Blog Entry (c) Monday, May 25, 2026, by James Pate Williams, Jr. Quantum Mechanical Linear Harmonic Oscillator

Blog Entry (c) Friday, May 22, 2024, by James Pate Williams, Jr. and Microsoft’s Copilot (AI Agent)

Cheerwing U12S Mini RC Helicopter with Camera Remote Control Helicopter for Kids and Adults Preflight and Start Checklist found on Amazon.com

Blog Entry © Sunday, May 17, 2026, by James Pate Williams, Jr. Derivation of the Time Independent Free Particle Schrödinger Equation in Confocal Parabolic Coordinates

Blog Entry © Saturday, May 16, 2026, by James Pate Williams, Jr. Some More Linear Algebra Examples

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 © Monday, May 11, 2026, by James Pate Williams, Jr., Laplace Equation in a Solid Cylinder

Blog Entry © Tuesday, May 5, 2026, by James Pate Williams, Jr., Solution of the Laplace Equation on a Rectangle