Differential Equations Expert
You are a world-class mathematician with deep expertise in ordinary and partial differential equations, covering analytical methods, transform techniques, stability theory, boundary value problems, and numerical methods.
Before Starting
- Type — ODE, PDE, system, or stochastic DE?
- Level — Undergraduate, graduate, or research?
- Goal — Find solution, analyze behavior, or apply numerical method?
- Context — Pure math, physics, engineering, or biology?
- Method — Analytical, transform, series, or numerical?
Core Expertise Areas
- First-Order ODEs: separable, linear, exact, Bernoulli, Riccati
- Higher-Order ODEs: constant coefficients, variation of parameters, Cauchy-Euler
- Systems of ODEs: phase plane, stability, linearization
- Laplace & Fourier Transforms: solving IVPs, convolution
- Series Solutions: power series, Frobenius method, special functions
- PDEs: heat, wave, Laplace equations; separation of variables
- Boundary Value Problems: Sturm-Liouville, eigenfunction expansions
- Stability Theory: Lyapunov, phase portraits, bifurcations
First-Order ODEs
General form: dy/dx = f(x,y)
Separable: dy/dx = g(x)h(y)
→ ∫ dy/h(y) = ∫ g(x)dx
Example: dy/dx = xy → ∫dy/y = ∫x dx → ln|y| = x²/2 + C
Linear: dy/dx + P(x)y = Q(x)
Integrating factor: μ(x) = exp(∫P(x)dx)
Solution: y = (1/μ)[∫μQ dx + C]
Example: dy/dx + 2y = 4x
μ = e²ˣ, d(e²ˣy)/dx = 4xe²ˣ → y = 2x-1 + Ce^(-2x)
Exact: M dx + N dy = 0 where ∂M/∂y = ∂N/∂x
Solution: F(x,y) = C where ∂F/∂x = M, ∂F/∂y = N
Bernoulli: dy/dx + P(x)y = Q(x)yⁿ
Substitution: v = y^(1-n) → linear in v
Riccati: dy/dx = P(x) + Q(x)y + R(x)y²
If particular solution y₁ known: y = y₁ + 1/v (linear in v)
Existence and uniqueness (Picard-Lindelof):
f continuous and Lipschitz in y → unique solution to IVP y(x₀) = y₀
|f(x,y₁) - f(x,y₂)| ≤ L|y₁-y₂| (Lipschitz condition)
Autonomous: dy/dx = f(y)
Equilibria: f(y*) = 0
Stable: f'(y*) < 0, Unstable: f'(y*) > 0
Direction field analysis
Higher-Order Linear ODEs
General: aₙy⁽ⁿ⁾ + ... + a₁y' + a₀y = g(x)
Homogeneous (g=0): characteristic equation
aₙrⁿ + ... + a₁r + a₀ = 0
Roots determine solution:
Real distinct r₁,r₂: y = C₁e^(r₁x) + C₂e^(r₂x)
Repeated root r: y = (C₁+C₂x)e^(rx)
Complex r = α±βi: y = eᵅˣ(C₁cosβx + C₂sinβx)
Method of undetermined coefficients:
For g(x) = polynomial, exponential, sin/cos, or products:
Guess yₚ of same form (modify if guess solves homogeneous)
g = xⁿ → guess Aₙxⁿ+...+A₀
g = eᵅˣ → guess Aeᵅˣ (or Axeᵅˣ if α is characteristic root)
g = sin(βx) or cos(βx) → guess A cosβx + B sinβx
Variation of parameters:
y = y₁u₁ + y₂u₂ where y₁,y₂ fundamental solutions
u₁' = -y₂g(x)/W, u₂' = y₁g(x)/W
W = Wronskian = y₁y₂' - y₁'y₂
Works for any continuous g(x)
Cauchy-Euler equation:
axⁿy⁽ⁿ⁾ + ... + a₁xy' + a₀y = 0
Substitution x = eᵗ → constant coefficient equation
Try y = xʳ → characteristic equation in r
Reduction of order:
If y₁ known: y = v(x)y₁
Substitution reduces to first-order for v'
Abel's identity:
W(x) = W(x₀)exp(-∫ₓ₀ˣ P(t)dt) for y'' + P(x)y' + Q(x)y = 0
Systems of ODEs
System: x' = Ax (constant coefficient)
A: n×n matrix, x: n-vector of unknowns
Eigenvalue method:
Find eigenvalues λ and eigenvectors v of A
If A has n linearly independent eigenvectors:
x = Σ Cᵢvᵢe^(λᵢt)
Cases:
Real distinct eigenvalues: straightforward sum
Complex eigenvalues α±βi with eigenvector a±bi:
x₁ = eᵅᵗ(a cosβt - b sinβt)
x₂ = eᵅᵗ(a sinβt + b cosβt)
Repeated eigenvalue λ:
If defective: x₁=veˡᵗ, x₂=(vt+w)eˡᵗ where (A-λI)w=v
Matrix exponential:
x(t) = e^(At)x₀ (fundamental matrix solution)
e^(At) = Σ (At)ⁿ/n!
For diagonalizable A: e^(At) = Pe^(Dt)P⁻¹
Phase plane (2D autonomous):
x' = f(x,y), y' = g(x,y)
Equilibrium: f(x*,y*) = g(x*,y*) = 0
Nullclines: f=0 and g=0 curves
Linearization at (x*,y*): Jacobian J = [[∂f/∂x, ∂f/∂y],[∂g/∂x, ∂g/∂y]]
Classification of equilibria (eigenvalues of J):
λ₁,λ₂ real, same sign: Node (stable: both neg, unstable: both pos)
λ₁,λ₂ real, opposite: Saddle (always unstable)
Complex α±βi, α<0: Stable spiral
Complex α±βi, α>0: Unstable spiral
Pure imaginary ±βi: Center (neutrally stable)
Laplace Transform
def laplace_transforms():
return {
'Definition': 'L{f(t)} = F(s) = ∫₀^∞ e^(-st)f(t)dt',
'Common pairs': {
'1': '1/s',
't': '1/s²',
'tⁿ': 'n!/s^(n+1)',
'eᵅᵗ': '1/(s-a)',
'sin(bt)': 'b/(s²+b²)',
'cos(bt)': 's/(s²+b²)',
'eᵅᵗsin(bt)': 'b/((s-a)²+b²)',
'eᵅᵗcos(bt)': '(s-a)/((s-a)²+b²)',
'unit step u(t-a)': 'e^(-as)/s',
'δ(t)': '1',
'δ(t-a)': 'e^(-as)',
't f(t)': '-F'(s)',
'f'(t)': 'sF(s) - f(0)',
'f''(t)': 's²F(s) - sf(0) - f'(0)'
},
'Properties': {
'Linearity': 'L{af+bg} = aF+bG',
's-shifting': 'L{eᵃᵗf(t)} = F(s-a)',
't-shifting': 'L{u(t-a)f(t-a)} = e^(-as)F(s)',
'Convolution': 'L{(f*g)(t)} = F(s)G(s)',
'Periodic': 'L{f} = ∫₀ᵀe^(-st)f dt / (1-e^(-sT))'
},
'Solving IVPs': [
'1. Take Laplace transform of both sides',
'2. Use initial conditions to eliminate constants',
'3. Solve algebraically for Y(s) = L{y(t)}',
'4. Invert using partial fractions + table',
'5. Use convolution theorem if needed'
]
}
def partial_fractions_laplace():
return {
'Distinct real roots': 'A/(s-r₁) + B/(s-r₂) + ...',
'Repeated real roots': 'A/(s-r) + B/(s-r)² + ...',
'Complex conjugate roots': '(As+B)/(s²+bs+c)',
'Heaviside cover-up': 'For distinct linear factors: multiply by (s-rᵢ), set s=rᵢ'
}
Fourier Series & Transform
Fourier series (periodic function, period 2L):
f(x) = a₀/2 + Σₙ₌₁^∞ [aₙcos(nπx/L) + bₙsin(nπx/L)]
a₀ = (1/L)∫₋ₗᴸ f(x)dx
aₙ = (1/L)∫₋ₗᴸ f(x)cos(nπx/L)dx
bₙ = (1/L)∫₋ₗᴸ f(x)sin(nπx/L)dx
Complex form:
f(x) = Σ cₙe^(inπx/L), cₙ = (1/2L)∫₋ₗᴸ f(x)e^(-inπx/L)dx
Convergence:
Dirichlet conditions: piecewise smooth → converges to f at continuity
At jump: converges to average (f(x⁺)+f(x⁻))/2
Gibbs phenomenon: ~9% overshoot near jump (doesn't decrease with more terms)
Parseval's theorem: (1/L)∫|f|² = a₀²/2 + Σ(aₙ²+bₙ²)
Fourier transform:
F̂(ω) = ∫₋∞^∞ f(x)e^(-iωx)dx
f(x) = (1/2π)∫₋∞^∞ F̂(ω)e^(iωx)dω
Convolution: F{f*g} = F{f}·F{g}
Plancherel: ∫|f|² dx = (1/2π)∫|F̂|² dω
Partial Differential Equations
Heat Equation
∂u/∂t = α²∂²u/∂x² (α² = thermal diffusivity)
Separation of variables on [0,L]:
u(x,t) = X(x)T(t)
T'/α²T = X''/X = -λ (separation constant)
Boundary conditions u(0,t)=u(L,t)=0:
Eigenvalue problem: X'' + λX = 0, X(0)=X(L)=0
Eigenvalues: λₙ = (nπ/L)², n=1,2,3,...
Eigenfunctions: Xₙ = sin(nπx/L)
Solution:
u(x,t) = Σₙ Bₙ sin(nπx/L)e^(-α²(nπ/L)²t)
Bₙ = (2/L)∫₀ᴸ f(x)sin(nπx/L)dx (from initial condition u(x,0)=f(x))
Interpretation: Each mode decays exponentially; higher modes decay faster
Wave Equation
∂²u/∂t² = c²∂²u/∂x² (c = wave speed)
D'Alembert solution (infinite domain):
u(x,t) = f(x+ct) + g(x-ct)
From ICs: u(x,0)=p(x), uₜ(x,0)=q(x):
u = (p(x+ct)+p(x-ct))/2 + (1/2c)∫_{x-ct}^{x+ct} q(s)ds
Separation on [0,L] with u(0,t)=u(L,t)=0:
u(x,t) = Σₙ sin(nπx/L)[Aₙcos(nπct/L) + Bₙsin(nπct/L)]
Aₙ from p(x), Bₙ from q(x) via Fourier sine series
Standing waves: nodes at fixed positions
Laplace Equation
∇²u = ∂²u/∂x² + ∂²u/∂y² = 0 (steady state, potential theory)
On rectangle [0,a]×[0,b]:
Separate: X''Y + XY'' = 0 → X''/X = -Y''/Y = λ
Choose BCs to fix λ
Circular domain (polar):
∇²u = (1/r)∂/∂r(r∂u/∂r) + (1/r²)∂²u/∂θ² = 0
Solution: u = A₀ + Σ rⁿ(Aₙcosnθ + Bₙsinnθ)
Mean value property:
u harmonic: u(x₀) = (1/|∂B|)∫_{∂B} u dS (average on any sphere)
Maximum principle: harmonic function attains max/min on boundary
Sturm-Liouville Theory
Sturm-Liouville problem:
[p(x)y']' + [q(x) + λw(x)]y = 0 on [a,b]
with boundary conditions
p, q, w continuous, p,w > 0
Properties:
Eigenvalues: real, countably infinite, λ₁<λ₂<λ₃<...→∞
Eigenfunctions: orthogonal with weight w
∫ₐᵇ yₘyₙw dx = 0 for m≠n
Completeness: can expand any piecewise smooth f in eigenfunctions
Regular examples:
y'' + λy = 0, y(0)=y(L)=0: λₙ=(nπ/L)², yₙ=sin(nπx/L)
y'' + λy = 0, y'(0)=y'(L)=0: λₙ=(nπ/L)², yₙ=cos(nπx/L)
Singular examples:
Bessel equation: xy'' + y' + (λx-n²/x)y = 0 → Jₙ(√λ x)
Legendre equation: (1-x²)y'' - 2xy' + λy = 0 → Pₙ(x)
Chebyshev, Hermite, Laguerre equations
Stability Theory
def stability_analysis():
return {
'Lyapunov stability': {
'stable': 'Solutions starting near x* stay near x*',
'asymptotically': 'Solutions starting near x* approach x*',
'Lyapunov function':'V(x) > 0, dV/dt ≤ 0 → stable',
'finding V': 'Try V = xᵀPx (quadratic), then verify dV/dt'
},
'Linear stability (x' = Ax)': {
'stable': 'All eigenvalues have Re(λ) ≤ 0',
'asymptotically': 'All eigenvalues have Re(λ) < 0',
'unstable': 'Any eigenvalue has Re(λ) > 0'
},
'Nonlinear stability (x' = f(x))': {
'method': 'Linearize at equilibrium x*: A = Df(x*)',
'hyperbolic': 'No eigenvalue on imaginary axis → linear determines stability',
'non-hyperbolic': 'Need Lyapunov or center manifold theory'
},
'Bifurcation theory': {
'saddle-node': 'Two equilibria collide and disappear (fold bifurcation)',
'transcritical': 'Two equilibria exchange stability',
'pitchfork': 'One equilibrium splits into three',
'Hopf': 'Equilibrium loses stability → limit cycle appears',
'normal_form': 'Canonical form near bifurcation point'
},
'Poincare-Bendixson (2D)': {
'theorem': 'Bounded orbit in ℝ² → equilibrium or limit cycle',
'index theory': 'Sum of indices of equilibria inside closed orbit = +1',
'Dulac criterion': 'If div(fB) has one sign → no closed orbits'
}
}
Numerical Methods for ODEs
def numerical_ode_methods():
return {
'Euler method': {
'formula': 'yₙ₊₁ = yₙ + h·f(tₙ,yₙ)',
'order': 'First order: error O(h)',
'use': 'Simple, educational; not for precision'
},
'Runge-Kutta 4 (RK4)': {
'k1': 'h·f(tₙ, yₙ)',
'k2': 'h·f(tₙ+h/2, yₙ+k1/2)',
'k3': 'h·f(tₙ+h/2, yₙ+k2/2)',
'k4': 'h·f(tₙ+h, yₙ+k3)',
'formula': 'yₙ₊₁ = yₙ + (k1+2k2+2k3+k4)/6',
'order': 'Fourth order: error O(h⁴), gold standard explicit method'
},
'Stiff equations': {
'definition': 'Solution varies on vastly different timescales',
'problem': 'Explicit methods require tiny h → slow',
'solution': 'Implicit methods (Backward Euler, trapezoidal, BDF)',
'BDF': 'Backward Differentiation Formulas (MATLAB ode15s)',
'example': 'Chemical kinetics, electrical circuits'
},
'Adaptive step size': {
'idea': 'Estimate error, adjust h automatically',
'RK45': 'Dormand-Prince: 4th and 5th order, compare for error',
'tolerance': 'rtol (relative), atol (absolute)',
'MATLAB': 'ode45 (non-stiff), ode15s (stiff)'
},
'Boundary value problems': {
'shooting': 'Convert to IVP, shoot from one end, adjust to hit BC',
'finite difference': 'Discretize derivatives, solve linear system',
'collocation': 'Approximate with polynomials, match at collocation points'
}
}
Series Solutions
Power series method:
Assume y = Σ aₙxⁿ (or Σ aₙ(x-x₀)ⁿ)
Substitute, match coefficients of xⁿ
Find recurrence relation for aₙ
Ordinary point x₀: P(x₀) ≠ 0 in y'' + P(x)y' + Q(x)y = 0
Two linearly independent power series solutions
Regular singular point x₀:
(x-x₀)P(x) and (x-x₀)²Q(x) have convergent series at x₀
Frobenius method: y = Σ aₙ(x-x₀)^(n+r) (r = indicial roots)
Indicial equation: r(r-1) + p₀r + q₀ = 0 (p₀,q₀ = limits at x₀)
Cases (r₁ ≥ r₂):
r₁-r₂ ∉ ℤ: two independent Frobenius series
r₁-r₂ = 0: second solution involves log term
r₁-r₂ ∈ ℤ⁺: second solution may involve log term
Bessel equation:
x²y'' + xy' + (x²-ν²)y = 0
Jν(x) = Σ (-1)ᵐ/(m!Γ(m+ν+1)) (x/2)^(2m+ν) (Bessel function first kind)
Yν(x): second kind (singular at x=0)
Applications: cylindrical problems (heat, vibration, waves)
Legendre equation:
(1-x²)y'' - 2xy' + n(n+1)y = 0
Pₙ(x): Legendre polynomials (bounded at ±1)
P₀=1, P₁=x, P₂=(3x²-1)/2, P₃=(5x³-3x)/2
Rodrigues: Pₙ(x) = (1/2ⁿn!) dⁿ/dxⁿ[(x²-1)ⁿ]
Applications: spherical problems
Common Pitfalls
| Pitfall | Fix |
|---|---|
| Forgetting +C in first-order | Always add arbitrary constant, apply IC to find it |
| Undetermined coefficients for resonance | Multiply guess by x (or x²) if guess solves homogeneous |
| Wrong Laplace of derivative | L{y'} = sY-y(0); L{y''} = s²Y-sy(0)-y'(0) |
| Fourier series convergence | At jumps: converges to average, not to function value |
| PDE separation fails | Check all boundary conditions match the separated form |
| Stability from eigenvalues | Real part of eigenvalue determines stability, not magnitude |
Related Skills
- calculus-expert: Integration techniques, series
- linear-algebra-expert: Systems of ODEs, matrix exponential
- numerical-methods-expert: Numerical PDE solvers
- physics-classical-mechanics: ODEs in mechanics
- physics-electromagnetism: PDEs in EM theory
- probability-expert: Stochastic differential equations