Summary of Differential Equations


1. Foundations

Notation:

  • Leibniz: dy/dx
  • Lagrange: f’(x), f”(x)
  • Newton: ẏ, ÿ (for time derivatives)

Differentials vs Derivatives:

  • Derivative dy/dx is defined as a limit (single symbol)
  • Differentials dx and dy are separate objects, defined later
  • dy = f’(x)·dx (definition)
  • Their ratio equals the derivative (by construction)
  • This justifies “separating” dy/dx algebraically

Multivariable chain rule:


2. First-Order ODEs

Separable:

  • Form: dy/dx = f(x)·g(y)
  • Method: Separate → ∫(1/g)dy = ∫f dx
  • Key: RHS must be product, not sum

Linear:

  • Form: y’ + P(x)y = Q(x)
  • Method: Integrating factor I = e^(∫P dx)
  • Solution: y = (1/I)∫I·Q dx
  • No constant in integrating factor; constant appears in final integration

Bernoulli:

  • Form: y’ + P(x)y = Q(x)yⁿ
  • Substitution: v = y^(1-n)
  • Divide by yⁿ first, then substitute
  • Transforms to linear equation

Homogeneous (y/x type):

  • Form: y’ = F(y/x)
  • Substitution: v = y/x, so y = vx, y’ = v’x + v
  • Transforms to separable

Exact:

  • Form: M(x,y)dx + N(x,y)dy = 0
  • Test: ∂M/∂y = ∂N/∂x
  • Meaning: ∃F such that dF = Mdx + Ndy
  • Solution: F(x,y) = C

3. Second-Order Linear ODEs

Homogeneous with Constant Coefficients

Form: ay” + by’ + cy = 0

Method: Guess y = e^(rx), get characteristic equation ar² + br + c = 0

Three cases based on discriminant b² - 4ac:

DiscriminantRootsSolution
> 0Two real r₁, r₂y = C₁e^(r₁x) + C₂e^(r₂x)
= 0Repeated ry = (C₁ + C₂x)e^(rx)
< 0Complex α ± βiy = e^(αx)(C₁cos(βx) + C₂sin(βx))

Why dimension 2:

  • Second-order → two initial conditions needed
  • Solution space corresponds to R²
  • Two independent solutions form a basis

Why xe^(rx) for repeated roots:

  • Reduction of order method
  • Assume y = v·e^(rx), find v” = 0, so v = Ax + B

Complex roots explained:

  • e^(ix) = cos(x) + i·sin(x) (Euler’s formula)
  • Real/imaginary parts of complex solution are each solutions (for real coefficients)

Non-Homogeneous

Form: ay” + by’ + cy = g(x)

General solution: y = y_c + y_p

Method 1: Undetermined Coefficients

  • Guess y_p based on form of g(x)
  • Works for: polynomials, exponentials, sin, cos, products
  • If guess matches y_c, multiply by x
  • Why multiplying by x works: L[xf] = x·L[f] + (extra terms) = 0 + (extra terms)

Method 2: Variation of Parameters

  • Always works
  • Assume y_p = u₁y₁ + u₂y₂
  • Impose: u₁’y₁ + u₂’y₂ = 0 (simplifies derivatives)
  • ODE gives: u₁’y₁’ + u₂’y₂’ = g(x)
  • Solve system for u₁’, u₂’, then integrate

Wronskian:

  • Measures linear independence
  • Used in variation of parameters

4. Applications

Mixing/Brine Problems

Setup:

  • y(t) = amount of substance in tank
  • dy/dt = (rate in) - (rate out)

Key formulas:

  • Rate in = C₁ · r₁ (concentration × flow rate)
  • Rate out = (y/V) · r₂ (current concentration × flow rate)
  • V(t) = V₀ + (r₁ - r₂)t

Three cases:

ConditionVolumeSolution shape
r₁ = r₂constantexponential decay
r₁ > r₂grows1/(a+t)ⁿ
r₁ < r₂shrinks(a-t)ⁿ

Newton’s Cooling

Solution: T(t) = T_ambient + (T₀ - T_ambient)e^(-kt)

Circuits

RL circuit (first-order):

RLC circuit (second-order):

Damping cases:

CaseDiscriminantBehavior
Overdamped (sovrasmorzato)> 0Smooth decay, no oscillation
Critically damped (smorzamento critico)= 0Fastest decay without oscillation
Underdamped (sottosmorzato)< 0Oscillates while decaying

Springs

Hooke’s Law: F = -kx (spring force)

Newton’s Law: F = ma = mx”

Combined: mx” + kx = 0

With damping: mx” + cx’ + kx = 0

Same three cases as circuits.


5. Qualitative Analysis

Direction Fields

  • At each point (t, y), draw slope = f(t, y)
  • Direction vector: (1, f(t,y))
  • Solution curves are tangent to the field

Autonomous Equations

Form: dy/dt = f(y) (no explicit t dependence)

Key property: Same y → same slope, regardless of t

Direction field: Horizontal bands of constant slope

Equilibrium Solutions

Definition: Values where f(y) = 0 (constant solutions)

Classification:

  • Stable (attractor): Both sides push toward equilibrium
  • Unstable (repeller): Both sides push away
  • Semi-stable: One side toward, one side away

Method: Check sign of f(y) just above and below equilibrium

Euler’s Method

  • Numerical approximation
  • Follow direction field in small steps
  • n = step number, not time value

6. Power Series Solutions

When to Use

  • At ordinary points (punto ordinario): P(x) and Q(x) analytic
  • At singular points (punto singolare): Need Frobenius method

Method

Step 1: Write y = Σcₙxⁿ and derivatives as series

Step 2: Substitute into ODE

Step 3: Get series “in phase” (same starting power of x)

  • May need to pull terms outside sum

Step 4: Re-index to match powers

Step 5: Combine and set coefficient of each xᵏ to zero

Step 6: Get recurrence relation, solve for cₙ

Key Techniques

Re-indexing example:

  • If sum has x^(n-1), let k = n-1, n = k+1
  • Subscript cₙ becomes c_{k+1}

Series multiplication:

  • For cos(x)·y, multiply term by term
  • Collect like powers of x

Common Results


7. Solution Process Summary

First-order:

  1. Is it separable? → Separate and integrate
  2. Is it linear? → Integrating factor
  3. Is it Bernoulli? → Substitute v = y^(1-n)
  4. Is it homogeneous (y/x)? → Substitute v = y/x
  5. Is it exact? → Find F where dF = 0

Second-order linear:

  1. Solve homogeneous first (characteristic equation)
  2. If non-homogeneous, find y_p via:
    • Undetermined coefficients (if g(x) is nice)
    • Variation of parameters (always works)
  3. General solution: y = y_c + y_p
  4. Apply initial conditions last