A highest-order method in this family has order . The Second Dahlquist barrier says that an irreducible A-stable multistep method has order at most two, so and hence . Part b then leaves only the trapezoidal rule. Its amplification factor is
and whenever . Thus the trapezoidal rule is the unique highest-order A-stable method of the stated form, apart from representations containing removable common factors.
The Second Dahlquist barrier states that an A-stable linear multistep method has order at most two. Part a shows that every method in this family has order at least three, so no member can be A-stable.
The exceptional reducible case does not evade the conclusion. At ,
Thus is an amplification root for every with , whereas the multistep A-stability criterion requires all such roots to lie strictly inside the unit disk. Hence
A linear multistep method for has the form
Its characteristic polynomials of a linear multistep method are and . Substitution of the exact solution, or equivalently expansion of at , gives the order conditions for a linear multistep method. The method has order when
with a nonzero coefficient at the next power. Its one-step defect is then , while its global error is when stability prevents accumulation from being amplified.
Order alone does not ensure convergence because the recurrence may contain growing parasitic modes. Zero-stability is the root condition for a multistep method: every root of lies in , and every root on the unit circle is simple. Consistency is the first-order condition
The Dahlquist equivalence theorem states that a consistent linear multistep method is convergent if and only if it is zero-stable. For example, the leapfrog method has ; its roots are simple, so this second-order method is convergent, although its parasitic mode can oscillate.
To study stiff decay, apply the method to and put . The amplification factors are the roots of
The linear stability domain consists of the for which these roots satisfy the strict interior condition appropriate away from the boundary, with simple unit roots where boundary stability is admitted. The method is A-stable when this domain contains the left half-plane, so every mode with remains bounded for every positive step size. The Second Dahlquist barrier says that an A-stable multistep method has order at most two.
The main families illustrate the tradeoffs. The explicit Adams-Bashforth methods interpolate past derivative values and are inexpensive, but their stability domains are bounded. The implicit Adams-Moulton methods include the new derivative value; the one-step second-order member is the trapezoidal rule, which is A-stable. The backward differentiation formulas interpolate past solution values and differentiate the interpolant; the first two are A-stable, while higher orders retain useful sectors of the left half-plane. Implicit methods require a nonlinear solve at each step, commonly initialized by an explicit predictor to form a predictor-corrector pair. Thus order controls consistency error, the root condition controls convergence as , and the amplification polynomial controls whether a convergent method remains useful on stiff equations.