# Manual Introduction to Spectral Theory in Hilbert Space.

Standard examples are spectral measures defined by means of multiplication operators or orthogonal sums of projections. We prove the one-to-one correspondence between resolutions of the identity and spectral measures on the Borel algebra of the real line and the theorem on the product of commuting spectral measures. Then integrals of measurable functions with respect to some spectral measure are defined and studied. These spectral integrals are unbounded normal operators on the underlying Hilbert space. The case of an unbounded function is reduced to the bounded case by means a so-called bounding sequence, that is, an increasing sequence of sets such that its union has full spectral measure and the function is bounded on each set.

Basic properties of spectral integrals algebraic properties, spectrum, behavior under transformations of spectral measures, permutation properties are developed in great detail. These results are applied in later chapters to the study of unbounded self-adjoint operators and their spectra. In the first section, the spectral theorem for a single bounded self-adjoint operator is proved. The spectral integrals with respect to the corresponding spectral measure are considered as functions of the self-adjoint operator.

Self adjoint operators over hilbert spaces and its eigen values and eigen vectors.(MATH)

Self-adjoint operators with simple spectra are studied. For an n -tuple of strongly commuting unbounded normal operators, the spectral theorem is proved, and the joint spectrum is defined and investigated. Permutability problems involving unbounded self-adjoint or normal operators are considered, and a number of equivalent characterizations of the strong commutavitity in terms of spectral measures, resolvents, and bounded transforms are given.

Chapter 6 gives a concise introduction into the theory of one-parameter groups or semigroups of operators with an emphasis on the interplay between groups and semigroups and their generators. Semigroups of operators are applied to Cauchy problems for abstract differential equations on Hilbert space. Then generators of semigroups of contractions on Banach spaces are studied, and the Hille—Yosida theorem is proved. Finally, generators of contraction semigroups on Hilbert space are characterized as m -dissipative operators.

Chapter 7 is devoted to a number of important technical tools and special topics for the study of closed operators and self-adjoint operators. We begin with the polar decomposition of a densely defined closed operator. Next, the bounded transform and its basic properties are developed. The usefulness of this transform has been already seen in the proofs of various versions of the spectral theorem in Chap.

Special classes of vectors analytic vectors, quasi-analytic vectors, Stieltjes vectors are studied in detail. They are used to derive criteria for the self-adjointness of symmetric operators Nelson and Nussbaum theorems and for the strong commutativity of self-adjoint operators. The last section of this chapter treats the tensor product of unbounded operators on Hilbert spaces. The Fourier transform allows us to give an elegant approach to these operators and their spectral properties. In the first section, the decomposition of a self-adjoint operator and its spectrum into a pure point part, a singularly continuous part, and an absolutely continuous part is obtained.

A short introduction into perturbation determinants is given in a separate section. Another main topic of Chap. We prove the Aronszajn—Donoghue theorem. The main theme of Chap. We begin with definitions and characterizations of closed and closable lower semibounded forms. Then the form associated with a self-adjoint operator is studied, and the first form representation theorem is proved. It establishes a one-to-one correspondence between lower semibounded self-adjoint operators and densely defined lower semibounded closed forms. Abstract boundary-value problems and abstract variational problems based on forms are formulated and solved.

Forms are used to define an order relation between self-adjoint operators. The Friedrichs extension of a densely defined lower semibounded symmetric operator is the largest self-adjoint extension of this operator. We derive it from the form representation theorem. For these operators, the abstract boundary-value problems and variational problems of forms become the weak Dirichlet problem and weak Neumann problem, respectively.

The final section of this chapter is devoted to the perturbation of forms and to the form sum of self-adjoint operators. First, the Lax—Milgram lemma for bounded coercive forms is obtained.

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The main results of this chapter are two form representation theorems, one for bounded coercive forms on densely and continuously embedded Hilbert spaces and another one for densely defined closed sectorial forms. The latter gives a one-to-one correspondence between densely defined closed sectorial forms and m -sectorial operators.

Finally, this form representation theorem is applied to second-order elliptic differential operators. The first main result is the Courant—Fischer—Weyl min—max principle. We state two versions of this theorem, one for operator domains and one for form domains. It allows us to compare the eigenvalues and discrete spectra of lower semibounded self-adjoint operators. The first one, due to J. The second one, due to M. Krein, is based on the Krein transform and describes positive self-adjoint extensions of a densely defined positive symmetric operator by means of bounded self-adjoint extensions of its Krein transform.

A classical theorem of T. Ando and K. Let y0 c M. Proof: Mz is a closed subspace. It should be remarked that the hypothesis of the preceding corollary cannot be weakened, i. We now study orthonormal sets and in particular orthonormal bases in a Hilbert space. Let yj j c I be an orthonormal set in E. Then for each x c E there exist at most countably many elements y c M such that xxy g0. Then 1 for every x c H the sum x y y converges in H where the sum is taken over all yM.

Bessels inequality implies: yM. If x c span M then there are y1, We now can make a meaningful definition of orthonormal basis 1. We dont need to mention the linear independence in the definition explicitly since an orthonormal set of elements is always linearly independent. Orthonormal bases in a Hilbert space can be characterized as follows 1. Then the sum x y y is called the Fourier series of x with respect to yM. The question whether a Hilbert space has an orthonormal basis, is answered by 1. Proof: If one of the cardinalities xMx or xNx is finite, then H is a finite dinmensional Hilbert space.

The same argument gives xMx[xNx, which implies equality. One useful result involving this concept is the following theorem 1. Then the following statements are equivalent: 1 H is separable i. By throwing out some of the elements of N we can get a subcollection N0 of independent vectors whose span finite linear combinations is the same as N. Applying the Gram-Schmidt procedure of this subcollection N0 we obtain a countable orthonormal basis of H.

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Since this set is countable, H is separable. Most Hilbert spaces that arise in practise have a countable orthonormal basis. We will show that such an infinite-dimensional Hilbert space is just a disguised copy of the sequence space l2. To some extent this has already been done in theorem 1.

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This theorem clarifies what is meant by disguised copy. Chapter 2: Bounded linear operators In this chapter we will study mappings of some subset D of a Hilbert space Hg into some other Hilbert space H. In this context we get confronted with two familiar aspects of such mappings: the algebraic aspect is well taken care of if the mapping A in question is linear. In order to be able to take care of the topological aspect we study two concepts for linear mappings which will turn out to be closely related with each other: boundedness and continuity.

## Introduction to Spectral Theory in Hilbert Space

This definition can also be extended to the case where H1,H2 are normed linear spaces. The same is true for the following characterizations in case of linear mappings. As soon as one thinks of a linear mapping one also has to think of its particular domain. The following example indicates that this may have something to do with unboundedness of the mapping in question. This theorem shows that in general case we ought to be careful about the domains of these operators Definition: Let H1,H2 be inner product spaces. A is linear and bounded, because of n. We denote the inverse of A by A The inverse of A is unique.

Proof: Suppose A-1 and B are inverses of A. A linear mapping of H into K is called a linear functional on H.