COMMON COMPLEMENTS OF TWO SUBSPACES OF A HILBERT SPACE

MICHAEL LAUZON AND SERGEI TREIL

Abstract. In this paper we find a necessary and sufficient condition for two closed subspaces, X and Y, of a Hilbert space H to have a common complement, i.e. a subspace Z having trivial intersection with X and Y and such that H = X + Z = Y + Z.

Unlike the finite-dimensional case the condition is significantly more subtle than simple equalities of dimensions and codimensions, and nontrivial examples of subspaces without a common complement are possible.

0. Introduction

0.1. Statement of the problem and discussion. In this paper we study when two subspaces X and Y of a Hilbert space H possess a common complement. Recall that a subspace Z of a Banach space H is called a complement of (or a complementary subspace to) a subspace X ⊂ H if X and Z have trivial intersection and H = X +Z. The latter means that any vector h ∈ H can be (uniquely, because X ∩ Z = {0}) represented as h = x + z, x ∈ X, z ∈ Z. This unique representation can serve as an alternative definition of a complement.

Clearly, if Z is a complement of X, then X is a complement of Z, and sometimes we will call X and Z complementary subspaces.

Unlike the finite dimensional case (dim H < ∞) the conditions

(i) X ∩ Z = {0} and (ii) X + Z is dense in H

are not sufficient for X and Z to be complementary subspaces; one more condition is needed. Namely, the closed graph theorem implies that if Z complements X, then the skew projection P = P_{X ||Z} onto X parallel to Z,

(0.1)  P_{X ||Z} (x + z) = x,  x ∈ X , z ∈ Z

is a bounded operator. Under the above assumptions (i) and (ii) this condition is necessary and sufficient for the subspaces X and Z to be complementary subspaces.

1991 Mathematics Subject Classification. 46C05.

Key words and phrases. Common complement, complementary subspaces, Hilbert space geometry, Gramian, lower linear dimension, upper linear codimension.

S. Treil is partially supported by NSF grant DMS 0200584 .

In the finite dimensional case finding a common complement is trivial. If X ⊂ H, dim X = n, and dim H = N, then the collection of all subspaces Z complementary to X is an open dense subset of the set of all subspaces of dimension m = N − n (Grassmannian). Note, that the set of all subspaces complementary to X is a set of full measure in the above Grassmannian (which is a compact smooth manifold of dimension n×(N−n)). So, using the Baire category theorem or measure theoretic reasoning one can conclude that any countable set of subspaces of dimension n has a common complement, and moreover, the set of all such common complements is a set of second category and a set of full measure in the Grassmannian of subspaces of dimension m = N − n.

The situation in the infinite dimensional case, as Theorem 0.1 below shows, is much more interesting. Of course, one could immediately see that the equality of dimensions (and codimensions) is not sufficient for the existence of a common complement. Indeed, it is possible that subspaces X and Y have equal dimensions and codimensions, but X ⫋ Y so they do not have a common complement.

The situation is, in fact, much more interesting. It can be easily shown, see Corollary 1.4 below, that the existence of a common complement implies that

codim_{X} X ∩ Y := dim(X ⊖ (X ∩ Y)) = = dim(Y ⊖ (X ∩ Y)) =: codim_{Y} X ∩ Y,

and we thought for some time that this equality of codimensions would be sufficient. To our surprise, this simple necessary condition turns out to be insufficient, and the real necessary and sufficient condition is much more subtle.

However, in some “philosophical” sense the equality of codimensions is necessary and sufficient. Namely, it is necessary and sufficient if we replace the intersection X ∩Y by the “ε-intersection”; see Theorem 5.1 for the precise statement.

Also note that we do not even have a conjecture about when three subspaces have a common complement.

0.2. Main result. To state our main result let us recall how one can describe the geometry of a pair of subspaces up to unitary equivalence. Let P = P_{Y} be the orthogonal projection onto Y, and let the operator G : X → Y (Gramian) be defined by

G = P_{Y} |X .

Clearly the adjoint operator G^{∗} : Y → X is defined by G^{∗} = P_{X} |Y.

It is a well known fact (and it will be shown later) that for any bounded operator G (from one Hilbert space to another) the essential parts of the operators G^{∗}G and GG^{∗}, i.e. the operators G^{∗}G|(ker G)^{⊥} and GG^{∗}|(ker G^{∗})^{⊥} are unitarily equivalent.

So, the geometry of a pair of subspaces is completely determined by the following objects:

(1) The operator G^{∗}G, or even only its essential part G^{∗}G|(ker G)^{⊥};

(2) The dimensions of two subspaces, X_{0} and Y_{0}

X_{0} := ker G = {x ∈ X : x ⊥ Y}, Y_{0} := ker G^{∗} = {y ∈ Y : x ⊥ X }

The following theorem is the main result of the paper. It holds for both real and complex Hilbert spaces.

Theorem 0.1. Let E( .) be the spectral measure of the operator G^{∗}G (or of G^{∗}G|(ker G)^{⊥}). Then the subspaces X and Y have a common complement if and only if

(0.2)  dim X_{0} + dim E((0, 1 − ε))X = dim Y_{0} + dim E((0, 1 − ε))X

for some ε > 0 (for all sufficiently small ε > 0).

Remark 0.2. We do not assume that the space H is separable. The dimension in this case means the cardinality of an orthonormal basis (it is well known, see Section 1.1 below, that it does not depend on the choice of basis). We add cardinalities according to usual rules, cf [2, Corollary I.4.30], i.e. the sum is the maximal dimension, except the case when both dimensions are finite.

Remark 0.3. It is easy to see that one can always replace E((0, 1 − ε)) by E((0, 1 − ε]) in the condition (0.2).

Remark 0.4. If dim X_{0} = dim Y_{0} then a common complement always exists.

Remark 0.5. If H is a separable space, the subspaces X and Y do not have a common complement if and only if dim X_{0} ≠ dim Y_{0} and the operator (I − G^{∗}G)|(ker G)^{⊥} is compact.

Indeed, if there is no common complement and H is seperable, then dim X_{0} ≠ dim Y_{0} and dim E((0, 1 − ε])X is finite for all ε > 0. The latter exactly means that (I − G^{∗}G)|(ker G)^{⊥} is a compact operator.

1. Preliminaries

1.1. Remarks about dimension. This subsection deals with the definition of dimension for non-separable Hilbert spaces. A reader uninterested in the non-separable case may skip this subsection, since the corresponding results are trivial for separable spaces.

As it is customary in functional analysis we assume the Axiom of Choice here. It is needed in too many places, and we do not have any desire to go very deep into the set theory to investigate what makes sense in its absence.

The dimension of a Hilbert space (or subspace) is defined as the cardinality of an orthonormal basis. An old theorem due to Löwig and Rellich, see [1, Theorem IV.4.14] asserts that all orthonormal bases in a given Hilbert space H have the same cardinality, so the dimension is well defined.

Since unitary operators map orthonormal bases to orthonormal bases, two Hilbert spaces are isometrically isomorphic if and only if they have the same dimension.

If A : H_{1} → H_{2} is an isomorphism (a bounded invertible operator) between two Hilbert spaces, it can be represented as A = UR (polar decomposition), where R = |A| := (A^{∗}A)^{1/2} and U : H_{1} → H_{2} is a unitary operator. So, if two Hilbert spaces are isomorphic, they are isometrically isomorphic, and therefore the dimension is preserved under the isomorphism.

1.2. Codimension. The codimension of a subspace X of a Hilbert space H is defined as dim X^{⊥}. We can, in fact, show that all complements of X have the same dimension (and therefore the same dimension as the orthogonal complement).

Proposition 1.1. Let X and Z be complementary subspaces of a Hilbert space H. Then codim X = dim Z.

Proof. Take arbitrary y ∈ X^{⊥}. Since Z complements X, y has the unique decomposition

y = x + z, x ∈ X, z ∈ Z, ∥z∥ ≤ C∥y∥.

Therefore, the orthogonal projection P_{X^{⊥}} onto X^{⊥} maps Z isomorphically onto X^{⊥}, hence dim Z = dim X^{⊥}. □

Corollary 1.2. The codimension of a subspace is preserved under isomorphisms (of the whole space).

1.3. Some trivial observations. Before discussing the main result, let us make several observations. The following trivial proposition holds for arbitrary Banach spaces

Proposition 1.3. The subspaces X and Y have a common complement if and only if there exists a bounded (not necessarily orthogonal) projection P onto one of the spaces (say, for definiteness, onto Y) such that the operator

G : X → Y, G := P|X

is an isomorphism (bounded invertible operator) between X and Y.

Proof. If such a P exists, then Z := ker P is a common complement of X and Y. Indeed, the projection P_{Y||Z} = P is bounded, so Z is a complement of Y. The projection P_{X ||Z} onto X parallel to Z can be defined by

P_{X ||Z} = G^{−1}P,

so it is also bounded. So Z is a complement of X as well. □

Now let us return to Hilbert spaces.

Corollary 1.4. If two subspaces X and Y of a Hilbert space have a common complement, then the dimensions of the spaces X ⊖(X ∩Y) and Y ⊖(X ∩Y) coincide (i.e. codim_{X} X ∩ Y = codim_{Y} X ∩ Y, where codim_{X} stands for the codimension in X).

Proof. Trivial, since the operator G from the above Proposition 1.3 maps X ⊖ (X ∩ Y) isomorphically onto Y ⊖ (X ∩ Y) □

Proposition 1.5. If X, Y ⊂ H have a common complement in the closure of X + Y then X and Y have a common complement in H.

Proof. Let Z be the common complement of X and Y in Clos(X +Y). Then Z ⊕ (X + Y)^{⊥} is a common complement of X and Y in H □

Thus without loss of generality we may always assume Clos(X + Y) = H.

2. Sufficiency

In this section we prove that condition (0.2) is sufficient for the subspaces X and Y to have a common complement. We first treat several simple cases, and then we show that the general case can be treated as a “direct sum” of the simple cases.

Recall that the Gramian G : X → Y is defined as

G = P_{Y} |X

and its adjoint G^{∗} is defined by

G^{∗} = P_{X} |Y.

2.1. Some simple cases. First we consider the case where X and Y are, in some sense, completely non-orthogonal.

Proposition 2.1. If G is invertible then Z = Y^{⊥} is a common complement of X and Y.

Proof. Follows immediately from Proposition 1.3 □

The next case will be treated by changing the inner product in H. Note that having a common complement is a topological property, meaning it does not change if we replace the norm (inner product) in H by an equivalent one. If we have a Hilbert space H and A = A^{∗} ≥ 0 is a bounded and invertible operator in H, then (·, ·)_{A}, (f, g)_{A} := (Af, g) defines an equivalent inner product in H (in fact, all equivalent inner products in H can be defined this way, but we won’t need that in what follows).

Let H = X ⊕ Y be the orthogonal sum of X and Y. Given an operator G : X → Y, ∥G∥ < 1 consider a norm on H defined by the operator

A = A_{G} = ( \begin{matrix}I & G^{∗} \\ G & I \end{matrix} )

Clearly, if ∥G∥ < 1, the operator A_{G} is positive and invertible, therefore the corresponding norm is equivalent to the original norm on H. Thus, all such norms are equivalent to each other.

Note that if G = G, then the corresponding norm in H is the original norm in X + Y ⊂ H. Also note that if G = 0 then X ⊥ Y in the norm generated by A_{G}.

Proposition 2.2. If ∥G∥ < 1 and dim{X ⊖ (X ∩ Y)} = dim{Y ⊖ (X ∩ Y)}, then X and Y have a common complement.

Proof. As in Proposition 1.5 we can assume without loss of generality that X + Y is dense in H.

The equality of dimensions implies that there exists an isomorphism (bounded invertible operator) G : X → Y. Multiplying it by a small number we can always assume that ∥G∥ < 1. So, as we just discussed above, the norms generated by the operators A_{G} and A_{G} are equivalent, and both are equivalent to the norm corresponding to A_{0} (meaning A_{G} with G = 0).

The norm corresponding to A_{G} is the norm on X + Y inherited from H. This norm is equivalent to the norm generated by A_{0}, therefore the subspace X + Y is closed, and so X + Y = H.

Therefore A_{G} gives the equivalent norm on H. Note that in this norm the corresponding Gramian G equals G. Since it is invertible, Proposition 2.1 implies that X and Y have a common complement. □

2.2. The general case. To treat the general case we split the subspaces X and Y into orthogonal sums, X = X_{1} ⊕ X_{2}, Y = Y_{1} ⊕ Y_{2}, so that the subspaces H_{k} := Clos(X_{k} + Y_{k}) are also orthogonal.

Then, if each pair X_{k}, Y_{k} has a common complement in H_{k}, k = 1, 2, then X and Y clearly have a common complement.

Let E(·) denote the spectral measure of the operator G^{∗}G and E_{∗}(·) be the spectral measure of GG^{∗}. Fix a ∈ (0, 1) and define

(2.1)  X_{1} := E([0, a))X , X_{2} := E([a, 1])X ,

and similarly,

(2.2)  Y_{1} := E_{∗}([0, a))Y, Y_{2} := E_{∗}([a, 1])Y.

where a = 1 − ε, ε is from the assumption (0.2) of the theorem.

2.2.1. The case of trivial kernels. Let us first consider the case when both ker G and ker G^{∗} are trivial (then the assumption (0.2) is automatically satisfied for all ε ∈ (0, 1)).

Consider the polar decomposition G = UR, where R = (G^{∗}G)^{1/2} and U : X → Y is a unitary operator. Since GG^{∗} = UR^{2}U^{∗} = U(G^{∗}G)U^{∗} we have for the spectral measures

E_{∗} = UEU^{∗}.

This implies that Y_{k} = UX_{k}, k = 1, 2, and therefore dim X_{k} = dim Y_{k}.

Since X_{k} are G^{∗}G-invariant, and so R-invariant

GX_{k} = URX_{k} ⊂ UX_{k} = Y_{k},

and similarly G^{∗}Y_{k} ⊂ X_{k}. Note that it is also easy to prove that GX_{2} = Y_{2} and GX_{1} is dense in Y_{1}, and similarly for Y_{k}, but we will not need these facts now.

To show that H_{1} ⊥ H_{2} it is sufficient to show that X_{1} ⊥ Y_{2} and X_{2} ⊥ Y_{1}. Let us show that X_{1} ⊥ Y_{2}. Take x ∈ X_{1}, y ∈ Y_{2}. We have

(x, y) = (P_{Y} x, y) = (Gx, y) = 0

since Gx ∈ Y_{1} ⊥ Y_{2}. The orthogonality X_{2} ⊥ Y_{1} is proved similarly.

Now we need to prove that the pairs X_{k}, Y_{k}, k = 1, 2 have a common complement. For the pair X_{k}, Y_{k} the corresponding Gramian is the restriction G|X_{k}. Then for X_{2}, Y_{2} the Gramian is invertible, and for X_{1}, Y_{1} its norm is less than 1. Since, as we discussed above, dim X_{k} = dim Y_{k}, Proposition 2.1 implies that subspaces X_{2}, Y_{2} have a common complement, and Proposition 2.2 asserts the existence of a common complement for the pair X_{1}, Y_{1}. □

2.2.2. The case of non-trivial kernels. Let us now consider the general case, when we allow non-trivial kernels for G and G^{∗}. We set a = 1 − ε, where ε is from the assumption (0.2) of Theorem 0.1, and define X_{k}, Y_{k} as above.

The simplest way to understand the geometry here is to first imagine the case of trivial kernels and then add to X_{1} and Y_{1} the orthogonal (to everything else) subspaces ker G and ker G^{∗} respectively. Since we added orthogonal subspaces, the orthogonality condition remains true. The subspaces X_{2}, Y_{2} will not change, so this pair has a common complement. As for the pair X_{1}, Y_{1}, the norm of corresponding Gramian remains the same (by adding two orthogonal to everything subspaces, we just added zero blocks to the “old” Gramian), so it is less than 1. Assumption (0.2) of the theorem means that the dimensions of the “new” X_{1} and Y_{1} coincide, so Proposition 2.2 implies that there is a common complement for this pair as well.

To write the last paragraph formally, let X^{0} := X ⊖ ker G, Y^{0} := Y ⊖ ker G^{∗}, and let G_{0} : X^{0} → Y^{0} be the restriction of G. Let us denote by X_{k}^{0}, Y_{k}^{0}, H_{k}^{0} the corresponding subspaces for G_{0}, and by E^{0}, E_{∗}^{0} the spectral measures for G_{0} and G_{0}^{∗} respectively. Clearly

X_{2} = X_{2}^{0}, Y_{2} = Y_{2}^{0},

and

X_{1} = X_{1}^{0} ⊕ ker G, Y_{1} = Y_{1}^{0} ⊕ ker G^{∗}.

Since ker G ⊥ Y ⊕ X^{0}, and ker G^{∗} ⊥ X ⊕ Y^{0}, the subspaces H_{1} and H_{2} are orthogonal.

Because they coincide with X_{2}^{0} and Y_{2}^{0}, the subspaces X_{2}, Y_{2} possess a common complement. Since, as we already discussed for the case of trivial kernels,

dim X_{1}^{0} = dim Y_{1}^{0} = dim E^{0}((0, a))X^{0} = dim E((0, a))X ,

the assumption (0.2) implies

dim X_{1} = dim X_{1}^{0} + dim ker G = dim Y_{1}^{0} + dim ker G^{∗} = dim Y_{1}.

Now notice that ∥G|X_{1}∥ = ∥G_{0}|X_{1}^{0}∥ < 1 (the operators differ by zero blocks), so Proposition 2.2 implies that X_{1} and Y_{1} have a common complement.

3. Necessity

Lemma 3.1. Let X and Y be subspaces of a Hilbert space H. Suppose there exists an isomorphism (bounded invertible operator) A : X → Y such that

∥x − Ax∥ ≤ q∥x∥ ∀x ∈ X,

for some q < 1. Then codim X = codim Y.

Proof. Define an operator A_{X} : X → X by A_{X} x := P_{X} Ax, where P_{X} is orthogonal projection onto X. Since

∥A_{X} x − x∥ = ∥P_{X} (Ax − x)∥ ≤ ∥Ax − x∥ ≤ q∥x∥,

we have ∥A_{X} − I∥ ≤ q < 1, so A_{X} is invertible.

For y ∈ Y we have

P_{X} y = A_{X} A^{−1}y,

so P_{X} defines an isomorphism between X and Y. Therefore, by Proposition 2.1, X^{⊥} is a common complement for X and Y. Hence, see Proposition 1.1, codim X = codim Y = dim X^{⊥}. □

Now suppose that X and Y have a common complement. Then, by Proposition 1.3, there exists a bounded projection P onto Y such that G := P|X is an isomorphism between X and Y.

We want to prove that condition (0.2) from Theorem 0.1 holds for some ε > 0. In the notation of the previous section, see (2.1) (2.2), this condition can be rewritten as

codim_{X} X_{2} := dim(X ⊖ X_{2}) = dim(Y ⊖ Y_{2}) =: codim_{Y} Y_{2},

where a = 1 − ε. Here codim_{X} stands for the codimension in X. Since G is an isomorphism between X and Y,

codim_{X} X_{2} = codim_{Y} GX_{2}.

So we want to show that the subspaces GX_{2} = PX_{2} and Y_{2} = GX_{2} = P_{Y} X_{2} have the same codimension in Y. To do that we will use Lemma 3.1.

Take x ∈ X_{2}. Then ∥Gx∥^{2} ≥ a∥x∥^{2}, so

∥x∥^{2} − ∥Gx∥^{2} ≤ (1 − a)∥x∥^{2} ≤ \frac{1 − a}{a}∥Gx∥^{2} = \frac{ε}{1 − ε}∥Gx∥^{2}.

Hence

∥Gx − Px∥^{2} = ∥P_{Y} x − Px∥^{2} = ∥P(P_{Y} x − x)∥^{2} ≤ ∥P∥^{2} · ∥P_{Y} x − x∥^{2}

= ∥P∥^{2}(∥x∥^{2} − ∥P_{Y} x∥^{2}) = ∥P∥^{2}(∥x∥^{2} − ∥Gx∥^{2})

≤ \frac{ε}{1 − ε}∥P∥^{2}∥Gx∥^{2}.

Thus for small ε > 0 the assumptions of Lemma 3.1 hold for subspaces P_{Y} X_{2} and PX_{2} in Y with the operator A : P_{Y} X_{2} → PX_{2} defined by

A = P · (G|X_{2})^{−1}

(recall that G maps X_{2} isomorphically to Y_{2}).

4. An Example of subspaces without common complement

As we said above, if the space H is separable the only situation when a common complement does not exists is when (I − G^{∗}G)|(ker G)^{⊥} is a compact operator, and dim ker G ≠ dim ker G^{∗}. This gives us the possibility to construct non-trivial examples of subspaces without a common complement.

By non-trivial example we mean here a pair of subspaces satisfying the simple necessary condition

codim_{X} (X ∩ Y) = codim_{Y} (X ∩ Y),

and not possessing a common complement.

In this section we construct subspaces X and Y of equal dimensions and codimensions and with trivial intersection, which do not have a common complement.

Let H = ℓ^{2} the space of square summable sequences with indices 0, 1, 2, . . .. We let {e_{k}}_{k=0}^{∞} be the standard orthonormal basis of H. We will define X and Y by defining a basis for these subspaces. We define:

y_{0} = e_{0},

and for k ≥ 1

y_{k} = cos \frac{1}{k} e_{2k−1} + sin \frac{1}{k} e_{2k}

x_{k} = cos \frac{1}{k} e_{2k−1} − sin \frac{1}{k} e_{2k}.

We see that X = span {x_{i}}_{i=1}^{∞} and Y = span {y_{i}}_{i=0}^{∞} are subspaces of equal dimension and codimension, X ∩ Y = {0}, with no common complement. Indeed, it is trivial that G is a compact perturbation of I, and 0 = dim ker G ≠ dim ker G^{∗} = 1.

5. A geometric interpretation of the results.

The interesting thing about the main result of the paper is that despite the fact that the existence of a common complement is a topological condition (i.e. it does not change when one replaces the norm by an equivalent one), the orthogonality mysteriously appears in the results and plays an important role here.

In this section we give a more geometric version of the above Theorem 0.1, which does not include orthogonality explicitly. We say here “explicitly” because it still requires a Hilbert space norm. We do not know if it is true if one replaces the Hilbert space norm by an equivalent Banach space norm.

Let us introduce a few definitions. Let K be a subset of a Hilbert space X. We define the lower linear dimension of K as

sup{dim L : L is a linear subspace of K}

and the upper linear codimension of K by

inf{codim L : L is a linear subspace of K}.

If the reader is not comfortable with taking the supremum or infimum of a family of cardinalities, he should not be worried, since in our case there always be subspaces of maximal dimension and subspaces of minimal codimension.

Let ε > 0. For the subspaces X, Y of H define the cones

K_{X}^{ε} := {x ∈ X : dist(x, Y) ≤ ε∥x∥},
K_{Y}^{ε} := {y ∈ Y : dist(y, X) ≤ ε∥y∥}.

For small ε one can treat the cones K_{X}^{ε}, K_{Y}^{ε} as “ε-intersection” of X and Y.

As was said before in Corollary 1.4, if the subspaces X and Y have a common complement, the intersection X ∩ Y has the same codimensions in X and in Y. Theorem 0.1 shows that the equality of codimensions is not sufficient for the existence of a common complement. The theorem below, which is a reformulation of the main result (Theorem 0.1) shows that if one replaces the intersection X ∩ Y with the “ε-intersections” K_{X}^{ε}, K_{Y}^{ε}, then the equality of codimensions is necessary and sufficient. While its condition is harder to check than condition (0.2) of Theorem 0.1, we think the Theorem 5.1 is still interesting because it provides a geometric interpretation of the results.

Theorem 5.1. Subspaces X and Y of a Hilbert space H have a common complement if and only if for some (small) ε > 0 the upper linear codimensions of the cones K_{X}^{ε} in X and K_{Y}^{ε} in Y coincide.

Proof. To prove the theorem we will show that the upper linear codimensions of the cones K_{X}^{ε} and K_{Y}^{ε} equal to

dim E([0, 1 − ε^{2})] = dim ker G + dim E((0, 1 − ε^{2}))

and

dim E_{∗}([0, 1 − ε^{2})] = dim ker G^{∗} + dim E_{∗}((0, 1 − ε^{2}))

respectively. Recalling that dim E_{∗}((0, 1 − ε^{2})) = dim E((0, 1 − ε^{2})) we will see that the condition of Theorem 5.1 is exactly the assumption (0.2) of Theorem 0.1 (with ε replaced by ε^{2}).

To compute the codimension of the cones, let us notice that for x ∈ X

[dist(x, Y)]^{2} = ∥x∥^{2} − ∥P_{Y} x∥^{2} = ∥x∥^{2} − ∥Gx∥^{2}.

Therefore, the cone K_{X}^{ε} is the cone of nonnegative vectors of the operator A = G^{∗}G − (1 − ε^{2})I, i.e. K_{X}^{ε} = {x ∈ X : (Ax, x) ≥ 0}, and similarly, K_{Y}^{ε} is the cone of the nonnegative vectors of A_{∗} := GG^{∗} − (1 − ε^{2})I. Then the theorem follows from the lemma below.

Let A be a bounded selfadjoint operator in a Hilbert space H, and let K be the cone of nonnegative vectors of A, K := {x ∈ H : (Ax, x) ≥ 0}. Let E be the spectral measure of A, and let

H_{+} := E([0, ∞)), H_{−} := E((−∞, 0)).

Lemma 5.2. The upper linear codimension of the cone K is exactly

codim H_{+} = dim H_{−}.

The theorem follows immediately from the lemma, since for the operator A = G^{∗}G − (1 − ε^{2})I defined above,

H_{+} = E([1 − ε^{2}, 1]), H_{−} = E((0, 1 − ε^{2})),

and similarly for A_{∗}.

Proof of Lemma 5.2. Consider a (closed) subspace X ⊂ K. Let P be the orthogonal projection onto H_{+}, and let Y := Clos P X.

By the construction of Y, the set Y_{0} := {y ∈ Y : y ⊥ X} = {0} Since X ⊥ H_{+} ⊖Y, any vector x ∈ X orthogonal to Y is automatically orthogonal to H_{+}. But since X ⊂ K, we have X ∩ H_{−} = {0}, so X_{0} := {x ∈ X : x ⊥ Y } = {0}. Therefore the condition (0.2) of Theorem 0.1 are satisfied (see Remark 0.4 there), and X and Y have a common complement, say Z. Proposition 1.1 implies that

codim X = codim Y = dim Z,

and since Y ⊂ H_{+}, we have codim Y ≥ codim H_{+}. Thus, H_{+} has the smallest codimension among all subspaces of K. □

□

References

[1] N. Dunford, J. Schwartz, Linear Operators. Part I, General Theory, John Willey & Sons, 1988.

[2] E. Hewitt, K. Stromberg, Real and abstract analysis : a modern treatment of the theory of functions of a real variable, 2nd edition, Springer-Verlag, New York, 1969.

Department of Mathematics, Box 1917, Brown University, Providence, RI 02912, USA

E-mail address: mlauzon@math.brown.edu, treil@math.brown.edu
URL: http://www.math.brown.edu/~treil