====== 2020-02-21, Friday ====== $$\gdef\ot\otimes$$ ===== Tensor power of a vector space ===== Let $V$ be a finite dimensional vector space. We denote the $k$-th tensor power of $V$ as $$ V^{\otimes k} = \underbrace{V\ot \cdots \ot V}_{\text{ $k$ times} } $$ Its elements are linear combinations of terms like $v_1 \otimes \cdots \ot v_k$, subject to the usual linearity relations. It is sometimes useful to consider the tensor algebra (we only mention it here, but do not use it later in this course). ** Definition (Tensor Algebra $T(V)$ ) ** $$T(V) = \R \oplus V \oplus V^{\ot 2} \oplus \cdots \oplus V^{\ot 3} \oplus \cdots $$ Given two elements $T = w_1 \ot \cdots \ot w_k$ and $T' = v_1 \ot \cdots \ot v_l$, their products is defined by juxtapostion. $$ T \ot T' = w_1 \ot \cdots \ot w_k \ot v_1 \ot \cdots \ot v_l $$ ===== Exterior power of a vector space ===== ** Definition (Exterior product $\wedge^k(V)$)** The $k$-th exterior product $\wedge^k(V)$ is the vector space consisting of linear combinations of the following terms $v_1 \wedge \cdots \wedge v_k$, where the expression is linear in each slot, $$ c \cdot (v_1 \wedge \cdots \wedge v_k) = (c v_1) \wedge v_2 \wedge \cdots \wedge v_k $$ $$ (v_1+v_1') \wedge \cdots \wedge v_k = v_1 \wedge \cdots \wedge v_k + v_1'\wedge \cdots \wedge v_k$$ and the expression changes signs if we swap any two slots $$ v_1 \wedge \cdots \wedge v_i \wedge \cdots \wedge v_j\wedge \cdots \wedge v_k = - v_1 \wedge \cdots \wedge v_j \wedge \cdots \wedge v_i\wedge \cdots \wedge v_k, \forall 1 \leq i < j \leq k. $$ If $k=0$, we set $\wedge^0 V = \R$. If $k=1$, then $\wedge^1 V =V$. ** Proposition ** If we choose a basis $e_1, \cdots, e_n$ of $V$, then for $0 \leq k \leq n$, the space $\wedge^k(V)$ has a basis consisting of the following vectors $$ e_{i_1} \wedge \cdots \wedge e_{i_k}, \quad 1 \leq i_1 < i_2 < \cdots < i_k \leq n. $$ **Corrollary** * $\dim \wedge^k(V) = {n \choose k}$. * If $k > n$, then $\wedge^k V = 0$. Just as we defined tensor algebra $T(V)$, we may define the exterior algebra $\wedge^* V$. This turns out to be very useful. ** Definition(Exterior algebra $\wedge^* V$) ** $$ \wedge^* V := \bigoplus_{k=0}^{n} \wedge^k V, \quad \text{ where } \wedge^0 V:= \R.$$ The product between two elements is given by juxtaposition, more precisely, if $A = v_1 \wedge \cdots \wedge v_k \in \wedge^k V$, $B = w_1 \wedge \cdots \wedge w_l \in \wedge^l V$, then $$ A \wedge B := v_1 \wedge \cdots \wedge v_k \wedge w_1 \wedge \cdots \wedge w_l \in \wedge^{k+1} V.$$ ==== Relationship between quotient algebra and tensor algebra ==== - As quotient of tensor algebra - As subalgebra of tensor algebra ===== Differential Forms ===== $\Omega^k(M) = \wedge^k T^*M.$ One can do integration of $k$-forms on $k$-submanifold. ===== exterior differentiation ===== In local coordinates $(x_1, \cdots, x_n)$, given a differential $k$-form, we have $$ d (\sum_I f_I dx^I) = \sum_I d(f_I) \wedge dx^I = \sum_I \sum_{i=1}^n \frac{\d f_I}{\d x^i} dx^i \wedge dx^I $$