Chapter X the Spectral Theorem of Gelfand
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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. -
Appendix A. Measure and Integration
Appendix A. Measure and integration We suppose the reader is familiar with the basic facts concerning set theory and integration as they are presented in the introductory course of analysis. In this appendix, we review them briefly, and add some more which we shall need in the text. Basic references for proofs and a detailed exposition are, e.g., [[ H a l 1 ]] , [[ J a r 1 , 2 ]] , [[ K F 1 , 2 ]] , [[ L i L ]] , [[ R u 1 ]] , or any other textbook on analysis you might prefer. A.1 Sets, mappings, relations A set is a collection of objects called elements. The symbol card X denotes the cardi- nality of the set X. The subset M consisting of the elements of X which satisfy the conditions P1(x),...,Pn(x) is usually written as M = { x ∈ X : P1(x),...,Pn(x) }.A set whose elements are certain sets is called a system or family of these sets; the family of all subsystems of a given X is denoted as 2X . The operations of union, intersection, and set difference are introduced in the standard way; the first two of these are commutative, associative, and mutually distributive. In a { } system Mα of any cardinality, the de Morgan relations , X \ Mα = (X \ Mα)and X \ Mα = (X \ Mα), α α α α are valid. Another elementary property is the following: for any family {Mn} ,whichis { } at most countable, there is a disjoint family Nn of the same cardinality such that ⊂ \ ∪ \ Nn Mn and n Nn = n Mn.Theset(M N) (N M) is called the symmetric difference of the sets M,N and denoted as M #N. -
Singular Value Decomposition (SVD)
San José State University Math 253: Mathematical Methods for Data Visualization Lecture 5: Singular Value Decomposition (SVD) Dr. Guangliang Chen Outline • Matrix SVD Singular Value Decomposition (SVD) Introduction We have seen that symmetric matrices are always (orthogonally) diagonalizable. That is, for any symmetric matrix A ∈ Rn×n, there exist an orthogonal matrix Q = [q1 ... qn] and a diagonal matrix Λ = diag(λ1, . , λn), both real and square, such that A = QΛQT . We have pointed out that λi’s are the eigenvalues of A and qi’s the corresponding eigenvectors (which are orthogonal to each other and have unit norm). Thus, such a factorization is called the eigendecomposition of A, also called the spectral decomposition of A. What about general rectangular matrices? Dr. Guangliang Chen | Mathematics & Statistics, San José State University3/22 Singular Value Decomposition (SVD) Existence of the SVD for general matrices Theorem: For any matrix X ∈ Rn×d, there exist two orthogonal matrices U ∈ Rn×n, V ∈ Rd×d and a nonnegative, “diagonal” matrix Σ ∈ Rn×d (of the same size as X) such that T Xn×d = Un×nΣn×dVd×d. Remark. This is called the Singular Value Decomposition (SVD) of X: • The diagonals of Σ are called the singular values of X (often sorted in decreasing order). • The columns of U are called the left singular vectors of X. • The columns of V are called the right singular vectors of X. Dr. Guangliang Chen | Mathematics & Statistics, San José State University4/22 Singular Value Decomposition (SVD) * * b * b (n>d) b b b * b = * * = b b b * (n<d) * b * * b b Dr. -
Can One Identify Two Unital JB $^* $-Algebras by the Metric Spaces
CAN ONE IDENTIFY TWO UNITAL JB∗-ALGEBRAS BY THE METRIC SPACES DETERMINED BY THEIR SETS OF UNITARIES? MAR´IA CUETO-AVELLANEDA, ANTONIO M. PERALTA Abstract. Let M and N be two unital JB∗-algebras and let U(M) and U(N) denote the sets of all unitaries in M and N, respectively. We prove that the following statements are equivalent: (a) M and N are isometrically isomorphic as (complex) Banach spaces; (b) M and N are isometrically isomorphic as real Banach spaces; (c) There exists a surjective isometry ∆ : U(M) →U(N). We actually establish a more general statement asserting that, under some mild extra conditions, for each surjective isometry ∆ : U(M) → U(N) we can find a surjective real linear isometry Ψ : M → N which coincides with ∆ on the subset eiMsa . If we assume that M and N are JBW∗-algebras, then every surjective isometry ∆ : U(M) → U(N) admits a (unique) extension to a surjective real linear isometry from M onto N. This is an extension of the Hatori–Moln´ar theorem to the setting of JB∗-algebras. 1. Introduction Every surjective isometry between two real normed spaces X and Y is an affine mapping by the Mazur–Ulam theorem. It seems then natural to ask whether the existence of a surjective isometry between two proper subsets of X and Y can be employed to identify metrically both spaces. By a result of P. Mankiewicz (see [34]) every surjective isometry between convex bodies in two arbitrary normed spaces can be uniquely extended to an affine function between the spaces. -
The Index of Normal Fredholm Elements of C* -Algebras
proceedings of the american mathematical society Volume 113, Number 1, September 1991 THE INDEX OF NORMAL FREDHOLM ELEMENTS OF C*-ALGEBRAS J. A. MINGO AND J. S. SPIELBERG (Communicated by Palle E. T. Jorgensen) Abstract. Examples are given of normal elements of C*-algebras that are invertible modulo an ideal and have nonzero index, in contrast to the case of Fredholm operators on Hubert space. It is shown that this phenomenon occurs only along the lines of these examples. Let T be a bounded operator on a Hubert space. If the range of T is closed and both T and T* have a finite dimensional kernel then T is Fredholm, and the index of T is dim(kerT) - dim(kerT*). If T is normal then kerT = ker T*, so a normal Fredholm operator has index 0. Let us consider a generalization of the notion of Fredholm operator intro- duced by Atiyah. Let X be a compact Hausdorff space and consider continuous functions T: X —>B(H), where B(H) is the set of bounded linear operators on a separable infinite dimensional Hubert space with the norm topology. The set of such functions forms a C*- algebra C(X) <g>B(H). A function T is Fredholm if T(x) is Fredholm for each x . Atiyah [1, Appendix] showed how such an element has an index which is an element of K°(X). Suppose that T is Fredholm and T(x) is normal for each x. Is the index of T necessarily 0? There is a generalization of this question that we would like to consider. -
A Short Introduction to the Quantum Formalism[S]
A short introduction to the quantum formalism[s] François David Institut de Physique Théorique CNRS, URA 2306, F-91191 Gif-sur-Yvette, France CEA, IPhT, F-91191 Gif-sur-Yvette, France [email protected] These notes are an elaboration on: (i) a short course that I gave at the IPhT-Saclay in May- June 2012; (ii) a previous letter [Dav11] on reversibility in quantum mechanics. They present an introductory, but hopefully coherent, view of the main formalizations of quantum mechanics, of their interrelations and of their common physical underpinnings: causality, reversibility and locality/separability. The approaches covered are mainly: (ii) the canonical formalism; (ii) the algebraic formalism; (iii) the quantum logic formulation. Other subjects: quantum information approaches, quantum correlations, contextuality and non-locality issues, quantum measurements, interpretations and alternate theories, quantum gravity, are only very briefly and superficially discussed. Most of the material is not new, but is presented in an original, homogeneous and hopefully not technical or abstract way. I try to define simply all the mathematical concepts used and to justify them physically. These notes should be accessible to young physicists (graduate level) with a good knowledge of the standard formalism of quantum mechanics, and some interest for theoretical physics (and mathematics). These notes do not cover the historical and philosophical aspects of quantum physics. arXiv:1211.5627v1 [math-ph] 24 Nov 2012 Preprint IPhT t12/042 ii CONTENTS Contents 1 Introduction 1-1 1.1 Motivation . 1-1 1.2 Organization . 1-2 1.3 What this course is not! . 1-3 1.4 Acknowledgements . 1-3 2 Reminders 2-1 2.1 Classical mechanics . -
C*-Algebraic Spectral Sets, Twisted Groupoids and Operators
C∗-Algebraic Spectral Sets, Twisted Groupoids and Operators Marius M˘antoiu ∗ July 7, 2020 Abstract We treat spectral problems by twisted groupoid methods. To Hausdorff locally compact groupoids endowed with a continuous 2-cocycle one associates the reduced twisted groupoid C∗-algebra. Elements (or multipliers) of this algebra admit natural Hilbert space representations. We show the relevance of the orbit closure structure of the unit space of the groupoid in dealing with spectra, norms, numerical ranges and ǫ-pseudospectra of the resulting operators. As an ex- ample, we treat a class of pseudo-differential operators introduced recently, associated to group actions. We also prove a Decomposition Principle for bounded operators connected to groupoids, showing that several relevant spectral quantities of these operators coincide with those of certain non-invariant restrictions. This is applied to Toeplitz-like operators with variable coefficients and to band dominated operators on discrete metric spaces. Introduction Many applications of C∗-algebras to spectral analysis rely on a very simple principle: a morphism between two C∗-algebras is contractive and reduces the spectrum of elements. In addition, if it is injective, it is isometric and preserves spectra. While working on this project, we became aware of the fact that such a principle works ef- fectively for much more than spectra (and essential spectra). We call C∗-algebraic spectral set a function Σ sending, for any unital C∗-algebra E , the elements E of this one to closed (usually com- pact) subsets Σ(E |E ) of C , having the above mentioned behavior under C∗-morphisms. Definition 1.1 states this formally. -
Geodesics of Projections in Von Neumann Algebras
Geodesics of projections in von Neumann algebras Esteban Andruchow∗ November 5, 2020 Abstract Let be a von Neumann algebra and A the manifold of projections in . There is a A P A natural linear connection in A, which in the finite dimensional case coincides with the the Levi-Civita connection of theP Grassmann manifold of Cn. In this paper we show that two projections p, q can be joined by a geodesic, which has minimal length (with respect to the metric given by the usual norm of ), if and only if A p q⊥ p⊥ q, ∧ ∼ ∧ where stands for the Murray-von Neumann equivalence of projections. It is shown that the minimal∼ geodesic is unique if and only if p q⊥ = p⊥ q =0. If is a finite factor, any ∧ ∧ A pair of projections in the same connected component of A (i.e., with the same trace) can be joined by a minimal geodesic. P We explore certain relations with Jones’ index theory for subfactors. For instance, it is −1 shown that if are II1 factors with finite index [ : ] = t , then the geodesic N ⊂M M N 1/2 distance d(eN ,eM) between the induced projections eN and eM is d(eN ,eM) = arccos(t ). 2010 MSC: 58B20, 46L10, 53C22 Keywords: Projections, geodesics of projections, von Neumann algebras, index for subfac- tors. arXiv:2011.02013v1 [math.OA] 3 Nov 2020 1 Introduction ∗ If is a C -algebra, let A denote the set of (selfadjoint) projections in . A has a rich A P A P geometric structure, see for instante the papers [12] by H. -
Noncommutative Geometry and Flavour Mixing
Noncommutative geometry and flavour mixing prepared by Jose´ M. Gracia-Bond´ıa Department of Theoretical Physics Universidad de Zaragoza, 50009 Zaragoza, Spain October 22, 2013 1 Introduction: the universality problem “The origin of the quark and lepton masses is shrouded in mystery” [1]. Some thirty years ago, attempts to solve the enigma based on textures of the quark mass matrices, purposedly reflecting mass hierarchies and “nearest-neighbour” interactions, were very popular. Now, in the late eighties, Branco, Lavoura and Mota [2] showed that, within the SM, the zero pattern 0a b 01 @c 0 dA; (1) 0 e 0 a central ingredient of Fritzsch’s well-known Ansatz for the mass matrices, is devoid of any particular physical meaning. (The top quark is above on top.) Although perhaps this was not immediately clear at the time, paper [2] marked a water- shed in the theory of flavour mixing. In algebraic terms, it establishes that the linear subspace of matrices of the form (1) is universal for the group action of unitaries effecting chiral basis transformations, that respect the charged-current term of the Lagrangian. That is, any mass matrix can be transformed to that form without modifying the corresponding CKM matrix. To put matters in perspective, consider the unitary group acting by similarity on three-by- three matrices. The classical triangularization theorem by Schur ensures that the zero patterns 0a 0 01 0a b c1 @b c 0A; @0 d eA (2) d e f 0 0 f are universal in this sense. However, proof that the zero pattern 0a b 01 @0 c dA e 0 f 1 is universal was published [3] just three years ago! (Any off-diagonal n(n−1)=2 zero pattern with zeroes at some (i j) and no zeroes at the matching ( ji), is universal in this sense, for complex n × n matrices.) Fast-forwarding to the present time, notwithstanding steady experimental progress [4] and a huge amount of theoretical work by many authors, we cannot be sure of being any closer to solving the “Meroitic” problem [5] of divining the spectrum behind the known data. -
Arxiv:1909.02676V3 [Math.DG] 25 Jul 2021 Elsetu Jcb Arcshv Ipera Pcrm.Mor a of Spectrum)
AN ATLAS ADAPTED TO THE TODA FLOW DAVID MART´INEZ TORRES AND CARLOS TOMEI Abstract. We describe an atlas adapted to the Toda flow on the mani- fold of full flags of any non-compact real semisimple Lie algebra, and on its Hessenberg-type submanifolds. We show that in these local coordinates the Toda flow becomes linear. The local coordinates are used to show that the Toda flow on the manifold of full flags is Morse-Smale, which generalizes the re- sult for traceless matrices in [27] to arbitrary non-compact real semisimple Lie algebras. As a byproduct we describe new features of classical constructions in matrix theory. 1. Introduction The non-periodic Toda lattice is a Hamiltonian model for a wave propagation along n particles in a line proposed by Toda [30]. A change of variables introduced by Flaschka [14] transforms the original O.D.E. into the matrix differential equation X′ = [X, πkX]= T (X), (1) where X runs over Jacobi matrices and πk is the first projection associated to the decomposition of a matrix into its antisymmetric and upper triangular summands. From a mathematical viewpoint (1) is a vector field everywhere defined on the Lie algebra of real traceless matrices. Since it is in Lax form it is tangent to every adjoint orbit and, in particular, to the orbit made of traceless matrices of any fixed simple real spectrum (Jacobi matrices have simple real spectrum). Moreover, formula (1) implies that the Toda vector field T is tangent to any vector subspace which is stable upon taking Lie bracket with antisymmetric matrices. -
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. -
Self-Adjoint Semigroups with Nilpotent Commutators ∗ Matjaž Omladiˇc A, ,1, Heydar Radjavi B,2
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Linear Algebra and its Applications 436 (2012) 2597–2603 Contents lists available at SciVerse ScienceDirect Linear Algebra and its Applications journal homepage: www.elsevier.com/locate/laa Self-adjoint semigroups with nilpotent commutators ∗ Matjaž Omladiˇc a, ,1, Heydar Radjavi b,2 a Department of Mathematics, University of Ljubljana, Ljubljana, Slovenia b Department of Pure Mathematics, University of Waterloo, Waterloo, Canada ARTICLE INFO ABSTRACT Article history: Let P be a projection and let S be a multiplicative semigroup of Received 19 June 2011 linear operators such that SP − PS is nilpotent for every S in S. Accepted 26 October 2011 We study conditions under which this implies the existence of an Available online 5 December 2011 invariant subspace for S and, in particular, when P commutes with Submitted by H. Schneider every member of S. © 2011 Elsevier Inc. All rights reserved. AMS classification: 15A30 47A15 Keywords: Reducibility Semigroups Commutators Nilpotent operators 1. Introduction Several authors have studied the effect of polynomial conditions on reducibility and (simultane- ous) triangularizability of semigroups of operators in the following sense. Let S be a (multiplicative) semigroup of linear operators on a finite-dimensional vector space V over an algebraically closed field. (The semigroup may have to satisfy more conditions to get certain results, e.g., it may be required that it be a group or an algebra.) Let f be a noncommutative polynomial in two variables. One may assume conditions such as f (S, T) = 0forallS and T in S,ortrf (S, T) = 0, or f (S, T) is nilpotent for all pairs.