Uncovering the Relationship Between Norms and Hilbert Spaces

In summary, the problem asks to show that for vectors u and v in a Hilbert space V, the statement ||u-4v|| = 2||u-v|| is equivalent to ||u|| = 2||v||. The proof involves using the parallelogram identity and squaring both sides of the equation to manipulate the norms. The backward direction can be shown by writing ||x-y||^2 as <x-y, x-y> and calculating ||u-4v||^2-4||u-v||^2.
  • #1
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Homework Statement


Given a Hilbert space ##V## and vectors ##u,v\in V##, show $$\|u-4v\| = 2\|u-v\| \iff \| u \| = 2 \| v\|.$$

Homework Equations


The parallelogram identity $$2\| x \|^2+2\| y \|^2 = \| x-y \|^2 + \| x+y \|^2$$

The Attempt at a Solution


Forward:
$$\|u-4v\| = 2\|u-v\| \implies\\
\|u-4v\|^2 = 4\|u-v\|^2\implies\\
\int(u-4v)^2 = 4\int(u-v)^2 \implies\\
\int(u^2-4v^2) = 0\implies\\
\int u^2 = 4\int v^2\implies\\
\| u \| = \| 2 v\|.$$

Backwards is tough. All I can think of is the parallelogram identity, but it is not immediately obvious to me if this helps. I can square the first equation to have a similar form as the parallelogram identity, but cannot see how it applies. I really just don't know how to break apart the summed terms inside the norm aside from inequalities, which won't help since I must show equality. I just read the text and nothing pops up.

EDIT: I must be slow today, backward is clear now (same thing I posted but opposite). Sorry for not seeing this earlier, but thanks for stopping by to help :)
 
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  • #2
Write ##||x-y||^2 = \langle x-y,x-y\rangle## and calculate ##||u-4v||^2-4||u-v||^2##.
 

FAQ: Uncovering the Relationship Between Norms and Hilbert Spaces

What is a norm in mathematics?

A norm in mathematics is a function that assigns a positive length or size to a vector in a vector space. It is a way to measure the magnitude of a vector and is often denoted by ||x||. In simpler terms, a norm is a mathematical tool that allows us to measure the size of a vector.

What is a Hilbert space?

A Hilbert space is a mathematical concept that represents a complete vector space. It is a space that contains all possible vectors and is equipped with an inner product, which is a way to measure the angle between two vectors. Hilbert spaces are widely used in functional analysis and quantum mechanics.

What is the difference between a norm and a metric?

A norm and a metric are both mathematical tools used to measure distance, but they have some key differences. A norm is a function that assigns a positive length to a vector, while a metric is a function that assigns a positive distance between two points in a space. Additionally, a norm is defined on a vector space, while a metric is defined on a set of points.

How are norms and inner products related?

Norms and inner products are closely related in the sense that an inner product can be used to define a norm. In fact, the norm of a vector is equal to the square root of the inner product of the vector with itself. This relationship allows us to use inner products to measure the size of a vector.

Why are norms and Hilbert spaces important in mathematics?

Norms and Hilbert spaces are important in mathematics because they provide a rigorous framework for studying vector spaces and their properties. They are used in various fields such as functional analysis, signal processing, and quantum mechanics. Additionally, norms and Hilbert spaces allow for the development of powerful mathematical tools and techniques that have practical applications in many areas of science and engineering.

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