# Definition:Chebyshev Distance

## Contents

## Definition

Let $M_1 = \left({A_1, d_1}\right)$ and $M_2 = \left({A_2, d_2}\right)$ be metric spaces.

Let $A_1 \times A_2$ be the cartesian product of $A_1$ and $A_2$.

The **Chebyshev distance** on $A_1 \times A_2$ is defined as:

- $d_\infty \left({x, y}\right) := \max \left\{{d_1 \left({x_1, y_1}\right), d_2 \left({x_2, y_2}\right)}\right\}$

where $x = \left({x_1, x_2}\right), y = \left({y_1, y_2}\right) \in A_1 \times A_2$.

### General Definition

The **Chebyshev distance** on $\displaystyle \mathcal A = \prod_{i \mathop = 1}^n A_i$ is defined as:

- $\displaystyle d_\infty \left({x, y}\right) = \max_{i \mathop = 1}^n \left\{{d_i \left({x_i, y_i}\right)}\right\}$

where $x = \left({x_1, x_2, \ldots, x_n}\right), y = \left({y_1, y_2, \ldots, y_n}\right) \in \mathcal A$.

### Real Number Plane

This metric is usually encountered in the context of the real number plane $\R^2$:

The **Chebyshev distance** on $\R^2$ is defined as:

- $\displaystyle d_\infty \left({x, y}\right):= \max \left\{ {\left\vert{x_1 - y_1}\right\vert, \left\vert{x_2 - y_2}\right\vert}\right\}$

where $x = \left({x_1, x_2}\right), y = \left({y_1, y_2}\right) \in \R^2$.

## Also known as

The **Chebyshev distance** is also known as the **maximum metric** or **sup metric**.

Another term is the **chessboard distance**, as it can be illustrated on the real number plane as the number of moves needed by a chess king to travel from one point to the other.

## Also see

- Results about
**the Chebyshev distance**can be found here.

## Source of Name

This entry was named for Pafnuty Lvovich Chebyshev.

## Sources

- 1975: W.A. Sutherland:
*Introduction to Metric and Topological Spaces*... (previous) ... (next): $2.2$: Examples: Example $2.2.7$