Biology, Murderous Maths

The All Common Ancestors Generation

This project is a simulation of how many people can stem from the same ancestor, something Simon has learned from James Grime’s “Every Baby is a Royal Baby” video on Numberphile. In this simplified version, there’re only 6 people per generation. Simon was throwing two dice to determine who the two parents were for every person (in the case when both dice came out to be the same number, this was considered “virgin birth” or simply that the father had come from outside the limited sample Simon was working with).

the present generation
Simon marking who the children of a person were in pink pencil
Some parents don’t have the digits corresponding to their children written next to them, but letters N and E: N means that that person from the parent generation had no children and is therefore related to no one from the future generations; E on the conrrary, means that that person “has been busy” and is related to everyone in the next generation!
identifying the most recent common ancestor generation and the identical ancestors generation
the all common ancestors generation
Coding, Milestones, Murderous Maths, Simon's Own Code, Simon's sketch book

Multiplicative Persistence in Wolfram Mathematica

Simon has tried Matt Parker’s multiplicative persistence challenge on Numberphile: by multiplying all the digits in a large number, looking for the number of steps it takes to bring that large number to a single digit. Are there numbers that require 12 steps (have the multiplicative persistence of 12)?

Simon explaining the project

Simon has worked on this for two days, creating an interface in Wolfram Mathematica. He wrote the code to make the beautiful floral shapes above, they are actually graphs of how many steps three digit numbers take to get to single digit numbers (each ”flower” has the end result at its center).

What about the numbers with many more digits than three? Simon has tried writing code to look for the multiplicative persistence of really large numbers and also came up with some efficiencies, i.e. shortcuts in the search process. He did manage to find the persistence for 2^233 (the persistence was 2):


persistence for 2^233

However after he applied one of his efficiencies to the code to be able to search through many numbers at once, the code didn’t run anymore. You can read Simon’s page about this project and see his code here:

https://www.wolframcloud.com/objects/monajune0/Published/persistence.nb

Simon writes:

277777788888899 is the smallest number with a persistence of 11.
The largest known is 77777733332222222222222222222:

This code works with a few efficiencies:
1. They’ve already checked up to 10^233, so we don’t have to check those again.
2. We can rearrange the digits, and the multiplication will be the same. So we don’t have to check any of the rearrangements of any of the numbers we’ve already checked.
3 
3a. We should never put in a 0 (a digit of the number). Because then you would be multiplying by 0, which would result in 0 in 1 step!
3b. We should also never put in a 5 and an even number. Because, in the next step, the number would be divisible both by 5 and by 2, so it’s also divisible by 10. That would put a 0 in the answer, which we saw we should never do!
3c. With similar reasoning (assuming we want to find the smallest number of the type we want), we’ll see we should never put in:
– Two 5s
– A 5 and a 7
– When we put in a… (- means anything, the order doesn’t matter):
1,- , remove the 1
2,2, put 4 instead
2,3, put 6 instead
2,4, put 8 instead
3,3, put 9 instead
So, we can reduce the search space and time collossaly, with just some logic!

Murderous Maths, Simon teaching, Simon's sketch book

Larger than Graham’s number!

Simon explains strong and weak tree sequences and reveals the greatest finite number used in mathematics: TREE(3), a lot larger than Graham’s number. The TREE sequence is a fast-growing function arising out of graph theory.

Simon comments: “What is you make TREE(TREE(3))?”

Inspired by:
http://googology.wikia.com/wiki/TREE_sequence 
https://www.youtube.com/watch?v=3P6DWAwwViU

Logic, Milestones, Murderous Maths, Notes on everyday life, Simon teaching

On Incompleteness

Simon is enchanted by Gödel’s incompleteness theorem (that he has learned about from Numberphile) and keeps talking about it:

“There’re problems that we just can’t solve. But if we prove that we can’t prove them, then we prove them! We can’t prove that we can’t prove that we can’t prove, and so on… Quirky! Standard math doesn’t really accept that because the statement goes on forever: you’ll just never get to what we can’t prove. What follows from Gödel’s incompleteness theorem is that that statement is actually true!”

The same evening, Simon is also bothered about the lies pupils are told in school. He repeatedly quotes James Grime that it’s a big lie that mathematics is about numbers. — “What is mathematics about? Mathematics is actually about proving! But there’s one more lie that even professional mathematicians don’t know. It’s that it’s about logic. Actually, mathematicians are a lot more creative!”