Banach Algebras and Spectral Theory Lecture 1 August 24Th. a Broad
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An Elementary Proof of the Spectral Radius Formula for Matrices
AN ELEMENTARY PROOF OF THE SPECTRAL RADIUS FORMULA FOR MATRICES JOEL A. TROPP Abstract. We present an elementary proof that the spectral ra- dius of a matrix A may be obtained using the formula 1 ρ(A) = lim kAnk =n; n!1 where k · k represents any matrix norm. 1. Introduction It is a well-known fact from the theory of Banach algebras that the spectral radius of any element A is given by the formula ρ(A) = lim kAnk1=n: (1.1) n!1 For a matrix, the spectrum is just the collection of eigenvalues, so this formula yields a technique for estimating for the top eigenvalue. The proof of Equation 1.1 is beautiful but advanced. See, for exam- ple, Rudin's treatment in his Functional Analysis. It turns out that elementary techniques suffice to develop the formula for matrices. 2. Preliminaries For completeness, we shall briefly introduce the major concepts re- quired in the proof. It is expected that the reader is already familiar with these ideas. 2.1. Norms. A norm is a mapping k · k from a vector space X into the nonnegative real numbers R+ which has three properties: (1) kxk = 0 if and only if x = 0; (2) kαxk = jαj kxk for any scalar α and vector x; and (3) kx + yk ≤ kxk + kyk for any vectors x and y. The most fundamental example of a norm is the Euclidean norm k·k2 which corresponds to the standard topology on Rn. It is defined by 2 2 2 kxk2 = k(x1; x2; : : : ; xn)k2 = x1 + x2 + · · · + xn: Date: 30 November 2001. -
Noncommutative Uniform Algebras
Noncommutative Uniform Algebras Mati Abel and Krzysztof Jarosz Abstract. We show that a real Banach algebra A such that a2 = a 2 , for a A is a subalgebra of the algebra C (X) of continuous quaternion valued functions on a compact setk kX. ∈ H ° ° ° ° 1. Introduction A well known Hirschfeld-Zelazkoú Theorem [5](seealso[7]) states that for a complex Banach algebra A the condition (1.1) a2 = a 2 , for a A k k ∈ implies that (i) A is commutative, and further° ° implies that (ii) A must be of a very speciÞc form, namely it ° ° must be isometrically isomorphic with a uniformly closed subalgebra of CC (X). We denote here by CC (X)the complex Banach algebra of all continuous functions on a compact set X. The obvious question about the validity of the same conclusion for real Banach algebras is immediately dismissed with an obvious counterexample: the non commutative algebra H of quaternions. However it turns out that the second part (ii) above is essentially also true in the real case. We show that the condition (1.1) implies, for a real Banach algebra A,thatA is isometrically isomorphic with a subalgebra of CH (X) - the algebra of continuous quaternion valued functions on acompactsetX. That result is in fact a consequence of a theorem by Aupetit and Zemanek [1]. We will also present several related results and corollaries valid for real and complex Banach and topological algebras. To simplify the notation we assume that the algebras under consideration have units, however, like in the case of the Hirschfeld-Zelazkoú Theorem, the analogous results can be stated for none unital algebras as one can formally add aunittosuchanalgebra. -
Weak and Norm Approximate Identities Are Different
Pacific Journal of Mathematics WEAK AND NORM APPROXIMATE IDENTITIES ARE DIFFERENT CHARLES ALLEN JONES AND CHARLES DWIGHT LAHR Vol. 72, No. 1 January 1977 PACIFIC JOURNAL OF MATHEMATICS Vol. 72, No. 1, 1977 WEAK AND NORM APPROXIMATE IDENTITIES ARE DIFFERENT CHARLES A. JONES AND CHARLES D. LAHR An example is given of a convolution measure algebra which has a bounded weak approximate identity, but no norm approximate identity. 1* Introduction* Let A be a commutative Banach algebra, Ar the dual space of A, and ΔA the maximal ideal space of A. A weak approximate identity for A is a net {e(X):\eΛ} in A such that χ(e(λ)α) > χ(α) for all αei, χ e A A. A norm approximate identity for A is a net {e(λ):λeΛ} in A such that ||β(λ)α-α|| >0 for all aeA. A net {e(X):\eΛ} in A is bounded and of norm M if there exists a positive number M such that ||e(λ)|| ^ M for all XeΛ. It is well known that if A has a bounded weak approximate identity for which /(e(λ)α) —>/(α) for all feA' and αeA, then A has a bounded norm approximate identity [1, Proposition 4, page 58]. However, the situation is different if weak convergence is with re- spect to ΔA and not A'. An example is given in § 2 of a Banach algebra A which has a weak approximate identity, but does not have a norm approximate identity. This algebra provides a coun- terexample to a theorem of J. -
Topological Vector Spaces and Algebras
Joseph Muscat 2015 1 Topological Vector Spaces and Algebras [email protected] 1 June 2016 1 Topological Vector Spaces over R or C Recall that a topological vector space is a vector space with a T0 topology such that addition and the field action are continuous. When the field is F := R or C, the field action is called scalar multiplication. Examples: A N • R , such as sequences R , with pointwise convergence. p • Sequence spaces ℓ (real or complex) with topology generated by Br = (a ): p a p < r , where p> 0. { n n | n| } p p p p • LebesgueP spaces L (A) with Br = f : A F, measurable, f < r (p> 0). { → | | } R p • Products and quotients by closed subspaces are again topological vector spaces. If π : Y X are linear maps, then the vector space Y with the ini- i → i tial topology is a topological vector space, which is T0 when the πi are collectively 1-1. The set of (continuous linear) morphisms is denoted by B(X, Y ). The mor- phisms B(X, F) are called ‘functionals’. +, , Finitely- Locally Bounded First ∗ → Generated Separable countable Top. Vec. Spaces ///// Lp 0 <p< 1 ℓp[0, 1] (ℓp)N (ℓp)R p ∞ N n R 2 Locally Convex ///// L p > 1 L R , C(R ) R pointwise, ℓweak Inner Product ///// L2 ℓ2[0, 1] ///// ///// Locally Compact Rn ///// ///// ///// ///// 1. A set is balanced when λ 6 1 λA A. | | ⇒ ⊆ (a) The image and pre-image of balanced sets are balanced. ◦ (b) The closure and interior are again balanced (if A 0; since λA = (λA)◦ A◦); as are the union, intersection, sum,∈ scaling, T and prod- uct A ⊆B of balanced sets. -
Regularity Conditions for Banach Function Algebras
Regularity conditions for Banach function algebras Dr J. F. Feinstein University of Nottingham June 2009 1 1 Useful sources A very useful text for the material in this mini-course is the book Banach Algebras and Automatic Continuity by H. Garth Dales, London Mathematical Society Monographs, New Series, Volume 24, The Clarendon Press, Oxford, 2000. In particular, many of the examples and conditions discussed here may be found in Chapter 4 of that book. We shall refer to this book throughout as the book of Dales. Most of my e-prints are available from www.maths.nott.ac.uk/personal/jff/Papers Several of my research and teaching presentations are available from www.maths.nott.ac.uk/personal/jff/Beamer 2 2 Introduction to normed algebras and Banach algebras 2.1 Some problems to think about Those who have seen much of this introductory material before may wish to think about some of the following problems. We shall return to these problems at suitable points in this course. Problem 2.1.1 (Easy using standard theory!) It is standard that the set of all rational functions (quotients of polynomials) with complex coefficients is a field: this is a special case of the “field of fractions" of an integral domain. Question: Is there an algebra norm on this field (regarded as an algebra over C)? 3 Problem 2.1.2 (Very hard!) Does there exist a pair of sequences (λn), (an) of non-zero complex numbers such that (i) no two of the an are equal, P1 (ii) n=1 jλnj < 1, (iii) janj < 2 for all n 2 N, and yet, (iv) for all z 2 C, 1 X λn exp (anz) = 0? n=1 Gap to fill in 4 Problem 2.1.3 Denote by C[0; 1] the \trivial" uniform algebra of all continuous, complex-valued functions on [0; 1]. -
Stat 309: Mathematical Computations I Fall 2018 Lecture 4
STAT 309: MATHEMATICAL COMPUTATIONS I FALL 2018 LECTURE 4 1. spectral radius • matrix 2-norm is also known as the spectral norm • name is connected to the fact that the norm is given by the square root of the largest eigenvalue of ATA, i.e., largest singular value of A (more on this later) n×n • in general, the spectral radius ρ(A) of a matrix A 2 C is defined in terms of its largest eigenvalue ρ(A) = maxfjλij : Axi = λixi; xi 6= 0g n×n • note that the spectral radius does not define a norm on C • for example the non-zero matrix 0 1 J = 0 0 has ρ(J) = 0 since both its eigenvalues are 0 • there are some relationships between the norm of a matrix and its spectral radius • the easiest one is that ρ(A) ≤ kAk n for any matrix norm that satisfies the inequality kAxk ≤ kAkkxk for all x 2 C , i.e., consistent norm { here's a proof: Axi = λixi taking norms, kAxik = kλixik = jλijkxik therefore kAxik jλij = ≤ kAk kxik since this holds for any eigenvalue of A, it follows that maxjλij = ρ(A) ≤ kAk i { in particular this is true for any operator norm { this is in general not true for norms that do not satisfy the consistency inequality kAxk ≤ kAkkxk (thanks to Likai Chen for pointing out); for example the matrix " p1 p1 # A = 2 2 p1 − p1 2 2 p is orthogonal and therefore ρ(A) = 1 but kAkH;1 = 1= 2 and so ρ(A) > kAkH;1 { exercise: show that any eigenvalue of a unitary or an orthogonal matrix must have absolute value 1 Date: October 10, 2018, version 1.0. -
Chapter 2 C -Algebras
Chapter 2 C∗-algebras This chapter is mainly based on the first chapters of the book [Mur90]. Material bor- rowed from other references will be specified. 2.1 Banach algebras Definition 2.1.1. A Banach algebra C is a complex vector space endowed with an associative multiplication and with a norm k · k which satisfy for any A; B; C 2 C and α 2 C (i) (αA)B = α(AB) = A(αB), (ii) A(B + C) = AB + AC and (A + B)C = AC + BC, (iii) kABk ≤ kAkkBk (submultiplicativity) (iv) C is complete with the norm k · k. One says that C is abelian or commutative if AB = BA for all A; B 2 C . One also says that C is unital if 1 2 C , i.e. if there exists an element 1 2 C with k1k = 1 such that 1B = B = B1 for all B 2 C . A subalgebra J of C is a vector subspace which is stable for the multiplication. If J is norm closed, it is a Banach algebra in itself. Examples 2.1.2. (i) C, Mn(C), B(H), K (H) are Banach algebras, where Mn(C) denotes the set of n × n-matrices over C. All except K (H) are unital, and K (H) is unital if H is finite dimensional. (ii) If Ω is a locally compact topological space, C0(Ω) and Cb(Ω) are abelian Banach algebras, where Cb(Ω) denotes the set of all bounded and continuous complex func- tions from Ω to C, and C0(Ω) denotes the subset of Cb(Ω) of functions f which vanish at infinity, i.e. -
Hilbert's Projective Metric in Quantum Information Theory D. Reeb, M. J
Hilbert’s projective metric in quantum information theory D. Reeb, M. J. Kastoryano and M. M. Wolf REPORT No. 31, 2010/2011, fall ISSN 1103-467X ISRN IML-R- -31-10/11- -SE+fall HILBERT’S PROJECTIVE METRIC IN QUANTUM INFORMATION THEORY David Reeb,∗ Michael J. Kastoryano,† and Michael M. Wolf‡ Department of Mathematics, Technische Universit¨at M¨unchen, 85748 Garching, Germany Niels Bohr Institute, University of Copenhagen, 2100 Copenhagen, Denmark (Dated: August 15, 2011) We introduce and apply Hilbert’s projective metric in the context of quantum information theory. The metric is induced by convex cones such as the sets of positive, separable or PPT operators. It provides bounds on measures for statistical distinguishability of quantum states and on the decrease of entanglement under LOCC protocols or other cone-preserving operations. The results are formulated in terms of general cones and base norms and lead to contractivity bounds for quantum channels, for instance improving Ruskai’s trace-norm contraction inequality. A new duality between distinguishability measures and base norms is provided. For two given pairs of quantum states we show that the contraction of Hilbert’s projective metric is necessary and sufficient for the existence of a probabilistic quantum operation that maps one pair onto the other. Inequalities between Hilbert’s projective metric and the Chernoff bound, the fidelity and various norms are proven. Contents I. Introduction 2 II. Basic concepts 3 III. Base norms and negativities 7 IV. Contractivity properties of positive maps 9 V. Distinguishability measures 14 VI. Fidelity and Chernoff bound inequalities 21 VII. Operational interpretation 24 VIII. -
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. -
Operator Algebras with Contractive Approximate Identities
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Journal of Functional Analysis 261 (2011) 188–217 www.elsevier.com/locate/jfa Operator algebras with contractive approximate identities David P. Blecher a,∗,1, Charles John Read b a Department of Mathematics, University of Houston, Houston, TX 77204-3008, United States b Department of Pure Mathematics, University of Leeds, Leeds LS2 9JT, England, United Kingdom Received 15 November 2010; accepted 24 February 2011 Available online 21 March 2011 Communicated by S. Vaes Abstract We give several applications of a recent theorem of the second author, which solved a conjecture of the first author with Hay and Neal, concerning contractive approximate identities; and another of Hay from the theory of noncommutative peak sets, thereby putting the latter theory on a much firmer foundation. From this theorem it emerges there is a surprising amount of positivity present in any operator algebras with contractive approximate identity. We exploit this to generalize several results previously available only for ∗ C -algebras, and we give many other applications. © 2011 Elsevier Inc. All rights reserved. Keywords: Operator algebras; One-sided ideals; Hereditary subalgebra; Approximate identity; Peak set; Pseudo-invertible elements; Completely positive operator 1. Introduction An operator algebra is a closed subalgebra of B(H), for a Hilbert space H . We recall that by a theorem due to Ralf Meyer, every operator algebra A has a unique unitization A1 (see [30] or [10, Section 2.1]). Below 1 always refers to the identity of A1 if A has no identity. -
Class Notes, Functional Analysis 7212
Class notes, Functional Analysis 7212 Ovidiu Costin Contents 1 Banach Algebras 2 1.1 The exponential map.....................................5 1.2 The index group of B = C(X) ...............................6 1.2.1 p1(X) .........................................7 1.3 Multiplicative functionals..................................7 1.3.1 Multiplicative functionals on C(X) .........................8 1.4 Spectrum of an element relative to a Banach algebra.................. 10 1.5 Examples............................................ 19 1.5.1 Trigonometric polynomials............................. 19 1.6 The Shilov boundary theorem................................ 21 1.7 Further examples....................................... 21 1.7.1 The convolution algebra `1(Z) ........................... 21 1.7.2 The return of Real Analysis: the case of L¥ ................... 23 2 Bounded operators on Hilbert spaces 24 2.1 Adjoints............................................ 24 2.2 Example: a space of “diagonal” operators......................... 30 2.3 The shift operator on `2(Z) ................................. 32 2.3.1 Example: the shift operators on H = `2(N) ................... 38 3 W∗-algebras and measurable functional calculus 41 3.1 The strong and weak topologies of operators....................... 42 4 Spectral theorems 46 4.1 Integration of normal operators............................... 51 4.2 Spectral projections...................................... 51 5 Bounded and unbounded operators 54 5.1 Operations..........................................