Leapfrog Method
Intuition
Stagger the bookkeeping: keep velocity at half-integer times and position at integer times, so each update uses information centered exactly where it's needed. The scheme "leapfrogs" over itself — and this symmetry buys something no amount of raw accuracy can: exact conservation of a discrete energy, forever. The workhorse of plasma and N-body simulation.
The scheme
with \(y_\text{new} = y(t + \Delta t/2)\), \(y_\text{old} = y(t - \Delta t/2)\) — a centered difference equated to a midpoint evaluation. Implicit in general, but for the Lorentz force it has a closed-form solution (see the leapfrog update equation page):
with \(\mathbf{A} = \frac{q\mathbf{B}}{m}\frac{\Delta t}{2}\) and \(\mathbf{C} = \mathbf{v}_\text{old} + \Delta t\left(\frac{q\mathbf{E}}{m} + \mathbf{v}_\text{old}\times\frac{q\mathbf{B}}{m}/2\right)\). No iteration, no matrix solve — pure algebra. This is the ancestor of the Boris pusher used in every serious PIC code.
Kick–drift–kick form
The equivalent split-step version, standard in N-body simulation:
Properties
- Order 2 — global error \(\mathcal{O}(\Delta t^2)\)
- Symplectic — preserves phase-space volume; energy error stays bounded (oscillates) instead of drifting, even over millions of steps
- Time-reversible — run it backwards and you retrace your path exactly
- Exact gyration — for uniform \(\mathbf{B}\) the orbit stays perfectly circular (the frequency is slightly off, the radius is not)
Why symplecticity beats order for orbits
RK4 makes a far smaller error per step — but each step's error pushes energy the same way, accumulating secularly. Leapfrog's errors are structure-preserving: the numerical trajectory is the exact orbit of a slightly perturbed Hamiltonian, so energy oscillates within a fixed band. For a three-orbit plot, use RK4; for a million-orbit tokamak or galaxy, use leapfrog. Watch both live in the integrator arena.
Common mistakes
- Mixing time levels. Velocity lives at half-steps: initializing \(v_0\) at \(t=0\) and treating it as \(v_{1/2}\) costs you the second order (fix: half-kick to start).
- Expecting exact energy. Leapfrog conserves a discrete (shadow) energy; the physical energy oscillates with amplitude \(\mathcal{O}(\Delta t^2)\).
- Using leapfrog for dissipative systems. Symplecticity assumes Hamiltonian dynamics; with drag, its magic evaporates.
Related concepts
- Leapfrog update (closed form)
- FDTD — leapfrog applied to Maxwell's equations (E and H staggered)
- N-body simulation · PIC method — its habitats
- Convergence and error
Knowledge graph position
Prerequisites: Forward & Backward Euler. Leads to: FDTD, N-body, PIC.
Quiz
Q1 (conceptual). Why is time-reversibility evidence of good long-time behavior?
Answer
A reversible scheme cannot have systematic dissipation or anti-dissipation — any energy gained forward would have to be lost backward, but the scheme is the same map. Errors must therefore oscillate rather than drift.
Q2 (computational). For the cross-field problem with \(\Omega\Delta t = 0.2\), the leapfrog velocity denominator is \(1 + (\Omega\Delta t/2)^2\). By what fraction does the scheme's effective gyration differ per step?
Answer
\((0.1)^2 = 0.01\) → denominators shift speeds at the 1% level per step, but rotations preserve \(|v|\): the error appears as a ~1% phase (frequency) shift, not an energy change.
Q3 (MCQ). Which system should not be integrated with plain leapfrog?
- (a) a galaxy of stars (b) a particle in a magnetic mirror
- (c) a damped oscillator (d) two-stream instability particles
Answer
(c). Damping breaks the Hamiltonian structure that leapfrog is built to preserve.