[-] HaSch@lemmygrad.ml 7 points 8 months ago

Andrei Kolmogorov organised the defence of Moscow in 1941 using statistics, and went on to formulate the axioms of probability theory.

Leonid Kantorovich made great progress in economic planning, numerical mathematics, and nuclear physics.

Lev Landau wrote what is to this day considered to be the most in-depth course in mathematical physics and explained superconductivity.

Andrei Markov developed the theory of Markov chains in probability theory and had a son who became a famous topologist.

Vladimir Smirnov worked on mechanics and differential equations and wrote a handbook of higher mathematics for engineers.

Sergei Sobolev is a household name to anyone who learns about functional analysis and PDEs. He invented distributions to generalise the concept of functions as solutions of differential equations.

Nikolai Bogolyubov solved many problems in mathematical physics and helped establish the theoretical foundations of renormalisation in QFT, which previously suffered from being mathematically dubious.

[-] HaSch@lemmygrad.ml 4 points 9 months ago

Adaptive Experimentation Facility

I am willing to bet real money that they fed the prompt "sinister building name" into an AI at least once

[-] HaSch@lemmygrad.ml 10 points 9 months ago* (last edited 9 months ago)

Marching band

I know it doesn't sound very athletic but have you TRIED playing a polka with three flats on the saxophone while also paying attention that you always put down your left foot on the 1, coordinate your sound with the trombonist next to you, and simultaneously trying to keep formation walking around the contorted corridors of a medieval timberframe town?

(It's also addictive af)

2

Comrades, today I had the pleasure of participating in our city's First of May demonstration, and to purchase two books from the local chapter of the MLPD (Marxist-Leninist Party of Germany). One of them is pretty well-known, it is the Dialectics of Nature by Friedrich Engels; the other was an obscure philosophy tract written by one Mr Oscar Creydt where he attempts to reframe the entire history of the universe from a ML point of view, which is why I went in there with high expectations, namely that it would use recent discoveries from natural science to develop new ML philosophy.

Unfortunately for me however, whilst the book started promising and ambitious and it does demonstrate a good grasp of the historical developments of quantum mechanics, by page 60 of 220 it occurs to the author that he wants to deny Einstein's theory of general relativity, arguably the most well-tested and internally consistent theory in all of physics. But this was only the hors-d'oeuvre of the work, he goes on to try and reduce every single phenomenon in the universe to the vibration inherent to photons (which he calls "radions"), he spouts metaphysical nonsense about why the speed of light is constant, he declares the cosmic microwave background radiation to be the "primitive stage" of this vibration because Big Bang cosmology isn't real either, and he makes no attempt to explain cosmological redshift, gravitational lensing, or the perihelion precession of Mercury with his mental construction.

Now bear in mind that I don't necessarily want to accuse the author of being bad at science. The foreword of the book explicitly remarks that due to the anticommunist Stroessner regime in Paraguay, he couldn't rely on qualified people to empirically test or mathematically proofread his work, it is possible that the libraries he frequented just didn't have reliable books on the topics, and even the best scientists might publish utter drivel after having to work in isolation for decades. However, it is obvious that the mistake with this approach is that you cannot start with your own interpretation of dialectical materialism, and then change science to fit into it. This is a misconception of ML philosophy which many theoretically-minded comrades have already exposed, including on this very website. The refutation to it is that rather than relying on some rigid dogma formulated by humans, nature begets the shape of her own dialectics via her own interactions with herself; which is why we must study nature to arrive at natural philosophy and not vice versa.

The last thing I want to remark is that, if instead it had been let's say a Christian fanfic of science, one would immediately have noticed from the lack of footnotes and historical background knowledge, the presence of biblical and other nonscientific references, the use of odd figures and diagrams derived from gnosticism, or the extensive use of all-capital letter words. Here, there were no such signs. Marxist-Leninist scientific malpractice is especially worrisome because you might not even notice it until several pages into the book and even then the errors are of a much more subtle nature and require background knowledge.

7
submitted 2 years ago* (last edited 2 years ago) by HaSch@lemmygrad.ml to c/mathematics@lemmygrad.ml

It is now over a year since I have sadly had to depart from my university upon obtaining my master's degree in mathematics. I have since obtained a job as a programming contractor, however classical mathematics done with pen and paper is still the love of my life. Luckily enough, I still live within two hours of my old campus, and I was able to obtain an external library card, which is my ticket to look into all the topics I missed out on for want of time (not all mathematical).

If anyone among you has a similar experience, I would like you to share your techniques, too. Be advised that my way might not be very efficient nor lend itself to people who still need to study for exams or have deadlines, because I am no longer under these pressures.

Scouting. The closer a field is to my interests, the more books I already know to be suitable or unsuitable for me to learn from. For me, the most important criterion for a maths or theoretical physics book is to have numerous exercises on many different levels of difficulty and abstraction. I also prefer the books that use familiar notations to my lectures, and those that are written in my native language. Least importantly, a little pet peeve of mine is that I don't like it when books are set in Times New Roman because I find the font hideous and I honestly can't bear to look at it for long periods of time.

Frequency. Due to my day job, I am usually unable to clear more than an hour each day to sit down and study. I tend to use this hour to either read through a chapter and fill in the blanks between the formulae and draw pictures, or to attempt to do the exercises when I am done with the required reading for them. If an exercise seems boring and not what I wanted to learn from the book, I still tend to look up the solution rather than not considering it at all.

Intensity. Because I am no longer under the pressure of cramming and deadlines, I might take longer or sometimes lack the motivation to learn a topic, but I also have the liberty to take a minute and ask questions about it for which there was no time during my student years. Unless there is an elephant in the room requiring more urgent attention, I always tend to go through three things to look for: Examples and applications, characteristics of the generic case and the singular cases, and analogies in the language of other fields.

Surroundings. I tend to learn at my desk for when I need to write or take notes, and from my bed when I don't, although I reckon that the latter is a bad habit. Although during my earlier time at uni I used to learn with classical or Latin music or even commentary, I now tend to find it too distracting and prefer silence for learning. For obvious reasons I learn alone now, but I have always found it more fun and also easier to have a study buddy.

HaSch

joined 3 years ago