In this article, we will explore the fascinating world of Polarization identity. From its origins to its influence today, this topic arouses great interest and curiosity in individuals of all ages. Through a detailed and exhaustive analysis, we will address the most relevant and significant aspects related to Polarization identity, providing the reader with a broad and enriching perspective. Likewise, we will examine its impact in various areas, from culture to science, including its relevance in contemporary society. Ultimately, this article seeks to shed light on Polarization identity and its importance in today's world.
Formula relating the norm and the inner product in a inner product space
In linear algebra, a branch of mathematics, the polarization identity is any one of a family of formulas that express the inner product of two vectors in terms of the norm of a normed vector space.
If a norm arises from an inner product then the polarization identity can be used to express this inner product entirely in terms of the norm. The polarization identity shows that a norm can arise from at most one inner product; however, there exist norms that do not arise from any inner product.
The norm associated with any inner product space satisfies the parallelogram law:
In fact, as observed by John von Neumann,[1] the parallelogram law characterizes those norms that arise from inner products.
Given a normed space, the parallelogram law holds for if and only if there exists an inner product on such that for all in which case this inner product is uniquely determined by the norm via the polarization identity.[2][3]
Polarization identities
Any inner product on a vector space induces a norm by the equation
The polarization identities reverse this relationship, recovering the inner product from the norm.
Every inner product satisfies:
Solving for gives the formula If the inner product is real then and this formula becomes a polarization identity for real inner products.
Real vector spaces
If the vector space is over the real numbers then the polarization identities are:[4]
This further implies that class is not a Hilbert space whenever , as the parallelogram law is not satisfied. For the sake of counterexample, consider and for any two disjoint subsets of general domain and compute the measure of both sets under parallelogram law.
Complex vector spaces
For vector spaces over the complex numbers, the above formulas are not quite correct because they do not describe the imaginary part of the (complex) inner product.
However, an analogous expression does ensure that both real and imaginary parts are retained.
The complex part of the inner product depends on whether it is antilinear in the first or the second argument.
The notation which is commonly used in physics will be assumed to be antilinear in the first argument while which is commonly used in mathematics, will be assumed to be antilinear in its second argument.
They are related by the formula:
The real part of any inner product (no matter which argument is antilinear and no matter if it is real or complex) is a symmetric bilinear map that for any is always equal to:[4][proof 1]
It is always a symmetric map, meaning that[proof 1]
and it also satisfies:[proof 1]
which in plain English says that to move a factor of to the other argument, introduce a negative sign. These properties can be proven either from the properties of inner products directly or from properties of norms by using the polarization identity.
Proof of properties of using the polarization identity
Let
Then
which proves that .
Additionally,
which proves that
Unlike its real part, the imaginary part of a complex inner product depends on which argument is antilinear.
Antilinear in first argument
The polarization identities for the inner product which is antilinear in the first argument, are
The polarization identities for the inner product which is antilinear in the second argument, follows from that of by the relationship:
So for any [4]
This expression can be phrased symmetrically as:[5]
Summary of both cases
Thus if denotes the real and imaginary parts of some inner product's value at the point of its domain, then its imaginary part will be:
where the scalar is always located in the same argument that the inner product is antilinear in.
Using , the above formula for the imaginary part becomes:
We will only give the real case here; the proof for complex vector spaces is analogous.
By the above formulas, if the norm is described by an inner product (as we hope), then it must satisfy
which may serve as a definition of the unique candidate for the role of a suitable inner product. Thus, the uniqueness is guaranteed.
It remains to prove that this formula indeed defines an inner product and that this inner product induces the norm
Explicitly, the following will be shown:
(This axiomatization omits positivity, which is implied by (1) and the fact that is a norm.)
For properties (1) and (2), substitute: and
For property (3), it is convenient to work in reverse.
It remains to show that
or equivalently,
Now apply the parallelogram identity:
Thus it remains to verify:
But the latter claim can be verified by subtracting the following two further applications of the parallelogram identity:
Thus (3) holds.
It can be verified by induction that (3) implies (4), as long as
But "(4) when " implies "(4) when ".
And any positive-definite, real-valued, -bilinear form satisfies the Cauchy–Schwarz inequality, so that is continuous.
Thus must be -linear as well.
Another necessary and sufficient condition for there to exist an inner product that induces a given norm is for the norm to satisfy Ptolemy's inequality, which is:[6]
Applications and consequences
If is a complex Hilbert space then is real if and only if its imaginary part is , which happens if and only if .
Similarly, is (purely) imaginary if and only if .
For example, from it can be concluded that is real and that is purely imaginary.
Isometries
If is a linearisometry between two Hilbert spaces (so for all ) then
that is, linear isometries preserve inner products.
The second form of the polarization identity can be written as
This is essentially a vector form of the law of cosines for the triangle formed by the vectors , , and .
In particular,
where is the angle between the vectors and .
The equation is numerically unstable if u and v are similar because of catastrophic cancellation and should be avoided for numeric computation.
Derivation
The basic relation between the norm and the dot product is given by the equation
Then
and similarly
Forms (1) and (2) of the polarization identity now follow by solving these equations for , while form (3) follows from subtracting these two equations.
(Adding these two equations together gives the parallelogram law.)
Generalizations
Jordan–von Neumann theorems
The standard Jordan–von Neumann theorem, as stated previously, is that the if a norm satisfies the parallelogram law, then it can be induced by an inner product defined by the polarization identity. There are variants of the theorem.[7]
Define various senses of orthogonality:
isosceles:
Roberts’: for all scalar .
Pythagorean:
Birkhoff–James: for all scalar .
Let be a vector space over the real or complex numbers. Let be a norm over . We consider conditions for which the norm is induced by an inner product. In the following statements, whenever a scalar appears, the scalar may be restricted to be merely real, even when is over the complex numbers.
(von Neumann–Jordan condition) The norm satisfies the parallelogram identity.
(weakened von Neumann–Jordan condition) for all unit vectors . That is, the norm satisfies the parallelogram identity for unit vectors.
For any , the set of points equidistant to is flat, that is, an affine subspace.
Orthogonality in either isosceles or Roberts’ sense is either additive or homogeneous on one variable.
For every two-dimensional subspace , for every , there exists that is Roberts’ orthogonal to .
For the real vector space, there is also the condition:
Any two-dimensional slice of the unit sphere is an ellipse, that is, parameterizable as , for some unit vectors .
Proof
Since the internal John ellipse is unique, for any bijective linear map that preserves the unit circle, it must have . Since must touch the circle at some point , we may map to any other point on the circle, thus every point touches the ellipse . Thus the circle is the ellipse.
The Banach-Mazur rotation problem: Given a separableBanach space such that any two unit vectors , there exists a linear surjective isometry such that or , is isometrically isomorphic to a Hilbert space?
The general case of the problem is open. When the space is parable finite-dimensional, the answer is yes. In other words, given a finite-dimensional normed vector space over the real or complex numbers, if any point on the unit sphere can be mapped (rotated) to any other point by a linear isometry, then the norm is induced by an inner product.[8]
Symmetric bilinear forms
The polarization identities are not restricted to inner products.
If is any symmetric bilinear form on a vector space, and is the quadratic form defined by
then
The so-called symmetrization map generalizes the latter formula, replacing by a homogeneous polynomial of degree defined by where is a symmetric -linear map.[9]
The formulas above even apply in the case where the field of scalars has characteristic two, though the left-hand sides are all zero in this case.
Consequently, in characteristic two there is no formula for a symmetric bilinear form in terms of a quadratic form, and they are in fact distinct notions, a fact which has important consequences in L-theory; for brevity, in this context "symmetric bilinear forms" are often referred to as "symmetric forms".
These formulas also apply to bilinear forms on modules over a commutative ring, though again one can only solve for if 2 is invertible in the ring, and otherwise these are distinct notions. For example, over the integers, one distinguishes integral quadratic forms from integral symmetric forms, which are a narrower notion.
More generally, in the presence of a ring involution or where 2 is not invertible, one distinguishes -quadratic forms and -symmetric forms; a symmetric form defines a quadratic form, and the polarization identity (without a factor of 2) from a quadratic form to a symmetric form is called the "symmetrization map", and is not in general an isomorphism. This has historically been a subtle distinction: over the integers it was not until the 1950s that relation between "twos out" (integral quadratic form) and "twos in" (integral symmetric form) was understood – see discussion at integral quadratic form; and in the algebraization of surgery theory, Mishchenko originally used symmetricL-groups, rather than the correct quadraticL-groups (as in Wall and Ranicki) – see discussion at L-theory.
^Becerra Guerrero, Julio; Rodríguez-Palacios, A. (2002). "Transitivity of the norm on Banach spaces". Extracta Mathematicae. 17 (1): 1–58. hdl:10662/18957. MR1914238.