Regularity and structure of pullback attractors for reaction–diffusion type systems without uniqueness
Introduction
A multi-valued non-autonomous dynamical system (m-NDS) is generated by an evolution equation whose solution is unnecessarily unique. The study on m-NDS has particular significance since m-NDS are often established under weaker conditions than usual (single-valued) dynamical systems. For an m-NDS on a Banach space , a pullback attractor is defined as a compact and negatively invariant non-autonomous set which attracts each bounded subset of (see Definition 2.7). This can be regarded as a generalization of pullback attractors for single-valued dynamical systems which have been studied widely, see for instance [3], [4], [5], [11].
In this paper, we study the structure and regularity of the pullback attractor for the m-NDS generated by the following reaction–diffusion equation defined on a bounded domain : where , , is a real matrix with a positive symmetric part for some , and satisfies some conditions unable to ensure the uniqueness of solutions (see Section 4). The most direct example of this system is the classical reaction–diffusion equation (taking ) frequently seen in the literature. Nevertheless, the system (1.1) covers more models, such as the Fitz-Hugh–Nagumo equations considered in Section 4.4, and others stated by [16], [15].
We get three aims in this work. The first is the existence of the -pullback attractor for (1.1), which is a non-autonomous set pullback attracting bounded sets of under the topology of , where This is a study of bi-spatial attractors which attracted much attention these years due to their higher regularity and stronger attracting ability compared with usual attractor, see [7], [13], [12] for single-valued non-autonomous/random cocycles and [21], [19] for multi-valued semi-groups and random cocycles, respectively. In this paper, we develop a study for m-NDS which can be regarded as an extension of the bi-spacial attractor theory on one hand, and is interesting because of the multi-valued feature on the other hand.
The second aim is to establish the backwards precompactness of , that is, This subject is new since the compactness of a pullback attractor is often considered for each fixed “section” in the literature. To achieve this, we first establish some sufficient conditions to ensure an attractor to be backwards precompact, and then apply them to the system (1.1) when the external force is backwards translation bounded, namely, with This condition is shown weaker than translation bounded condition considered in [8] and stronger than tempered conditions seen in recent studies for random dynamical systems, such as [17] and references therein. Establishing a non-autonomous set which is absorbing and increasing in plays a key role to obtain the backwards compactness of the attractor.
The third main aim is to characterize the pullback attractor by complete trajectories. For strict m-NDS we first introduce the concept of an m-NDS generating smooth trajectories, and then prove that backwards bounded pullback attractors for such systems are composed of backwards bounded trajectories, see Theorem 2.24. Note that, the class of dynamical systems who generate smooth trajectories is rather general. A direct example is the so-called generalized dynamical systems, first studied by Ball [1] and recently studied by Simsen [14] for generalized semiflows and Kapustyan et al. [9] for generalized processes, etc. Therefore, Theorem 2.24 is interesting even in single-valued cases as single-valued systems must be strict.
We carry out this work as follows.
In Section 2, we first make some necessary definitions, and then establish some abstract results on the existence of a backwards bounded pullback attractor and on the structure of pullback attractors is also studied in this section.
In Section 3, we first establish a result on the existence of a bi-spatial pullback attractor by making a direct comparison on bi-spatial and single-spatial attractors, see Theorem 3.9. This result indicates an interesting fact that the regularity of a pullback attractor, once the attractor exists, is determined by the dynamical compactness of the system. Then we establish several sufficient conditions to verify the backwards precompactness of a pullback attractor. These conditions are established by strengthening the dynamical compactness of the system (see Theorem 3.18), and this coincides with the observation that the regularity properties of the attractor have a close relationship with the dynamical compactness.
In Section 4, we study the system (1.1) and find that, under certain conditions the system (1.1) admits an -pullback attractor which is invariant and composed of backwards compact complete trajectories. A Fitz-Hugh–Nagumo equation is studied as a specific example.
Section snippets
Backwards bounded pullback attractors for m-NDS
Throughout this paper, let be a separable Banach space. Denote by the set of all nonempty closed subsets of and the set of all bounded closed subsets of . . The Hausdorff semi-distance between two nonempty subsets and of is defined by . Denote the open -neighborhood of a subset of by . Suppose is a group of translation operators acting on defined by
Definition 2.1 A non-autonomous set in is a
Bi-spatial pullback attractors for strongly dispersive m-NDS
Many m-NDS have a smoothing property that they admit a pullback absorbing set more regular than the initial data. In this part we study the so-called bi-spatial pullback attractors for smoothing m-NDS.
In the following we let and be two separable Banach spaces with continuously except otherwise stated. We first make some elementary definitions. Definition 3.1 Suppose is an m-NDS in , then is called -dispersive if has a pullback absorbing set which is a bounded non-autonomous
Notations
Let be a positive integer and with a bounded open domain with smooth boundary. Suppose it holds in the Poincare inequality for some We often write as an element of for simplicity. Let be arbitrarily given. Define Let be arbitrarily a vector in with . Denote , and Then it makes sense to define the
Acknowledgments
The authors would like to thank the referees for their carefully reading the script and helpful comments which lead to a great improvement of this work. Hongyong Cui would like to express his sincere thanks to Prof. José A. Langa for his careful guidance and great hospitality during the joint-training program. H. Cui was supported by State Scholarship Fund grant 201506990049, J.A. Langa was partially supported by Junta de Andalucía under Proyecto de Excelencia FQM-1492 and Brazilian-European
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