As is well known, the space of bounded linear operators on any Hilbert space forms a *-algebra, and (pure) states on this algebra are defined by unit vectors. Considering a Hilbert space , the space of bounded linear operators
is denoted as
. This forms an algebra under the usual pointwise addition and scalar multiplication operators, and involution of the algebra is given by the operator adjoint,
for any and all
. A unit vector
defines a state
by
.
The Gelfand-Naimark–Segal (GNS) representation allows us to go in the opposite direction and, starting from a state on an abstract *-algebra, realises this as a pure state on a *-subalgebra of for some Hilbert space
.
Consider a *-algebra and positive linear map
. Recall that this defines a semi-inner product on the *-algebra
, given by
. The associated seminorm is denoted by
, which we refer to as the
-seminorm. Also, every
defines a linear operator on
by left-multiplication,
. We use
to denote its operator norm, and refer to this as the
-seminorm. An element
is bounded if
is finite, and we say that
is bounded if every
is bounded.
Theorem 1 Let
be a bounded *-probability space. Then, there exists a triple
where,
is a Hilbert space.
is a *-homomorphism.
satisfies
for all
.
is cyclic for
, so that
is dense in
.
Furthermore, this representation is unique up to isomorphism: if
is any other such triple, then there exists a unique invertible linear isometry of Hilbert spaces
such that
The GNS representation is constructed by taking a Hilbert space completion of under the
semi-inner product. Rather than proving theorem 1 in one go, I will first show a few preliminary lemmas from which the full result will follow. Any triple
satisfying the conclusion of theorem 1 will be called a (or, the) GNS representation of
. First, assuming that the GNS representation exists, then it is called faithful if all
satisfy
only when
. This occurs precisely when the the state
is nondegenerate and, in this case,
identifies
with a *-subalgebra of
.
Lemma 2 Let
be a bounded *-probability space with GNS representation
. Then,
- the map
is an
-isometry from
to
.
is an
-isometry, so that
.
has kernel
.
- the representation is faithful if and only if
is nondegenerate.
Proof: That is an
-isometry follows from,
Next, as is cyclic for
, the inequality
gives . Similarly,
gives , so
is an
-isometry. The second statement is immediate, as
iff
. The third statement is also immediate, as
is faithful iff its kernel is
and
is nondegenerate iff
whenever
. ⬜
Now, consider a nonnegative linear map . As this does not have to be a state, and elements of
might not be
-bounded, the full GNS representation as described by theorem 1 need not exist. However, it is still possible to define the Hilbert space
by taking the
-completion of
. Note that, if the GNS representation does exist, then
satisfies the properties of the isometry defined by the following result.
Lemma 3 Let
be a *-algebra and
be a positive linear map. Then, there exists a Hilbert space
and a linear isometry
with dense image.
Proof: As previously explained, we make into a semi-inner product space by
. Then, we take
to be its completion. ⬜
If we introduce the condition that every is
-bounded, then the *-homomorphism
can be constructed.
Lemma 4 Let
be a *-algebra and
be a positive linear map such that every
is
-bounded. If
is as in lemma 3 then there is a unique *-homomorphism
satisfying
(1) for all
. Furthermore,
.
Proof: As is bounded,
is a bounded linear map on
with operator norm
. By continuous linear extension, there is a unique
satisfying (1), and has operator norm
. That
is a *-homomorphism is immediate from the definitions. For example,
so that ⬜
Alternatively, if it is assumed that is a state or, equivalently,
is a *-probability space, then the distinguished element
can be constructed. To simplify matters, to handle the case where
is not unitial, we use the fact that
uniquely extends to a state on the unitial algebra
by taking
for
. In fact, by lemma 10 of the post on states,
is
-dense in
.
Lemma 5 Let
be a *-probability space and let
be as in lemma 3. Then, there exists a unique
satisfying
(2) for all
. Furthermore,
and, if
is unitial,
. More generally,
uniquely extends to an
-isometry
, in which case
.
Proof: Uniqueness of is immediate from (2) and the requirement that
is dense in
. When
is unitial, then taking
gives
In the non-unitial case, by existence and uniqueness of bounded linear extensions, uniquely extends to an isometry
. Then, as above,
and, hence,
⬜
In particular, if we have a GNS representation , then
satisfies the requirements of lemma 5, and we see that
is necessarily a unit vector.
Corollary 6 Let
be a bounded *-probability space with GNS representation
. Then,
.
The existence of the GNS representation follows from what we have shown so far.
Lemma 7 Let
be a bounded *-probability space, and assume the notation of lemmas 4 and 5. Then,
satisfies the requirements of the GNS representation of theorem 1, and
.
Proof: By definition, is a Hilbert space and
is a *-homomorphism. Extend
to an
-isometry
. By lemma 4,
extends to a *-homomorphism
satisfying (1). Then,
(3) |
Hence
as required. Finally, (3) shows that , which is dense in
. ⬜
To easily handle non-unitial algebras, we note that GNS representations of automatically extend to GNS representations of the unitial algebra
.
Lemma 8 Let
be a bounded *-probability space with GNS representation
. Then,
uniquely extends to a *-homomorphism
, in which case
is a GNS representation for
.
Proof: Any extension satisfies
so, as is cyclic for
,
. Hence,
is the unique extension of
to a *-homomorphism from
. As
by corollary 6,
as required. ⬜
Next, the GNS representation is functorial. A homomorphism between *-probability spaces is a state preserving *-homomorphism of their *-algebras, and these canonically induce isometries of their GNS Hilbert spaces.
Lemma 9 Let
be a homomorphism of bounded *-probability spaces
and
, which have GNS representations
and
respectively. Then, there exists a unique isometric linear map
satisfying
(4) for all
.
Proof: Let which, by definition, is a dense subspace of
. Combining equations (4),
(5) |
which uniquely determines on
and, by continuity, this uniquely determines
. Conversely, we can use (5) to construct
on
. We need to show that this is an isometry and, to be well-defined, that the right-hand-side of (5) is zero whenever
. Using
we see that is well-defined and an isometry. Hence, by continuous linear extension it uniquely extends to an isometry
. Next, we show that (4) is satisfied. Using
we see that the first identity of (4) holds on and, by continuity, holds on all of
. Finally, by extending the constructions above to
and
, we can wlog assume that
and
are unitial. Then,
as required. ⬜
Finally, we put together the previous steps to complete the proof of theorem 1.
Proof of Theorem 1: The existence of the GNS representation was proven in lemma 7, so only uniqueness remains. Suppose that and
are two GNS representations. Applying lemma 9 to the identity map
on
gives a unique isometry
satisfying
and
. Similarly, there is a unique isometry
satisfying
and
. Then,
satisfies
and, hence, is the identity map. Similarly,
is the identity, so
is invertible. ⬜