Instability of unidirectional flows for the 2D $\alpha$-Euler equations
Holger Dullin, Yuri Latushkin, Robert Marangell, Shibi Vasudevan,, Joachim Worthington

TL;DR
This paper investigates the linear stability of unidirectional flows in the 2D α-Euler equations on a torus, revealing conditions under which these flows are unstable and characterizing their eigenvectors using continued fractions.
Contribution
It provides a necessary and sufficient instability criterion for unidirectional flows in the 2D α-Euler equations, employing continued fractions techniques.
Findings
Unidirectional flows with a specific geometric condition are linearly unstable.
Derived a complete characterization of eigenvectors associated with unstable modes.
Established a criterion for positive eigenvalues based on continued fractions.
Abstract
We study stability of unidirectional flows for the linearized 2D -Euler equations on the torus. The unidirectional flows are steady states whose vorticity is given by Fourier modes corresponding to a vector . We linearize the -Euler equation and write the linearized operator in as a direct sum of one-dimensional difference operators in parametrized by some vectors such that the set covers the entire grid . The set can have zero, one, or two points inside the disk of radius . We consider the case where the set has exactly one point in the open disc of radius . We show…
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Instability of unidirectional flows for the 2D -Euler equations
Holger Dullin
School of Mathematics and Statistics, University of Sydney NSW 2006, Australia
,
Yuri Latushkin
Department of Mathematics, University of Missouri, Columbia, MO 65211, USA
,
Robert Marangell
School of Mathematics and Statistics, University of Sydney NSW 2006, Australia
,
Shibi Vasudevan
International Centre for Theoretical Sciences, Tata Institute of Fundamental Research, Bengaluru, 560089, India
and
Joachim Worthington
School of Mathematics and Statistics, University of Sydney NSW 2006, Australia
Cancer Research Division, Cancer Council NSW, Woolloomooloo, NSW 2011, Australia
Dedicated to Prof. Tomás Caraballo on the occasion of his 60-th birthday
Abstract.
We study stability of unidirectional flows for the linearized 2D -Euler equations on the torus. The unidirectional flows are steady states whose vorticity is given by Fourier modes corresponding to a vector . We linearize the -Euler equation and write the linearized operator in as a direct sum of one-dimensional difference operators in parametrized by some vectors such that the set covers the entire grid . The set can have zero, one, or two points inside the disk of radius . We consider the case where the set has exactly one point in the open disc of radius . We show that unidirectional flows that satisfy this condition are linearly unstable. Our main result is an instability theorem that provides a necessary and sufficient condition for the existence of a positive eigenvalue to the operator in terms of equations involving certain continued fractions. Moreover, we are also able to provide a complete characterization of the corresponding eigenvector. The proof is based on the use of continued fractions techniques expanding upon the ideas of Friedlander and Howard.
Key words and phrases:
2D -Euler equations, instability, continued fractions, essential spectrum, unidirectional flows
Partially supported by NSF grant DMS-171098, Research Council of the University of Missouri and the Simons Foundation.
1. Introduction and basic setup
1.1. Introduction
The study of eigenvalues of the differential operators obtained by linearizing the Euler and Navier Stokes equations about a steady state using the methods and techniques of continued fractions was initiated by Meshalkin and Sinai in the 1960s in their paper [25], and since then has been pursued by many authors, for example [5, 12, 14]. We caution the reader that this is a non exhaustive sample of the literature. See [4, 6, 9, 10, 16, 23] for related work on the stability of steady state solutions to the Euler equations.
In this paper we continue the work in this direction, and study stability of a special steady state, the unidirectional flow, of the 2D -Euler equations on the torus written for the Fourier coefficients of vorticity. The -Euler equations are an inviscid regularization of the classical Euler equations. They were introduced and studied in a series of foundational papers by C. Foias, D. Holm, J. Marsden, T. Ratiu, E. Titi and others; see [17], [19], [20] and references therein. The unidirectional steady state has exactly two nonzero Fourier mode corresponding to a twodimensional vector with integer components and its negative . We linearize the -Euler equation and write the linearized operator in as a direct sum of one-dimensional difference operators in parametrized by some vectors such that the set covers the entire grid , see [9, 23, 24]. The set can have zero, one or two points inside the disk with radius centred at the origin. We primarily consider the second case, and apply continued fractions to the study of spectral properties of the respective difference operator , cf. [12, 23, 25]. We show the existence of a positive eigenvalue for in this case, which implies that has unstable spectrum. Therefore, the unidirectional steady states that have one point inside the disk of radius are linearly unstable. Our main result is an instability theorem that provides a necessary and sufficient condition for the existence of a positive eigenvalue to the operator in terms of equations involving certain continued fractions. Moreover, we are also able to provide a list of additional properties of the corresponding eigenvectors.
More details and a precise formulation are given in Theorem 2.9 in Section 2. Section 3 contains some results on continued fractions that are used in the proofs of the instability theorem in Section 2. In Section 4, following the ideas presented in [24], we characterize the essential spectrum of the linearized operator and prove the spectral mapping theorem for the group generated by .
1.2. Basic setup and governing equations
We consider two dimensional -Euler equations for incompressible ideal fluid on the torus written in vorticity form,
[TABLE]
where is the vorticity of the fluid and the smoothed velocity, . Here
[TABLE]
where is a positive real number. Since , there exists a stream function , such that , where . This means that
[TABLE]
Assuming allows one to solve (1.3) for the stream function , and in addition, by imposing the condition one obtains a unique solution. Using the Fourier series
[TABLE]
and equation (1.3), one obtains the following relationship among the Fourier modes of and ,
[TABLE]
for every . Here denotes the standard Euclidean norm in . Using the Fourier series expansion one can re-write the first equation in (1.1) for each Fourier mode of as
[TABLE]
where the coefficients for are defined as
[TABLE]
for , and otherwise. Here
[TABLE]
The derivation of (1.5) is given in the Appendix. We refer to [23] for equation (1.5) in the Euler case when .
The choice of spaces for the sequences depends on the choice of vorticity in (1.1). For instance, if , the Sobolev space, then , the space of sequences square summable with the weight . In what follows we will mainly consider the case , that is, and as the case is analogous.
1.3. Unidirectional flows
A unidirectional flow is the flow induced by a time independent solution of (1.1) that has only one nonzero Fourier mode, that is,
[TABLE]
i.e., the Fourier coefficients are given by
[TABLE]
where is the complex conjugate of .
A well-known example of the unidirectional flow is given by the Kolmogorov flow with vorticity , (see, e.g., [25]); this corresponds to the choice and . In the case when the steady state solution of the Euler equation is called in [4] a bar-state. Unidirectional flows by definition are special cases of shear flows. A shear flow has a general Fourier series but still only a flow in one direction.
The unidirectional flows have been studied by many authors, see e.g. [4, 9, 10, 23, 24] and the literature therein. We demonstrate that the unidirectional flow is indeed a steady state of (1.5) in Lemma 7.2 in the Appendix.
We use notation , where stands for the “bar state”, for the linearization of (1.5) about the steady state (1.8), that is, we linearize (1.5) about the unidirectional flow and consider in the following operator,
[TABLE]
(see the Appendix for derivation of formula (1.10)).
Our objective is to show that the spectrum of the operator contains an unstable eigenvalue (i.e., an eigenvalue that has a positive real part) provided is sufficiently large.
1.4. Remarks
We remark that our results also pertain to the 2D Euler case by formally putting in the -Euler setting. Although this paper is written for the -Euler equations, all the ideas, techniques and results of this current paper will carry over to the Euler case. One can thus claim instability of unidirectional steady states for the Euler equations using the same techniques of the current paper. In other words, our results hold for every . We present the results for the -Euler model because, despite being used in diverse areas such as turbulence modeling (see [7, 8]) and data assimilation (see [3]), very little seems to be known about the stability properties of this model. The velocity and the vorticity are related via the following Biot-Savart law . Notice that the velocity is more regular in this case compared the the Euler () case. Similar ideas involving continued fractions have been used by S. Friedlander and R. Shvydkoy, see [13] , to characterize the unstable point spectrum of the quasi geostrophic equation which is much more singular than the present model in the sense that the Biot-Savart law relating a scalar quantity and the velocity is given by . The paper [13] also characterizes the unstable essential spectrum of the surface quasi geostrophic equations. Furthermore, R. Shvydkoy, in paper [27], has provided a characterization of the essential spectrum of a wide class of linear advective equations, examples which include, see Section 3.3 in [27], the 2D Euler equations with and without the Coriolis rotation term, the -Euler equations, the surface quasi-geostrophic equations, the Boussinesq equations and the kinematic dynamo.
2. Instability of the unidirectional flows
In this section we first review some results regarding the operator defined in (1.10). We use the approach taken in [9, 10, 23, 24]. Next, we show the existence of a positive eigenvalue of . Our main result is Theorem 2.9 proved below.
2.1. Decomposition of subspaces and operators
In this subsection we follow [9, 23, 24] and explain how to decompose the operator acting in into the direct sum of operators , , acting in the space , for some set .
Let be the fixed vector from (1.8). Our first objective is to construct the set such that the translated vectors of the form , with and , cover the entire grid in a way that for different and from the sets of the translated vectors, formed by all , are disjoint. To begin the construction, for any we denote and note that the line may contain several different sets . For a given , we let temporarily denote the radius of the smallest circle centered at zero that has a nonempty intersection with the set . The intersection consists of either one point (which we will denote by ) or two points (in this case we denote by one of them). In other words, for each we identify the unique vector in such that the following holds:
[TABLE]
The second condition simply fixes one of the possibly two points in that belong to the circle of radius . We let .
We will now decompose the operator in into a direct sum of operators acting on the spaces isomorphic to . Indeed, for each we denote by the subspace of of sequences supported in , that is, we let X_{B,{\mathbf{q}}}=\{(\omega_{\mathbf{k}})_{{\mathbf{k}}\in{\mathbb{Z}}^{2}}:\omega_{\mathbf{k}}=0\text{ for all {\mathbf{k}}\notin\Sigma_{B,{\mathbf{q}}}}}. Clearly, , the operator leaves invariant, and therefore where is the restriction of onto . To emphasise that depends on from (1.8), we sometimes write and . For we denote , , and remark that the map is an isomorphism of onto . Under this isomorphism the operator in induces an operator in (that we will still denote by ) given by the formula
[TABLE]
By (1.6), if is parallel to then ; therefore, in what follows we will always assume that and are not parallel.
We recall that is the Sobolev space of -periodic functions with derivatives in . Via Fourier transform, is isometrically isomorphic to , the set of sequences which are summable with the weight . As above, we may decompose , where is the space with the weight . Since the results for and are analogous, in what follows we will consider only the space .
Our objective is to study the spectrum of in . From now on we assume that . Then can be written as , where is the shift operator in and we introduce the notation
[TABLE]
with as defined in (1.7).
Lemma 2.1**.**
The nonzero eigenvalues of are symmetric about the coordinate axes, i.e., if is an eigenvalue, then are also eigenvalues.
This is a result of the Hamiltonian structure of the -Euler equation. We refer to [24, Prop.4, p.269] and the Appendix for a proof.
Due to Lemma 2.1, to prove spectral instability of the unidirectional flow we need to show the existence of at least one such that has an eigenvalue with nonzero real part. In turn, this is equivalent to showing that the spectrum of a multiple of has an eigenvalue with nonzero real part. Here, is any non-zero real constant that we choose. In particular, dividing by the -independent real multiple , we pass to the operator of the same structure as but with the term in (2.1) replaced by . In fact, this procedure is equivalent to rescaling . In order to simplify notations we will assume in what follows that in (2.1) already satisfies the normalization condition
[TABLE]
We introduce notation
[TABLE]
Using the normalization condition, we see that . Therefore, we want to study the spectrum of the operator
[TABLE]
Remark 2.2**.**
We will now classify points recalling notations and introduced in the beginning of Subsection 2.1. For any the intersection of the set with the open disc of radius may have either zero, one, or two points. If this is the case then we call a point of type [math], and .
If is a point of type then the set contains exactly one vector whose norm is stricly smaller than . We further classify points of type as follows, see Figure 1 and Examples 2.3, 2.4, 2.5. We say that is of type if all other vectors in have norms strictly larger than . This means that the only vector in whose norm does not exceed is located strictly inside the disk of radius .
There are two more possibilities for to be strictly inside the disc of radius . The first is when the preceeding point, , belongs to the boundary of the disc and the second possibility is when the following point belongs to the boundary of the disc. These two cases are classified as type and respectively: we say that is of type if , , and all other vectors in have norms strictly larger than and is of type if , , and all other vectors in have norms strictly larger than .
Example 2.3**.**
See Figure 1 and [9]. Let . Then is of type [math], is of type , is of type , is of type and is of type .
Example 2.4**.**
Let . Then is of type , while is of type whereas is of type .
Example 2.5**.**
Let . Then is of type .
In what follows, dealing with the operator from (2.1), we will drop hat in the notation , that is, we assume that satisfies .
Remark 2.6**.**
The fact that is a point of type [math], , or leads to the following respective conclusions:
(i) Assume that , that is, is a point of type [math]. Since is chosen to minimize , we know that and therefore or for all .
(ii) Assume that and that the line has exactly one point in the open disc of radius (that is, we assume that is a point of type ). Then . If is of type then and for all . If is of type , then and and for all . If is of type , then and and for all .
(iii) Assume that is a point of type , i.e., we assume that , that , and that for all . Then , but for all .
The operator defined in (2.4) is a product of two operators and can be viewed as an infinite matrix with two nonzero diagonals. It is sometimes convenient to make this matrix more symmetric by putting a square root of the operator in front of the multiple . To achieve that, using (2.3), we introduce the following notation,
[TABLE]
so that . Since , the nonzero elements of the spectrum of coincide with the nonzero elements of the spectrum of the operator defined by
[TABLE]
This is a consequence of the following well-known fact:
Lemma 2.7**.**
Suppose are bounded linear operators on a Banach space . Then .
We can thus study the spectrum of the operator instead of . The operator has the following structure:
[TABLE]
The “central” entry has been marked with a box, for future reference. We remark that and since and that is a compact perturbation of , therefore .
If is a point of type [math] then has no unstable point spectrum (cf. [24, Remark 4]). Indeed, if for all , i.e., is a point of type [math] and , then , i.e., is skew-adjoint and its spectrum is thus purely imaginary.
We now consider for being of type or . Then two cases are possible:
- (a)
and for all ; 2. (b)
and for all .
We note that case (a) corresponds to item (ii) while case (b) corresponds to item (iii) in the list given in Remark 2.6.
In case (a) the block
[TABLE]
is self adjoint while the remaining part of is skew-adjoint because only for and for . In case (b) we have and for and then provided that and for . This means that in case (a) or (b) we do not know that the spectrum of is purely imaginary and there is a possibility that unstable eigenvalues exist.
Indeed, if is a point of type then the arguments given in Subsection 2.2 (cf. also [9]) based on the use of continued fractions yield the existence of an unstable eigenvalue for . In a sense, we adapt to the current setting the proof from [12] used therein for the Orr-Sommerfeld operator, see also [25]. However, if is a point of type then the question whether or not there are unstable (complex) eigenvalues is an important open problem.
2.2. Unstable eigenvalues for unidirectional flows in case of the point of type
The main result of this subsection states that the linearized Euler operator has a positive eigenvalue provided at least one point is of type . Here, we are using the classification of points given in the previous subsection, see Remark 2.2. Specifically, we will show that if is the only point in satisfying , i.e. if is of type , then has a positive eigenvalue. We recall that by (2.3) the coefficients in from (2.4) are given by the formula
[TABLE]
For simplicity, we first consider a point of type , and outline an informal argument that shows the existence of a positive eigenvalue of . In this case and for all . That is, for all and . This implies that if the point is of type then
[TABLE]
We consider the eigenvalue problem
[TABLE]
Letting , equation (2.9) is equivalent to the difference equation
[TABLE]
where are given by formula (2.7). Note that as . Assuming for any , we introduce the notation (and note that for any since ), and re-write (2.10) as
[TABLE]
Forwards iterating the first equation in (2.11) for and backwards iterating the second equation for , we obtain two -depending sequences,
[TABLE]
from which we obtain the following two formulas for the entry of the solution to the difference equation (2.11):
[TABLE]
where we introduce and as the continued fractions
[TABLE]
We refer to Section 3 for basic results concerning continued fractions. The continued fractions in (2.14) converge by the Van Vleck Theorem, see [21, Theorem 4.29].
Clearly (as we prove in Lemma 2.12(1) below), is an eigenvalue of with an eigenvector provided there is a corresponding solution to (2.11) which, in turn, happens if and only if , or, equivalently, if and only if satisfies the equation
[TABLE]
Thus, to show the existence of a positive eigenvalue of it is enough to show the existence of a positive root of equation (2.15).
Using (2.8) we observe that if is of type then both functions and take positive values for positive . We will also see in Lemma 2.10(4) that
[TABLE]
Since by (2.8), equation (2.15) must have a positive root, as claimed. A similar argument works if is of type , that is, and . In this case we will use as in (2.14) and set in (2.15). If is of type , that is, and , we will use as in (2.14) and set in (2.15).
We will show below that condition (2.15) is not only sufficient but is also necessary for to be an eigenvalue of the operator . Since the respective eigensequence is related to the sequence from (2.11), and the latter is eventually given by means of the continued fractions in equations (2.12) and (2.13), where, by construction, for and for , the sequence must possess some additional properties. Indeed, due to (2.12) and (2.13), we require our to be such that for and for . Using the formulas and one can check directly that either one of the following two possibilities must happen: Either (a): must be so that for , , and are all positive while are all negative; or (b): the sequence satisfies these inequalities.
We will now proceed with a more formal proof of the fact that if is a point of type then has a positive eigenvalue with the eigenvector satisfying
Property 2.8**.**
- (1)
In case is of type , the eigenvector of (2.9) is such that the following holds: either for , for , and for , or the entries of the vector satisfy the inequalities just listed. 2. (2)
In case is of type , the eigenvector of (2.9) is such that the following holds: either for , , for , and for , or the entries of the vector satisfy the inequalities just listed. 3. (3)
In case is of type , the eigenvector of (2.9) is such that the following holds: either for , for , and for , or the entries of the vector satisfy the inequalities just listed.
Thus, if is of type and Property 2.8 holds then the entries are of alternating signs if , that is, are all negative and are all positive, and, in particular, for any integer . If is of type and Property 2.8 holds then the entries of the eigenvector satisfy the same inequalities as the case when is of type except that for . If is of type and Property 2.8 holds then the entries of the eigenvector satisfy the same inequalities as the case when is of type except that for .
We recall the notation for the weighted spaces and given in the discussion following (2.1). Our main theorem is the following.
Theorem 2.9**.**
Assume that is such that at least one point is of type , where is not parallel to . Also, we assume that and satisfies the normalization condition
[TABLE]
Then the steady state defined in (1.9) is linearly unstable.
In particular, the operator in the space has a positive eigenvalue and therefore in has a positive eigenvalue.
Moreover, the following assertions hold.
- (1)
If is of type then is an eigenvalue of with eigenvector satisfying Property 2.8(1) if and only if is a solution to the equation
[TABLE] 2. (2)
If is of type then is an eigenvalue of with eigenvector satisfying Property 2.8(2) if and only if is a solution to the equation
[TABLE] 3. (3)
If is of type then is an eigenvalue of with eigenvector satisfying Property 2.8(3) if and only if is a solution to the equation
[TABLE]
Before presenting the proof of Theorem 2.9 we will need two lemmas. Their proofs rely on the auxiliary material on continued fractions contained in Section 3.
Lemma 2.10**.**
Assume is of type , fix any positive and consider the following continued fractions,
[TABLE]
[TABLE]
Then the following assertions hold:
- (1)
* and are convergent continued fractions and the functions and are continuous in .* 2. (2)
There exist limits
[TABLE]
satisfying , . 3. (3)
For some and , the following hold
[TABLE]
[TABLE] 4. (4)
, for .
Proof.
(1) This follows from the Van Vleck theorem and the Stjeltjes-Vitali Theorem, see [21, Theorem 4.29 and Theorem 4.30], since , and thus satisfies and hence the continued fractions and converge. In addition, the Van Vleck Theorem also guarantees that the maps are holomorphic in since implying the continuity clause.
(2) The fact that the limits and exist follows from item (3) in Lemma 3.1 proved in Section 3. Passing to the limit as in (2.20) and (2.21) we see that
[TABLE]
since as . Thus, we notice that both and satisfy the following quadratic equation
[TABLE]
the solutions of which are given by . Notice also that must be positive and must be negative. From these it is seen that and and , .
(3) Let . Note that from (2), since , there exists an integer such that if , then . We thus have that,
[TABLE]
where we have denoted C=C(q^{\prime})=\big{(}{u^{(1)}_{1}(\lambda)\ldots u^{(1)}_{N_{q^{\prime}}}(\lambda)}{q^{\prime-N_{q^{\prime}}}}\big{)}^{-1}. Let and we thus obtain (2.22). Since , we have that for a fixed such that , there exists an integer such that if , then . We thus have that,
[TABLE]
where we have denoted . This proves (2.23).
(4) Noticing that and , this follows from items (4) and (5) in Lemma 3.1 proved in Section 3. ∎
Remark 2.11**.**
If is of type , we will use the continued fraction for and if is of type , we will use the continued fraction for .
Lemma 2.12**.**
Fix any positive and consider the continued fractions and given in (2.20) and (2.21). Then the following hold.
- (1)
If is of type , then with eigenvector satisfying Property 2.8(1) if and only if . 2. (1P)
If is of type , then with eigenvector satisfying Property 2.8(2) if and only if . 3. (1M)
If is of type , then with eigenvector satisfying Property 2.8(3) if and only if . 4. (2)
The respective eigenvectors for are exponentially decaying sequences and therefore belong to for any . 5. (3)
Equation has at least one positive root provided is of type , equation has at least one positive root provided is of type , and equation has at least one positive root provided is of type .
Proof.
(1) Let be of type and suppose , , with eigenvector that satisfies Property 2.8(1). We wish to show that . Beginning at the eigenvalue equation (2.9), that is,
[TABLE]
and putting , we obtain equation (2.10). Notice that Property 2.8 implies that for any and hence for any . Putting , we obtain (2.11) from (2.10).
Consider the continued fractions (2.20) and (2.21). We claim that for every and for every . This would then imply that .
We now give the proof of the fact that the continued fraction defined by matches the given by (2.11) when . It follows, from standard facts of continued fractions, see for example [21, Chapter 2], that the odd truncations form a monotonically decreasing sequence and the even truncations form a monotonically increasing sequence and is sandwiched in between these. That is, we have, for every ,
[TABLE]
Denote by the finite continued fraction obtained by iterating the first formula in (2.11) times. That is, for every fixed positive integer , and is given by the formulas
[TABLE]
Since for and , for (recall that for of type , and for every ). This then implies that for . Using this fact, one can directly check that and and similarly, and . Proceeding this way, one can directly check that the following holds for every and for fixed
[TABLE]
Taking limits as and using (2.24) and the fact that one obtains that for .
We now prove that for . The argument is similar to the previous case of and one now needs to keep track of the negative signs in the definition of and the fact that for . Since and its truncations are negative, it follows, from standard facts of continued fractions, see, for example, [21, Chapter 2] that the odd truncations form a monotonically increasing sequence and the even truncations form a monotonically decreasing sequence and is sandwiched in between these. That is, we have, for every ,
[TABLE]
Denote by the finite continued fraction obtained by iterating the second formula in (2.11) times. That is, for every and fixed positive integer , and is given by the formulas
[TABLE]
Notice that by assumption for all . One can directly check that and . Furthermore, the following holds for every and ,
[TABLE]
Taking limits as and using (2.25) and the fact that one obtains that for every . This proves that .
Suppose for some . We wish to construct an eigenvector that solves the eigenvalue problem (2.9) and satisfies Property 2.8 (1). First define and as in (2.20) and (2.21) respectively for every , with given by (2.7). We now define as follows:
[TABLE]
Note that is well defined for all because of our assumption that . Furthermore, thus defined in (2.26) satisfies (2.11). Indeed, one obtains, from (2.20) and (2.26) that for every ,
[TABLE]
where in the second equality above, in the denominator we again used the expression from (2.20) for . Similarly, from (2.21) and (2.26) that for every ,
[TABLE]
where, again, in the second equality in the denominator, we used the expression from (2.21) for . This shows that thus defined satisfies (2.11). Fix and for let
[TABLE]
and for , we define,
[TABLE]
Notice that thus defined satisfies for every . Using this one can see that the sequence satisfies equation (2.10) because the sequence satisfies (2.11). We now let for every to obtain that the sequence satisfies the eigenvalue equation (2.9). This follows from the fact that satisfies the first equation in (2.10). By construction, since for and for , one can directly check, using formulas for given in equations (2.27), (2.28) and the formula that satisfies Property 2.8 (1). It follows that , where satisfies Property 2.8 (1) if . The fact that follows from assertion (2) in the lemma.
(1P) Let be of type and suppose that , , with eigenvector satisfying Property 2.8(2). We wish to show that . Notice first that in this case . Starting with the eigenvalue equation (2.9) and putting we will obtain the equation
[TABLE]
Now define for to obtain the equations
[TABLE]
Consider the continued fraction
[TABLE]
The proof that for is the same as in the case of type . The second equation in (2.2) gives and thus we have, by putting in the continued fraction above, that .
Now, suppose there exists a positive root to the equation . We wish to construct satisfying Property 2.8 (2) such that solves the eigenvalue problem (2.9) with eigenvector . We first define for . Notice that by assumption . From the definition of the continued fractions , we can see that the thus defined satisfies
[TABLE]
Now let and for , define . The thus defined satisfies . Also, define for every . From the first equation in (2.31) and using the fact that , we obtain the following equations for ,
[TABLE]
Notice that the third equation above implies that the equation is trivially satisfied for . Using this fact, if we now let for and , we obtain from the equations above,
[TABLE]
The two middle equations above can be rewritten as . This is precisely the eigenvalue equation (2.9),
[TABLE]
where for and when . Notice that the thus constructed satisfies Property 2.8 (2). The fact that the eigenfunctions are exponentially decaying follows from part (2) of the Lemma.
(1M) Let be of type and suppose that , , with eigenvector satisfying Property 2.8(3). We need to show that . Starting with the eigenvalue equation (2.9) and putting we will obtain the equation
[TABLE]
Now define for to obtain the equations
[TABLE]
Notice that . Consider the continued fraction
[TABLE]
By the same proof as in case , we obtain that for every . We thus have, by putting in the equation above, that .
Now, suppose there exists a positive root to the equation . We wish to construct satisfying Property 2.8 such that solves the eigenvalue problem (2.9) with eigenvector . We first define for . From the definition of the continued fractions, we can see that the thus defined satisfies
[TABLE]
Now let and for , define , . The thus defined satisfies . Also, define for every . We thus obtain the following equations for ,
[TABLE]
Notice that the third equation above implies that the equation is trivially satisfied for . And the second equation above can be rewritten as . Using these facts, if we now let for and , we obtain from the equations above,
[TABLE]
The two middle equations above can be rewritten as when . This is precisely the eigenvalue equation (2.9),
[TABLE]
where satisfies Property 2.8 (3). The fact that the eigenfunctions are exponentially decaying follows from part (2) of the Lemma.
(2) First consider case . Note that from (2.27), we have that,
[TABLE]
We now use (2.22) to conclude that
[TABLE]
where is a constant and . Note that for some , i.e., we have that if ,
[TABLE]
Notice also, from (2.28), we have,
[TABLE]
We now use (2.23) to conclude that (2.37) also holds if . Using arguments similar to that between (2.37) and (2.38) we see that (2.38) holds if . We thus have that for and since where is a bounded sequence with , we have that for .
In the case of , we use the estimates for when and set for , i.e., use estimate (2.38) for and the estimate is also trivially true for thus implying that for .
In the case of , we use the estimates for when and set for , i.e., use estimate (2.38) for and the estimate is also trivially true for thus implying that for .
(3) We first treat the case . The fact that has a positive root is equivalent to the fact that equation (2.15) has a positive root . The latter fact follows from (2.16). Indeed, the assertion regarding the two limits in (2.16) follow from Lemma 3.1 (4) and (5) by replacing and in equation (3.1) by and and respectively for and . The fact that since is of type and the fact that by the Van Vleck Theorem, are holomorphic in provided that together guarantee that (2.15) has a positive root .
Next consider the case . The fact that has a positive root is equivalent to the fact that the equation has a positive root (recall ). This follows from the facts, as outlined in the case above, that , is a holomorphic function provided that , and the fact that is positive for and satisfies the limits as and as .
Next consider the case . The fact that has a positive root is equivalent to the fact that the equation has a positive root. This follows from the facts, as in the case and , that , is a holomorphic function provided that , and the fact that is positive for and satisfies the limits as and as . ∎
We are ready to present the proof of Theorem 2.9.
Proof.
(1) We begin with the case when is of type . The fact that equation (2.17), , has a positive solution is equivalent to the fact that the equation has a positive solution . This follows from Lemma 2.12 item (3). Item (1) of Lemma 2.12 then guarantees that is an eigenvalue satisfying the eigenvalue equation (2.9) with eigenvector satisfying Property 2.8 if and only if solves equation . The fact that eigenvector forms an exponentially decaying sequence is a consequence of item (2) in Lemma 2.12 which implies that for any .
(2) We now consider the case . The fact that equation (2.18), , has a positive solution is equivalent to the fact that the equation has a positive solution . This follows from Lemma 2.12 item (3). Item (1P) of Lemma 2.12 then guarantees that is an eigenvalue satisfying the eigenvalue equation (2.9) with eigenvector satisfying Property 2.8 if and only if solves equation . The fact that eigenvector forms an exponentially decaying sequence is a consequence of item (2) in Lemma 2.12 which implies that for any .
(3) We now consider the case . The fact that equation (2.19), , has a positive solution is equivalent to the fact that the equation has a positive solution . This follows from Lemma 2.12 item (3). Item (1M) of Lemma 2.12 then guarantees that is an eigenvalue satisfying the eigenvalue equation (2.9) with eigenvector satisfying Property 2.8 if and only if solves equation . The fact that eigenvector forms an exponentially decaying sequence is a consequence of item (2) in Lemma 2.12 which implies that for any . ∎
Having established an instability argument, we now need to identify when a value of can be found of type for a given .
Remark 2.13**.**
Let where . If satisfies , then and . If , then certainly there is a point satisfying the above conditions. Therefore this would lead to a subsystem of type and Theorem 2.9 applies. The proof of this fact is a straightforward geometric exercise analogous with the argument presented in Lemma 4.2 of [9]. This defines a for all choices of satisfying . The small number of exceptions can be checked by hand, leading to the result that an appopriate can be found and Theorem 2.9 applied in all cases except and . Here, corresponds to the steady state for the case , i.e., the Euler case, described by Arnold [2].
3. Some auxiliary results on continued fractions
In this section we collect several simple facts about continued fractions needed in Subsection 2.2. We follow the Appendix in [12] and mention [21] as a general reference. Although the results are not new we have added some arguments not made explicit in [12].
Assume that is a sequence of positive numbers that has a positive limit. For we introduce the function
[TABLE]
defined by means of a continued fraction. By changing , when necessary, we can and will assume in what follows that . We note that the continued fraction (3.1) converges, that is, the limit of the truncated continued fractions
[TABLE]
exists and is positive, that is, . This follows from the Van Vleck Theorem, see [21, Theorem 4.29] since by the divergence test. Moreover, the proof of [21, Theorem 4.29] based on the Stjeltjes-Vitali Theorem [21, Theorem 4.30] yields that the function is holomorphic for satisfying , for any .
In addition we will use the notations
[TABLE]
[TABLE]
and, given positive numbers , we denote
[TABLE]
the latter continued fractions also converge by the Van Vleck Theorem.
Lemma 3.1**.**
Assume that and . Then the following assertions hold:
- (1)
[TABLE] 2. (2)
If for , then
[TABLE] 3. (3)
The limit exists and is equal to
[TABLE] 4. (4)
[TABLE] 5. (5)
[TABLE]
Proof.
(1) The -th truncated continued fraction for are given by F^{(2k)}(a,b)=\big{[}a,b,\ldots,a,b\big{]}, F^{2k+1}(a,b)=\big{[}a,b,\ldots,a\big{]} and satisfy
[TABLE]
Since the continued fraction converges, that is, as , we conclude that
[TABLE]
or , yielding (3.5).
(2) For each -th truncated continued fraction G^{(k)}(x)=\big{[}xc_{1},\ldots,xc_{k}\big{]} we replace the odd-numbered by the smaller value and even-numbered by the larger value . Thus, is majorated by the -th truncation of \big{[}A,B,A,B,\ldots\big{]}. Passing to the limit as and using (1) yields the second inequality in (3.6). The first inequality follows from .
(3) Formula follows from (3.5) with . It remains to show that the limit exists and is equal to . For any choose such that for all we have . For any we apply assertion (2) with replaced with , and . This yields
[TABLE]
where we introduce the notations
[TABLE]
We note that . For any , we fix such that
[TABLE]
Then (3.10) yields for all as claimed.
(4) Pick a small to be determined later and choose such that (3.10) holds. Fix an even number and notice that
[TABLE]
where we used that by (3.10). Clearly, yielding
[TABLE]
A similar argument shows that . Passing to the limit as proves (4).
(5) As before, we arrive at (3.12) and notice that by (3). Then
[TABLE]
yields (5). ∎
4. The essential spectrum and the spectral mapping theorem
In this section, we follow [24] and prove for the linearized -Euler operator that the essential spectrum of the operator is the imaginary axis. We also prove the spectral mapping theorem for the group generated by the operator .
First note that is the direct sum of operators , i.e., , where is given by
[TABLE]
with
[TABLE]
and given by (2.3). We note that in general, if , then is a complex number. We thus write for some . Equation (4.1) then becomes,
[TABLE]
Lemma 4.1**.**
The essential spectrum of the operator is given by
[TABLE]
Proof.
We observe that the Fourier transform is an isometric isomorphism, where is given by for . The operator acting on is similar via to the operator of multiplication by acting on , where . That is,
[TABLE]
The above equality follows from the observation that
[TABLE]
We now use the fact that the spectrum of a multiplication operator on is equal to its essential spectrum and is given by the closure of the range of the multiplier. In other words, the spectrum of the operator of multiplication by on is the closure of the range of as . But this is equal to . We thus conclude that the essential spectrum of the operator is . Now, notice that the operator is a compact perturbation of the operator by the operator . Here, the operator is compact because as . Weyl’s theorem [26, Lemma XIII.4.3] allows us to conclude that the essential spectrum of is the same as the essential spectrum of . Thus (4.3) holds. ∎
We now prove that the spectrum of is exactly the union of the spectra of cf. [24].
Proposition 4.2**.**
.
Proof.
Since trivially holds, it is enough to show that
[TABLE]
We first split the operator , where and correspond to with small and big norms. We have that , and since is the sum of finitely many operators we have that
[TABLE]
It is thus enough to show that . Since as (see (4.2)), and using the fact that , we see that . It therefore suffices to show that . Let us denote
[TABLE]
and
[TABLE]
Thus and , i.e.,
[TABLE]
In order to show that we show that if , then is in the resolvent set of . Thus, to prove the proposition, we need to show that
[TABLE]
Notice that
[TABLE]
Notice that , i.e., is a bounded skew self-adjoint operator with . It’s spectrum lies along the imaginary axis and since we have that,
[TABLE]
Also
[TABLE]
Claim: , where is a constant.
Proof of Claim: Using the definition of (see (2.3)) and (see (4.2)) we have,
[TABLE]
Now use the fact that and the fact that and the Cauchy-Schwarz inequality to see that . This then implies that,
[TABLE]
We thus have that,
[TABLE]
which finishes the proof of the Claim.
Now choose so that for all , the inequality
[TABLE]
holds. We stress that depends on but does not depend on . Denote and . If , using (4.7), and the fact that , we have,
[TABLE]
This proves that as long as , the operator \bigg{[}I-\bigg{(}\frac{\lambda}{|c|}-N_{{\mathbf{q}}}^{0}\bigg{)}^{-1}N_{{\mathbf{q}}}^{0}\operatorname{diag}_{n\in{\mathbb{Z}}}\{\gamma_{n}\}\bigg{]} is invertible and
[TABLE]
Therefore, as long as , we have that
[TABLE]
Thus,
[TABLE]
To finish the proof, we note that the set is finite and since is a bounded linear operator for every , it follows that is also a bounded linear operator, where, if , with , then the resolvent operator grows as as . We have that,
[TABLE]
Since , equations (4.8), (4.9) show that (4.4) holds. This proves the proposition. ∎
Proposition 4.3**.**
* and is a bounded set with accumulation points only on .*
Proof.
The facts that as and (4.3), together with the fact that imply that . It is thus enough to prove that . We have,
[TABLE]
Notice that, since is a sum of finitely many bounded linear operators and using (4.3), we have that
[TABLE]
From the proof of Proposition 4.2, see Equation (4.4), we know that , i.e., does not have points in the spectrum with non zero imaginary values. Thus,
[TABLE]
This proves that . The second statement of the Proposition follows from the above and from the fact that is a finite sum of bounded linear operators. ∎
We now prove the spectral mapping theorem for the operator .
Proposition 4.4**.**
The spectral mapping property,
[TABLE]
holds for the operator .
Proof.
We know from Proposition 4.3, that the essential spectrum of satisfies . This tells us that . Since for any semigroup, we see that . We want to show that . We use a general Gearhart-Pruss spectral mapping theorem for Hilbert spaces, see [24, Th.2, p.268]. On a Hilbert space, , , is the set of points such that either belongs to for all or the sequence is unbounded. Suppose . Then, there exists such that and either for all or the sequence is unbounded. The first outcome is precluded by the fact that . So if and then we must have that . But this is impossible because, as we prove below that for each , . So it remains to establish the following fact.
Claim: Assume , then .
Let as in the proof of Proposition 4.2 and fix . Since is a finite set, the operator is a bounded linear operator such that the norm of its resolvent decays as as and (4.9) holds, i.e., one has . One also has that if , then (4.8) holds, i.e., the norm of the resolvent operator . These two facts above can be combined to give
[TABLE]
By estimate (4.10), we know that if , then is not in the spectrum of . This shows that the essential spectrum of , , is contained in the unit circle. One also knows that the spectral mapping property always holds for the point spectrum. One can combine these facts to obtain the result. ∎
5. Concluding comments
The main result of the present paper, Theorem 2.9, states that for steady states (which are a function of the vector ), that have a point of type , that is, the set has one point inside the open disc of radius , (see Subsection 2.1, Remark 2.2 for a precise definition of point of type I) are linearly unstable. The existence of an unstable eigenvalue is equivalent to the existence of a positive root to an equation involving continued fractions (equations (2.17), (2.18), (2.19), respectively, for points of type , and ). We are able to provide a list of additional properties that the respective eigenvectors satisfy. In Section 4, we also characterized the essential spectrum of the operator and proved a spectral mapping theorem for the group generated by . Moving forward, proving linear instability, as done in the current paper, can be seen as a first step to prove full nonlinear instability. In [18], the authors are able to characterize the nonlinear growth rate of the solution in terms of the largest real eigenvalue of the linearized operator. This allows them to study the nonlinear instability of interfacial fluid motions, examples of which include vortex sheets with surface tension and Hele-Shaw flows. In [15], the authors prove nonlinear instability and ill-posedness of the magneto-geostrophic equations by first proving that the linearized operator has an unstable eigenvalue using continued fractions techniques. Similarly, in [11], the authors study the ill-posedness of a nonlinear singular porous media equation by studying first the instability of the linearized operator using continued fractions. In [22], the authors show that the gradient of the vorticity to the 2D nonlinear Euler equation has double exponential growth rate. A related question is to show single exponential growth in the case of the 2D -Euler equations.
6. Acknowledgements
We thank the referees for their valuable comments which improved the exposition of our paper.
7. Appendix
The purpose of this Appendix is to collect some proofs of results used in the main body of the text.
Lemma 7.1**.**
Equation (1.1) holds if and only if satisfies equation (1.5) for every .
Proof.
Using the facts that and , one can rewrite equation (1.1) as
[TABLE]
Using (1.4), we see that,
[TABLE]
Equation (7.1) then reads, in terms of the Fourier series,
[TABLE]
Using the identity
[TABLE]
first for , and then for , , equation (7.2) is seen to be
[TABLE]
Alternatively, using the identity
[TABLE]
first for , and then for , , equation (7.2) is seen to be
[TABLE]
Noticing that and taking the average of (7.3) and (7.4) we obtain that (1.5) for each mode of holds if and only if (1.1) holds. ∎
We now prove that the unidirectional flow given by (1.8) and (1.9) is a steady state.
Lemma 7.2**.**
A unidirectional flow given by the vorticity equations (1.8) and (1.9) is a steady state solution of the -Euler equation (1.1) on the torus .
Proof.
For every one needs to check that the right hand side of (1.5) is zero, where the Fourier coefficients of are given by (1.9). Since is nonzero only when , the right hand side of(1.9) reduces to
[TABLE]
Now using the fact that is nonzero only when and is nonzero only when and using (1.9), the above equation reduces to
[TABLE]
which is zero because and . ∎
Derivation of Equation (1.10):
We briefly indicate how to obtain equation (1.10). Linearizing the right hand side of (1.5) about the steady state (1.8) reduces the right hand side of (1.5) to
[TABLE]
where in the first sum, if , i.e., if and if , i.e., if and zero otherwise and in the second sum, if and if and zero otherwise. Using these in (7.5), we see that (7.5) reduces to,
[TABLE]
Now use the facts that if , then and in the above equation to get (1.10).
We now give the proof of Lemma 2.1.
Proof.
Recall (2.1) and the assumption that . Note that , where
[TABLE]
We thus have that,
[TABLE]
Thus . Thus the eigenvalues are symmetric about the imaginary axes.
The fact that the eigenvalues are symmetric about the real axes can be proved as follows. The fact that if is an eigenvalue then is also an eigenvalue is a consequence of the fact that for any . From this it follows that if is an eigenvalue with eigenvector , then is an eigenvalue with eigenvector . This proves the Lemma.
Additionally, one can also prove the fact that if is an eigenvalue then is also an eigenvalue. Let be an operator on defined by and notice that and and . Thus,
[TABLE]
Thus,
[TABLE]
which concludes the proof. We used Lemma 2.7 in the last part of the proof. ∎
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