Abstract
We consider the Benjamin–Bona–Mahony (BBM) equation of the form where or We establish norm inflation (NI) with infinite loss of regularity at general initial data in Fourier amalgam and Wiener amalgam spaces with negative regularity. This strengthens several known NI results at zero initial data in established by Bona–Dai (2017) and the ill-posedness result established by Bona–Tzvetkov (2008) and Panthee (2011) in Our result is sharp with respect to the local well-posedness result of Banquet–Villamizar–Roa (2021) in modulation spaces for .
Keywords:
BBM equation; ill-posedness; Fourier amalgam spaces; Wiener amalgam spaces; Fourier–Lebesgue spaces; modulation spaces MSC:
35Q53; 35R25 (primary); 42B35 (secondary)
1. Introduction
We study strong ill-posedness for the Benjamin–Bona–Mahony (BBM) equation of the form
where unknown function and or . The BBM (1) can be written as
where , and is the Fourier multiplier operator defined by
This BBM (1) model is the regularized counterpart of the Korteweg–de Vries (KdV) equation. This is extensively studied in the literature; see [1,2,3,4,5]. BBM equation (1) is well-suited for modeling wave propagation on star graphs; see [6]. This model gave a good description of the propagation of surface water waves in a channel; see [5].
The aim of this paper is to establish the following strong ill-posedness (norm inflation at general initial data with infinite loss of regularity) for (1) in Fourier amalgam and Wiener amalgam spaces (to be defined in Section 2). We recall that
These time–frequency spaces are proven to be very fruitful in handling various problems in analysis and have gained prominence in nonlinear dispersive PDEs, e.g., [7,8,9,10,11,12,13,14,15]. We now state our main theorem.
Theorem 1.
Assume that and let
Then, norm inflation with infinite loss of regularity occurs to (1) everywhere in , i.e., for any , and , there exists a smooth and satisfying
such that the corresponding smooth solution to (1) with data exists on and
In particular, for any the solution map for (1) is discontinuous everywhere in for all .
In [3], Bona and Tzvetkov proved that (1) is globally well-posed in for . Moreover, they also proved that (1) is ill-posed for in the sense that the solution map is not from to . Later, in [16], Panthee proved that it is discontinuous at the origin from to . Recently, Bona and Dai, in [17], established norm inflation for (1) at zero initial data in for We note that Theorem 1 also holds for the corresponding homogeneous spaces; see Remark 1. The particular case of Theorem 1 strengthens these results by establishing the infinite loss of regularity at every initial datum in for In [18] (Theorem 1.7), Banquet and Villamizar-Roa proved that (1) is locally well-posed in for Thus, the particular case of Theorem 1 complements this result by establishing sharp, strong ill-posedness in for To the best of the authors’ knowledge, there is no well-posedness result for (1) in Fourier amalgam (except in ; see Corollary 1) or in (except in ) spaces. The infinite loss of regularity for (1) is initiated in the present paper and thus Theorem 1 is new.
We use a Fourier analytic approach to prove Theorem 1. This approach dates back to Bejenaru and Tao [19] to obtain ill-posedness for quadratic NLS and further developed by Iwabuchi in [20]. Later, Kishimoto [21] established norm inflation (NI) for NLS on a special domain (special domain: and with non-linearity: where , , with ) and Oh [22] established NI at general initial data for cubic NLS. Recently, this approach has been used to obtain strong ill-posedness for NLW in [15,23]. We refer to [21] (Section 2) for a detailed discussion of this approach.
We now briefly comment on and outline the proof of Theorem 1. We first justify the convergence of a series of Picard terms, the smooth solutions to (1), in Wiener algebra (see Corollary 1). This is possible since the linear BBM propagator is unitary on and the bilinear operator for the nonlinearity in (2) is bounded (see Lemma 1). Then, (1) experiences NI at general initial data because (with appropriately chosen initial data close to the given data) one Picard term dominates, in norm, the rest of the Picard iterate terms in the series for and also this term becomes arbitrarily large (see (16)–(18)). To this end, we perturb general initial data by Here, is defined on the Fourier side by a scalar (depends on N) multiplication of the characteristic function on the union of two intervals obtained by translation of by and so the size of support of remains uniform. Specifically, we set
where with (to be chosen later) and
Eventually, this will play the role of in Theorem 1. Similarly, was used by Bona and Tzvetkov to establish that the solution map fails to become in [3] and also by Panthee [16] to conclude that, in fact, the solution map is discontinuous. In [3], the size of the support of on the Fourier side was allowed to vary as with a normalizing constant to ensure that , whereas in [16], is taken as , which implies as . To establish NI with infinite loss of regularity, we multiply with Panthee’s choice of to ensure that the second Picard iterates have the desired property (as mentioned above) and reduce the analysis when considering a single term on the norm:
as done in NLW case in [23]. We note that finite loss of regularity of NLW was initiated by Lebeau in [24] and infinite loss of regularity for NLS, via a geometric optics approach, by Carles et al. in [25].
The rest of the paper is organized as follows. In Section 2, we recall the definitions of the time–frequency spaces. In Section 3, we establish power series expansion of the solution in , by establishing -estimates of the Picard terms for general data. In Section 4, we first prove various estimates of the Picard terms with particular choices of data, and this enables us to conclude the proof of Theorem 1.
2. Function Spaces
The notation means for some constant , whereas means for some . Let denote the Fourier transform and Here, denotes the Pontryagin dual of i.e., if and if . denotes the space of tempered distributions; see, e.g., [26] (Part II) for details. The Fourier–Lebesgue space is defined by
In the 1980s, Feichtinger [27] introduced the modulation spaces and Wiener amalgam spaces using shrot-time Fourier transform (STFT) (STFT is also known as windowed Fourier transform and is closely related to Fourier–Wigner and Bargmann transform. See, e.g., [28] (Lemma 3.1.1) and [28] (Proposition 3.4.1)). The STFT of a with respect to a window function is defined by
whenever the integral exists. Here, is the translation operator on . We define modulation and Wiener amalgam spaces , for , by the norms:
The definition of the modulation space is independent of the choice of the particular window function; see [28] (Proposition 11.3.2(c)). There is also equivalent characterization of these spaces via frequency uniform decomposition (which is quite similar to Besov spaces—where decomposition is dyadic). To do this, let , be a smooth function satisfying and Set and Then, define the frequency-uniform decomposition operators by
It is known [7] (Proposition 2.1), [27] that
Recently, in [29], Oh and Forlano introduced Fourier amalgam spaces
where The homogeneous spaces corresponding to the above spaces can be defined by replacing the Japanese brackets with in their definitions.
3. Local Well-Posedness in Wiener Algebra
Let us define the operator given by
Definition 1
(Picard iteration). For define and for
Lemma 1.
Let Then, we have
- (1)
- (2)
Proof.
Note that
Using the fact that , we have
□
Lemma 2
(See [21]). Let be a sequence of nonnegative real numbers such that
Then, we have , for all , where .
Lemma 3.
There exists such that for all and , we have
Proof
Let be a sequence of nonnegative real numbers such that
By Lemma 2, we have for some . In view of this, it is enough to prove the following claim:
By Definition 1, Lemma 1 and using the fact that , we have
Thus, we have
Hence, the claim is true for as . Assume that the result is true up to the label . Then, from (4), we obtain
Thus, the claim is true at the level k. This completes the proof. □
Corollary 1.
Proof.
Define
By Lemma 1, we have
Then, considering the ball
with , we find a fixed point of in and hence a solution to (3). This completes the proof of the first part of the lemma. For the second part, we note that in view of Lemma 3, the series (5) converges absolutely if . Then, for , there exists such that for all , one has
where
Note that for all j as . Using the continuity of on , we find such that for all
Note that
where we set
Note that has a lower number of terms in the sum above compared to that of . Hence, proceeding as in the proof of Lemma 3, one achieves the same estimates for . Thus, using ,
Then, there exists such that for , one has
Thus, u is the required fixed point for . □
4. Proof of Theorem 1
We first prove NI with infinite loss of regularity at general data in . Subsequently, for general data in , we use the density of in (). Thus, let us begin with . Now, define on via the following relation
where and to be chosen later. Note that
Let us set
Lemma 4
4.1. Estimates in
Lemma 5.
Let be given by (9), and Then, there exists C such that
- (1)
- (2)
- (3)
- (4)
Proof.
(1) follows from (10). By Lemma 1 and (10), we have . Then, (2) follows by using triangle inequality. By Lemma 3 and (10), we obtain
where denotes the -measure of the set A. Since , for any bounded set , we have
where is the interval centered at the origin with In view of this and Lemma 4, we obtain
Therefore,
Now, observe that
where . Observe that has atleast one coordinate as . Using Lemma 1 and the proof of Lemma 3, it follows that
as . Note that (3) is the particular case and (4) follows using the above and (12). □
Lemma 6.
Let be given by (9), , and and then we have
Proof
For notational convenience, we write
Using the symmetry of set , we have
Note that, with , one has
and so for and we have Hence, for . Thus,
Moreover, note that for . Thus, we have for
as . The above pointwise estimate immediately gives the desired estimate:
provided . □
4.2. Estimates in
Lemma 7
(inclusion). Let and . Then,
- (1)
- if
- (2)
- if
Proof.
(1) is a consequence of Minkowski inequality and Plancherel theorem, whereas (2) follows from the fact that if . □
Lemma 8.
Let be given by (9), and Then, there exists C such that
- (1)
- (2)
- (3)
- (4)
Proof.
By Lemma 7, we have
using Lemma 5 (1). Similarly, the other estimates also follow from Lemmata 5. □
Lemma 9.
Let be given by (9), , and then we have
Proof.
Note that using Plancherel theorem and (14), we have
This completes the proof. □
Proof of Theorem 1.
We first consider the case . If the initial data satisfy (11), Corollary 1 guarantees the existence of the solution to (3) and the power series expansion in up to time (as ). By Lemma 5, we obtain
provided Note that
Using Corollary 1 and triangle inequality, we have
Let . In order to ensure , we rely on the conditions
Thus, to establish NI with infinite loss of regularity at in , we claim that it is enough to have the following:
- (1)
- (2)
- (3)
- (4)
- ⇔ (2)
- (5)
as . Note that (1) ensures , whereas (2) ensures the convergence of the infinite series in view of Lemma 5. In order to use Lemma 6, we need (4). In order to prove (Section 4.2), in view of Lemma 6 and (15), we need (4). Condition (3) implies (Section 4.2) using Lemma 5 (3) and Lemma 6. In order to prove (Section 4.2), we need (1) and (3) by using Lemma 5 (2) and Lemma 6. Thus, it follows that
Hence, the result is established. We shall now choose R and T as follows:
where are to be chosen below. Therefore, it is enough to check
Thus, we only need to achieve:
and take N large enough. Let us concentrate on the choice of first. Note that the second and third conditions in the above are equivalent to
To make room for , we must have Thus, r must satisfy
where the latter condition comes from the first condition. Thus, it is enough to choose
which will satisfy all the above four conditions. Hence, the result follows.
For the case , we use same argument as above. Note that using Lemmata 8 and 9, we have
and provided that we choose as in the case of □
Remark 1.
It is easy to check that our proof of the main results will work even if we replace the weight by in the function spaces involved. Since the analysis will be similar, we omit the details. We simply note that as for large n, we have , where is as in (9). Moreover, it should work with any weight that is decreasing in and behaves as as .
Author Contributions
Both authors D.G.B. and S.H. have equally contributed in the present paper. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
Not applicable.
Acknowledgments
Divyang G Bhimani is thankful to DST-INSPIRE (DST/INSPIRE/04/2016/001507) for the research grant. Saikatul Haque acknowledges the Department of Atomic Energy, Govt of India, for the financial support and Harish-Chandra Research Institute for the research facilities provided.
Conflicts of Interest
The authors declare no conflict of interest.
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