← Module 02 / Vectors & spaces

Lesson 02.8 · §3.4

Does changing length change convergence?

Compare p-norms and explain the finite-dimensional norm equivalence statement.

In this lesson 4 ideas
  1. Measure one vector three ways
  2. A family of lengths
  3. Equivalent does not mean equal
  4. Transfer

Source scope: §3.4. Worked numerical examples, experiments, and practice are teaching supplements unless identified as source results.

Measure one vector three ways

For x=(3,4)x=(3,4), the one-norm is 77, the two-norm is 55, and the infinity-norm is 44. Each measures length using a different unit ball.

A norm on a real vector space satisfies, for all x,yx,y and real α\alpha,

∥x∥≥0 with equality iff x=0,∥αx∥=∣α∣∥x∥,∥x+y∥≤∥x∥+∥y∥.\|x\|\ge0\text{ with equality iff }x=0,\qquad \|\alpha x\|=|\alpha|\|x\|,\qquad \|x+y\|\le\|x\|+\|y\|.

A vector space with a norm is a normed space. Its induced metric is d(x,y)=∥x−y∥d(x,y)=\|x-y\|. Positivity gives separation; ∥x−y∥=∥−(y−x)∥=∥y−x∥\|x-y\|=\|-(y-x)\|=\|y-x\| gives symmetry; writing x−z=(x−y)+(y−z)x-z=(x-y)+(y-z) gives the triangle inequality.

A family of lengths

On Rn\mathbb R^n,

∥x∥1=∑i∣xi∣,∥x∥2=∑ixi2,∥x∥p=(∑i∣xi∣p)1/p (p≥1),∥x∥∞=max⁡i∣xi∣.\|x\|_1=\sum_i|x_i|,\qquad \|x\|_2=\sqrt{\sum_i x_i^2},\qquad \|x\|_p=\left(\sum_i|x_i|^p\right)^{1/p}\ (p\ge1),\qquad \|x\|_\infty=\max_i|x_i|.

The first two are special cases of the pp-norm. To see the infinity limit, put M=max⁡i∣xi∣M=\max_i|x_i|. Then M≤∥x∥p≤n1/pMM\le\|x\|_p\le n^{1/p}M, and n1/p→1n^{1/p}\to1.

For 0<p<10<p<1, the formula is not a norm. With u=(1,0)u=(1,0) and v=(0,1)v=(0,1), ∥u+v∥p=21/p>2=∥u∥p+∥v∥p\|u+v\|_p=2^{1/p}>2=\|u\|_p+\|v\|_p. This supplies the counterexample requested in the source.

Equivalent does not mean equal

On any fixed finite-dimensional real space, any two norms admit constants α,β>0\alpha,\beta>0 such that

α∥x∥A≤∥x∥B≤β∥x∥Afor all x.\alpha\|x\|_A\le\|x\|_B\le\beta\|x\|_A\quad\text{for all }x.

Consequently convergence in either norm implies convergence in the other: apply the upper bound to the differences from the limit, and use the lower bound for the reverse implication. The source states norm equivalence without a proof and warns that it can fail in infinite-dimensional function spaces.

Source footnote 4: A normed space complete in its induced metric is a Banach space. Complete means every Cauchy sequence has a limit in the space; being Cauchy means its terms eventually become arbitrarily close to one another.

Explore it yourself

Change the rule for length

The curve contains vectors of length one in the selected p-norm. Predict how the readout changes.

Preparing interactive controls…

x₁x₂-4-4-3-3-2-2-1-1011223344v

v = (1.000, 1.000); length = 1.414. L₁ = 2.000; L₂ = 1.414; L∞ = 1.000. Blue curve: all points with selected length one. Red endpoint: v.

Axes: first and second real coordinates, in unit steps. Endpoints and labels identify each vector.

Transfer

If a sequence tends to zero in the two-norm in R10\mathbb R^{10}, can it fail to tend to zero in the one-norm?

Use a fixed constant

No. ∥x∥1≤10∥x∥2\|x\|_1\le\sqrt{10}\|x\|_2. The constant does not depend on the term of the sequence, so the one-norm also tends to zero.