Traveling waves for the diffusive Nicholson's blowflies equation

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Abstract

We consider traveling wave front solutions for the diffusive Nicholson's blowflies equation on the real line. The existence of such solutions is proved using the technique developed by J. Wu and X. Zou (J. Dyn. Differ. Equations 13 (3) (2001)). Some numerical simulation using the iteration formula of Wu and Zou [7] is also provided.

Introduction

Consider the reaction–diffusion equation with a discrete time delayN(t,x)t=2N(t,x)x2−δN(t,x)+pN(t−τ,x)e−aN(t−τ,x),where x∈R and t⩾0. Such an equation had been studied in [4], [5], [8]. For the case when there is no spatial dependence, the corresponding delay equation was referred to as Nicholsons's blowflies equation, cf. [1] after the experiments of Nicholson [2], [3] had been extensively studied. Eq. (1) can be derived based on first principles by making use of the spatial (this leads to the diffusion term) and age structures (this leads to the discrete delay τ) of the population. The general theory of reaction–diffusion equations with delays can be found in [6].

Assume p/δ>1. Then there are two equilibria: N0=0 and Ne=1/aln(p/δ). A traveling wave front is a solution of (1) of the form u(t,x)=φ(x+ct), where c>0, φ(t) is monotone increasing and it satisfies(t)=φ″(t)−δφ(t)+pφ(t−cτ)e−aφ(t−cτ),φ(−∞)=N0,φ(+∞)=Ne.The main result of this paper is:

Theorem

If 1<(p/δ)⩽e, then there exists c*>0 such that for every c>c* there exists a traveling wave front for (1) with speed c.

In Section 2, we will prove this theorem by applying [7, Theorem 3.6], which is for delayed reaction–diffusion systems. Since we are considering a scalar equation here, for the convenience of reference and for simplicity, we only need a scalar version of this theorem, which is stated below.

Consider the delayed reaction–diffusion equationu(t,x)t=D2u(t,x)x2+f(ut(x)),where t⩾0,x∈R,u∈R with D>0, and f:C([−τ,0],R)R is continuous and ut(x) is an element in C([−τ,0],R) parameterized by x∈R and given byut(x)(s)=u(t+s,x),s∈[−τ,0],t⩾0,x∈R.Looking for traveling wave solutions of the form u(t,x)=φ(x+ct) leads to a second-order functional differential equationDφ″(t)−cφ(t)+fct)=0,t∈R,where fc:Xc=C([−cτ,0],R)R is defined byfc(ψ)=f(ψc),ψc(s)=ψ(cs),s∈[−τ,0].We assume

  • (A1) There exists K>0 such that fc(0̂)=fc(K̂)=0 and fc(û)≠0 for u∈(0,K), where û denotes the constant function taking the value u on [−,0].

  • (A2) (Quasi-monotonicity). There exists β⩾0 such thatfc(φ)−fc(ψ)+β[φ(0)−ψ(0)]⩾0for φ,ψXc with 0⩽ψ(s)⩽φ(s)⩽K,s∈[−cτ,0].

If for some c>0, (4) has a monotone solution φ satisfying limt−∞φ(t)=0 and limtφ(t)=K, then u(t,x)=φ(x+ct) is called a traveling wave front of (3) with speed c.

Next we define the profile set for traveling wave fronts of (3) byΓ=φ∈C(R;Rn),

  • (i) φ is nondecreasing in R,

  • (ii) limt→−φ(t)=0,limtφ(t)=K.

A function φ∈C(R,R) is called an upper (resp., lower) solution of (4) if it is differentiable almost everywhere (a.e.) and satisfies⩾Dφ″(t)+fct),a.e.inR,resp.,⩽Dφ″(t)+fct),a.e.inR.Now we are in the position to state a scalar version of [7, Theorem 3.6].

Theorem A

Assume that (A1)–(A2) hold. Suppose that (4) has an upper solution φ in Γ and a lower solution φ (which is not necessarily in Γ) with 0⩽φ(t)⩽φ(t)⩽K and φ(t)≢0 in R, then (3) has a traveling wave front.

Section snippets

Proof of existence of traveling waves

Define the functional fc by fc(φ)=−δφ(0)+(−)e(−) . Then

Claim 2.1

If (p/δ)>1, then fc(N̂0)=fc(N̂e)=0, and fc(K̂)≠0 for any K∈(N0,Ne), where denotes the constant function taking the value K on [−,0].

Claim 2.2

If 1<(p/δ)⩽e, then fc satisfies the following quasi-monotonicity condition:

For all βδ, we havefc1)−fc2)+β[φ1(0)−φ2(0)]⩾0for all φ12∈C([−cτ,0],R) with N0φ2(s)⩽φ1(s)⩽Ne for all s∈[−,0].

Proof

fc1)−fc2)=−δ[φ1(0)−φ2(0)]+pφ1(−cτ)e−aφ1(−cτ)−φ2(−cτ)e−aφ1(−cτ).Consider the function h(y)=yeay. Thenh

Numerical simulations

By the results in Section 3 in [7], the wave profile φ can be obtained by the convergence of the following iteration:φm(t)=1λ2−λ1−∞teλ1(t−s)H(φm−1)(s)ds+∫teλ2(t−s)H(φm−1)(s)ds,φ0(t)=φ(t),where t∈R,m=1,2,…, and H:C(R,R)C(R,R) is defined byH(φ)(t)=pφ(t−cτ)e−aφ(t−cτ),φ∈C(R,R),t∈R.Now we take some particular values for the parameters values, p=2, δ=1, a=1, τ=1 and c=2. Then Ne=0.6931471806, λ1=0.1954954948, λ2=2.408480501 and t0=−1.874789600. The graphs of φ and φ1 (i.e., after one iteration)

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Research partially supported by Natural Sciences and Engineering Research Council of Canada.

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