Calculus of variations

Derive equations and stability from optimization over functions, while distinguishing stationarity from existence.

10 published lessons1 module309 min of guided study
  1. 01
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Calculus of variations

Derive equations and stability from optimization over functions, while distinguishing stationarity from existence.

  1. 01

    Functionals and first variations

    Differentiate an objective over admissible functions while keeping the function space, boundary values, and topology explicit.

    28 min
  2. 02

    Euler–Lagrange equations and boundary terms

    Derive an interior differential equation without losing the endpoint information carried by integration by parts.

    29 min
  3. 03

    Natural boundary conditions and transversality

    Derive endpoint conditions from free endpoint motions, terminal costs, and moving terminal curves.

    30 min
  4. 04

    Constrained variations and multipliers

    Restrict perturbations to a constraint tangent space and derive a valid multiplier equation under a constraint qualification.

    30 min
  5. 05

    Noether identities for variational symmetries

    Derive conserved quantities from smooth continuous symmetries and identify exactly where the Euler–Lagrange equation is used.

    30 min
  6. 06

    Second variation and the Legendre condition

    Compute the quadratic response to perturbations and distinguish a necessary pointwise curvature condition from a sufficient functional estimate.

    30 min
  7. 07

    Jacobi fields and conjugate points

    Linearize the stationary equation and use endpoint zeros of its variational equation to detect a loss of second-variation positivity.

    32 min
  8. 08

    The direct method and weak lower semicontinuity

    Prove that a minimizing sequence has an admissible limit whose energy achieves the infimum.

    32 min
  9. 09

    Relaxation and Young measures

    Explain how fine oscillations defeat weak lower semicontinuity and how a relaxed energy records unresolved phase mixtures.

    34 min
  10. 10

    Variational inequalities and obstacle problems

    Derive one-sided optimality for a convex feasible set and solve a one-dimensional contact problem with a verified reaction force.

    34 min
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