Ciro Santilli @cirosantilli 40

The intersection of two beautiful arts: coding and physics!

Computational physics is a good way to get valuable intuition about the key equations of physics, and train your numerical analysis skills:

Other child sections:

Finance is a cancer of society. But I have to admit it, it's kind of cool.

arstechnica.com/information-technology/2016/11/private-microwave-networks-financial-hft/ The secret world of microwave networks (2016) Fantastic article.

As mentioned at Section "Computer security researcher", Ciro Santilli really tends to like people from this area.

Also, the type of programming Ciro used to do, systems programming, is particularly useful to security researchers, e.g. Linux Kernel Module Cheat.

The reason he does not go into this is that Ciro would rather fight against the more eternal laws of physics rather than with some typo some dude at Apple did last week and which will be patched in a month.

Static case of Maxwell's law for electricity only.

Is implied by Gauss' law if Maxwell's equations: physics.stackexchange.com/questions/44418/are-the-maxwells-equations-enough-to-derive-the-law-of-coulomb

The "static" part is important: if this law were true for moving charges, we would be able to transmit information instantly at infinite distances. This is basically where the idea of field comes in.

Two symmetric matrices $A$ and $B$ are defined to be congruent if there exists an $S$ in $GL(n)$ such that:

A conjecture is an open problem in mathematics for which some famous dude gave heuristic arguments which indicate if the theorem is true or false.

A Drosophila melanogaster has about 135k neurons, and we only managed to reconstruct its connectome in 2023.

The human brain has 86 billion neurons, about 1 million times more. Therefore, it is obvious that we are very very far away from a full connectome.

Instead however, we could look at larger scales of connectome, and then try from that to extract modules, and then reverse engineer things module by module.

This is likely how we are going to "understand how the human brain works".

Some notable connectomes: