Blog Entry © Thursday, May 14, 2026, by James Pate Williams, Jr. More Numerical Integration Results

// NumericalIntegrals.cpp (c) Thursday, May 14, 2026
// by James Pate Williams, Jr., BA, BS, MSwE, PhD

#include <iomanip>
#include <iostream>
#include <vector>
#include <stdlib.h>

static double f(double x) {
    return sin(x);
}

static double MonteCarlo(double a, double b,
    double (*f)(double), int n){ 
    double sum = 0;

    for (int i = 0; i < n; i++) {
        double x = (b - a) * (double)rand() / RAND_MAX;

        sum += f(x);
    }

    return (b - a) * sum / n;
}

static double Factorial(int n) {
    double factorial = 1.0;

    for (int i = 2; i <= n; i++)
        factorial *= i;

    return factorial;
}

static double Series(double a, double b, int n)
{
    double sumA = 0.0, sumB = 0.0;
    int sign = 1;

    for (int i = 0; i <= n; i++) {
        sumA += sign * pow(a, 2 * i + 2) /
            Factorial(2 * i + 2);

        sign *= -1;
    }

    sign = 1;

    for (int i = 0; i <= n; i++) {      
        sumB += sign * pow(b, 2 * i + 2) /
            Factorial(2 * i + 2);

        sign *= -1;
    }

    return sumB - sumA;
}

static double CompositeTrapezoidalRule(
    double a, double b, int n) {
    double pi = 4.0 * atan(1.0);
    double endPts = 0.5 * (f(a) + f(b));
    double sum = 0, xk = 0.0;
    double h = (b - a) / n;

    for (int k = 1; k <= n - 1; k++) {
        xk = a + k * h;
        sum += f(xk);
    }

    return h * (0.5 * endPts + sum);
}

static double SimpsonsRule(
    int n, double a, double b, double(*fx)(double)) {
    double h = (b - a) / n;
    double h2 = 2.0 * h;
    double s = 0.0;
    double t = 0.0;
    double x = a + h;

    for (int i = 1; i < n; i += 2) {
        s += fx(x);
        x += h2;
    }

    x = a + h2;

    for (int i = 2; i < n; i += 2) {
        t += fx(x);
        x += h2;
    }

    return h * (fx(a) + 4 * s + 2 * t + fx(b)) / 3.0;
}

static void Romberg(double a, double b,
    double (*f)(double), int mStart, int nRow,
    std::vector<std::vector<double>>& T) {
    int m = mStart;
    double h = (b - a) / m;
    double sum = 0.5 * (f(a) + f(b));

    if (m > 1) {
        for (int i = 1; i <= m - 1; i++) {
            sum += f(a + i * h);
        }
    }

    T[0][0] = sum * h;

    std::cout << "romberg t-table" << std::endl;
    std::cout << std::fixed;
    std::cout << std::setprecision(5) << T[0][0];
    std::cout << std::endl;

    if (nRow < 2)
        return;

    for (int k = 2; k <= nRow; k++) {
        h /= 2.0;
        m *= 2;
        sum = 0.0;

        for (int i = 1; i <= m; i += 2) {
            sum += f(a + i * h);
        }

        T[k][1] = 0.5 * T[k - 1LL][1] + sum * h;

        for (int j = 1; j <= k - 1; j++) {
            T[k - 1LL][j] = T[k][j] - T[k - 1LL][j];
            T[k][j + 1LL] = T[k][j] + T[k - 1LL][j] /
                (pow(4.0, j) - 1.0);
        }

        for (int j = 1; j <= k; j++) {
            std::cout << std::fixed;
            std::cout << std::setprecision(5);
            std::cout << T[k][j] << '\t';
        }

        std::cout << std::endl;
    }

    if (nRow < 3) {
        return;
    }

    std::cout << "table of ratios" << std::endl;
    double ratio = 0.0;

    for (int k = 1; k <= nRow - 2; k++) {
        for (int j = 1; j <= k; j++) {
            if (T[k + 1LL][j] == 0.0) {
                ratio = 0.0;
            }

            else {
                ratio = T[k][j] / T[k + 1LL][j];
            }

            T[k][j] = ratio;
        }

        for (int j = 1; j <= k; j++) {
            std::cout << std::fixed;
            std::cout << std::setprecision(5);
            std::cout << T[k][j] << '\t';
        }

        std::cout << std::endl;
    }
}

double MonteCarloVolume(double R, int n)
{
    double pi = 4.0 * atan(1.0), pi2 = 2.0 * pi;
    double R2 = R * R, sum = 0;

    for (int i = 0; i < n; i++)
    {
        double r = R2 * (double)rand() / RAND_MAX;
        double t = pi * (double)rand() / RAND_MAX;
        double p = pi2 * (double)rand() / RAND_MAX;
        sum += r * r * sin(t);
    }

    return R * pi * pi2 * sum / n;
}

int main()
{
    srand(1);
    std::vector<std::vector<double>> T;
    T.resize(35);
    for (int i = 0; i < 35; i++) {
        T[i].resize(35);
    }
    Romberg(0.0, 2.0, f, 2, 7, T);
    std::cout << std::setprecision(11);
    std::cout << "analytic integral of sine = " << -cos(2.0) + cos(0.0);
    std::cout << std::endl;
    std::cout << "simpson's rule integral   = " << SimpsonsRule(500, 0, 2.0, f);
    std::cout << std::endl;
    std::cout << "monte carlo integral      = " << MonteCarlo(0.0, 2.0, f, 2130);
    std::cout << std::endl;
    std::cout << "infinite series integral  = " << Series(0.0, 2.0, 16);
    std::cout << std::endl;
    double integral = CompositeTrapezoidalRule(0.0, 2.0, 175000000);
    std::cout << "romberg integral          = " << integral << std::endl;
    std::cout << "actual spherical volume   = " << 4.0 * 4.0 * atan(1.0) / 3.0;
    std::cout << std::endl;
    double volume = MonteCarloVolume(1.0, 1000000);
    std::cout << "approx spherical volume   = " << volume;
    std::cout << std::endl;
}

Blog Entry © Wednesday, May 13, 2026, by James Pate Williams, Jr. Adaptive n-Quadrature Versus Monte Carlo Integration

Blog Entry © Sunday, November 9, 2025, by James Pate Williams, Jr. Hydrogenic Wavefunctions, Radial Probability Functions, Distribution Functions, and First Moment Integrals

Blog Entry © Sunday, August 10, 2025, First-Order Perturbation Treatment of the Helium Atom by James Pate Williams, Jr.

Blog Entry © Tuesday, July 29, 2025, Double and Triple Monte Carlo Integration by James Pate Williams, Jr.

#include <math.h>
#include <stdio.h>
#include <stdlib.h>

static double randomRange(double lo, double hi)
{
	return (hi - lo) * (double)rand() / RAND_MAX + lo;
}

static double integrand(double r, double w)
{
	return pow(r, 4.0) * (2.0 - r) * w * w * exp(-r);
}

static double StarkEffectIntegral(double E, int N)
{
	double sum = 0.0;

	for (int i = 0; i <= N; i++)
	{
		double r = randomRange(0.0, 100.0);
		double w = randomRange(-1.0, 1.0);

		sum += integrand(r, w);
	}

	return 100.0 * 2.0 * E * sum / (16.0 * (N - 1));
}

static void firstOrderStarkEffect(double E)
{
	double exact = -3.0 * E;
	int N[9] = {
		1000000, 2000000, 3000000, 4000000,
		5000000, 6000000, 7000000, 8000000,
		9000000 };

	for (int n = 0; n < 9; n++)
	{
		int iN = N[n];
		double integ = StarkEffectIntegral(E, iN);
		double error = 100.0 * fabs(integ - exact) / fabs(exact);

		printf("N = %4ld\tintegral = %13.10lf\t%% error = %13.10lf\n",
			iN, integ, error);
	}

	printf("exact value = %13.10lf\n", exact);
}

static double ee1(int N, double R, double Z)
{
	double pi = 4.0 * atan(1.0);
	double sum = 0.0;

	for (int i = 0; i <= N; i++)
	{
		double r1 = randomRange(1.0e-25, R);
		double r2 = randomRange(0.0, r1);

		sum += R * r1 * r1 * exp(-2.0 * Z * (r1 + r2)) * r2 * r2;
	}

	return 16.0 * pi * pi * sum / (N - 1);
}

static double ee2(int N, double R, double Z)
{
	double pi = 4.0 * atan(1.0);
	double sum = 0.0;

	for (int i = 0; i <= N; i++)
	{
		double r1 = randomRange(1.0e-25, R);
		double r2 = randomRange(r1, R);
		
		sum += R * (R - r2) * r2 * exp(-2.0 * Z * (r1 + r2)) * r1 * r1;
	}

	return 16.0 * pi * pi * sum / (N - 1);
}

static void firstOrderHelium(double Z)
{
	double pi = 4.0 * atan(1.0), R = 25.0;
	double exact = 5.0 * pi * pi / (8.0 * pow(Z, 5.0));

	int N[9] = {
		1000000, 2000000, 3000000, 4000000,
		5000000, 6000000, 7000000, 8000000,
		9000000 };

	for (int n = 0; n < 9; n++)
	{
		int iN = N[n];
		double integ = ee1(iN, R, Z) + ee2(iN, R, Z);
		double error = 100.0 * fabs(integ - exact) / fabs(exact);

		printf("N = %4ld\tintegral = %13.10lf\t%% error = %13.10lf\n",
			iN, integ, error);
	}

	printf("exact value = %13.10lf\n", exact);
}

int main(void)
{
	firstOrderStarkEffect(2.0);
	firstOrderHelium(2.0);
	return 0;
}
#include <math.h>
#include <stdio.h>
#include <stdlib.h>

static double randomRange(double lo, double hi)
{
	return (hi - lo) * (double)rand() / RAND_MAX + lo;
}

static double f(double x, double y, double z)
{
	return pow(sin(x), 2.0) + y * sin(z);
}

static double g(double x, double y, double z)
{
	return x + y * z * z;
}

static double integral(
	double x0, double x1,
	double y0, double y1,
	double z0, double z1,
	double (*f)(double, double, double),
	int N)
{
	double sum = 0.0;

	for (int n = 0; n <= N; n++)
	{
		double x = randomRange(x0, x1);
		double y = randomRange(y0, y1);
		double z = randomRange(z0, z1);

		sum += f(x, y, z);
	}

	return (x1 - x0) * (y1 - y0) * (z1 - z0) *
		sum / (N - 1);
}

int main(void)
{
	double pi = 4.0 * atan(1.0);
	double x0 = 0.0, x1 = pi;
	double y0 = 0.0, y1 = 1.0;
	double z0 = 0.0, z1 = pi;
	double exact = 0.5 * pi * (2.0 + pi);
	int N[9] = {
		1000000, 2000000, 3000000, 4000000,
		5000000, 6000000, 7000000, 8000000,
		9000000 };

	printf("integrand pow(sin(x), 2.0) + y * sin(z)\n");
	printf("x = 0 to pi, y = 0 to 1, z = 0 to pi\n");

	for (int n = 0; n < 9; n++)
	{
		int iN = N[n];
		double integ = integral(
			x0, x1, y0, y1, z0, z1, f, iN);
		double error = 100.0 * fabs(integ - exact) / fabs(exact);

		printf("N = %4ld\tintegral = %13.10lf\t%% error = %13.10lf\n",
			iN, integ, error);
	}

	printf("exact value = %13.10lf\n", exact);

	x0 = -1.0;
	x1 = 5.0;
	y0 = 2.0;
	y1 = 4.0;
	z0 = 0.0;
	z1 = 1.0;
	exact = 36.0;

	printf("integrand x + y * z * z\n");
	printf("x = -1 to 5, y = 2 to 4, z = 0 to 1\n");

	for (int n = 0; n < 9; n++)
	{
		int iN = N[n];
		double integ = integral(
			x0, x1, y0, y1, z0, z1, g, iN);
		double error = 100.0 * fabs(integ - exact) / fabs(exact);

		printf("N = %4ld\tintegral = %13.10lf\t%% error = %13.10lf\n",
			iN, integ, error);
	}

	printf("exact value = %13.10lf\n", exact);
	return 0.0;
}

Four Methods of Numerical Double Integration: Sequential Simpson’s Rule, Multitasking Simpson’s Rule, Sequential Monte Carlo and Multitasking Monte Carlo Methods © Wednesday April 16 – 18, 2025, by James Pate Williams, Jr.

Approximation of the Ground-State Total Energy of a Beryllium Atom © Sunday, March 30 to Tuesday April 1, 2025, by James Pate Williams, Jr., BA, BS, Master of Software Engineering, PhD Computer Science

Blog Entry © Thursday, March 27, 2025, by James Pate Williams, Jr., BA, BS, Master of Software Engineering, PhD Lithium (Li, Z = 3) Total Ground-State Energy Numerical Experiments

Revised Helium Ground-State Total Energy Computation (c) Sunday, March 23, 2025, by James Pate Williams, Jr.