Slide transcript#

I am working on finding ways to increase accessibility of the beamer slides provided. The following is an automatically generated transcript from the pdf of the slides but is still not perfect. I would be happy to hear feedback on how this transcript can be improved for additional usefulness.

Lecture 5 - Here Comes the Homology#

Goals#

Goals for today:

  • Ch 2.4: Cycles and Boundaries

Linear Algebra Review & Homology#

Definition: A field \((k,+,\cdot)\) is a set \(k\) with two operations \(+\) and \(\cdot\) such that for any \(a,b,c \in k\):

  • Closure:

  • Commutativity:

  • Associativity:

  • Identity:

  • Inverses:

  • Distributivity:

Examples:

Vector space#

Definition: A vector space over a field \(k\) is a set \(V\) with vector addition and scalar multiplication such that

  • Associative \(+\):

  • Commutative \(+\):

  • Identity

  • Inverses:

  • Scalar vs. field mult:

  • Distributivity:

Examples:

Basis#

Definition: A basis for a vector space \(V\) is a collection of vectors \(\{b_\alpha\}_{\alpha \in A}\) such that

  • they are linearly independent and,

  • they span \(V\).

Goal#

Build a vector space from a simplicial complex!

\(p\)-Chains#

Let \(K\) be a simplicial complex and fix a dimension \(p\). A \(p\)-chain is a finite formal sum of \(p\)-simplices in \(K\), written $$\alpha = \sum a_i \sigma_i

\[ \begin{align}\begin{aligned}![image](../Figures/SimplexExamples_WithTet-web.png) ## Addition of chains\\$p$-chains are added component-wise: if $\alpha = \sum a_i \sigma_i$ and $\beta = \sum b_i \sigma_i$, then $\alpha + \beta =$ ## Chain group\\The collection of $p$-chains with addition is called the $p^\text{th}$-chain group (vector space), $C_p(K)$.\\**Some checks**\\- Associative $+$:\\- Commutative $+$:\\- Zero element\\- Inverses: ## Linear Transformations\\A linear transformation between two vector spaces $V$ and $W$ is a map $T:V\to W$ such that the following hold:\\- - \\Matrix representation: ## Boundary maps[^1]\\$$\begin{matrix} \partial _p: & C_p(K) & \to & C_{p-1}(K)\ & \sigma = [v_0,\cdots,v_p] & \mapsto & \sum_{j=0}^p[v_0,\cdots,\widehat{v_j}, \cdots v_p] \end{matrix}\end{aligned}\end{align} \]

Checking linearity#

\[\partial_p(\alpha + \beta) = \partial_p(\alpha) + \partial_p(\beta); \hspace{.5in} \alpha = \sum a_i \sigma_i,\qquad \beta = \sum b_i, \sigma_i\]

Homework#

image

  • \(\partial_1([a,e]) =\)

  • \(\partial_1([a,e] + [b,e]) =\)

  • \(\partial_1([a,e] + [c,e] + [c,d] + [a,d]) =\)

  • \(\partial_2([a,c,e] + [a,c,d]) =\)