Special and General Relativity Lecture Notes: Day 2 (08/29/08) Haridis Pal, Benjamin Hall Contents 1 Vectors 1.1 Vector Types . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 1-form . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 2 3 2 Tensors 2.1 Tensor Types . 2.2 Transformations 2.3 Other examples: 2.4 Other types: . . 4 4 4 4 5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Homework from Lecture 1 5 4 Next Class 4.1 Reading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Exercises . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Topics for next class . . . . . . . . . . . . . . . . . . . . . . . 5 5 5 5 1 1 Vectors 1.1 Vector Types • as displacement • as operators • by components • basis vectors • as geometrical objects Note that, for vectors: 1. index location matters 2. Einstein index summation applies There are 2 types of vectors distinguished by placing the indices as a superscript or a subscript: dxa (λ) dλ ∂φ = ∂xa Va = (1) Va (2) where φ and λ are scalars. Also, they are differentiated by the way they transform: Let xa → X A (xa ), then: VA ≡ ∂φ ∂xa ∂φ ∂xa ≡ = Ua ∂X A ∂X A ∂xa ∂xA (3) Note: In this sense, the position vector is not a vector, but change in position is. 2 Although we have 2 types of vectors, our definition is slightly different from a mathematician’s definition: V a e~a ' V ' e~a Va (4) Above e~a are basis vectors, not necessarily normalized • Basis vectors exist. • Come in two types. • Conventional relation: ea eb = δab Now, V → v a ∂x∂ a . Here 1.2 ∂ ∂xa (5) behaves as e~a , i.e., as basis vectors. 1-form ∂φ a dx ∂xa V 2 = v a va dφ = 3 (6) (7) 2 Tensors 2.1 Tensor Types If v a , wa are vectors, (i.e. first rank tensors), then we can form new quantities called tensors: y ab = v a wb , v a zb , va zb (8) All these are second rank tensors of different type. 2.2 Transformations Transformation → y AB = 2.3 ∂xA ∂xB ab y ∂xa ∂xb Other examples: • Mba Ndb = Pda • gab g bc = δac v a → called contravariant; va → called covariant. Let’s see how much we can proceed further without using a metric. Let Aa ,Ba → matrices such that Aa Bb = Mba M |n×n = εabc...n Msa Mrb Mtc ...Mba εsrt...n ∂φ Henceforth we will write ∂x a as ∂a φ. The covariant way to write this is ∇a φ. 4 (9) 2.4 Other types: • ∂i Bj − ∂j Bi : exterior derivative • vj = Ai ∂i Bj + Bi ∂j Ai : lieder, transform as a vector • y a = Mba V b ; xa Mba = Zb 3 Homework from Lecture 1 Example of scalars without using the metric: 4 R ∇a φdxa , εabc Aa Bb Cc Next Class 4.1 Reading Handout #3 and #5 4.2 Exercises Problems 1 - 3 on http://www.phys.ufl.edu/courses/phz6607/fall08/Questions.pdf 4.3 Topics for next class • Parameterized curves • Metric 5