# Numerical integration.

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# Numerical integration

In analysis, numerical integration comprises a broad family of algorithms for calculating the numerical value of a definite integral.

All numerical approximations of the integral $\int_{a}^{b} f(x)dx$ will start with a partition of the interval [a, b] into n equal parts, a = x0 < x1 < ··· < xn = b, Δx = xi-xi-1, y0 = f(x0), y1 = f(x1), ···, yn = f(xn). Loosely speaking, we want to average or add the y’s to get an approximation. We define the left Riemann sum as follows = (y0 + y1 + ··· + yn-1)Δx = f(x0)Δx + f(x1)Δx + ··· + f(xn-1)Δx = $\sum_{k=0}^{n-1} f(x_k)Δx$, and the right Riemann sum is defined similarly = (y1 + y2 + ··· + yn)Δx = f(x1)Δx + f(x2)Δx + ··· + f(xn)Δx = $\sum_{k=1}^{n} f(x_k)Δx$ -Figure 1.b.-

A trapezoid is a four-sided region with two opposite sides parallel. Given a partition of [a, b] as above, we can define the associated trapezoid sum to correspond to the area shown below. The area of a trapezoid is the average length of the parallel sides, times the distance between them, e.g., base * average_height = Δx(y2+y32). Adding all the areas of the individual trapezoids together, gives the trapezoid sum: $Δx(\frac{y_0+y_1}{2} + \frac{y_1+y_2}{2} + ··· + \frac{y_{n-1}+y_n}{2}) = Δx(\frac{y_0}{2} + y_1 + y_2 + ··· y_{n-1}+\frac{y_n}{2}) = \frac{left Riemann Sum + Right Riemann Sum}{2}$ -Figure 1.c.-.

Simpson’s rule gives us another approximation of the integral. Again, we start by partitioning [a, b] into intervals all of the same width, but this time we must use an even number of intervals, so n needs to be even. We are going to use a parabola through the three points (xk-1, f(xk-1)), (xk, f(xk)), and (xk+1, f(xk+1)), and the area under the parabola (it is left as an exercise) equals base*average height = $2Δx(\frac{y_{k-1}+4y_k+y_{k+1}}{6})=\frac{b-a}{3n}[f(x_{k-1})+4f(x_k)+f(x_{k+1})]$, and the total sum is $\frac{Δx}{3}((y_0+4y_1+y_2) + (y_2+4y_3+y_4) + ··· (y_{n-2}+4y_{n-1}+y_n))$ = 🚀

=[🚀] $\frac{Δx}{3}(y_0 +4y_1 +2y_2 +4y_3 + ··· + 2y_{n-2}+4y_{n-1}+y_n)$ -Figure 1.d.- Here, the coefficients 1, 4, and 2 alternate. Simpson's Rule is more accurate than the trapezoidal rule for approximating integrals because it uses quadratic functions to model the curve. It provides a good balance between simplicity and accuracy for numerical integration. Futhermore, it is exact when integrating polynomials of degree 3 or less.

# Example

$\int_{1}^{2} \frac{dx}{x}= ln(x)\bigg|_{1}^{2} = ln(2) -ln(1) = ln(2)$ ≈ 0.693147 where b = x2 = 2, y2 = 2, x1 = 3/2, y1 = 2/3, a = x0 = 1, y0 = 1, b -a = 1, n = 2, $\Delta x = \frac{b-a}{n} = \frac{1}{2},$ Figure 1.a.

1. Trapezoidal rule. $\Delta x(\frac{1}{2}y_0 + y_1 + \frac{1}{2}y_2)=\frac{1}{2}(\frac{1}{2})·1 + \frac{2}{3} + \frac{1}{2}·\frac{1}{2}$ ≈ 0.96 it is obviously not a good approximation 😞, but it was expected we should split the interval into more subintervals.

2. Sympson’s rule. $\frac{\Delta x}{3}(y_0 +4y_1 +y_2) = \frac{1}{6}(1 + 4·\frac{2}{3}+\frac{1}{2}) ≈ 0.69444$ that is surprisingly a relatively good approximation of the correct value.

# Exercise

$\int_{-∞}^{∞} e^{-t^{2}}dt$ =[Recall F(x) = $\int_{0}^{x} e^{-t^{2}}dt$] 2F(∞) =[F(∞)=$\frac{\sqrt{π}}{2}$] $\sqrt{π}$ -Figure 1.b.-.

Volume of the function 0 < y < x rotated around y-axis, $\int_{0}^{1} 2π(x-x^3)dx = π(x^2-\frac{x^4}{2})\bigg|_{0}^{1} = π(1-\frac{1}{2}) = \frac{π}{2},$ Figure 1.c.

# Bibliography

1. NPTEL-NOC IITM, Introduction to Galois Theory.
2. Algebra, Second Edition, by Michael Artin.
3. LibreTexts, Calculus. Abstract and Geometric Algebra, Abstract Algebra: Theory and Applications (Judson).
4. Field and Galois Theory, by Patrick Morandi. Springer.
5. Michael Penn, and MathMajor.
6. Contemporary Abstract Algebra, Joseph, A. Gallian.
7. YouTube’s Andrew Misseldine: Calculus. College Algebra and Abstract Algebra.
8. MIT OpenCourseWare 18.01 Single Variable Calculus, Fall 2007 and 18.02 Multivariable Calculus, Fall 2007.
9. Calculus Early Transcendentals: Differential & Multi-Variable Calculus for Social Sciences.
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