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Delay differential equations and history discretization — Examples

1 · Prerequisites

2 · Summary

Objective

These examples work through four boundaries of the A-page results. A constant delayed-feedback problem gives an explicit two-block Euler recurrence and the exact endpoint error a2τh/2. A classical RK4 step crossing a retarded-delay breakpoint has an explicitly computed second-order exact-start defect, so smooth-ODE order does not transfer across that kink. A compatible scalar neutral history shows geometric derivative amplification for ∣a∣>1 and a finite-horizon shift inverse whose norm grows at a=1. A quadratic history with constant kernel computes the distributed-delay midpoint remainder and the additional stored-history contribution separately, including their signed-error cancellation. These are concrete calculations under their stated data; they do not assert general convergence on unstable neutral branches or a fourth-order delay-equation method across breakpoints.

3 · Logical flowchart

4 · Definitions, theorems and proofs

None yet.

5 · Examples, counterexamples and false statements

ExampleConstruction: AI-generatedVerification: AI-generatedOpen item page →

Delayed feedback gives an explicit two-block Euler recurrence

Example

Let τ>0, a∈R, and consider y′(t)=ay(t−τ) with history ϕ(s)=1 on [−τ,0], through T=2τ. This is the retarded problem of Retarded delay equations and their history space, and its unique solution is supplied by Method of steps gives a unique retarded-delay solution. For h=τ/m with integer m≥1, apply Explicit Euler with a stored piecewise-linear delay history. The exact endpoint error is ∣y(2τ)−Y2m∣=a2τh2. It vanishes when a=0 and is first order in h otherwise, in agreement with Grid-aligned Euler has first-order error for retarded delays.

Facts & Assumptions

Given: A fixed delay τ>0, scalar coefficient a, constant history ϕ=1, target 2τ, and the aligned grid h=τ/m.

[F1]

The exact equation is y′(t)=ay(t−τ) with the given history; the retarded method of steps gives its unique solution (Retarded delay equations and their history space, Method of steps gives a unique retarded-delay solution).

[F2]

The algorithm initializes exact history values and updates Yn+1=Yn+haYn−m (Explicit Euler with a stored piecewise-linear delay history).

[F3]

Under grid alignment, compact-tube, and time-Lipschitz assumptions, this algorithm has uniform first-order error for the returned interpolation (Grid-aligned Euler has first-order error for retarded delays).

Proof

1.1F1givenalgebra

On the first block 0≤t≤τ, the delayed value is 1, so y(t)=1+at. On the second block, writing s=t−τ∈[0,τ], the delayed value is y(s)=1+as, hence y′(τ+s)=a+a2s and y(2τ)=1+2aτ+a2τ2/2.

1.2F2givenalgebra

The first Euler block gives Yj=1+ajh for 0≤j≤m. On the second block, [F2] gives Ym+j+1=Ym+j+ahYj for 0≤j<m. Summing yields Y2m=1+aτ+ah∑j=0m−1(1+ajh). Pairing the terms j and m−1−j (and retaining the middle term when m is odd) gives ∑j=0m−1j=m(m−1)/2, so Y2m=1+2aτ+a2h2m(m−1)/2.

2.1F1F2F3step 1.1step 1.2givenalgebra∎

Subtracting step 1.2 from step 1.1 and using τ=mh gives y(2τ)−Y2m=a2h2m/2=a2τh/2. Since this is nonnegative, its absolute value is the claimed error, including a=0. On the first Euler block, ∣Yj∣≤1+∣a∣τ; on the second, ∣Ym+j∣≤1+∣a∣τ+∣a∣τ(1+∣a∣τ) for 0≤j≤m. The exact solution is polynomial on each of the first three delay blocks: besides step 1.1, on [2τ,3τ] it is y(2τ+s)=y(2τ)+(a+a2τ)s+(a2/2)s2+(a3/6)s3. These formulas give a common bounded tube independent of h. The data therefore satisfy [F3] with η=h0=τ, because f(t,x,z)=az is time-independent, the history has zero second derivative, and the tube is compact. Thus the exact error formula is consistent with the first-order guarantee.

ExampleConstruction: AI-generatedVerification: AI-generatedjudge pass (gpt-6-luna)Open item page →

A breakpoint-crossing RK4 step has a second-order defect

Example

Let τ>0 and solve the retarded equation y′(t)=y(t−τ) with history ϕ(s)=s on [−τ,0]. Choose an integer m≥1 and h=τ/(m+1/2), so a classical four-stage RK4 step from t−=mh to t+=(m+1)h crosses the first breakpoint t=τ at its midpoint. This example computes its exact-start local defect; it does not assert a fourth-order DDE bound for a mesh that crosses a breakpoint. On an ODE y′=g(t), the classical RK4 rule used here is Q=h(k1+2k2+2k3+k4)/6, with k1=g(t−), k2=k3=g(t−+h/2), and k4=g(t−+h). For affine g, the weighted average is g(t−+h/2), so this rule integrates g exactly.

Facts & Assumptions

Given: The retarded problem, m≥1, and the step [mh,(m+1)h] for h=τ/(m+1/2).

[F1]

The history and delayed equation are as in Retarded delay equations and their history space.

[F2]

The exact-start one-step local defect is the difference between the numerical output from the exact starting value and the exact next value (One-step ODE methods, local defect, uniform order, and step stability).

Verification

1.1givenF1algebra

For 0≤t≤τ, the delayed value is ϕ(t−τ)=t−τ, so y′(t)=t−τ and the solution matching y(0)=0 is y(t)=t2/2−τt. Earlier RK4 steps lie wholly in this interval, where g(t)=t−τ is affine and the RK4 rule in the Example integrates it exactly. Moreover y′′ jumps at τ: its left limit is 1, while its right limit is y′(0+)=−τ.

2.1step 1.1givenalgebra

Write x=t−τ. On the crossing step, the delayed right-hand side is g(t)=x for x≤0 and g(t)=x2/2−τx for x≥0. The terminal stage queries y(t+−τ)=y(h/2), and h/2<t−=mh for m≥1, so this value is already computed exactly by step 1.1; the midpoint uses y(0)=0. Therefore the RK4 stage values are g(t−)=−h/2, g(τ)=0, and g(t+)=h2/8−τh/2.

3.1givenstep 2.1algebra

The RK4 increment from the stated rule is Q=h[−h/2+(h2/8−τh/2)]/6=−(1+τ)h2/12+h3/48.

4.1step 2.1step 3.1algebra

The exact increment is ∫−h/20x dx+∫0h/2(x2/2−τx) dx=−(1+τ)h2/8+h3/48. Subtracting this from Q gives the exact-start defect (1+τ)h2/24>0.

5.1F2step 4.1algebra∎

This defect is not O(h5) as h→0, so the smooth-RHS fourth-order local-defect premise cannot be transferred across this breakpoint. Aligning or restarting at the breakpoint removes this particular crossing step but supplies no higher-order theorem without separate smoothness and error bounds.

ExampleConstruction: AI-generatedVerification: AI-generatedjudge pass (gpt-6-luna)Open item page →

Neutral derivative feedback amplifies outside the stable branch

Example

For any a∈R, let q(s)=1+(a−1)(s+τ)/τ and ϕ(s)=(s+τ)+(a−1)(s+τ)2/(2τ) on [−τ,0]. Consider y′(t)−ay′(t−τ)=0,y∣[−τ,0]=ϕ. This is the scalar neutral problem of Scalar neutral delay equations and the derivative-segment shift. Its history is compatible at zero. On each later delay segment its derivative is multiplied by a: y′(kτ+s)=ak+1q(s−τ),0≤s≤τ. Thus for ∣a∣>1, derivative norms grow geometrically from segment to segment. At the boundary a=1, the finite-horizon shift inverse exists but its norm grows with the number K of segments. The uniform resolvent bound in The neutral derivative shift has a bounded Neumann inverse when ∣a∣<1 is therefore restricted to ∣a∣<1.

Facts & Assumptions

Given: A positive delay τ, the compatible history above, real a, and a finite horizon T=Kτ with integer K≥1.

[F1]

The scalar neutral equation is y′(t)−ay′(t−τ)=f(t,y(t),y(t−τ)), and compatibility is ϕ′(0)=aϕ′(−τ)+f(0,ϕ(0),ϕ(−τ)) (Scalar neutral delay equations and the derivative-segment shift).

[F2]

Compatible C1 history and continuous state-Lipschitz f give a unique solution by method of steps (Method of steps gives a unique compatible neutral-delay solution).

[F3]

When ∣a∣<1, the segment shift inverse has norm at most (1−∣a∣)−1 (The neutral derivative shift has a bounded Neumann inverse when ∣a∣<1).

Proof

1.1F1F2givenalgebra

Differentiating the displayed polynomial gives ϕ′=q, q(−τ)=1, and q(0)=a. With f=0, the compatibility equation [F1] reads a=a⋅1+0, so it holds. The zero right-hand side is continuous and Lipschitz in the two state variables. Therefore [F2] supplies the unique solution on every finite horizon Kτ.

2.1F1step 1.1inductionalgebra

On the first segment, the equation gives y′(s)=aϕ′(s−τ)=aq(s−τ). If on segment k−1 the derivative is akq(s−τ), then on segment k the same equation gives y′(kτ+s)=ay′((k−1)τ+s)=ak+1q(s−τ). Compatibility makes the left and right endpoint values agree at every breakpoint, so induction proves the formula for 0≤k<K. Since q(−τ)=1, each segment derivative has supremum at least ∣a∣k+1; for ∣a∣>1 this is geometric amplification.

3.1F1F3givenalgebra∎

For a=1, on the K-segment space from [F1], let rk(s)=1 and uk(s)=k+1 for 0≤k<K. The defined shift has (SKu)0=0 and (SKu)k=uk−1 for k≥1, so (I−SK)u=r. Also SKK=0, hence (I−SK)−1=I+SK+⋯+SKK−1 by multiplying the finite sum. Since ∥r∥XK=1 and ∥u∥XK=K, the inverse norm is at least K. Thus no horizon-independent bound follows at a=1, consistent with the strict hypothesis ∣a∣<1 in [F3].

ExampleConstruction: AI-generatedVerification: AI-generatedOpen item page →

Distributed-delay midpoint quadrature separates two history errors

Example

Take a scalar delay window of length τ, constant kernel K(θ)=1, and continuous path y(t)=t2 on [−τ,T], so its history is ϕ(s)=s2. At query time t=0, let h=τ/m and refine the composite midpoint rule with r=qm cells, where m,q≥1 are integers and Δ=τ/r=h/q. The exact integral is τ3/3. The exact-history midpoint remainder is τΔ2/12, while using the piecewise-linear stored history adds a distinct node-history term. The stored-history rule returns an error of τh2/6 in this example; the two terms are separated in Distributed-delay midpoint error separates history and quadrature errors.

Facts & Assumptions

Given: A scalar history ϕ(s)=s2 on [−τ,0], the constant kernel on [0,τ], an aligned state mesh h=τ/m, and midpoint refinement Δ=h/q.

[F1]

The distributed-delay integral is IK[y](t)=∫0τK(θ)y(t−θ) dθ (Distributed delays through a finite-window history integral).

[F2]

The composite midpoint rule samples the stored piecewise-linear history at θj=(j+1/2)Δ (Composite midpoint quadrature for a distributed delay history).

[F3]

Under its uniform stored-path error bound on [−τ,T], the error bound splits into a stored-history node term and an exact-history quadrature remainder (Distributed-delay midpoint error separates history and quadrature errors).

Proof

1.1F1givenalgebra

At t=0, [F1] gives I=∫0τθ2dθ=τ3/3. Put Qex=Δ∑j=0r−1θj2, the midpoint sum using the exact history. On a cell centered at cj, write θ=cj+u with −Δ/2≤u≤Δ/2. Then ∫−Δ/2Δ/2(cj+u)2du=cj2Δ+Δ3/12. Summing the cells gives I−Qex=rΔ3/12=τΔ2/12.

1.2F2givenalgebra

On the history cell [ℓh,(ℓ+1)h] in the variable θ=−s, the stored chord of ϕ satisfies ϕ^h(−θ)−θ2=(θ−ℓh)((ℓ+1)h−θ). Its maximum is h2/4, so the uniform interpolation error on [−τ,0] is h2/4. Since Δ=h/q, every midpoint subcell is contained in one such chord cell.

2.1step 1.1step 1.2algebra

The stored chord is affine on each width-h cell, and the midpoint rule is exact for an affine function on each of its q equal subcells: the centered linear term integrates to zero. Therefore the stored-history midpoint sum Qst equals the integral of the chord. The area between the chord and θ2 on one width-h cell is ∫0hv(h−v)dv=h3/6. Summing m cells gives Qst−I=mh3/6=τh2/6. Combining with step 1.1 yields Qst−Qex=τh2/6+τΔ2/12.

3.1F2F3givenstep 1.1step 1.2step 2.1algebra∎

At t=0 every sampled time −θj lies in [−τ,0], so [F2] and step 1.2 give ∣Qst−Qex∣≤Δ∑j=0r−1∣ϕ^h(−θj)−θj2∣≤τh2/4. Combining this with step 1.1 directly gives ∣I−Qst∣≤τh2/4+τΔ2/12, the same history/quadrature split as [F3]; this calculation needs no error bound for positive-time stored values. The exact node-history term from step 2.1 is τh2/6+τΔ2/12≤τh2/4 because Δ≤h. Its positive sign cancels the midpoint underestimate Qex−I=−τΔ2/12, leaving ∣Qst−I∣=τh2/6.

Sources