Chebyshev Polynomials in the 16th Century (2022)
arxiv.org
arxiv.org
https://ar5iv.org/html/2203.10955
I am getting more and more excited about converting TeX sources to HTML5 to be more accessible to students and researchers.
I do think PDF is still king for final results and of course print, but the accessibility and searchability the web format provides is fantastic.
Something that has always confused me about these Russians, Chebyschev and Krylov, what use did they have for their iterative methods and subspaces? I guess they weren’t solving big sparse linear systems on distributed computers in the year 1900.
For Chebyshev, who devoted his life to the construction of various 'mechanisms' [1][2], his motivation was to determine the parameters of mechanisms (that minimizes the maximal error of the approximation on the whole interval).
In the course of developing that theory he founded the modern field of approximation theory, and the St. Petersburg school of mathematics. I think his approach of using applied problems and techniques to inform the development of pure math deeply influenced the whole of Soviet and Slavic mathematics in the century that followed
(and yes, the book by Karl-Georg Steffens is beautiful!)
Edit: To answer the grandparent's question, aside from things directly invented by Chebyshev or his students, often things are called "Chebyshev" when there's either a Chebyshev polynomial or a minimax problem lurking in the background
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1. I may have this confused with my similar investigations into Mersenne primes and x^p-1=0.
2. My hypothesis that I could find factors of a Fermat number with n > 5 by multiplying the roots together and setting x = 2 failed on writing a program to actually check the result, but looking back on my memories of doing this, I may have made an error.
https://en.wikipedia.org/wiki/Chebyshev_nodes
The nth roots of unity are incredibly well studied, and some of that stemmed in the 1700-1800s on trying to factor things. The entire field of analytic numbers theory has taken these ideas to incredible (think decades of study and research to be state of the art) depths.
Up to around 1940, the vast majority of the world's computers were people, and there were legions of them across all areas of government and industry.
There were around 250 total automated computers in 1955, around 20,000 in 1965, so I doubt human computers were outnumberd until the 1970s/1980s at best.
s/people/women/g
https://www.smithsonianmag.com/science-nature/history-human-...
No need to promote sex-based divisiveness.
From your own link:
"So the French mathematician Alexis-Claude Clairaut decided to break the work up—by dividing the calculations among several people. In 1757, he sat down with two friends, the young astronomer Jérôme-Joseph Lalande and Nicole-Reine Lepaute, a clockmaker’s wife with a penchant for numbers. ... The age of human computers began."
"By the 19th century, scientists and governments were beginning to collect reams of data that needed to be processed, particularly in astronomy, navigation and surveying. So they began breaking their calculations down into tiny basic math problems and hiring gangs of people to solve them. The work wasn’t always hard, though it required precision and an ability to work for long hours. Mostly, the computers were young men."
"But by the late 19th century, some scientists realized that hiring women could reduce the cost of computation. The growth of education and middle-class prosperity had produced a generation of young women trained in math. So when the Harvard Observatory decided to process years of astronomic data it had gathered using its telescope, it assembled one all-female team of computers."
With the revenue secured by that job, he decided that he can afford to marry my mother.
The odd thing with what I listed is that these methods (nowadays) are really mostly useful for massive sparse problems, which wouldn’t really be practical without computing machines.
I’m pretty sure the Chebyschev semi-iterative method for solving linear systems is just named after his polynomials (and you can use his polynomials by hand for other stuff), but I really am at a loss as to what Krylov was up to.
The minimax property is one of the ways you can generalize to other kinds of sets, allowing you to talk about the Chebyshev polynomial of, say, an arc or a Jordan curve or a union of intervals, and many of the properties enjoyed by the classical Chebyshev polynomials end up carrying over as well, but faaaaar less is known about these generalizations. In many cases all you can hope for are asymptotics, and you need much more in the way of machinery and sophisticated tools to prove anything -- even to compute explicit formulas for the coefficients.
The classical case is nice though because they can be explored fruitfully without very much background