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second-order-odes

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Problem-solving strategies for second order odes in odes pdes

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SKILL.md

Second Order Odes

When to Use

Use this skill when working on second-order-odes problems in odes pdes.

Decision Tree

  1. Classify the ODE

    • Constant coefficients: ay'' + by' + cy = f(x)?
    • Variable coefficients: y'' + P(x)y' + Q(x)y = R(x)?
    • Cauchy-Euler: x^2 y'' + bxy' + cy = 0?
  2. Homogeneous with Constant Coefficients

    • Characteristic equation: ar^2 + br + c = 0
    • Distinct real roots: y = c1e^{r1x} + c2e^{r2x}
    • Repeated root: y = (c1 + c2x)e^{rx}
    • Complex roots a +/- bi: y = e^{ax}(c1cos(bx) + c2sin(bx))
    • sympy_compute.py solve "a*r**2 + b*r + c" --var r
  3. Particular Solution (Non-homogeneous)

    • Undetermined coefficients: guess based on f(x)
    • Variation of parameters: y_p = u1y1 + u2y2
    • sympy_compute.py dsolve "y'' + y = sin(x)"
  4. Numerical Solution

    • Convert to first-order system: let v = y', then v' = y''
    • solve_ivp(system, [t0, tf], [y0, v0])
  5. Boundary Value Problems

    • Shooting method: guess initial slope, iterate
    • scipy.integrate.solve_bvp(ode, bc, x, y_init)

Tool Commands

Scipy_Solve_Ivp_System

uv run python -c "from scipy.integrate import solve_ivp; sol = solve_ivp(lambda t, Y: [Y[1], -Y[0]], [0, 10], [1, 0]); print('y(10) =', sol.y[0][-1])"

Sympy_Charpoly

uv run python -m runtime.harness scripts/sympy_compute.py solve "r**2 + r + 1" --var r

Sympy_Dsolve_2Nd

uv run python -m runtime.harness scripts/sympy_compute.py dsolve "Derivative(y,x,2) + y"

Key Techniques

From indexed textbooks:

  • [An Introduction to Numerical Analysis... (Z-Library)] Modern Numerical Methods for Ordinary Wiley, New York. User's guide for DVERK: A subroutine for solving non-stiff ODEs. Keller (1966), Analysis of Numerical Methods.
  • [Elementary Differential Equations and... (Z-Library)] Riccati equation and that y1(t) = 1 is one solution. Use the transformation suggested in Problem 33, and nd the linear equation satised by v(t). Find v(t) in the case that x(t) = at, where a is a constant.
  • [An Introduction to Numerical Analysis... (Z-Library)] Test results on initial value methods for non-stiff ordinary differential equations, SIAM J. Comparing numerical methods for Fehlberg, E. Klassische Runge-Kutta-Formeln vierter und niedrigerer Ordnumg mit Schrittweiten-Kontrolle und ihre Anwendung auf Warme leitungsprobleme, Computing 6, 61-71.
  • [Elementary Differential Equations and... (Z-Library)] Two papers by Robert May cited in the text are R. May,“Biological Populations with Nonoverlapping Generations: Stable Points, Stable Cycles, and Chaos,” Science 186 (1974), pp. Biological Populations Obeying Difference Equations: Stable Points, Stable Cycles, and Chaos,” Journal of Theoretical Biology 51 (1975), pp.
  • [An Introduction to Numerical Analysis... (Z-Library)] COLSYS: collocation software for boundary-value ODEs, ACM Trans. Numerical Solutions of Boundary Value Problems for Ordinary Differential Equations. Elementary Differential Equations and Boundary Value Problems, 4th ed.

Cognitive Tools Reference

See .claude/skills/math-mode/SKILL.md for full tool documentation.

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AI Quality Score

75/100Analyzed last week

Solid technical reference skill for solving second-order ODEs with clear decision tree, executable tool commands, and comprehensive coverage of analytical and numerical methods. Deeply nested path and internal references suggest internal agent config, but the mathematical content is accurate and well-structured. Tags and .claude reference indicate project-specific tailoring."

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Licenseunknown
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Updated3 weeks ago
Publishercarmandale

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