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Infinite Limits in Python

This talk got re-worked as The $\sin(x)$ Button.

This talk uses a bit of Python code.

You can download the relevant code here.

First, we consider the following mysterious function in Python.

def mystery(x, N):
    """This mystery function outputs some value based on x and N.
    We assume that x is a real number, and N is a positive integer."""

    output = 0;

    for n in range(0, N + 1):
        output += ((-1)**n)*(x**(2*n+1))/(math.factorial(2*n+1));

    return output;

Our big question today is:

What is this function calculating?

We will try various strategies to get a handle on it.

  1. Calculate some specific values of the function.

  2. Write a function table(C,R) which produces a similar table of values with columns $x = 0, 1, 2, \dots, C$ and rows $N = 1, 2, \dots, R.$ Your function should return a two dimensional array of values.

For reference, the output of table(10,10).
$x = 0$ $x = 1$ $x = 2$ $x = 3$ $x = 4$ $x = 5$ $x = 6$ $x = 7$ $x = 8$ $x = 9$ $x = 10$
$N = 1$ $0.0000$ $0.8333$ $0.6667$ $-1.5000$ $-6.6667$ $-15.8333$ $-30.0000$ $-50.1667$ $-77.3333$ $-112.5000$ $-156.6667$
$N = 2$ $0.0000$ $0.8417$ $0.9333$ $0.5250$ $1.8667$ $10.2083$ $34.8000$ $89.8917$ $195.7333$ $379.5750$ $676.6667$
$N = 3$ $0.0000$ $0.8415$ $0.9079$ $0.0911$ $-1.3841$ $-5.2927$ $-20.7429$ $-73.5097$ $-220.3683$ $-569.4268$ $-1307.4603$
$N = 4$ $0.0000$ $0.8415$ $0.9093$ $0.1453$ $-0.6617$ $0.0896$ $7.0286$ $37.6940$ $149.4998$ $498.2002$ $1448.2716$
$N = 5$ $0.0000$ $0.8415$ $0.9093$ $0.1409$ $-0.7668$ $-1.1336$ $-2.0603$ $-11.8422$ $-65.6961$ $-287.9615$ $-1056.9392$
$N = 6$ $0.0000$ $0.8415$ $0.9093$ $0.1411$ $-0.7560$ $-0.9376$ $0.0372$ $3.7172$ $22.5894$ $120.2379$ $548.9652$
$N = 7$ $0.0000$ $0.8415$ $0.9093$ $0.1411$ $-0.7568$ $-0.9609$ $-0.3224$ $0.0867$ $-4.3167$ $-37.2105$ $-215.7512$
$N = 8$ $0.0000$ $0.8415$ $0.9093$ $0.1411$ $-0.7568$ $-0.9588$ $-0.2748$ $0.7407$ $2.0142$ $9.6767$ $65.3945$
$N = 9$ $0.0000$ $0.8415$ $0.9093$ $0.1411$ $-0.7568$ $-0.9589$ $-0.2798$ $0.6470$ $0.8294$ $-1.4281$ $-16.8119$
$N = 10$ $0.0000$ $0.8415$ $0.9093$ $0.1411$ $-0.7568$ $-0.9589$ $-0.2794$ $0.6580$ $1.0100$ $0.7135$ $2.7611$
  1. If you examine the table of values, then you’ll notice that mystery(x,N) eventually stops changing as a function of $N$. That is, the value of mystery(x,N) is essentially the same for all large values of $N$. We call this the limiting value of the function. To be concrete, we say that two numbers $a$ and $b$ are essentially the same if they differ by less than $10^{-10}$. $$ |a - b| < 10^{-10} = 0. 000 000 000 1 $$ Create a new Python function limit(x) which calculates the limiting value of mystery(x,N) for each $x$. You will want to use the built-in Python function abs() to compute the absolute value.

  2. Use Python to approximate the smallest and biggest values of mystery(x,N) on the domain $-3 \leq x \leq 3$ when $N$ is big. To do so, calculate the value of limit(x) at a large number of points in the domain $-3 \leq x \leq 3$. Your final answers for the biggest and smallest values should specify both: the value of limit(x) and the x where this value is obtained.

  3. On paper: If you look carefully at the code, you’ll notice that mystery(x,N) is a sum of powers of $x$. Write it out as a polynomial, for $N = 3$. To do so, you are going to need to use the factorial function. The function math.factorial(n) computes the product of the first $n$ whole numbers. For example, $$ \texttt{math.factorial(4)} = 1 \cdot 2 \cdot 3 \cdot 4 = 24. $$ In mathematics, we usually write the factorial function as $n!$ because it grows so quickly. It’s a very exciting function!

  4. In Desmos: Graph the function mystery(x,N) with a slider for $N$. Notice that mystery(x,N) is a summation from $n = 0$ to $n = N$. In Desmos, typing sum produces a summation sign $\displaystyle \sum_{n=}$.

  5. What is the mystery function calculating?

Acknowledgements

Thanks to Mr. Nanthivarman for inviting me to speak at Lester B Pearson Collegiate Institute. Thanks to the following people for feedback on early drafts of this talk.

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Published: Feb 5, 2024

Last Modified: Mar 26, 2024

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