Spectral Theory for Bounded Operators on Hilbert Space
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Functional Analysis Lecture Notes Chapter 2. Operators on Hilbert Spaces
FUNCTIONAL ANALYSIS LECTURE NOTES CHAPTER 2. OPERATORS ON HILBERT SPACES CHRISTOPHER HEIL 1. Elementary Properties and Examples First recall the basic definitions regarding operators. Definition 1.1 (Continuous and Bounded Operators). Let X, Y be normed linear spaces, and let L: X Y be a linear operator. ! (a) L is continuous at a point f X if f f in X implies Lf Lf in Y . 2 n ! n ! (b) L is continuous if it is continuous at every point, i.e., if fn f in X implies Lfn Lf in Y for every f. ! ! (c) L is bounded if there exists a finite K 0 such that ≥ f X; Lf K f : 8 2 k k ≤ k k Note that Lf is the norm of Lf in Y , while f is the norm of f in X. k k k k (d) The operator norm of L is L = sup Lf : k k kfk=1 k k (e) We let (X; Y ) denote the set of all bounded linear operators mapping X into Y , i.e., B (X; Y ) = L: X Y : L is bounded and linear : B f ! g If X = Y = X then we write (X) = (X; X). B B (f) If Y = F then we say that L is a functional. The set of all bounded linear functionals on X is the dual space of X, and is denoted X0 = (X; F) = L: X F : L is bounded and linear : B f ! g We saw in Chapter 1 that, for a linear operator, boundedness and continuity are equivalent. -
Quantum Mechanics, Schrodinger Operators and Spectral Theory
Quantum mechanics, SchrÄodingeroperators and spectral theory. Spectral theory of SchrÄodinger operators has been my original ¯eld of expertise. It is a wonderful mix of functional analy- sis, PDE and Fourier analysis. In quantum mechanics, every physical observable is described by a self-adjoint operator - an in¯nite dimensional symmetric matrix. For example, ¡¢ is a self-adjoint operator in L2(Rd) when de¯ned on an appropriate domain (Sobolev space H2). In quantum mechanics it corresponds to a free particle - just traveling in space. What does it mean, exactly? Well, in quantum mechanics, position of a particle is described by a wave 2 d function, Á(x; t) 2 L (R ): The physical meaningR of the wave function is that the probability 2 to ¯nd it in a region at time t is equal to jÁ(x; t)j dx: You can't know for sure where the particle is for sure. If initially the wave function is given by Á(x; 0) = Á0(x); the SchrÄodinger ¡i¢t equation says that its evolution is given by Á(x; t) = e Á0: But how to compute what is e¡i¢t? This is where Fourier transform comes in handy. Di®erentiation becomes multiplication on the Fourier transform side, and so Z ¡i¢t ikx¡ijkj2t ^ e Á0(x) = e Á0(k) dk; Rd R ^ ¡ikx where Á0(k) = Rd e Á0(x) dx is the Fourier transform of Á0: I omitted some ¼'s since they do not change the picture. Stationary phase methods lead to very precise estimates on free SchrÄodingerevolution. -
Operator Algebras: an Informal Overview 3
OPERATOR ALGEBRAS: AN INFORMAL OVERVIEW FERNANDO LLEDO´ Contents 1. Introduction 1 2. Operator algebras 2 2.1. What are operator algebras? 2 2.2. Differences and analogies between C*- and von Neumann algebras 3 2.3. Relevance of operator algebras 5 3. Different ways to think about operator algebras 6 3.1. Operator algebras as non-commutative spaces 6 3.2. Operator algebras as a natural universe for spectral theory 6 3.3. Von Neumann algebras as symmetry algebras 7 4. Some classical results 8 4.1. Operator algebras in functional analysis 8 4.2. Operator algebras in harmonic analysis 10 4.3. Operator algebras in quantum physics 11 References 13 Abstract. In this article we give a short and informal overview of some aspects of the theory of C*- and von Neumann algebras. We also mention some classical results and applications of these families of operator algebras. 1. Introduction arXiv:0901.0232v1 [math.OA] 2 Jan 2009 Any introduction to the theory of operator algebras, a subject that has deep interrelations with many mathematical and physical disciplines, will miss out important elements of the theory, and this introduction is no ex- ception. The purpose of this article is to give a brief and informal overview on C*- and von Neumann algebras which are the main actors of this summer school. We will also mention some of the classical results in the theory of operator algebras that have been crucial for the development of several areas in mathematics and mathematical physics. Being an overview we can not provide details. Precise definitions, statements and examples can be found in [1] and references cited therein. -
The Notion of Observable and the Moment Problem for ∗-Algebras and Their GNS Representations
The notion of observable and the moment problem for ∗-algebras and their GNS representations Nicol`oDragoa, Valter Morettib Department of Mathematics, University of Trento, and INFN-TIFPA via Sommarive 14, I-38123 Povo (Trento), Italy. [email protected], [email protected] February, 17, 2020 Abstract We address some usually overlooked issues concerning the use of ∗-algebras in quantum theory and their physical interpretation. If A is a ∗-algebra describing a quantum system and ! : A ! C a state, we focus in particular on the interpretation of !(a) as expectation value for an algebraic observable a = a∗ 2 A, studying the problem of finding a probability n measure reproducing the moments f!(a )gn2N. This problem enjoys a close relation with the selfadjointness of the (in general only symmetric) operator π!(a) in the GNS representation of ! and thus it has important consequences for the interpretation of a as an observable. We n provide physical examples (also from QFT) where the moment problem for f!(a )gn2N does not admit a unique solution. To reduce this ambiguity, we consider the moment problem n ∗ (a) for the sequences f!b(a )gn2N, being b 2 A and !b(·) := !(b · b). Letting µ!b be a n solution of the moment problem for the sequence f!b(a )gn2N, we introduce a consistency (a) relation on the family fµ!b gb2A. We prove a 1-1 correspondence between consistent families (a) fµ!b gb2A and positive operator-valued measures (POVM) associated with the symmetric (a) operator π!(a). In particular there exists a unique consistent family of fµ!b gb2A if and only if π!(a) is maximally symmetric. -
Asymptotic Spectral Measures: Between Quantum Theory and E
Asymptotic Spectral Measures: Between Quantum Theory and E-theory Jody Trout Department of Mathematics Dartmouth College Hanover, NH 03755 Email: [email protected] Abstract— We review the relationship between positive of classical observables to the C∗-algebra of quantum operator-valued measures (POVMs) in quantum measurement observables. See the papers [12]–[14] and theB books [15], C∗ E theory and asymptotic morphisms in the -algebra -theory of [16] for more on the connections between operator algebra Connes and Higson. The theory of asymptotic spectral measures, as introduced by Martinez and Trout [1], is integrally related K-theory, E-theory, and quantization. to positive asymptotic morphisms on locally compact spaces In [1], Martinez and Trout showed that there is a fundamen- via an asymptotic Riesz Representation Theorem. Examples tal quantum-E-theory relationship by introducing the concept and applications to quantum physics, including quantum noise of an asymptotic spectral measure (ASM or asymptotic PVM) models, semiclassical limits, pure spin one-half systems and quantum information processing will also be discussed. A~ ~ :Σ ( ) { } ∈(0,1] →B H I. INTRODUCTION associated to a measurable space (X, Σ). (See Definition 4.1.) In the von Neumann Hilbert space model [2] of quantum Roughly, this is a continuous family of POV-measures which mechanics, quantum observables are modeled as self-adjoint are “asymptotically” projective (or quasiprojective) as ~ 0: → operators on the Hilbert space of states of the quantum system. ′ ′ A~(∆ ∆ ) A~(∆)A~(∆ ) 0 as ~ 0 The Spectral Theorem relates this theoretical view of a quan- ∩ − → → tum observable to the more operational one of a projection- for certain measurable sets ∆, ∆′ Σ. -
ASYMPTOTICALLY ISOSPECTRAL QUANTUM GRAPHS and TRIGONOMETRIC POLYNOMIALS. Pavel Kurasov, Rune Suhr
ISSN: 1401-5617 ASYMPTOTICALLY ISOSPECTRAL QUANTUM GRAPHS AND TRIGONOMETRIC POLYNOMIALS. Pavel Kurasov, Rune Suhr Research Reports in Mathematics Number 2, 2018 Department of Mathematics Stockholm University Electronic version of this document is available at http://www.math.su.se/reports/2018/2 Date of publication: Maj 16, 2018. 2010 Mathematics Subject Classification: Primary 34L25, 81U40; Secondary 35P25, 81V99. Keywords: Quantum graphs, almost periodic functions. Postal address: Department of Mathematics Stockholm University S-106 91 Stockholm Sweden Electronic addresses: http://www.math.su.se/ [email protected] Asymptotically isospectral quantum graphs and generalised trigonometric polynomials Pavel Kurasov and Rune Suhr Dept. of Mathematics, Stockholm Univ., 106 91 Stockholm, SWEDEN [email protected], [email protected] Abstract The theory of almost periodic functions is used to investigate spectral prop- erties of Schr¨odinger operators on metric graphs, also known as quantum graphs. In particular we prove that two Schr¨odingeroperators may have asymptotically close spectra if and only if the corresponding reference Lapla- cians are isospectral. Our result implies that a Schr¨odingeroperator is isospectral to the standard Laplacian on a may be different metric graph only if the potential is identically equal to zero. Keywords: Quantum graphs, almost periodic functions 2000 MSC: 34L15, 35R30, 81Q10 Introduction. The current paper is devoted to the spectral theory of quantum graphs, more precisely to the direct and inverse spectral theory of Schr¨odingerop- erators on metric graphs [3, 20, 24]. Such operators are defined by three parameters: a finite compact metric graph Γ; • a real integrable potential q L (Γ); • ∈ 1 vertex conditions, which can be parametrised by unitary matrices S. -
Functional Analysis (WS 19/20), Problem Set 8 (Spectrum And
Functional Analysis (WS 19/20), Problem Set 8 (spectrum and adjoints on Hilbert spaces)1 In what follows, let H be a complex Hilbert space. Let T : H ! H be a bounded linear operator. We write T ∗ : H ! H for adjoint of T dened with hT x; yi = hx; T ∗yi: This operator exists and is uniquely determined by Riesz Representation Theorem. Spectrum of T is the set σ(T ) = fλ 2 C : T − λI does not have a bounded inverseg. Resolvent of T is the set ρ(T ) = C n σ(T ). Basic facts on adjoint operators R1. | Adjoint T ∗ exists and is uniquely determined. R2. | Adjoint T ∗ is a bounded linear operator and kT ∗k = kT k. Moreover, kT ∗T k = kT k2. R3. | Taking adjoints is an involution: (T ∗)∗ = T . R4. Adjoints commute with the sum: ∗ ∗ ∗. | (T1 + T2) = T1 + T2 ∗ ∗ R5. | For λ 2 C we have (λT ) = λ T . R6. | Let T be a bounded invertible operator. Then, (T ∗)−1 = (T −1)∗. R7. Let be bounded operators. Then, ∗ ∗ ∗. | T1;T2 (T1 T2) = T2 T1 R8. | We have relationship between kernel and image of T and T ∗: ker T ∗ = (im T )?; (ker T ∗)? = im T It will be helpful to prove that if M ⊂ H is a linear subspace, then M = M ??. Btw, this covers all previous results like if N is a nite dimensional linear subspace then N = N ?? (because N is closed). Computation of adjoints n n ∗ M1. ,Let A : R ! R be a complex matrix. Find A . 2 M2. | ,Let H = l (Z). For x = (:::; x−2; x−1; x0; x1; x2; :::) 2 H we dene the right shift operator −1 ∗ with (Rx)k = xk−1: Find kRk, R and R . -
Lecture Notes on Spectra and Pseudospectra of Matrices and Operators
Lecture Notes on Spectra and Pseudospectra of Matrices and Operators Arne Jensen Department of Mathematical Sciences Aalborg University c 2009 Abstract We give a short introduction to the pseudospectra of matrices and operators. We also review a number of results concerning matrices and bounded linear operators on a Hilbert space, and in particular results related to spectra. A few applications of the results are discussed. Contents 1 Introduction 2 2 Results from linear algebra 2 3 Some matrix results. Similarity transforms 7 4 Results from operator theory 10 5 Pseudospectra 16 6 Examples I 20 7 Perturbation Theory 27 8 Applications of pseudospectra I 34 9 Applications of pseudospectra II 41 10 Examples II 43 1 11 Some infinite dimensional examples 54 1 Introduction We give an introduction to the pseudospectra of matrices and operators, and give a few applications. Since these notes are intended for a wide audience, some elementary concepts are reviewed. We also note that one can understand the main points concerning pseudospectra already in the finite dimensional case. So the reader not familiar with operators on a separable Hilbert space can assume that the space is finite dimensional. Let us briefly outline the contents of these lecture notes. In Section 2 we recall some results from linear algebra, mainly to fix notation, and to recall some results that may not be included in standard courses on linear algebra. In Section 4 we state some results from the theory of bounded operators on a Hilbert space. We have decided to limit the exposition to the case of bounded operators. -
Quantum Dynamics
Quantum Dynamics William G. Faris August 12, 1992 Contents I Hilbert Space 5 1 Introduction 7 1.1 Quantum mechanics . 7 1.2 The quantum scale . 8 1.2.1 Planck's constant . 8 1.2.2 Diffusion . 9 1.2.3 Speed . 9 1.2.4 Length . 10 1.2.5 Energy . 10 1.2.6 Compressibility . 10 1.2.7 Frequency . 11 1.2.8 Other length scales . 11 1.3 The Schr¨odingerequation . 11 1.3.1 The equation . 11 1.3.2 Density and current . 13 1.3.3 Osmotic and current velocity . 14 1.3.4 Momentum . 15 1.3.5 Energy . 15 1.4 The uncertainty principle . 17 1.5 Quantum stability . 18 2 Hilbert Space 21 2.1 Definition . 21 2.2 Self-duality . 24 2.3 Projections . 26 2.4 Operators . 27 2.5 Bounded operators . 28 1 2 CONTENTS 3 Function Spaces 31 3.1 Integration . 31 3.2 Function spaces . 34 3.3 Convergence . 36 3.4 Integral operators . 37 4 Bases 41 4.1 Discrete bases . 41 4.2 Continuous bases . 42 5 Spectral Representations 49 5.1 Multiplication operators . 49 5.2 Spectral representations . 50 5.3 Translation . 52 5.4 Approximate delta functions . 53 5.5 The Fourier transform . 54 5.6 Free motion . 57 5.6.1 Diffusion . 57 5.6.2 Oscillation . 58 6 The Harmonic Oscillator 61 6.1 The classical harmonic oscillator . 61 6.2 The one dimensional quantum harmonic oscillator . 62 6.3 The Fourier transform . 65 6.4 Density theorems . 65 6.5 The isotropic quantum harmonic oscillator . -
Notes on Von Neumann Algebras
Notes on von Neumann algebras Jesse Peterson April 5, 2013 2 Chapter 1 Spectral theory If A is a complex unital algebra then we denote by G(A) the set of elements which have a two sided inverse. If x 2 A, the spectrum of x is σA(x) = fλ 2 C j x − λ 62 G(A)g: The complement of the spectrum is called the resolvent and denoted ρA(x). Proposition 1.0.1. Let A be a unital algebra over C, and consider x; y 2 A. Then σA(xy) [ f0g = σA(yx) [ f0g. Proof. If 1 − xy 2 G(A) then we have (1 − yx)(1 + y(1 − xy)−1x) = 1 − yx + y(1 − xy)−1x − yxy(1 − xy)−1x = 1 − yx + y(1 − xy)(1 − xy)−1x = 1: Similarly, we have (1 + y(1 − xy)−1x)(1 − yx) = 1; and hence 1 − yx 2 G(A). Knowing the formula for the inverse beforehand of course made the proof of the previous proposition quite a bit easier. But this formula is quite natural to consider. Indeed, if we just consider formal power series then we have 1 1 X X (1 − yx)−1 = (yx)k = 1 + y( (xy)k)x = 1 + y(1 − xy)−1x: k=0 k=0 1.1 Banach and C∗-algebras A Banach algebra is a Banach space A, which is also an algebra such that kxyk ≤ kxkkyk: 3 4 CHAPTER 1. SPECTRAL THEORY A Banach algebra A is involutive if it possesses an anti-linear involution ∗, such that kx∗k = kxk, for all x 2 A. -
Notes on Von Neumann Algebras
Von Neumann Algebras. Vaughan F.R. Jones 1 October 1, 2009 1Supported in part by NSF Grant DMS93–22675, the Marsden fund UOA520, and the Swiss National Science Foundation. 2 Chapter 1 Introduction. The purpose of these notes is to provide a rapid introduction to von Neumann algebras which gets to the examples and active topics with a minimum of technical baggage. In this sense it is opposite in spirit from the treatises of Dixmier [], Takesaki[], Pedersen[], Kadison-Ringrose[], Stratila-Zsido[]. The philosophy is to lavish attention on a few key results and examples, and we prefer to make simplifying assumptions rather than go for the most general case. Thus we do not hesitate to give several proofs of a single result, or repeat an argument with different hypotheses. The notes are built around semester- long courses given at UC Berkeley though they contain more material than could be taught in a single semester. The notes are informal and the exercises are an integral part of the ex- position. These exercises are vital and mostly intended to be easy. 3 4 Chapter 2 Background and Prerequisites 2.1 Hilbert Space A Hilbert Space is a complex vector space H with inner product h; i : HxH! C which is linear in the first variable, satisfies hξ; ηi = hη; ξi, is positive definite, i.e. hξ; ξi > 0 for ξ 6= 0, and is complete for the norm defined by test jjξjj = phξ; ξi. Exercise 2.1.1. Prove the parallelogram identity : jjξ − ηjj2 + jjξ + ηjj2 = 2(jjξjj2 + jjηjj2) and the Cauchy-Schwartz inequality: jhξ; ηij ≤ jjξjj jjηjj: Theorem 2.1.2. -
Spectrum (Functional Analysis) - Wikipedia, the Free Encyclopedia
Spectrum (functional analysis) - Wikipedia, the free encyclopedia http://en.wikipedia.org/wiki/Spectrum_(functional_analysis) Spectrum (functional analysis) From Wikipedia, the free encyclopedia In functional analysis, the concept of the spectrum of a bounded operator is a generalisation of the concept of eigenvalues for matrices. Specifically, a complex number λ is said to be in the spectrum of a bounded linear operator T if λI − T is not invertible, where I is the identity operator. The study of spectra and related properties is known as spectral theory, which has numerous applications, most notably the mathematical formulation of quantum mechanics. The spectrum of an operator on a finite-dimensional vector space is precisely the set of eigenvalues. However an operator on an infinite-dimensional space may have additional elements in its spectrum, and may have no eigenvalues. For example, consider the right shift operator R on the Hilbert space ℓ2, This has no eigenvalues, since if Rx=λx then by expanding this expression we see that x1=0, x2=0, etc. On the other hand 0 is in the spectrum because the operator R − 0 (i.e. R itself) is not invertible: it is not surjective since any vector with non-zero first component is not in its range. In fact every bounded linear operator on a complex Banach space must have a non-empty spectrum. The notion of spectrum extends to densely-defined unbounded operators. In this case a complex number λ is said to be in the spectrum of such an operator T:D→X (where D is dense in X) if there is no bounded inverse (λI − T)−1:X→D.