Continuing on from the previous post, I look at cases where the abstract concept of states on algebras correspond to classical probability measures. Up until now, we have considered commutative real algebras but, before going further, it will help to look instead at algebras over the complex numbers . In the commutative case, we will see that this is equivalent to using real algebras, but can be more convenient, and in the non-commutative case it is essential. When using complex algebras, we will require the existence of an involution, which can be thought of as a generalisation of complex conjugation.
Recall that, by an algebra over a field
, we mean that
is a
-vector space together with a binary product operation satisfying associativity, distributivity over addition, compatibility with scalars, and which has a multiplicative identity.
Definition 1 A *-algebra
is an algebra over
together with an involution, which is a unary operator
,
, satisfying,
- Anti-linearity:
.
.
for all
and
.
Here, I am using to denote the complex conjugate of
. Examples of *-algebras include:
-
is a *-algebra, with involution given by complex conjugation.
- The algebra
of complex polynomials over indeterminates
is a commutative *-algebra. Involution,
is given by taking complex conjugates of the polynomial coefficients.
- For a topological space
, the collection
of continuous functions
is a commutative *-algebra, where addition and multiplication are defined pointwise, and involution is pointwise complex conjugation,
.
- For a (complex) Hilbert space
, the space
of bounded linear operators
is a *-algebra. Involution is defined as the operator adjoint, so
for all
.
A homomorphism of *-algebras is a map from
to
preserving the algebra operations,
for all and
. Sometimes, such maps are called *-homomorphisms to distinguish them from algebra homomorphisms which need not preserve the involution. Also, we will occasionally want to consider non-unitial *-algebras, for which the existence of the unit
is not required. For homomorphisms of non-unitial *-algebras, we simply drop the requirement that
.
An element of a *-algebra is called self-adjoint or real, if
. Using
to denote the set of self-adjoint elements of
, anti-linearity implies that
is closed under taking real linear combinations, so is a vector subspace of
over the real numbers. The product of two self-adjoint elements need not be self adjoint. Considering
, the identity
shows that the product
is in
if and only if
and
commute. Finding self-adjoint elements of an algebra is easy enough. For an element
then
and
are both self-adjoint,
Also, the identity is automatically self-adjoint,
Every can be uniquely decomposed into its real and imaginary parts,
(1) |
for self-adjoint , which are given by
Commutative *-algebras are equivalent to commutative real algebras (precisely, they are equivalent categories). For any commutative *-algebra , the subset
of self-adjoint elements is a commutative real algebra. In the opposite direction, if
is a commutative real algebra, then we can consider its complexification
. Every element of
can be written uniquely as
for
, which is written more simply as
. Multiplication and involution are given by
which makes into a commutative *-algebra. The self-adjoint elements of
are precisely
for
. Hence,
gives an isomorphism of real algebras from
to
. Hence, up to isomorphism, any commutative real algebra can be considered as the set of self-adjoint elements of a commutative *-algebra. Conversely, (1) shows that any commutative *-algebra
is isomorphic to the complexification of the real algebra
.
States on *-algebras are defined as follows.
Definition 2 Let
be a *-algebra. Then, a linear map
is
- real, or self-adjoint, if
for all
.
- positive if
for all
.
- a state if it is positive and
.
It can be seen that is self-adjoint if and only if
is real for all
. If
is positive then it must also be self-adjoint. Noting that, for
, the value
is a nonnegative real number so, writing
as a combination of squares,
(2) |
shows that is real.
We previously defined the concept of states on commutative real algebras, and have noted above that there is an equivalence between commutative real algebras and commutative *-algebras. The definitions of states on real and *-algebras are consistent with this equivalence. For a state on a commutative *-algebra
, its restriction,
, to
is a state. Conversely, any state
extends uniquely to a state on
. By writing
in terms if its real and imaginary parts (1) then, by linearity, we have
. The linear map
satisfies positivity,
so is a state. This means that the theorems stated in the previous post concerning states on commutative real algebras can be translated to statements for *-algebras. We start with theorem 3 of that post.
Theorem 3 Let
be a state on *-algebra
, and
be self-adjoint. Then, there exists a probability measure
on
such that
for all polynomials
.
We do not need to assume that is commutative here, as it only depends only the restriction of
to the subalgebra generated by
, which is always commutative. We also translate theorem 5 of the previous post to the language of *-algebras.
Theorem 4 Let
be a state on *-algebra
and
be commuting self-adjoint elements of
satisfying Carleman’s condition
Then, there exists a unique probability measure
on
such that
for all polynomials
.
Again, only the restriction of to the subalgebra generated by
is important for the statement of this theorem, and this subalgebra is necessarily a commutative *-algebra.
Before moving on, we note a simple but extremely useful inequality for states and positive linear maps on a *-algebra. If is positive, then
defines a semi-inner product on
. Hence, the Cauchy–Schwarz inequality applies,
(3) |
Bochner’s Theorem
An alternative method by which states on *-algebras lead to classical probability measures is via groups of unitary elements. An element of a *-algebra
is called unitary if it satisfies
States on a *-algebra automatically imply probability distributions on the unit circle associated to each unitary element.
Theorem 5 Let
be a state on *-algebra
, and
be unitary. Then, there is a unique probability measure
on
satisfying
for all
.
Groups of unitary elements also lead to probability measures on more general spaces, although continuity requirements are imposed. As an example, we have an equivalence between probability measures on and states defined on certain spaces of unitary algebra elements.
Theorem 6 Let
be a state on *-algebra
, and
be unitary elements of
satisfying
. If
is continuous, then there is a unique probability measure
on
satisfying
for all
.
Theorems 5 and 6 are both instances of a much more general form of Bochner’s theorem. For a locally compact abelian group , we denote its dual group by
. This is the set of continuous group homomorphisms
, and is itself a locally compact abelian group under the multiplication rule
and topology of uniform convergence on compact sets. The elements
can also be considered as maps
under the action
. This identifies elements of
with elements of the dual of
which, by Pontryagin duality, is an isomorphism. That is, the natural map from
to its double-dual is an isomorphism. So, really, we have a pair
of locally compact abelian groups and a pairing
,
, with respect to which
is the dual of
and
is the dual of
. Important examples of dual pairs of locally compact abelian groups are:
-
and
are dual groups under the pairing
.
-
is self-dual under the pairing
.
- For any
, the quotient
under addition is self-dual under the pairing
.
- if
and
are pairs of dual groups then so is
.
We now give the general statement of Bochner’s theorem.
Theorem 7 Let
be a state on *-algebra
and
be a locally compact abelian group. If
are unitary elements of
satisfying
, and
is continuous, then there is a unique regular probability measure
on
satisfying
(4) for all
.
Regularity of the probability measure simply means that, for any Borel ,
is the supremum of
over compact
. This is a technicality which is not needed for for spaces with a countable base for the topology as, then, all probability measures are regular.
In the opposite direction, start with any group , which I will express multiplicatively, so the group composition of two elements
will be written as
. We construct the group algebra
. Elements of
can be defined as formal sums
(5) |
where is zero outside of a finite subset of
, so (5) can be thought of as a finite sum. Multiplication and involution are given by
This makes into a *-algebra, with
being unitary elements and
being the identity, and is commutative if
is commutative (i.e., abelian). If
is a locally compact abelian group, then elements of the dual
can be extended to operate on all of
by,
Any probability measure on
defines a state
on
as,
so that (4) holds. Noting that , we see that
is a state. Hence, Bochner’s theorem provides a one-to-one mapping between states on
such that
is continuous and regular probability measures on
.
The Riesz–Markov Representation Theorem
I will now look at the Riesz–Markov representation theorem, and consider how states on certain *-algebras correspond naturally to probability measures on locally compact topological spaces. For any space , we use
to denote the space of continuous functions
, with the algebra operations of addition and multiplication defined pointwise, and involution being pointwise complex conjugation. This expresses
as a *-algebra. We start with compact spaces which, by convention, I take to be Hausdorff. For a compact space
, the theorem can be stated as follows.
Theorem 8 Let
be a compact space and
be a state on
. Then, there is a unique regular probability measure
on
satisfying
(6) for all
.
A few comments are in order. In most statements of the theorem, nonnegativity of of the state is required in the sense that whenever
. However, this is implied by definition 2 for states on a *-algebra, since
. Sometimes, continuity of
is also required but, again, this is implied by our definition of a state. By Cauchy–Schwarz (3), and using the fact that
,
In the opposite direction, every probability measure on
defines a state on
, given by (6). So, theorem 8 gives a one-to-one correspondence between states on
and regular probability measures on
.
There is a more general form of the Riesz-Markov theorem which applies to locally compact spaces. This involves linear functions on the space of continuous functions
which vanish at infinity. To be precise, this means that for each
, there exists a compact
such that
on
. If
is not itself compact, then the constant function
is not in
. This results in
being a non-unitial *-algebra.
Recall that, so far, we are requiring algebras to contain a multiplicative identity, or unit. When we do not assume that an identity exists, then I will refer to the algebra as non-unitial. Note that this does not mean that the algebra does not contain a multiplicative identity, it just means that we do not require it. So, a non-unitial algebra may or may not be unitial.
As non-unitial algebras need not contain a multiplicative identity, definition 2 cannot be used, as the equality is undefined. So, we need to extend the definition of a state to include non-unitial *-algebras. For the algebra
, we have the norm
equal to the supremum of
over
which, in fact, gives
the structure of a C*-algebra. In this case, the operator norm can be used, which I will denote by
, and is the smallest nonnegative real number satisfying
for all , and is infinite if there is no such real number. States on C*-algebras can be defined using the condition
in place of
. However, definition (2) for the unitial case did not require any additional structure on the *-algebra, such as a C*-norm. We would prefer to not require any such structure when considering the non-unitial case either.
Suppose that we have a non-unitial *-algebra . This can always be embedded in the unitial *-algebra
, elements of which can be uniquely expressed as
for
and
. Multiplication and involution in
are defined as,
This makes into a unitial *-algebra, with unit
. In the case where
for a locally compact space
, it can be seen that
is isomorphic to
, where
is the compactification of
formed by adding a `point at infinity’. Next, consider a linear map
which is self-adjoint and positive, so that
and
for all
. For each real
, there is a unique extension of
to a self-adjoint linear map
satisfying
, given by,
We would like to be a state on
, which requires it to be positive and also that
. We ask, for what values of
is this positive? To answer this, we compute
This is positive for all if and only if
for all . By the standard result for quadratics, this is equivalent to
This suggests defining a norm of the positive linear map by
(7) |
So, can be extended to a state on
if and only if
. We would want equality to hold since, otherwise, the state on
assigns nonzero probability to the `point at infinity’. We arrive at the following definition of states on non-unitial *-algebras.
Definition 9 Let
be a (non-unitial) *-algebra. Then, a linear map
is
- real, or self-adjoint, if
for all
.
- positive if it is self-adjoint and
for all
.
- a state if it is positive and
.
Note that, here, positive maps are required to also be self-adjoint. In the unitial case, (2) was used to express as a combination of squares and imply that
is self-adjoint, so it was not required as part of the definition. However, that made use of the unit, so does not apply in the non-unitial case.
We had better check that this definition of a state coincides with definition 2 when it applies. Suppose that the algebra does, in fact, contain a unit. The Cauchy–Schwarz inequality (3) can be applied,
with equality holding at . So,
. Hence, definition 9 coincides with 2 for the unitial case. We now state the extension of the Riesz–Markov representation theorem to locally compact spaces.
Theorem 10 Let
be a locally compact space and
be a state. Then, there is a unique regular probability measure
on
such that
for all
.
Since statements of the theorem, such as the one given at Wikipedia, usually make use of the operator norm of rather than the norm defined by (7) above, we check that they agree.
Lemma 11 Let
be a locally compact space and
be positive. Then,
.
Proof: Consider satisfying
. Then
giving,
So, . Next, suppose that
. Then, by what we have just shown,
so,
Taking the supremum over all such shows that
. To prove the reverse inequality, consider any
with
and apply the Cauchy–Schwarz inequality (3),
Now, for each , by the definition of
, there exists a compact
such that
outside of
. By standard properties of locally compact spaces, there exists continuous
with compact support such that
on
. Then,
. Assuming that
is finite, so that
is norm-continuous,
giving as required. ⬜
The Commutative Gelfand–Naimark theorem
The commutative Gelfand–Naimark theorem shows that general commutative C*-algebras can be represented as spaces of continuous functions on a locally compact space. This enables the Riesz–Markov theorem described above to be applied, so that states on such algebras are in one-to-one correspondence with regular probability measures.
For any (non-unitial) *-algebra , we define a character to be a *-homomorphism
which does not vanish everywhere. The collection of all characters is denoted
, and can be given the weak topology, which is the weakest topology making the maps
continuous, for each
. It can be seen that this makes
into a locally compact space and, in the case that
has a unit, a compact space.
In the case where for a locally compact space, then we have a natural map
given by
, where
. This can be seen to be a homeomorphism, so the space of characters allows us to reconstruct the space
, up to homeomorphism, from the abstract representation of
as a *-algebra. In the opposite direction, for any (non-unitial) *-algebra
, we have a natural map
given by
, where
. The Gelfand–Naimark theorem states that this is an isomorphism precisely when
is a (non-unitial) commutative C*-algebra and, hence, gives an equivalence between locally compact spaces and commutative C*-algebras.
For a (non-unitial) *-algebra to be a C*-algebra, we require that it has a norm satisfying the usual norm inequalities,
for all and
, together with the C*-norm identity,
In order to be a true norm, rather than just a semi-norm, we require for all
and, to be a C*-algebra,
should be complete with respect to this norm. Combining the Gelfand–Naimark theorem with theorem 10 gives an equivalence between states on a C*-algebra and regular probability measures on its character space.
Theorem 12 Let
be a (non-unitial) commutative C*-algebra and
be a state. Then, there exists a unique regular probability measure
on
such that
for all
.
This theorem can be used even in the case where is not a C*-algebra, by first constructing a C* completion. Let us suppose that
is a (non-unitial) *-algebra and that
is a state. As previously noted, this defines a semi-inner product
on
, which can only fail to be a true inner product as it need not be positive definite. Also, every
defines a linear operator on
given by left-multiplication,
. We define
to be the operator norm,
This need not be finite but, if it is, then we will say that is bounded. Repeated applications of the Cauchy–Schwarz inequality can be used to show that
is increasing in
and, if the algebra is commutative,
If every is bounded, then
will satisfy all of the requirements of a C*-norm other than, possibly, positive definiteness and completeness. Furthermore, the state satisfies
so is continuous with respect to this norm. We can take the completion with respect to this norm, which will be a C*-algebra, and
has a unique continuous extension to
.
We use to denote the space of continuous characters
. By definition, these satisfy
for some
. In fact, we can take
. To see this, use the homomorphism property
to obtain
Taking the limit as goes to infinity shows that a character is continuous if and only if
for all . Every
has a unique continuous extension to
and, conversely, characters on a C*-algebra can be shown to be continuous, so every character on
restricts to a continuous character on
. This identifies
with the space of characters on
.
With this notation, theorem 12 can be applied to the C*-algebra . Subject to boundedness conditions, this gives a natural representation of a state on a commutative *-algebra as the expectation under a regular probability measure on an algebra of continuous functions on a locally compact space.
Theorem 13 Let
be a state on (non-unitial) commutative *-algebra
such that each
is bounded. Then, there exists a unique regular probability measure
on
satisfying
for all
.