Quantum Mechanics I - Session 4

Similar documents
Quantum Mechanics for Scientists and Engineers. David Miller

= = = (a) Use the MATLAB command rref to solve the system. (b) Let A be the coefficient matrix and B be the right-hand side of the system.

C/CS/Phy191 Problem Set 3 Solutions Out: Oct 1, 2008., where ( 00. ), so the overall state of the system is ) ( ( ( ( 00 ± 11 ), Φ ± = 1

763622S ADVANCED QUANTUM MECHANICS Solution Set 1 Spring c n a n. c n 2 = 1.

(A and B must have the same dmensons to be able to add them together.) Addton s commutatve and assocatve, just lke regular addton. A matrx A multpled

1 Vectors over the complex numbers

ψ = i c i u i c i a i b i u i = i b 0 0 b 0 0

Lectures - Week 4 Matrix norms, Conditioning, Vector Spaces, Linear Independence, Spanning sets and Basis, Null space and Range of a Matrix

Salmon: Lectures on partial differential equations. Consider the general linear, second-order PDE in the form. ,x 2

332600_08_1.qxp 4/17/08 11:29 AM Page 481

n α j x j = 0 j=1 has a nontrivial solution. Here A is the n k matrix whose jth column is the vector for all t j=0

Difference Equations

APPENDIX A Some Linear Algebra

MATH Sensitivity of Eigenvalue Problems

U.C. Berkeley CS294: Beyond Worst-Case Analysis Luca Trevisan September 5, 2017

1 Matrix representations of canonical matrices

Section 8.3 Polar Form of Complex Numbers

8.4 COMPLEX VECTOR SPACES AND INNER PRODUCTS

The Order Relation and Trace Inequalities for. Hermitian Operators

1 GSW Iterative Techniques for y = Ax

PHYS 215C: Quantum Mechanics (Spring 2017) Problem Set 3 Solutions

Representation theory and quantum mechanics tutorial Representation theory and quantum conservation laws

Tensor Analysis. For orthogonal curvilinear coordinates, ˆ ˆ (98) Expanding the derivative, we have, ˆ. h q. . h q h q

MEM 255 Introduction to Control Systems Review: Basics of Linear Algebra

Inner Product. Euclidean Space. Orthonormal Basis. Orthogonal

5 The Rational Canonical Form

Lecture 6/7 (February 10/12, 2014) DIRAC EQUATION. The non-relativistic Schrödinger equation was obtained by noting that the Hamiltonian 2

Singular Value Decomposition: Theory and Applications

Lorentz Group. Ling Fong Li. 1 Lorentz group Generators Simple representations... 3

Solution 1 for USTC class Physics of Quantum Information

Workshop: Approximating energies and wave functions Quantum aspects of physical chemistry

Some Comments on Accelerating Convergence of Iterative Sequences Using Direct Inversion of the Iterative Subspace (DIIS)

The Feynman path integral

Solutions to Problem Set 6

Norms, Condition Numbers, Eigenvalues and Eigenvectors

Advanced Quantum Mechanics

Computing π with Bouncing Balls

Section 3.6 Complex Zeros

NOTES ON SIMPLIFICATION OF MATRICES

From Biot-Savart Law to Divergence of B (1)

LECTURE 9 CANONICAL CORRELATION ANALYSIS

Problem Do any of the following determine homomorphisms from GL n (C) to GL n (C)?

Solution 1 for USTC class Physics of Quantum Information

Poisson brackets and canonical transformations

MATH 241B FUNCTIONAL ANALYSIS - NOTES EXAMPLES OF C ALGEBRAS

Ph 219a/CS 219a. Exercises Due: Wednesday 23 October 2013

Vector Norms. Chapter 7 Iterative Techniques in Matrix Algebra. Cauchy-Bunyakovsky-Schwarz Inequality for Sums. Distances. Convergence.

MATH Homework #2

CONDITIONS FOR INVARIANT SUBMANIFOLD OF A MANIFOLD WITH THE (ϕ, ξ, η, G)-STRUCTURE. Jovanka Nikić

COMPLEX NUMBERS AND QUADRATIC EQUATIONS

Lecture 12: Discrete Laplacian

The exponential map of GL(N)

Quantum Mechanics for Scientists and Engineers

On Finite Rank Perturbation of Diagonalizable Operators

DISCRIMINANTS AND RAMIFIED PRIMES. 1. Introduction A prime number p is said to be ramified in a number field K if the prime ideal factorization

Snce h( q^; q) = hq ~ and h( p^ ; p) = hp, one can wrte ~ h hq hp = hq ~hp ~ (7) the uncertanty relaton for an arbtrary state. The states that mnmze t

Errata to Invariant Theory with Applications January 28, 2017

P A = (P P + P )A = P (I P T (P P ))A = P (A P T (P P )A) Hence if we let E = P T (P P A), We have that

STAT 309: MATHEMATICAL COMPUTATIONS I FALL 2018 LECTURE 16

Homework Notes Week 7

The Dirac Equation for a One-electron atom. In this section we will derive the Dirac equation for a one-electron atom.

arxiv: v2 [quant-ph] 29 Jun 2018

MEM633 Lectures 7&8. Chapter 4. Descriptions of MIMO Systems 4-1 Direct Realizations. (i) x u. y x

ρ some λ THE INVERSE POWER METHOD (or INVERSE ITERATION) , for , or (more usually) to

Phys304 Quantum Physics II (2005) Quantum Mechanics Summary. 2. This kind of behaviour can be described in the mathematical language of vectors:

9 Characteristic classes

THEOREMS OF QUANTUM MECHANICS

Chapter 5. Solution of System of Linear Equations. Module No. 6. Solution of Inconsistent and Ill Conditioned Systems

14 The Postulates of Quantum mechanics

THE CHINESE REMAINDER THEOREM. We should thank the Chinese for their wonderful remainder theorem. Glenn Stevens

Digital Signal Processing

Feb 14: Spatial analysis of data fields

The Prncpal Component Transform The Prncpal Component Transform s also called Karhunen-Loeve Transform (KLT, Hotellng Transform, oregenvector Transfor

First day August 1, Problems and Solutions

3 d Rotations Rotating dumbbells in lab frame Moment of Inertial Tensor

Formulas for the Determinant

7. Products and matrix elements

Point cloud to point cloud rigid transformations. Minimizing Rigid Registration Errors

Inexact Newton Methods for Inverse Eigenvalue Problems

However, since P is a symmetric idempotent matrix, of P are either 0 or 1 [Eigen-values

CHALMERS, GÖTEBORGS UNIVERSITET. SOLUTIONS to RE-EXAM for ARTIFICIAL NEURAL NETWORKS. COURSE CODES: FFR 135, FIM 720 GU, PhD

Mathematical Preparations

Complex Numbers. x = B B 2 4AC 2A. or x = x = 2 ± 4 4 (1) (5) 2 (1)

Some basic inequalities. Definition. Let V be a vector space over the complex numbers. An inner product is given by a function, V V C

Fisher Linear Discriminant Analysis

Exercises. 18 Algorithms

CHAPTER 4. Vector Spaces

Fall 2012 Analysis of Experimental Measurements B. Eisenstein/rev. S. Errede

Unit 5: Quadratic Equations & Functions

Solutions to exam in SF1811 Optimization, Jan 14, 2015

Ph 219a/CS 219a. Exercises Due: Wednesday 12 November 2008

Lecture 3: Dual problems and Kernels

Random Walks on Digraphs

This model contains two bonds per unit cell (one along the x-direction and the other along y). So we can rewrite the Hamiltonian as:

THE VIBRATIONS OF MOLECULES II THE CARBON DIOXIDE MOLECULE Student Instructions

LINEAR REGRESSION ANALYSIS. MODULE IX Lecture Multicollinearity

If A(k ; ), A(k ; 2),..., A(`) are all nvertble, then one could use the state transton matrx to obtan x(k) from x(`) even when k < `, but we shall typ

Moments of Inertia. and reminds us of the analogous equation for linear momentum p= mv, which is of the form. The kinetic energy of the body is.

Transfer Functions. Convenient representation of a linear, dynamic model. A transfer function (TF) relates one input and one output: ( ) system

Errors for Linear Systems

Transcription:

Quantum Mechancs I - Sesson 4 Aprl 3, 05 Contents Operators Change of Bass 4 3 Egenvectors and Egenvalues 5 3. Denton....................................... 5 3. Rotaton n D.................................... 5 4 Dagonalzng a matrx 6

Operators In order to dene a lnear operator we need to dene how the operator operates on each vector n the space..e for each ket ψ we need to dene A ψ = φ For example the dentty operator s dened by ψ = ψ. If a bass s orthonormal then t has the very useful property that = n n n. () proof: ψ = ( n n n ) ψ = n n n m c m m = n,m n n m c m = n,m c mδ nm n = n c n n = ψ However, t s sucent to dene how a lnear operator acts on all the members of a certan bass nstead of on all the members of the space. That s, f A n = m a m,n m () then we know that A ψ = A n c n n = n,m a m,n c n m. (3) The numbers a m,n are the matrx representaton of the operator A n the bass { n }. Once agan, they are to be found usng the nner-product m A n = l a l,n m l = a m,n, (4) these are called the matrx elements of A. We can use these numbers n order to wrte the operator n a derent way A = a n,m n m (5) n,m Wth ths denton t s easy to see that ψ A φ = ( ψ A) φ = ψ (A ψ ) How does the hermtan conjugate of that operator looks lke? By denton we have m A n == n A m = a n,m. (6) Thnkng of t as a matrx, we have changed the rows and the columns and taken the complexconjugate of each entry.

Lnear operators can be multpled, the result beng a lnear operator by tself. B ψ = ϕ and A ϕ = ξ then Suppose AB ψ = A(B ψ ) = A ϕ = ξ. (7) In general of course the operator AB s not equal to the operator BA snce the order of In the matrx representaton of operators ths s convenently done by multplyng the matrces. We'll denote the matrx representaton of the operator AB by the coecents (AB) n,m, so (AB) n,m = n AB m (8) ( ) = n A l l B m = l l n A l l B m = l a n,l b l,m. Queston: Let K be the operator dened by K = φ ψ where φ and ψ are two vectors of the space state.. Under what condton s K Hermtan?. Calculate K. Under what condton s K a projector? 3. Show that K can always be wrtten n the form K = λp P where λ s a constant to be calculated and P and P are projectors. Answer:. The denton of Hermtan s K j = ( j K ) On the one hand, pluggng n K ( j K ) = ( j φ ψ ) = ψ φ j so we see that the requrement s. The denton of a projector s φ ψ = ψ φ K = K K = φ ψ φ ψ so the requrement s ψ φ = 3

3. We can always wrte K as K = φ φ ψ ψ / φ ψ Change of Bass Generally there are many derent orthonormal bass we can choose for a gven vector space. Let us revew how we go from one representaton { n } to another { ξ }. We saw that ψ = n c n n, (9) wth c n = n ψ. We can also wrte ψ = ξ e ξ ξ, (0) wth e ξ = ξ ψ. The transformaton s done by usng the dentty operator ψ = c n n = c n ξ ξ n = ( ) c n ξ n ξ () n n ξ n so we conclude that e ξ = n ξ n c n. wth s ξ,n = ξ n we get that ξ e ξ = n s ξ,n c n. () We can thnk of t as a matrx multplyng a vector. A change of bass s lke a rotaton. Denng the operator S = ξ,n s ξ,n ξ n (3) we have that S ψ s the rotated vector. How does the representaton of operators transform from one bass to another? We'll use agan the dentty operator A = a n,m n m = a n,m ξ ξ n m η η = n,m n ξ η = ( ) a n,m ξ n m η ξ η. (4) ξ,η n,m So the new coecents of the matrx representaton α ξ,η are gven by α ξ,η = a n,m ξ n m η. (5) n,m 4

Ths can be wrtten agan usng a matrx multplcaton formalsm. Usng the same operator S we get that α ξ,η = n,m s ξ,n a n,m s η,m (6) = n,m s ξ,n a n,m ( s ) m,η or, n matrx form (usng the notaton à to wrte the operator A n the new bass) à = SAS. (7) The operator S s a untary operator, whch means t has an mportant property S S = SS =. (8) 3 Egenvectors and Egenvalues 3. Denton An Egenvector, v, of a matrx, M s dened as M v = λ v (9) where the scalar λ s the Egenvalue of the matrx. The nterpretaton of the egenvector s that of a vector that when s multpled by the matrx remans n the same drecton but only changes ts magntude. The way to nd the egenvalues of a matrx s the followng. Frst you calculate the characterstc polynomal of the matrx dened as M λi = 0 (0) where I s the unt matrx. Solvng for λ gves us the egenvalues of a matrx and then solvng 9 gves us the egenvectors (up to a multplcaton by a scalar). 3. Rotaton n D The rotaton of a coordnate system n D s done by the matrx ( ) cos θ sn θ sn θ cos θ Lets nd the egenvalues and egenvectors of ths matrx. The characterstc polynomal s λ cos θλ + = 0 or n other words λ λ(e θ + e θ ) + = 0 5

whose soluton s λ = e θ λ = e θ The egenvectors are gven by ( e θ + e θ e θ e θ ) eθ +e (x ) ( ) θ x = e θ e θ + e θ y y ( + e θ + e θ e θ + e θ whose soluton s ( ) The other egenvector s gven by ) ( ) ( ) x x = y y ( e θ + e θ e θ e θ ) eθ +e (x ) ( ) θ x = e θ e θ + e θ y y and ts soluton s ( ) We see that the egenvalues have a mgantude of whch s expected snce the matrx s untary (preserves the lengthes of vectors). 4 Dagonalzng a matrx Assume that A has n dstnct egenvalues. Then A s dagonalzable. Moreover, f P s the matrx wth the columns C, C,..., and Cn the n egenvectors of A, then the matrx P AP s a dagonal matrx (just lke equaton 7). As an example let us dagonalze the matrx 0 The polynomal s who has the trval soluton λ 3 + 4λ + 4λ = 0 λ = 0 The other two are gven by 6

λ = λ 3 = + and the egenvectors are 0 λ 3 λ So we have 0 λ 3 λ P = The nverse of P s gven by 0 P = λ 3 λ λ λ 3 (λ λ λ 3 λ λ λ 3 ) 3 So the dagonal matrx s gven by 0 0 0 0 P P = 0 λ 3 0 0 0 λ The dagonal matrx always has the egenvalues on the dagonal correspondng to the egenvectors column n P. 7