Topology
Topological Spaces
A coffee cup and a donut are the same object. To a topologist. Both have exactly one hole, and one deforms into the other without tearing. A sphere and a cube are also the same. But a sphere and a torus are different. This is not wordplay. This exact distinction is used in topological data analysis (TDA) to find structure in high-dimensional genomic and neural data.
- **Topological Data Analysis (TDA):** persistent homology finds 'holes' in point clouds in hundreds of dimensions - applied in genomics (cancer clusters), neuroscience (shape of neural activation patterns), and materials science
- **Mapper algorithm:** UMAP and t-SNE compress dimensions linearly; Mapper (Carlsson 2009) builds a topological graph of data - used to analyze brain activity patterns and predict cancer recurrence
- **Robotics:** the robot configuration space is a topological space; motion planning = finding a path avoiding obstacles in this space
Open Sets
In analysis, the open interval (0, 1) is a set where every point is surrounded by a 'buffer zone' lying entirely inside the set. Topology generalizes this intuition: an **open set** is a set declared to be open, provided the collection of such sets satisfies certain axioms.
**Three axioms of open sets:** 1. The empty set and the whole space X are open. 2. The union of any number of open sets is open. 3. The intersection of finitely many open sets is open. Why only finite? Because an infinite intersection of open sets may fail to be open.
A critical point: the notion of 'open' is not absolute - it is defined by the chosen topology. The same set can be open in one topology and not open in another. This freedom of choice is what makes topology so powerful.