Polarization identity

Summary

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.

Vectors involved in the polarization identity

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 identitiesEdit

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 spacesEdit

If the vector space is over the real numbers then the polarization identities are:[4]

 


These various forms are all equivalent by the parallelogram law:[proof 1]

 


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 spacesEdit

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 its the 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]
 
Thus   which in plain English says that to move a factor of   to the other argument, introduce a negative sign.
Proof of properties of  

Let

 
Then   implies
 
and
 

Moreover,

 
which proves that  

From   it follows that   and   so that

 
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

 

where   The second to last equality is similar to the formula expressing a linear functional   in terms of its real part:  

Antilinear in second argument

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:

 

Reconstructing the inner productEdit

In a normed space   if the parallelogram law

 
holds, then there exists a unique inner product   on   such that   for all  [4][1]
Proof

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:

  1.  
  2.  
  3.  
  4.  

(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 consequencesEdit

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.

IsometriesEdit

If   is a linear isometry between two Hilbert spaces (so   for all  ) then

 
that is, linear isometries preserve inner products.

If   is instead an antilinear isometry then

 

Relation to the law of cosinesEdit

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  

DerivationEdit

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.)

GeneralizationsEdit

Symmetric bilinear formsEdit

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.[7]

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 symmetric L-groups, rather than the correct quadratic L-groups (as in Wall and Ranicki) – see discussion at L-theory.

Homogeneous polynomials of higher degreeEdit

Finally, in any of these contexts these identities may be extended to homogeneous polynomials (that is, algebraic forms) of arbitrary degree, where it is known as the polarization formula, and is reviewed in greater detail in the article on the polarization of an algebraic form.

See alsoEdit

Notes and referencesEdit

  1. ^ a b Lax 2002, p. 53.
  2. ^ Philippe Blanchard, Erwin Brüning (2003). "Proposition 14.1.2 (Fréchet–von Neumann–Jordan)". Mathematical methods in physics: distributions, Hilbert space operators, and variational methods. Birkhäuser. p. 192. ISBN 0817642285.
  3. ^ Gerald Teschl (2009). "Theorem 0.19 (Jordan–von Neumann)". Mathematical methods in quantum mechanics: with applications to Schrödinger operators. American Mathematical Society Bookstore. p. 19. ISBN 978-0-8218-4660-5.
  4. ^ a b c d Schechter 1996, pp. 601–603.
  5. ^ Butler, Jon (20 June 2013). "norm - Derivation of the polarization identities?". Mathematics Stack Exchange. Archived from the original on 14 October 2020. Retrieved 2020-10-14. See Harald Hanche-Olson's answer.
  6. ^ Apostol, Tom M. (1967). "Ptolemy's Inequality and the Chordal Metric". Mathematics Magazine. 40 (5): 233–235. doi:10.2307/2688275. JSTOR 2688275.
  7. ^ Butler 2013. See Keith Conrad (KCd)'s answer.
  1. ^ a b c d A proof can be found here.

BibliographyEdit

  • Lax, Peter D. (2002). Functional Analysis (PDF). Pure and Applied Mathematics. New York: Wiley-Interscience. ISBN 978-0-471-55604-6. OCLC 47767143. Retrieved July 22, 2020.
  • Rudin, Walter (1991). Functional Analysis. International Series in Pure and Applied Mathematics. Vol. 8 (Second ed.). New York, NY: McGraw-Hill Science/Engineering/Math. ISBN 978-0-07-054236-5. OCLC 21163277.
  • Schechter, Eric (1996). Handbook of Analysis and Its Foundations. San Diego, CA: Academic Press. ISBN 978-0-12-622760-4. OCLC 175294365.