \langle v , v\rangle$. Or am I misunderstanding something? $\endgroup$ Commented yesterday
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    $\begingroup$ A square root is normally needed. I thought the question was asking whether a norm could be defined whose range is entirely rational. $\endgroup$ Commented yesterday
  • $\begingroup$ This is not a norm. In addition to Martin R's comment, this does not satisfy the triangle inequality (say when our vector space is just $\mathbb R$). Consider $$(1+2)^2\not\leq1^2+2^2.$$ $\endgroup$ Commented yesterday
  • $\begingroup$ You are all right, I forgot a square root. $\endgroup$ Commented yesterday
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    $\begingroup$ Square roots do not necessarily exist for all positive elements of an arbitrary ordered field, see for example $\mathbb Q$. $\endgroup$ Commented 21 hours ago

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