Functional Analysis, Math 7321 Lecture Notes from April 04, 2017 taken by Chandi Bhandari

Similar documents
The spectrum of a self-adjoint operator is a compact subset of R

Spectral theory for compact operators on Banach spaces

Linear Normed Spaces (cont.) Inner Product Spaces

SPECTRAL THEOREM FOR SYMMETRIC OPERATORS WITH COMPACT RESOLVENT

Math 123 Homework Assignment #2 Due Monday, April 21, 2008

SPECTRAL THEOREM FOR COMPACT SELF-ADJOINT OPERATORS

Your first day at work MATH 806 (Fall 2015)

Remarks on the Spectrum of Bounded and Normal Operators on Hilbert Spaces

Lemma 3. Suppose E, F X are closed subspaces with F finite dimensional.

I teach myself... Hilbert spaces

LECTURE OCTOBER, 2016

4 Linear operators and linear functionals

On compact operators

ON THE GENERALIZED FUGLEDE-PUTNAM THEOREM M. H. M. RASHID, M. S. M. NOORANI AND A. S. SAARI

4.6. Linear Operators on Hilbert Spaces

5 Compact linear operators

Analysis Comprehensive Exam Questions Fall 2008

Selçuk Demir WS 2017 Functional Analysis Homework Sheet

Functional Analysis. Martin Brokate. 1 Normed Spaces 2. 2 Hilbert Spaces The Principle of Uniform Boundedness 32

Functional Analysis II held by Prof. Dr. Moritz Weber in summer 18

Fredholm Theory. April 25, 2018

Some Properties of Closed Range Operators

Available online at J. Math. Comput. Sci. 4 (2014), No. 1, 1-9 ISSN:

Analysis Preliminary Exam Workshop: Hilbert Spaces

08a. Operators on Hilbert spaces. 1. Boundedness, continuity, operator norms

DEFINABLE OPERATORS ON HILBERT SPACES

2. Dual space is essential for the concept of gradient which, in turn, leads to the variational analysis of Lagrange multipliers.

1 Definition and Basic Properties of Compa Operator

Lecture Notes in Functional Analysis

Functional Analysis. Franck Sueur Metric spaces Definitions Completeness Compactness Separability...

INF-SUP CONDITION FOR OPERATOR EQUATIONS

2.2 Annihilators, complemented subspaces

Compact operators on Banach spaces

Problem Set 6: Solutions Math 201A: Fall a n x n,

Spectral Theory, with an Introduction to Operator Means. William L. Green

PROBLEMS. (b) (Polarization Identity) Show that in any inner product space

SPECTRAL THEORY EVAN JENKINS

MTH 503: Functional Analysis

A Brief Introduction to Functional Analysis

C.6 Adjoints for Operators on Hilbert Spaces

Diffun2, Fredholm Operators

LECTURE 7. k=1 (, v k)u k. Moreover r

Functional Analysis, Math 7320 Lecture Notes from August taken by Yaofeng Su

The Dirichlet-to-Neumann operator

CHAPTER 1. Metric Spaces. 1. Definition and examples

A Note on Operators in Hilbert C*-Modules

Functional Analysis Exercise Class

Lecture 5. Ch. 5, Norms for vectors and matrices. Norms for vectors and matrices Why?

Real Analysis, 2nd Edition, G.B.Folland Elements of Functional Analysis

Moore-Penrose Inverse of Product Operators in Hilbert C -Modules

1 Invariant subspaces

Projection Theorem 1

Contents. Preface for the Instructor. Preface for the Student. xvii. Acknowledgments. 1 Vector Spaces 1 1.A R n and C n 2

Introduction to Empirical Processes and Semiparametric Inference Lecture 22: Preliminaries for Semiparametric Inference

CHAPTER 3. Hilbert spaces

Finite-dimensional spaces. C n is the space of n-tuples x = (x 1,..., x n ) of complex numbers. It is a Hilbert space with the inner product

(1) Consider the space S consisting of all continuous real-valued functions on the closed interval [0, 1]. For f, g S, define

UNITIZATIONS AND CROSSED PRODUCTS

Fredholmness of Some Toeplitz Operators

Intertibility and spectrum of the multiplication operator on the space of square-summable sequences

Professor Carl Cowen Math Fall 17 PROBLEMS. (b) (Polarization Identity) Show that in any inner product space

j=1 x j p, if 1 p <, x i ξ : x i < ξ} 0 as p.

REPRESENTATION THEORY WEEK 7

V. SUBSPACES AND ORTHOGONAL PROJECTION

Measure, Integration & Real Analysis

Inner product on B -algebras of operators on a free Banach space over the Levi-Civita field

1 The Projection Theorem

The Gram matrix in inner product modules over C -algebras

Linear Analysis Lecture 5

OPERATOR THEORY - PART 3/3. Contents

Math 5520 Homework 2 Solutions

Recall that any inner product space V has an associated norm defined by

Research Article Bessel and Grüss Type Inequalities in Inner Product Modules over Banach -Algebras

The Residual Spectrum and the Continuous Spectrum of Upper Triangular Operator Matrices

Short note on compact operators - Monday 24 th March, Sylvester Eriksson-Bique

A Spectral Characterization of Closed Range Operators 1

Some Inequalities for Commutators of Bounded Linear Operators in Hilbert Spaces

The best generalised inverse of the linear operator in normed linear space

About Grupo the Mathematical de Investigación Foundation of Quantum Mechanics

The following definition is fundamental.

Problem Set 2: Solutions Math 201A: Fall 2016

David Hilbert was old and partly deaf in the nineteen thirties. Yet being a diligent

FUNCTIONAL ANALYSIS LECTURE NOTES: ADJOINTS IN HILBERT SPACES

BEST APPROXIMATIONS AND ORTHOGONALITIES IN 2k-INNER PRODUCT SPACES. Seong Sik Kim* and Mircea Crâşmăreanu. 1. Introduction

Chapter 4 Euclid Space

SPECTRAL PROPERTIES OF THE LAPLACIAN ON BOUNDED DOMAINS

Homework If the inverse T 1 of a closed linear operator exists, show that T 1 is a closed linear operator.

OPERATOR THEORY ON HILBERT SPACE. Class notes. John Petrovic

von Neumann algebras, II 1 factors, and their subfactors V.S. Sunder (IMSc, Chennai)

Math 7330: Functional Analysis Fall 2005

MA5206 Homework 4. Group 4. April 26, ϕ 1 = 1, ϕ n (x) = 1 n 2 ϕ 1(n 2 x). = 1 and h n C 0. For any ξ ( 1 n, 2 n 2 ), n 3, h n (t) ξ t dt

Functional Analysis F3/F4/NVP (2005) Homework assignment 3

Where is matrix multiplication locally open?

1 Functional Analysis

Functional Analysis Exercise Class

Review 1 Math 321: Linear Algebra Spring 2010

Some Properties in Generalized n-inner Product Spaces

dominant positive-normal. In view of (1), it is very natural to study the properties of positivenormal

Chapter 8 Integral Operators

Sectorial Forms and m-sectorial Operators

Transcription:

Functional Analysis, Math 7321 Lecture Notes from April 0, 2017 taken by Chandi Bhandari Last time:we have completed direct sum decomposition with generalized eigen space. 2. Theorem. Let X be separable Banach space and T B(X) is compact, then (a) If dimx =, 0 σ(t ), if c σ(t )\{0}, then c is an eigen value of finite multiplicity (i.e. eigen space has finite dimension). (b) σ(t ) is an at most countable compact set with 0 being only possible accumulation point. Proof. (a) From the ideal property of compact operators, if T is compact on an infinitedimensional space X, then T is not invertible,because otherwise I = T 1 T would be compact. if c σ(t )\{0}, T ci is not injective or not surjective, hence 0 dim(ker(t ci)) = codim(ran(t ci)) = dim(ker(t ci)) (by duality) = codim(ran(t ci)) < (Here we have used the result from the note on March 23 and 28, 2017) (b) If c σ(t )\{0} then the generalized eigen space N k as in Theorem on lecture note 03/30/2017 is closed and S = (T ci) Nk is nilpotent of index k in B(N k ). For any α 0, from S k = 0, I = α 1 S k + I = α 1 (S k + α k I) Assuming (S αi) 1 is invertible, then (S αi) 1 = α 1 (S k 1 + αs k 2 +... + α k 1 I) Moreover, we see that for α 0, multiplying the right hand side by (S αi) shows that (S αi) is invertible for α 0. So, for z c, letting α = z c 0, we get is invertible. (T zi) Nk = S αi Moreover, by the Theorem on lecture note 03/30/2017, 1

A = (T zi) Mk is invertible, so for α < A 1 1, A αi is invertible. And hence for 0 < z c < A 1 1, (T zi) is invertible on X = N k M k, and consequently, z / σ(t ). Thus, c is an isolated point in σ(t ). By the positive distance between an element in σ(t )\{0} and all other elements, there is an open covers of disjoint balls of σ(t )\{0} and vol( λ σ(t )\{0} B ɛ(λ) (λ)) vol(b 2r(T ) (0)) So the number of such balls is at most countable. We deduced the so-called Fredholm alternative. 2.5 Corollary. Let X be a separable Banach space, T B(X) is compact and c 0 then either (T ci) is invertible or 0 < dim(ker(t ci)) <. Proof. As from the above theorem (Theorem 11.1.2) we have 0 dim(ker(t ci)) = codim(ran(t ci)) < if the codim(ran(t ci)) = 0, then (T ci) is one-one and onto invertible by the open mapping theorem. Otherwise, 0 < dim(ker(t ci)) < from the above theorem (Theorem 11.1.2) because if (T ci) is not invertible then c is an eigen value of finite multiplicity, which means eigen space has finite dimension. In both of the cases, there is a non-trivial closed invariant subspace of T, 2.A Operators on Hilbert Spaces: ker(t ci) or ran(t ci) Given Hilbert Spaces H 1, H 2 and T B(H 1, H 2 ), then the (Hilbert) adjoint T B(H 1, H 2 ) satisfies for each x H 1, y H 2. This is the sesquilinear inner product. Note:(CT + S) = ct + S because T x, y H2 = x, T y H1 x, (ct + S) y = c x, T y + x, S y. 2.6 Definition. Involution: An involution on a Banach Algebra B, is a map i : B B such that for a, b B, c K i(i(a)) = a, i(a + b) = i(a) + i(b) i(ca) = c i(a), (ab) = b a 2

2.7 Definition. A C Algebra is a Banach algebra with an involution i such that i(x)x = x 2 2.8 Remarks. For C Algebra, i(x) = x because x 2 = i(x)x i(x) x Thus, we have And, Moreover, if x n x then So, i is continuous. x i(x) i(x) i(i(x)) = x x n x = i(x n ) i(x) 0. 2.9 Theorem. Let H 1, H 2, be Hilbert spaces, then T B(H 1, H 2 ) satisfies: T T = T 2. Proof. We recall So, Conversely, for x, with x 1 T = sup T x x 1 = sup T x, y x, y 1 = sup x, T y x, y 1 = sup T y, x x, y 1 = T T T T T T x 2 = T x, T x = T T x, x T T x x (By Cauchy Schwarz inequality) T T x x = T T x 2 Thus, we have now T 2 T T From above two case, we conclude that T T = T 2. 3

Polarization identity: Let x denotes the norm of vector x and x, y be the inner product of vectors x, y and let V be a vector space then the polarization identity to define x, y : If V = R, x, y = 1 ( x + y 2 x y 2) x, y V. If V = C, x, y = 1 ( x + y 2 x y 2 + ı x + ıy 2 ı x ıy 2), x, y V. 2.50 Lemma. Given T B(H), H be a complex Hilbert space then T = 0 iff T x, x = 0. Proof. Let T is characterized by values T x, y for x, y H. Then by using the polarization identity we have x, y H, T x, y = 1 [ T (x+y), (x+y) T (x y), (x y) +i T (x+iy), (x+iy) i T (x iy), (x iy) )]. Since T is linear then we have, T x, y = 1 [ T x, x + T y, x + T x, y + T y, y T x, x + T y, x + T x, y T y, y + i( T x, x + i T y, x i T x, y + T y, y ) i( T x, x + i T y, x i T x, y + T y, y )] Which means, T x, y = 1 [ T x, x + T y, x + T x, y + T y, y T x, x + T y, x + T x, y T y, y + i T x, x T y, x + T x, y + i T y, y ) i T x, x + T y, x T x, y i T y, y ] Thus, we get This implies, Substituting y = T x we get, T x, y = 1 [2 T x, y + 2 T y, x ] = 1 [ T x, y + T y, x ] 2 T x, y = 0 for all x, y H T x, T x = 0 for all x H. T x 2 = 0 for all x H. Thus, T = 0. Conversly, to show that T x, x = 0 when T = 0, we have from the polarization identity T x, y = 1 [ T (x+y), (x+y) T (x y), (x y) +i T (x+iy), (x+iy) i T (x iy), (x iy) )]. Substituting y = x above we get and by linearity T we get T x, x = 1 [ T (x + x), (x + x) T (x x), (x x) + i T (x + ix), (x + ix) i T (x ix), (x ix) )] = 1 [ T x, x + T x, x + T x, x + T x, x T x, x + T x, x + T x, x T x, x + i T x, x T x, x + T x, x + i T x, x ) i T x, x + T y, x T x, x i T x, x ]

Since T = 0 implies T x, x = 0 2.B Orthogonal Projection: 2.51 Definition. A projection P = P 2 in B(H) is orthogonal if ker(p ) ran(p ). 2.52 Theorem. If P is a non-zero projection, then the following are equivalent (a) P is orthogonal (b) P = P (c) P = 1 Proof. First, (a) = (b), If P is orthogonal then, ran(p ) ran(i P ). Thus, for each x H, P x, (I P )x = 0. = (I P ) P x, x = 0. = (I P ) P = 0. = P = P P Thus, P = (P P ) = P P = P P = P from above relation Now, to show (b) = (c) since we have P = P which gives P x 2 = P x, P x = P P x, x = P 2 x, x because P = P = P x, x because P 2 = P by defination P x x by Cauchy Schwarz Inequality Thus, P 1 by taking max X 1. Choosing x ran(p )\{0} gives P x = x then combining both the results we get, P = 1. Finally, to show (c) = (a) we show this by contrapositive, for this assume P is not orthogonal. Then there are x, y H with x = y = 1, and x ran(p ), y ker(p ), x, y 0 WLoG, assume x, y = t < 0 otherwise replace x by λx, λ = 1. 5

Let z = x + ty then z 2 = x 2 + 2t x, y + t 2 y 2 = 1 t 2 because x = 1 = y and x, y = t < 1 = x 2 = P z 2 This shows that This implies z 2 < P z 2 P > 1 Hence by contrapositive we got that if P = 1 = P is orthogonal. 6