# Definition:Norm/Vector Space

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*This page is about Norm on Vector Space. For other uses, see Norm.*

## Definition

Let $\struct {R, +, \circ}$ be a division ring with norm $\norm {\,\cdot\,}_R$.

Let $V$ be a vector space over $R$, with zero $0_V$.

A **norm** on $V$ is a map from $V$ to the nonnegative reals:

- $\norm{\,\cdot\,}: V \to \R_{\ge 0}$

satisfying the **(vector space) norm axioms**:

\((\text N 1)\) | $:$ | Positive Definiteness: | \(\ds \forall x \in V:\) | \(\ds \norm x = 0 \) | \(\ds \iff \) | \(\ds x = \mathbf 0_V \) | |||

\((\text N 2)\) | $:$ | Positive Homogeneity: | \(\ds \forall x \in V, \lambda \in R:\) | \(\ds \norm {\lambda x} \) | \(\ds = \) | \(\ds \norm {\lambda}_R \times \norm x \) | |||

\((\text N 3)\) | $:$ | Triangle Inequality: | \(\ds \forall x, y \in V:\) | \(\ds \norm {x + y} \) | \(\ds \le \) | \(\ds \norm x + \norm y \) |

### Division Ring

When the vector space $V$ is the $R$-vector space $R$, the definition reduces to the division ring norm:

Let $\struct {R, +, \circ}$ be a division ring whose zero is denoted $0_R$.

A **(multiplicative) norm** on $R$ is a mapping from $R$ to the non-negative reals:

- $\norm {\,\cdot\,}: R \to \R_{\ge 0}$

satisfying the **(ring) multiplicative norm axioms**:

\((\text N 1)\) | $:$ | Positive Definiteness: | \(\ds \forall x \in R:\) | \(\ds \norm x = 0 \) | \(\ds \iff \) | \(\ds x = 0_R \) | |||

\((\text N 2)\) | $:$ | Multiplicativity: | \(\ds \forall x, y \in R:\) | \(\ds \norm {x \circ y} \) | \(\ds = \) | \(\ds \norm x \times \norm y \) | |||

\((\text N 3)\) | $:$ | Triangle Inequality: | \(\ds \forall x, y \in R:\) | \(\ds \norm {x + y} \) | \(\ds \le \) | \(\ds \norm x + \norm y \) |

## Notes

This page or section has statements made on it that ought to be extracted and proved in a Theorem page.In particular: Replace this with something precise that proves the definitions are consistent.You can help $\mathsf{Pr} \infty \mathsf{fWiki}$ by creating any appropriate Theorem pages that may be needed.To discuss this page in more detail, feel free to use the talk page. |

In the literature, it is more common to define the norm only if $R$ is $\R$ or $\C$ (and consequently $\norm {\,\cdot\,}_R$ is the absolute value or modulus function respectively).

However, the definition given here incorporates this approach.

## Also known as

The term **length** is occasionally seen as an alternative for **norm**.

## Also see

- Definition:Norm on Division Ring
- Definition:Norm on Algebra
- Definition:Norm on Bounded Linear Transformation
- Definition:Norm on Bounded Linear Functional

## Sources

- 2011: Graham R. Allan and H. Garth Dales:
*Introduction to Banach Spaces and Algebras*... (previous) ... (next): $2.1$: Normed Spaces - 2013: Francis Clarke:
*Functional Analysis, Calculus of Variations and Optimal Control*... (next): $1.1$: Basic Definitions - 2017: Amol Sasane:
*A Friendly Approach to Functional Analysis*... (previous) ... (next): $\S 1.2$: Normed and Banach spaces. Normed spaces - 2020: James C. Robinson:
*Introduction to Functional Analysis*... (previous) ... (next) $3.1$: Norms