As I was shifting my books from one location to another, I found a big heap of books, I had not even started reading or looked at in detail. Being me, I got distracted by them and decided to at-least give them a chance to fulfill their destiny (to be read cover to cover by their owners or the friends of the owners).
I started with Tom Apostol's Mathematical Analysis. It is a wonderfully terse book and I found myself struggling by the time I reached the topic on "Point Set Topology". I had been through a quick journey of the past - real and complex numbers, sets and cardinality, prime numbers and many more things.
I also ran into the famous Cauchy-Schwarz inequality. I remember having proved the inequality in the exercise of Don Knuth's Art of computer programming volume I, but by now I had forgotten it all -- the sum manipulation, the whole of chapter 1 as hiding somewhere in my memory and seeking it was a hard/impossible task. This time, I found myself taking the help of a symbolic computation package - maxima. My dialog was as follows
(%i2) expand((a1^2 + a2^2)*(b1^2 + b2^2));
(%o2) a2^2*b2^2+a1^2*b2^2+a2^2*b1^2+a1^2*b1^2
(%i4) expand((a1b1 + a2b2)^2);
(%o4) a2b2^2+2*a1b1*a2b2+a1b1^2
(%i31) (a1^2 + a2^2)*(b1^2 + b2^2) - ((a1b1 + a2b2)^2);
(%o31) (a2^2+a1^2)*(b2^2+b1^2)-(a2b2+a1b1)^2
(%i32) expand(%);
(%o32) a2^2*b2^2+a1^2*b2^2+a2^2*b1^2+a1^2*b1^2-a2b2^2-2*a1b1*a2b2-a1b1^2
To cut the long output short, I ended up with Lagrange's inequality.
This is just a small part of the mathematics I have to (re)learn, there is also graph theory, game theory, probability theory, Markov chains and theory of computation.
All the mathematics is very exciting, but time consuming. I have loads of other information to read and digest. Let's see where all this I need to learn this crazy math attitude takes me.
Showing posts with label symbolic mathematics. Show all posts
Showing posts with label symbolic mathematics. Show all posts
Monday, January 07, 2008
Saturday, February 24, 2007
Using maxima -- baby steps
The use of symbolic computing makes it easy to visualize and solve problems that were otherwise dry and would put you to sleep. To test the simplicity of a freely available tool called maxima, I tried to solve a common problem with it.
The problem is quite simple, remember high school physics? Well I don't :-). Consider a tuning fork, which oscillates and produces a sound (depending on it's frequency).
We start by entering the mathematical model of the fork
'm*diff(x(t), t, 2)=-k*x(t);
Maxima prints

We now request maxima to solve the equation for us by
desolve([%],[x(t)]);
Maxima asks
Is k * m positive, negative, or zero? We say positive
Maxima prints

We ask maxima to simplify the result for us
radcan(%);
Maxima outputs

That's it, we have our solution.
The problem is quite simple, remember high school physics? Well I don't :-). Consider a tuning fork, which oscillates and produces a sound (depending on it's frequency).
We start by entering the mathematical model of the fork
'm*diff(x(t), t, 2)=-k*x(t);
Maxima prints

We now request maxima to solve the equation for us by
desolve([%],[x(t)]);
Maxima asks
Is k * m positive, negative, or zero? We say positive
Maxima prints

We ask maxima to simplify the result for us
radcan(%);
Maxima outputs

That's it, we have our solution.
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