Notes & Textbooks

Computer science

1. How to cope with NP-hardness

2. Generating graphs

3. Three formats: graph6, sparse6 and digraph6

4. NP in Graph Theory

5. NP in Group Theory

6. Clusters and nodes

7. Compute Canada

8. What is latexify_py? Mathematical description for your Python function

9. Venn diagram plotting routines for Python/Matplotlib:

import matplotlib.pyplot as plt

from matplotlib import venn2

venn2(

subset = (1,2,3)

set_labels = ("good","bad")

)

plt.show()

10. pix2tex is a Python library that allows you to convert images of equations into LaTeX code.

11. pdoc:Automatically generate API documentation based on the docstrings of your Python files and objects.

Algebraic Graph Theory

1. Graphical Regular Representation

2. Transitive Graphs

3. Realizing groups as automorphism groups of graphs.

4. Toroidal Groups

Linear Algebra

1. Diagonalizable matrices

Geometric/Combinatorial Group Theory

1. Properly Discontinuous Action

2. Can – or can’t – act on Trees.

3. Weird Groups

4. Accessibility, cycle space and cut space

5. Pair of Ends of Groups

6. Refining Boundary: From End Space to Hyperbolic Boundary

7. What is Morse Boundary?

Miscellaneous

1. Life as a PhD student.

2. Recurrence Relations and Generating Functions by Chung-Chih Li and Kishan Mehrotra.

3. Will machines change mathematics? by Maia Fraser, Andrew Granville, Michael H. Harris, Colin McLarty, Emily Riehl and Akshay Venkatesh.

4. Some thoughts on automation and mathematical research by Akshay Venkatesh.

5. Abstraction boundaries and spec driven development in pure mathematics by Johan Commelin and Adam Topaz.

6. Is deep learning a useful tool for the pure mathematician? by Geordie Williamson.

7. How machines can make mathematics more congressive by Eugenia Cheng.