Unipotent Flows and Applications
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Lecture Notes: Qubit Representations and Rotations
Phys 711 Topics in Particles & Fields | Spring 2013 | Lecture 1 | v0.3 Lecture notes: Qubit representations and rotations Jeffrey Yepez Department of Physics and Astronomy University of Hawai`i at Manoa Watanabe Hall, 2505 Correa Road Honolulu, Hawai`i 96822 E-mail: [email protected] www.phys.hawaii.edu/∼yepez (Dated: January 9, 2013) Contents mathematical object (an abstraction of a two-state quan- tum object) with a \one" state and a \zero" state: I. What is a qubit? 1 1 0 II. Time-dependent qubits states 2 jqi = αj0i + βj1i = α + β ; (1) 0 1 III. Qubit representations 2 A. Hilbert space representation 2 where α and β are complex numbers. These complex B. SU(2) and O(3) representations 2 numbers are called amplitudes. The basis states are or- IV. Rotation by similarity transformation 3 thonormal V. Rotation transformation in exponential form 5 h0j0i = h1j1i = 1 (2a) VI. Composition of qubit rotations 7 h0j1i = h1j0i = 0: (2b) A. Special case of equal angles 7 In general, the qubit jqi in (1) is said to be in a superpo- VII. Example composite rotation 7 sition state of the two logical basis states j0i and j1i. If References 9 α and β are complex, it would seem that a qubit should have four free real-valued parameters (two magnitudes and two phases): I. WHAT IS A QUBIT? iθ0 α φ0 e jqi = = iθ1 : (3) Let us begin by introducing some notation: β φ1 e 1 state (called \minus" on the Bloch sphere) Yet, for a qubit to contain only one classical bit of infor- 0 mation, the qubit need only be unimodular (normalized j1i = the alternate symbol is |−i 1 to unity) α∗α + β∗β = 1: (4) 0 state (called \plus" on the Bloch sphere) 1 Hence it lives on the complex unit circle, depicted on the j0i = the alternate symbol is j+i: 0 top of Figure 1. -
Bounded Orbits of Homogeneous Dynamics
BOUNDED ORBITS OF HOMOGENEOUS DYNAMICS JINPENG AN AND LIFAN GUAN Abstract. Homogeneous dynamics is a special kind of dynamics given by Lie groups, and is closely related to Diophantine approximation and other areas in number theory. In this paper, we survey main problems and results concerning bounded orbits of homogeneous dynamics, and discuss their relations with Diophantine approximation problems including the Oppenheim conjecture, the Littlewood conjecture, and the Schmidt conjecture. 1. Introduction Homogeneous dynamics is a special kind of dynamics. Its phase space is a homogeneous space of a Lie group, and the dynamical system is induced by the group multiplication. More precisely, let G be a Lie group1,Γ ⊂ G be a closed subgroup, and consider the homogeneous space X = G=Γ. In homogeneous dynamics, one studies the natural translation action of another subgroup H ⊂ G on X, examines properties of orbits and invariant measures of the action, and investigates the asymptotic behavior of the action when elements in H tend to infinity. This kind of dynamical systems gives rise to several classical examples, including geodesic flows and horocycle flows on surfaces of constant negative curvature. By combining methods from dynamical systems and Lie theory, one is able to obtain stronger results in homogeneous dynamics than in more general dynamics. A typical example is Ratner's theorems for unipotent flows [63], which state that if the subgroup H is generated by unipotent elements, then the closures of H-orbits in X are algebraically defined submanifolds, and the H-invariant measures on X can be also classified in an algebraic way. -
Matrix Lie Groups
Maths Seminar 2007 MATRIX LIE GROUPS Claudiu C Remsing Dept of Mathematics (Pure and Applied) Rhodes University Grahamstown 6140 26 September 2007 RhodesUniv CCR 0 Maths Seminar 2007 TALK OUTLINE 1. What is a matrix Lie group ? 2. Matrices revisited. 3. Examples of matrix Lie groups. 4. Matrix Lie algebras. 5. A glimpse at elementary Lie theory. 6. Life beyond elementary Lie theory. RhodesUniv CCR 1 Maths Seminar 2007 1. What is a matrix Lie group ? Matrix Lie groups are groups of invertible • matrices that have desirable geometric features. So matrix Lie groups are simultaneously algebraic and geometric objects. Matrix Lie groups naturally arise in • – geometry (classical, algebraic, differential) – complex analyis – differential equations – Fourier analysis – algebra (group theory, ring theory) – number theory – combinatorics. RhodesUniv CCR 2 Maths Seminar 2007 Matrix Lie groups are encountered in many • applications in – physics (geometric mechanics, quantum con- trol) – engineering (motion control, robotics) – computational chemistry (molecular mo- tion) – computer science (computer animation, computer vision, quantum computation). “It turns out that matrix [Lie] groups • pop up in virtually any investigation of objects with symmetries, such as molecules in chemistry, particles in physics, and projective spaces in geometry”. (K. Tapp, 2005) RhodesUniv CCR 3 Maths Seminar 2007 EXAMPLE 1 : The Euclidean group E (2). • E (2) = F : R2 R2 F is an isometry . → | n o The vector space R2 is equipped with the standard Euclidean structure (the “dot product”) x y = x y + x y (x, y R2), • 1 1 2 2 ∈ hence with the Euclidean distance d (x, y) = (y x) (y x) (x, y R2). -
Theory of Angular Momentum and Spin
Chapter 5 Theory of Angular Momentum and Spin Rotational symmetry transformations, the group SO(3) of the associated rotation matrices and the 1 corresponding transformation matrices of spin{ 2 states forming the group SU(2) occupy a very important position in physics. The reason is that these transformations and groups are closely tied to the properties of elementary particles, the building blocks of matter, but also to the properties of composite systems. Examples of the latter with particularly simple transformation properties are closed shell atoms, e.g., helium, neon, argon, the magic number nuclei like carbon, or the proton and the neutron made up of three quarks, all composite systems which appear spherical as far as their charge distribution is concerned. In this section we want to investigate how elementary and composite systems are described. To develop a systematic description of rotational properties of composite quantum systems the consideration of rotational transformations is the best starting point. As an illustration we will consider first rotational transformations acting on vectors ~r in 3-dimensional space, i.e., ~r R3, 2 we will then consider transformations of wavefunctions (~r) of single particles in R3, and finally N transformations of products of wavefunctions like j(~rj) which represent a system of N (spin- Qj=1 zero) particles in R3. We will also review below the well-known fact that spin states under rotations behave essentially identical to angular momentum states, i.e., we will find that the algebraic properties of operators governing spatial and spin rotation are identical and that the results derived for products of angular momentum states can be applied to products of spin states or a combination of angular momentum and spin states. -
LIE GROUPS and ALGEBRAS NOTES Contents 1. Definitions 2
LIE GROUPS AND ALGEBRAS NOTES STANISLAV ATANASOV Contents 1. Definitions 2 1.1. Root systems, Weyl groups and Weyl chambers3 1.2. Cartan matrices and Dynkin diagrams4 1.3. Weights 5 1.4. Lie group and Lie algebra correspondence5 2. Basic results about Lie algebras7 2.1. General 7 2.2. Root system 7 2.3. Classification of semisimple Lie algebras8 3. Highest weight modules9 3.1. Universal enveloping algebra9 3.2. Weights and maximal vectors9 4. Compact Lie groups 10 4.1. Peter-Weyl theorem 10 4.2. Maximal tori 11 4.3. Symmetric spaces 11 4.4. Compact Lie algebras 12 4.5. Weyl's theorem 12 5. Semisimple Lie groups 13 5.1. Semisimple Lie algebras 13 5.2. Parabolic subalgebras. 14 5.3. Semisimple Lie groups 14 6. Reductive Lie groups 16 6.1. Reductive Lie algebras 16 6.2. Definition of reductive Lie group 16 6.3. Decompositions 18 6.4. The structure of M = ZK (a0) 18 6.5. Parabolic Subgroups 19 7. Functional analysis on Lie groups 21 7.1. Decomposition of the Haar measure 21 7.2. Reductive groups and parabolic subgroups 21 7.3. Weyl integration formula 22 8. Linear algebraic groups and their representation theory 23 8.1. Linear algebraic groups 23 8.2. Reductive and semisimple groups 24 8.3. Parabolic and Borel subgroups 25 8.4. Decompositions 27 Date: October, 2018. These notes compile results from multiple sources, mostly [1,2]. All mistakes are mine. 1 2 STANISLAV ATANASOV 1. Definitions Let g be a Lie algebra over algebraically closed field F of characteristic 0. -
Rotation Matrix - Wikipedia, the Free Encyclopedia Page 1 of 22
Rotation matrix - Wikipedia, the free encyclopedia Page 1 of 22 Rotation matrix From Wikipedia, the free encyclopedia In linear algebra, a rotation matrix is a matrix that is used to perform a rotation in Euclidean space. For example the matrix rotates points in the xy -Cartesian plane counterclockwise through an angle θ about the origin of the Cartesian coordinate system. To perform the rotation, the position of each point must be represented by a column vector v, containing the coordinates of the point. A rotated vector is obtained by using the matrix multiplication Rv (see below for details). In two and three dimensions, rotation matrices are among the simplest algebraic descriptions of rotations, and are used extensively for computations in geometry, physics, and computer graphics. Though most applications involve rotations in two or three dimensions, rotation matrices can be defined for n-dimensional space. Rotation matrices are always square, with real entries. Algebraically, a rotation matrix in n-dimensions is a n × n special orthogonal matrix, i.e. an orthogonal matrix whose determinant is 1: . The set of all rotation matrices forms a group, known as the rotation group or the special orthogonal group. It is a subset of the orthogonal group, which includes reflections and consists of all orthogonal matrices with determinant 1 or -1, and of the special linear group, which includes all volume-preserving transformations and consists of matrices with determinant 1. Contents 1 Rotations in two dimensions 1.1 Non-standard orientation -
Contents 1 Root Systems
Stefan Dawydiak February 19, 2021 Marginalia about roots These notes are an attempt to maintain a overview collection of facts about and relationships between some situations in which root systems and root data appear. They also serve to track some common identifications and choices. The references include some helpful lecture notes with more examples. The author of these notes learned this material from courses taught by Zinovy Reichstein, Joel Kam- nitzer, James Arthur, and Florian Herzig, as well as many student talks, and lecture notes by Ivan Loseu. These notes are simply collected marginalia for those references. Any errors introduced, especially of viewpoint, are the author's own. The author of these notes would be grateful for their communication to [email protected]. Contents 1 Root systems 1 1.1 Root space decomposition . .2 1.2 Roots, coroots, and reflections . .3 1.2.1 Abstract root systems . .7 1.2.2 Coroots, fundamental weights and Cartan matrices . .7 1.2.3 Roots vs weights . .9 1.2.4 Roots at the group level . .9 1.3 The Weyl group . 10 1.3.1 Weyl Chambers . 11 1.3.2 The Weyl group as a subquotient for compact Lie groups . 13 1.3.3 The Weyl group as a subquotient for noncompact Lie groups . 13 2 Root data 16 2.1 Root data . 16 2.2 The Langlands dual group . 17 2.3 The flag variety . 18 2.3.1 Bruhat decomposition revisited . 18 2.3.2 Schubert cells . 19 3 Adelic groups 20 3.1 Weyl sets . 20 References 21 1 Root systems The following examples are taken mostly from [8] where they are stated without most of the calculations. -
Linear Operators Hsiu-Hau Lin [email protected] (Mar 25, 2010)
Linear Operators Hsiu-Hau Lin [email protected] (Mar 25, 2010) The notes cover linear operators and discuss linear independence of func- tions (Boas 3.7-3.8). • Linear operators An operator maps one thing into another. For instance, the ordinary func- tions are operators mapping numbers to numbers. A linear operator satisfies the properties, O(A + B) = O(A) + O(B);O(kA) = kO(A); (1) where k is a number. As we learned before, a matrix maps one vector into another. One also notices that M(r1 + r2) = Mr1 + Mr2;M(kr) = kMr: Thus, matrices are linear operators. • Orthogonal matrix The length of a vector remains invariant under rotations, ! ! x0 x x0 y0 = x y M T M : y0 y The constraint can be elegantly written down as a matrix equation, M T M = MM T = 1: (2) In other words, M T = M −1. For matrices satisfy the above constraint, they are called orthogonal matrices. Note that, for orthogonal matrices, computing inverse is as simple as taking transpose { an extremely helpful property for calculations. From the product theorem for the determinant, we immediately come to the conclusion det M = ±1. In two dimensions, any 2 × 2 orthogonal matrix with determinant 1 corresponds to a rotation, while any 2 × 2 orthogonal HedgeHog's notes (March 24, 2010) 2 matrix with determinant −1 corresponds to a reflection about a line. Let's come back to our good old friend { the rotation matrix, cos θ − sin θ ! cos θ sin θ ! R(θ) = ;RT = : (3) sin θ cos θ − sin θ cos θ It is straightforward to check that RT R = RRT = 1. -
DECOMPOSITION of SYMPLECTIC MATRICES INTO PRODUCTS of SYMPLECTIC UNIPOTENT MATRICES of INDEX 2∗ 1. Introduction. Decomposition
Electronic Journal of Linear Algebra, ISSN 1081-3810 A publication of the International Linear Algebra Society Volume 35, pp. 497-502, November 2019. DECOMPOSITION OF SYMPLECTIC MATRICES INTO PRODUCTS OF SYMPLECTIC UNIPOTENT MATRICES OF INDEX 2∗ XIN HOUy , ZHENGYI XIAOz , YAJING HAOz , AND QI YUANz Abstract. In this article, it is proved that every symplectic matrix can be decomposed into a product of three symplectic 0 I unipotent matrices of index 2, i.e., every complex matrix A satisfying AT JA = J with J = n is a product of three −In 0 T 2 matrices Bi satisfying Bi JBi = J and (Bi − I) = 0 (i = 1; 2; 3). Key words. Symplectic matrices, Product of unipotent matrices, Symplectic Jordan Canonical Form. AMS subject classifications. 15A23, 20H20. 1. Introduction. Decomposition of elements in a matrix group into products of matrices with a special nature (such as unipotent matrices, involutions and so on) is a popular topic studied by many scholars. In the n × n matrix k ring Mn(F ) over a field F , a unipotent matrix of index k refers to a matrix A satisfying (A − In) = 0. Fong and Sourour in [4] proved that every matrix in the group SLn(C) (the special linear group over complex field C) is a product of three unipotent matrices (without limitation on the index). Wang and Wu in [6] gave a further result that every matrix in the group SLn(C) is a product of four unipotent matrices of index 2. In particular, decompositions of symplectic matrices have drawn considerable attention from numerous 0 I scholars (see [1, 3]). -
An Effective Lie–Kolchin Theorem for Quasi-Unipotent Matrices
Linear Algebra and its Applications 581 (2019) 304–323 Contents lists available at ScienceDirect Linear Algebra and its Applications www.elsevier.com/locate/laa An effective Lie–Kolchin Theorem for quasi-unipotent matrices Thomas Koberda a, Feng Luo b,∗, Hongbin Sun b a Department of Mathematics, University of Virginia, Charlottesville, VA 22904-4137, USA b Department of Mathematics, Rutgers University, Hill Center – Busch Campus, 110 Frelinghuysen Road, Piscataway, NJ 08854, USA a r t i c l e i n f oa b s t r a c t Article history: We establish an effective version of the classical Lie–Kolchin Received 27 April 2019 Theorem. Namely, let A, B ∈ GLm(C)be quasi-unipotent Accepted 17 July 2019 matrices such that the Jordan Canonical Form of B consists Available online 23 July 2019 of a single block, and suppose that for all k 0the Submitted by V.V. Sergeichuk matrix ABk is also quasi-unipotent. Then A and B have a A, B < C MSC: common eigenvector. In particular, GLm( )is a primary 20H20, 20F38 solvable subgroup. We give applications of this result to the secondary 20F16, 15A15 representation theory of mapping class groups of orientable surfaces. Keywords: © 2019 Elsevier Inc. All rights reserved. Lie–Kolchin theorem Unipotent matrices Solvable groups Mapping class groups * Corresponding author. E-mail addresses: [email protected] (T. Koberda), fl[email protected] (F. Luo), [email protected] (H. Sun). URLs: http://faculty.virginia.edu/Koberda/ (T. Koberda), http://sites.math.rutgers.edu/~fluo/ (F. Luo), http://sites.math.rutgers.edu/~hs735/ (H. -
Inclusion Relations Between Orthostochastic Matrices And
Linear and Multilinear Algebra, 1987, Vol. 21, pp. 253-259 Downloaded By: [Li, Chi-Kwong] At: 00:16 20 March 2009 Photocopying permitted by license only 1987 Gordon and Breach Science Publishers, S.A. Printed in the United States of America Inclusion Relations Between Orthostochastic Matrices and Products of Pinchinq-- Matrices YIU-TUNG POON Iowa State University, Ames, lo wa 5007 7 and NAM-KIU TSING CSty Poiytechnic of HWI~K~tig, ;;e,~g ,?my"; 2nd A~~KI:Lkwe~ity, .Auhrn; Al3b3m-l36849 Let C be thc set of ail n x n urthusiuihaatic natiiccs and ;"', the se! of finite prnd~uctpof n x n pinching matrices. Both sets are subsets of a,, the set of all n x n doubly stochastic matrices. We study the inclusion relations between C, and 9'" and in particular we show that.'P,cC,b~t-~p,t~forn>J,andthatC~$~~fori123. 1. INTRODUCTION An n x n matrix is said to be doubly stochastic (d.s.) if it has nonnegative entries and ail row sums and column sums are 1. An n x n d.s. matrix S = (sij)is said to be orthostochastic (0.s.) if there is a unitary matrix U = (uij) such that 2 sij = luijl , i,j = 1, . ,n. Following [6], we write S = IUI2. The set of all n x n d.s. (or 0s.) matrices will be denoted by R, (or (I,, respectively). If P E R, can be expressed as 1-t (1 2 54 Y. T POON AND N K. TSING Downloaded By: [Li, Chi-Kwong] At: 00:16 20 March 2009 for some permutation matrix Q and 0 < t < I, then we call P a pinching matrix. -
On a Quantitative Version of the Oppenheim Conjecture
ELECTRONIC RESEARCH ANNOUNCEMENTS OF THE AMERICAN MATHEMATICAL SOCIETY Volume 1, Issue 3, 1995 ON A QUANTITATIVE VERSION OF THE OPPENHEIM CONJECTURE ALEX ESKIN, GREGORY MARGULIS, AND SHAHAR MOZES Abstract. The Oppenheim conjecture, proved by Margulis in 1986, states that the set of values at integral points of an indefinite quadratic form in three or more variables is dense, provided the form is not proportional to a rational form. In this paper we study the distribution of values of such a form. We show that if the signature of the form is not (2, 1) or (2, 2), then the values are uniformly distributed on the real line, provided the form is not proportional to a rational form. In the cases where the signature is (2, 1) or (2, 2) we show that no such universal formula exists, and give asymptotic upper bounds which are in general best possible. Let Q be an indefinite nondegenerate quadratic form in n variables. Let Q = L Q(Zn)denotethesetofvaluesofQat integral points. The Oppenheim conjecture, proved by Margulis (cf. [Mar]) states that if n 3, and Q is not proportional ≥ to a form with rational coefficients, then Q is dense. The Oppenheim conjecture enjoyed attention and many studies sinceL it was conjectured in 1929 mostly using analytic number theory methods. In this paper1 we study some finer questions related to the distribution the values of Q at integral points. 1. Let ν be a continuous positive function on the sphere v Rn v =1 ,and { ∈ |k k } let Ω = v Rn v <ν(v/ v ) .WedenotebyTΩthedilateofΩbyT.