The Lumenary · Early undergraduate
Ordinary differential equations
Name: ______________________
Date: ______________________
You will learn to
- Solve separable equations, first-order linear equations (by an integrating factor) and linear equations with constant coefficients
- Solve linear systems with the matrix exponential and eigenvalues, and classify planar phase portraits by trace and determinant
- State and prove the Picard–Lindelöf theorem, and give examples of non-uniqueness and of finite-time blow-up when its conclusions or hypotheses fail
- Analyse equilibria and their stability qualitatively, without solving the equation
- Compare exact, qualitative and numerical solutions, and say what kind of evidence each provides
- 1.
Carbon-14 decays according to , with a half-life of about years. A piece of charcoal from an ancient hearth is years old. Its carbon-14 content is of the original amount. Find .
- 2.
Solve with using an integrating factor. What is ?
- 3.
Which is the general real solution of ?
- A.
- B.
- C.
- D.
- 4.
Classify the equilibrium of for .
- A.A saddle
- B.An unstable node
- C.An unstable spiral
- D.A centre
- 5.
For which initial value problems does the Picard–Lindelöf theorem guarantee a unique solution near ? (Select all that apply.)
- A.,
- B.,
- C.,
- D.,
- E.,
- 6.
The solution of with blows up at a finite time . Find .
- 7.
In the uniqueness proof, satisfies for , and . Which step finishes the proof that ?
- A. and , so ; with this gives , hence .
- B.Since and , dividing by gives , a contradiction.
- C.Differentiate to get , so is a decaying exponential.
- D.Use the Picard iterates: they converge, so the solution is unique.
- 8.
Which Lean statement says that solves the differential equation at every time?
- A.
∀ t, HasDerivAt x (a * x t) t - B.
HasDerivAt x (a * x 0) 0 - C.
∀ t, x t = a * x t - D.
∀ t, HasDerivAt (fun s => a * x s) (x t) t
- A.
- 9.
Write
euler(f, t0, x0, t1, n)implementing Euler's method with equal steps of size , returning the approximation of . Check that for , it returns , and that doubling roughly halves the error.Computational — Practice