[julie1]

A branch of physics used to be taught a long time ago called "numerical analysis" to deal with this issue.

We even used to be careful about the difference between 'precise and exact'.

Pi = acos(0) is absolutely exact. But computer don't know about symbolic calculus. So to put the value in a register we used tricks.

Pi as a the converging value at the infinite of the Taylor development is awesome. But computer don't know about infinite.

3.1415926535897932384626433832795028841971 is precise.... it has a lot of digit and people loves that.

In ana num 3.15159 +- 0.00001 is exact. It bounds your result. Hence you can estimate your error and its propagation.

Because we thought humans were smart we thought that 3.14159 would be so meaningful people would understand that a constant should be considered to be exact with the implicit meaning that 9 was the last significant digit and people would be wise to use upper and lower bounds to estimates their results.

Then Computer Science was taught in university.

People not understanding why they had to study math and physics to simply program 2 + 2 and thought, stop bothering us. We just compute TVA we don't send a rocket to mars. Why learn boring math (integration, derivation, Newton's methods for approximation, Taylos's development, Cauchy Suites, condition of converging Suites, Integration in the complex field to compute generalized integrals, simplex, LU/RU matrices ....)

Yes people loves recurrence. They cannot apply the reasoning to simple maths series.

And that's how we have funny stuff like a lot of coder not understanding why :

   1.198 * 10.10
   12.099799999999998

Yes ... why are computers' maths so odd. What can we do about it?

Having a look at HP Saturn opcode makes you wonder if the lack of solution is because it does not exists or because people forgot. http://www.hpcalc.org/details.php?id=1693

[xiaq]

I can't speak for other nations, but they still teach numeric analysis in Chinese universities as an undergraduate course. In my university it is a required subject. Many of us have countless dreadful memories of Runge-Kutta method, Euler's method, Newton's method, rate of convergence, numerical stability and error margins, just to name a few of the dreads...

[julie1]

And this ? https://zh.wikipedia.org/wiki/%E6%91%84%E5%8A%A8%E7%90%86%E8... (pt https://pt.wikipedia.org/wiki/Teoria_de_perturba%C3%A7%C3%B5...) (fr https://fr.wikipedia.org/wiki/Th%C3%A9orie_des_perturbations)

[ovis]

Yes, perturbation methods are still taught and are still recognized as important. The first math course I took during my graduate degree (Intro analytic methods) covered it, for example.

[pedrosorio]

Same in Portugal

[kirrent]

Taught to me at university. Far more important in the age of computers than before.

[lucb1e]

> at university

In which country though?

[ninguem2]

Physics? Numerical analysis is Mathematics. It's still active and very important, e.g., in solving PDEs using the finite element method.

[julie1]

Mathematics? The people trying to find solutions of an equation by solving them?

Mathematicians is a weird education I hardly understand. The last PhD I met from Mc Gill university ignored the existence of non euclidean geometry. His excuse? He was on formal proof.

I am sorry, I have a hard time with people that never were challenged to make equations spit their solutions in order to make something actually work in the real world with limited time and money.

It is the same difference I see between athletes and ergotherapists, or Einstein and Poincaré.

[conceit]

> He was on formal proof.

Wat?

[thoth]

>A branch of physics used to be taught a long time ago called "numerical analysis" to deal with this issue.

Freshmen engineers had to take a year-long Numerical Analysis and FORTRAN programming class at my undergrad university. We would learn various iteration methods for solving equations and the homeworks would be more problems to solve with a program or two to write too.

This stuff is still taught, it just might be out of a different department than physics.

[SixSigma]

When you watch Walter Lewin's physics lectures, he repeatedly says "measurement means nothing without stating the uncertainty".

see - Lec 01: Units, Dimensions, and Scaling Arguments | 8.01 Classical Mechanics (Walter Lewin) [1]

[1] https://www.youtube.com/watch?v=X9c0MRooBzQ#t=4m30s

Physics Works !

[stephencanon]

Numerical analysis is the cornerstone of the applied mathematics curriculum, and still very much taught. Any applied mathematician, physicist, or engineer will have at least some background in the subject, and anyone with a good graduate degree will usually have taken two or three courses (source: I TA'd one of the graduate numerical analysis courses at Berkeley for a couple years, it was a requirement for many engineering grad students).