Matrix representation of a closed symmetric operator

In summary, to prove that a closed symmetric operator A has a matrix representation, we construct a dense sequence in the operator's domain and a basis for the Hilbert space. Using these, we can define a matrix representation for A, and show that it is symmetric.
  • #1
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Homework Statement



Show that a closed symmetric operator has a matrix representation.

Homework Equations



There are lots. I'm hoping somebody familiar with linear operators in Hilbert spaces is reading this!

The Attempt at a Solution



Hi,

I'm trying to prove that a closed symmetric operator A with a dense domain
D(A) in a separable, infinite-dimensional Hilbert space H has a matrix
representation given by

a_{kl} = (Ae_l, e_k)

where {e_n} is a suitable basis in D(A) (the exercise asks to construct this
basis too). I constructed a proof, but I did not use the fact that A is
closed, so I'm worried that I made a mistake somewhere. I would appreciate
if someone could help point out where the closed property of A is used.

My proof follows. (Note that in all cases "inf" is the symbol for infinity.)
It consists of four parts:

STEP 1: There exists an everywhere dense sequence (g_n) \subset D(A) with the
following property: for every f in D(A) there exists a subsequence (g_n_k) of
(g_n) such that

f = lim_{k -> inf} g_n_k,

Af = lim_{k -> inf} Ag_n_k.

PROOF OF STEP 1: Let f be an element of D(A). Since H is separable, there
exists a sequence (h_n) in H such that {h_n} is dense in H. For each
ordered triple of natural numbers (l,m,n), let G_lmn be a set consisting of
all g in D(A) such that

|| h_m - g || < 1/l, || h_n - Ag || < 1/l

Next, let G be a set containing one member of each G_lmn, where (l,m,n)
is an ordered triple of natural numbers, which is non-empty. It is clear
that G is countable; let us label its elements thus:

G = {g_n}

We claim that G is dense in D(A). For let f be in D(A) and eps > 0; then
there exits an ordered triple of natural numbers (l,m,n) s.t. 2/l < eps
and

|| f - h_m || < 1/l, || Af - h_n || < 1/l

Therefore f is in G_lmn, so G_lmn is not empty. Accordingly, there exists
g_k in G such that

(eq1) || g_k - h_m || < 1/l, || Ag_k - h_n || < 1/l

Therefore

(eq2) || f - g_k || <= || f - h_m || + || h_m - g_k ||

< 1/l + 1/l < eps.

Hence G is dense in D(A). Since D(A) is dense in H, so is G. We also have

|| Af - Ag_k || <= || Af - h_n || + || h_n - Ag_k || < 1/l + 1/l < eps.

We now prove the main result. Let f be in D(A); if f is also in G, we don't really
need a subsequence. Otherwise, if f is not in G, for each natural number
k, Equations (eq1) and (eq2) imply that there exists a natural number
n_k such that g_n_k is in G and

|| f - g_n_k || < 1/k, || Af - Ag_n_k || < 1/k

Furthermore, there are an infinite number of elements in G which satisfy these
relations, so we can always choose a g_n_k such that n_k > n_{k-1}, etc.

In this way we construct the subsequence (g_n_k), which has the properties

f = lim_{k -> inf} g_n_k, Af = lim_{k -> inf} Ag_n_k

QED

STEP 2: there exits a basis {e_n} in D(A) for H with the following property:
let W be the linear manifold of finite complex linear combinations of basis
vectors e_k (k a natural number); for every f in D(A) there exists a
sequence {f_n} in A such that

f = lim_{n -> inf} f_n, Af = lim_{n -> inf} Af_n

PROOF OF STEP 2: We construct a linearly independent set from {g_n} in
step 1 as follows. Let n_1 be the smallest natural number such that
g_n_1 is not zero. If n_1 < n_2 < ... < n_k have already been chosen
so that g_n_1, ..., g_n_k are linearly independent and g_n is a finite
linear combination of g_n_1, ..., g_n_k for 1 <= n <= n_k, let n_{k+1} > n_k
be the smallest integer such that g_n_1, ..., g_n_{k+1} are linearly
independent. In this way, we define the linearly independent set

U = {g_n_k: k a natural number}

(This set is countably infinite since H is infinite-dimensional). We
apply the Gram-Schmidt orthogonalisation process to the members of U to
construct a new family of vectors:

U' = (g'_n: n a natural number}

We then define the following family of orthonormal vectors:

B = {e_n: n a natural number}

where e_n is defined by g'_n / || g'_n || for all natural numbers n. Now
each original g_n is a finite linear combination of members of U, and the
members of U are finite linear combinations of the members of U', and by
implication those of B. Hence each g_n is a finite linear combination of
vectors in B. Now, let f be in D(A). From step 1, there exists
a subsequence (g_n_k) of (g_n) such that

f = lim_{k -> inf} g_n_k, Af = lim_{k -> inf} Ag_n_k

But by the foregoing, each g_n is actually a member of W. We can relabel
the g_n_k's as f_n's to obtain the desired result.

Finally, we show that {e_n} is a basis for H. By construction, {e_n}
is an orthonormal set; all that remains is to show that it is maximal.
Suppose there exists u in H such that (e_n, u) = 0 for all natural numbers
n. Let f be in D(A); then by the earlier result, there exists a sequence
(f_n) in W such that

f = lim_{n -> inf} f_n, Af = lim_{n -> inf} Af_n

Since each f_n is a finite linear combination of members of {e_n}, we have
(f_n, u) = 0 for all natural numbers n. Thus,

(f,u) = lim_{n -> inf} (f_n, u) = 0.

Thus u is perpendicular to all vectors in D(A). Next, let x be in H. Since
D(A) is dense in H, there exists a sequence (x_n) in D(A) such that

x = lim_{n -> inf} x_n

Now (x_n, u) = 0 for all natural numbers n, so

(x, u) = lim_{n -> inf} (x_n, u) = 0

In particular, letting x = u gives (u,u) =0, so u =0. Therefore the set
{e_n} is maximal in H, so it is a basis.

QED.

STEP 3: Suppose A is symmetric, let {e_k} be a basis as in step 2, and
define

a_{kl} = (Ae_l, e_k) for all natural numbers k and l.

Furthermore, define the operator A' on the linear manifold

D(A') = {g = sum{k=1 to inf} b_l e_l: sum_{k=1 to inf} | sum_{l=1 to inf} a_{kl} b_l|^2 < inf }

by

A'g = sum_{k = 1 to inf} ( sum_{l = 1 to inf} a_{kl} b_l ) e_k.

Then A' = A* (where A* is the adjoint of A).

PROOF OF STEP 3: We first show that A* \subset A'. Let g be in D(A*),
where D(A*) is the domain of A*. Since {e_k} is a basis for H, g has the
Fourier expansion

g = sum_{l = 1 to inf} b_l e_l

Now Parseval's identity gives

inf > || A*g ||^2 = sum_{k=1 to inf} |(A*g, e_k)|^2 = sum_{k=1 to inf} |(Ae_k, g)|^2

From the Fourier expansion of g and the continuity of the inner product,
we have

(Ae_k, g) = sum_{l = 1 to inf) (Ae_k, b_l e_l) = sum_{l = 1 to inf) conj(b_l) (Ae_k, el)

= sum_{l = 1 to inf} conj(b_l) a_{lk}.

Note that conj(x) denotes the complex conjugate of x. Since A is symmetric,
from the definition of a_{kl} we see that a_{lk} = conj(a_{kl}, so

(Ae_k, g) = sum_{l = 1 to inf} conj(a_{kl} b_l).

Therefore

inf > || A*g ||^2 = sum_{k = 1 to inf} | sum_{l = 1 to inf} a_{kl} b_l |^2,

hence g is in D(A'), the domain of A'. To show that A*g = A'g,

A*g = sum_{k = 1 to inf} (A*g, e_k) e_k = sum_{k = 1 to inf} conj( (e_k, A*g) )e_k

= sum{k = 1 to inf} conj( (Ae_k, g) ) e_k

= sum{k = 1 to inf} ( sum_{l = 1 to inf} a_{kl} b_l ) e_k

= A'g.

Therefore A* \subset A'.

We now show that A' \subset A*. Let g be in D(A'). Now g has the Fourier
expansion

g = sum_{l = 1 to inf} b_l e_l

Let l be a natural number; then

(Ae_l, g) = sum_{k = 1 to inf} conj(b_k) (Ae_l, e_k)

= sum{k = 1 to inf) conj(b_k) a_{kl}

But A'g = sum{k = 1 to inf} ( sum_{l = 1 to inf} a_{kl} b_l ) e_k, so

(e_l, A'g) = sum_{k = 1 to inf) conj( a_{lk} b_k ) = sum_{k = 1 to inf} conj(b_k) a_{kl}
= (Ae_l, g).

It follows then that if u is any vector which is a finite linear
combination of basis vectors, we have

(eq3) (Au, g) = (u, A'g).

We now let f be in D(A) and let eps > 0. By step 2, there exists a
sequence (f_n) in W such that

f = lim_{n -> inf} f_n, Af = lim_{n -> inf} Af_n

Now

|(Af, g) - (f, A'g)|
<= |(Af - Af_n, g)| + |(Af_n, g) - (f_n, A'g)| + |(f-f_n, A'g)|

But from (eq3), we know that |(Af_n, g) - (f_n, A'g)| = 0, so

|(Af, g) - (f, A'g)| <= || Af - Af_n || || g || + || f - f_n || || A'g ||

since || g || and || A'g || are bounded, there exits a natural number N
such that

|| Af - Af_n || || g || < eps/2, || f - f_n || || A'g || < eps/2

for all n >= N. Therefore

|(Af, g) - (f, A'g)| < eps.

Since eps is arbitrary, (Af, g) = (f, A'g). Thus g is in D(A*) and
A'g = A*g, so A' \subset A*.

From the above considerations, we see that A' = A*.

QED

STEP 4: The operator A has a matrix representation.

PROOF OF STEP 4: Since A is symmetric, we have for all f in D(A):

Af = A*f = A'f.

QED

As one can see, I have used the assumptions that A is symmetric, that H
is separable and infinite-dimensional, and that D(A) is dense in H. But
I have not used (at least explicitly) the fact that A is closed. I know the
above proof is quite long but again I would greatly appreciate it if someone
could point out to me either where I have made a mistake or I have implicitly
used the assumption that A is closed.

Thanks in advance.
 
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  • #2


Hi there,

Your proof looks good to me. The closed property of A is not needed in your
proof because you have already assumed that D(A) is dense in H. This is
equivalent to saying that the closure of D(A) is equal to H, which implies
that A is closed. So you have already taken care of the closed property
implicitly.

Hope this helps!
 

Related to Matrix representation of a closed symmetric operator

1. What is a closed symmetric operator?

A closed symmetric operator is a linear transformation on a vector space that is self-adjoint, meaning it is equal to its own adjoint. This means that the operator and its adjoint have the same eigenvalues and eigenvectors.

2. How is a closed symmetric operator represented in a matrix?

A closed symmetric operator can be represented in a matrix form using the eigenvectors and eigenvalues of the operator. The matrix will be a square matrix with the eigenvalues along the diagonal and the eigenvectors as the columns.

3. What is the significance of a closed symmetric operator?

A closed symmetric operator has many important applications in mathematics and physics. It is used to study the properties and behavior of linear transformations, and is especially useful in studying quantum mechanics and differential equations.

4. How do you determine if an operator is closed and symmetric?

To determine if an operator is closed and symmetric, you can check if it is self-adjoint, meaning it is equal to its own adjoint. This can be done by checking if the matrix representation of the operator is equal to its transpose.

5. Can a closed symmetric operator have complex eigenvalues?

Yes, a closed symmetric operator can have complex eigenvalues. However, in order for the operator to be self-adjoint, the complex eigenvalues must come in conjugate pairs. This means that if a complex number is an eigenvalue, its complex conjugate will also be an eigenvalue.

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