Tag: linear order

Bootcamp 5 – Ramsey DocCourse Prague 2016

The following notes are from the Ramsey DocCourse in Prague 2016. The notes are taken by me and I have edited them. In the process I may have introduced some errors; email me or comment below and I will happily fix them.

Title: Bootcamp 5 (of 8)

Lecturer: Jan Hubička

Date: Friday September 30, 2016.

Main Topics: Rado Graph, Fraïssé’s Theorem, Examples of Fraïssé classes, Ramsey implies Amalgamation, Lifts and Reducts, Ramsey classes have linear orders

Definitions: Extension Property, Ultrahomogeneous, Universal, \text{Age}(A) , Fraïssé class, irreducible structure, Lifts/Expansions and Shadows/reducts.

Bootcamp 1 – Bootcamp 2 – Bootcamp 3 – Bootcamp 4 – Bootcamp 5 – Bootcamp 6 – Bootcamp 7 – Bootcamp 8

Continue reading Bootcamp 5 – Ramsey DocCourse Prague 2016

Reading the Dictionary

I have a confession to make: I am a bibliophile. Reading, owning, perusing, lending, alphabetizing and buying books are all things that make me happy. High on my list are hardcover graphic novels and quality dictionaries. One of the skills you learn quickly while reading a dictionary (so I hear) is how to look up words. Of course the words in a dictionary are laid out in a very orderly fashion; first the ‘A’s then the ‘B’s, etc.. This order turns out to be a useful example of an interesting linear order.

Example: Consider \{a,b,c\}\times\{a,b\} with the dictionary ordering. We get aa < ab < ba < bb < ca < cb .

In general to get a dictionary ordering on A\times B out of two linear orders A,B we do the following:

  1. Compare first elements. If they are the different, use the ordering on A.
  2. If the first coordinates are different, compare the second coordinates. If the second coordinates are different, use the ordering on B . If the second coordinates are the same, the elements you are comparing are the same (as they have the same first and second coordinates).

You can extend this process if you want and compare third, fourth or fifth coordinates if you start with three, four or five linear orders. Of course this is just saying something you already know; I don’t need to tell you how to figure out whether ‘oscillate’ comes before ‘ossifrage‘.

Example: Now my fellow sesquipedalians might be interested in the following linear order: Let D = \{*, a,b,c, \ldots, z\} where * < a < b < \ldots < z and * stands for a blank space. Now consider D^{189819} with the dictionary ordering. This will contain every English word both technical and non-technical. Granted it will also contain silly non-words like: “this*word*asserts*that*it*is*a*silly*word”.

Continue reading Reading the Dictionary

Creeping Along

In my ongoing love affair with compactness I am constantly revisiting a particular proof of the Heine-Borel theorem, a characterization of compactness in \mathbb{R} . There are two proofs that I know of: the standard “subdivision” proof and the “creeping along” proof. I am going to focus on the creeping along proof.

Heine-Borel Theorem. A subset A \subseteq \mathbb{R} is compact if and only if it is closed and bounded.

To do some creeping we need to collect some useful facts.

Fact 1. A subset \mathcal{A} \subseteq \mathbb{R} is bounded if and only if is contained in some closed interval [a,b]

Fact 2. The set \mathbb{R} is complete (as a linear order) because every non-empty set A \subseteq \mathbb{R} with an upper bound has a least upper bound, called \sup A .

Fact 3. Closed subsets of compact subsets of \mathbb{R} are in fact themselves compact. With fact 1 this means that it is enough to show that closed and bounded intervals in \mathbb{R} are compact. (In general closed subsets of compact T_2 spaces are compact.)

So now let us creep:

Continue reading Creeping Along