Some dynamical properties for a one-dimensional hybrid Fermi-Ulam-bouncer model are studied
under the framework of scaling description. The model is described by using a two-dimensional nonlinear area preserving mapping. Our results show that the chaotic regime below the lowest energy invariant spanning curve is scaling invariant and the obtained critical exponents are used to find a universal plot for the second momenta of the average velocity.
1. Introduction
The investigation of nonlinear dynamical systems has
awaken special interest along last decades since they can explain and/or
predict some phenomena until then incomprehensible. A special class of systems
that present nonlinear phenomena and that can be described via recursive
equations is the so-called classical nonlinear billiard problems [1, 2]. Generally, a billiard
problem consists of a system in which a point-like particle moves freely inside
a bounded region and suffers specular reflections with the boundaries. This
system has been extensively studied during several years considering both its
classical and quantized formulation.
It is well known in the literature that the phase
space of billiard problems highly depends on the shape of the boundary. The
dynamics of the particle might generate phase spaces of different kinds that
can be settled in three different classes of universality including (i)
integrable, (ii) ergodic, and (iii) mixed. A typical example of case (i) is the
circle billiard, as the integrability of such a
case resembles the angular momentum conservation. Two examples of case (ii) are
the Bunimovich stadium [3] and the Sinai billiard [4]. In case (iii), the most
important property present in the phase space is that chaotic seas, generally
surrounding Kolmogorov-Arnold-Moser (KAM) islands, are confined by invariant
spanning curves [2]
sometimes also called as primary KAM tori. Particularly, such curves cross the
phase plane from one side to the other one thus separating different portions
of the phase space. The mixed structure in the phase portrait is such that
regions of regular motion and regions with chaotic behavior could coexist
together. This property is generic for nondegenerate Hamiltonian systems
[5]. Some examples of
systems with this particular structure are the one-dimensional Fermi-Ulam model
[6–12], the bouncer model
[13–19], time-dependent potentials well [20, 21], and many other different
problems considering different degrees of freedom.
In this paper, we will consider a 1D model that is described using the formalism
of discrete mappings, the so-called hybrid Fermi-Ulam-bouncer model [22, 23]. We are seeking to understand
and describe a scaling property present in the chaotic sea of such a model. The
model was originally proposed to merge together two different nonlinear
problems commonly studied apart from each other, that is, the Fermi-Ulam model
and the bouncer model. The Fermi-Ulam model (FUM) consists of a classical
particle, in the total absence of any external field, which is confined to
bounce between two rigid walls, where one of them is fixed and the other one is
periodically time varying. The returning mechanism of the particle for a next
collision with the moving wall is due to a reflection with the fixed wall. On
the other hand, the bouncer model consists of a classical particle falling in a
constant gravitational field and that hits a periodically oscillating wall. The
returning mechanism of the bouncer model is related to the gravitational field
only. Despite the very similar models, the different returning mechanisms of
the two models cause profound consequences on the dynamics of the particle
[24]. Particularly,
depending on the combination of the control parameters and initial conditions,
the average velocity of the particle reaches a constant value for sufficient
long time in the FUM, while it diverges on the bouncer model. Such a divergency
is basically related to the phenomenon of Fermi acceleration. Therefore, Fermi
acceleration (FA) is a phenomenon in which a classical particle acquires
unbounded energy from collisions with a massive moving wall [25, 26]. Applications of FA have acquired a broad interest in
different fields of physics including plasma physics [27], astrophysics [28, 29], atomic physics [30], optics [31, 32], and even in the well-known time-dependent billiard
problems [33, 34]. The interesting posed question
that should be answered is whether the FA results from the nonlinear dynamics
itself considering the complete absence of any imposed random motion. An
one-dimensional model exhibiting such a phenomenon, which is modelled by a
nonlinear mapping, is the bouncer model. For two-dimensional time-dependent
billiards (billiards with moving boundaries), the answer for this question is
not unique and it depends on the kind of phase space for the corresponding
static version of the problem. Therefore, as conjectured by
Loskutov et al. [35]
(such a conjecture is known in the literature as the LRA conjecture), the
regular dynamics for a fixed boundary implies a bound to the energy gained by the
bouncing particle, but the chaotic dynamics of a billiard with a fixed boundary
is a sufficient condition for FA in the system when a boundary perturbation is
introduced. Such a conjecture was confirmed in different billiards [36–38]. It was, therefore, observed recently
FA in a time
varying elliptical billiard [39]. The oval billiard, however, seems not to exhibit FA
for the breathing case [40].
Thus, the hybrid Fermi-Ulam-bouncer model consists of
a classical particle which is confined in and bouncing elastically between two
rigid walls in the presence of a constant gravitational field. Thus, properties
that are individually observed in the FUM and bouncer model come together and
coalesce in the hybrid Fermi-Ulam-bouncer model [22]. As we will show, the phase
space of this model is of mixed kind. Our main goal is to characterize some
properties on the chaotic regime for the region below the first invariant
spanning curve, particularly the behavior of the average velocity and the
deviation of the average velocity.
This paper is organized as follows. In Section 2, we
give all the details needed for the construction of the nonlinear mapping. We
illustrate some results for the phase space of the model considering both the
simplified and the complete versions of the Fermi-Ulam-bouncer model. The
scaling hypotheses are present and numerical results are discussed in Section 3. Finally, in Section 4, we draw our conclusions.
2. The Model and the Mapping
We discuss in this section all the details needed for
the mapping construction. We also present the phase space and obtain the
positive Lyapunov exponent for the low-energy chaotic sea. The one-dimensional
hybrid Fermi-Ulam-bouncer model thus consists of a classical particle confined
to bounce elastically between two rigid walls. One of the walls is assumed to
be fixed at the position while the other one moves periodically in time
according to the equation .
Here, and denote, respectively, the amplitude of
oscillation and the frequency of the moving wall. Additionally, the particle is
suffering the action of a constant gravitational field .
As it is so usual in the literature, the dynamics of the particle is described
in terms of a two-dimensional nonlinear area preserving map that gives the velocity of the particle and the corresponding time at the instant of the nth
impact with the moving wall, that is, .
Before we write the equations of the mapping, it is convenient to define
dimensionless and much more appropriated variables to describe the dynamics of
the particle. We define , and .
Finally, we measure the time in terms of .
Incorporating this new set of variables in the dynamics, the map is written
aswhere the expressions for both and depend on the kind of collision occurs. There
are three different possible situations, namely (i) multiple collisions, (ii)
collisions without reflection in the upper wall, and (iii) collisions with
reflection in the upper wall. Considering the first case, where the particle
suffers an impact before leaving the collision zone, which is given by the
interval ,
the expressions are and ,
where is obtained as the smallest solution of with .
Such solution is equivalent to the position of the particle being the same as
the position of the moving wall. Thus, the transcendental equation is given byIf does not have a solution in the interval ,
the particle leaves the collision zone without suffering a successive hit.
Considering the case (ii), the needed condition for the particle not colliding
with the upper wall after leaving the collision zone is .
In this case, and ,
where the auxiliary terms assume the following expressions:The term is obtained by solution of .
Again, considering the condition that matches the same position of the moving
wall and of the particle. Thus, is given by
Finally, for the case (iii), where ,
the corresponding expressions for and are the same as those of the case (ii).
However, the auxiliary terms, and , assume the following
expressions:The value of is obtained from (2.4) using, however, the new
expressions for and .
Figure 1(a) shows the phase space for the complete
hybrid Fermi-Ulam-bouncer model generated from (2.1). The control parameters used
in Figure 1 are and .
It is easy to see the presence of KAM islands surrounded by a chaotic sea, that
is, limited by an invariant spanning curve. The presence of the invariant
spanning curves in the phase space implies that the particle cannot acquire
unlimited energy. To illustrate the behavior of the average energy, we
define and finally
obtain the average energy as where corresponds to an ensemble of different
initial conditions.
Figure 1: (a) Phase space for the complete hybrid
Fermi-Ulam-bouncer model. (b) Behavior of the average energy,
,
as function of
.
The control parameters used in (a) and (b) were
and
.
Figure 1(b) shows the behavior of the average energy, ,
as a function of .
We can see that the energy grows for small and then, after a changeover, it reaches a
regime of saturation for large .
The initial velocity was considered fixed as while we have considered an ensemble of different initial phases uniformly distributed in the interval .
Each initial condition was evolved up to iterations. Since the instant of each impact
of the particle with the moving wall can only be obtained numerically, the
computational time for evaluation of (2.7) is very large. As an attempt to reduce
the time consuming in the numerical simulations, we will discuss in Section 2.1 a simplified version of the hybrid Fermi-Ulam-bouncer model.
2.1. A Simplified Hybrid Fermi-Ulam-Bouncer Model
In this section, we discuss a simplification used in
the model. For the complete model, the instant of the impact of the particle
with the moving wall is obtained via a solution of a transcendental equation,
which yields the simulations to be long-time consuming. However, instead of
considering solving transcendental equations, we will use a simplification in
the model which is commonly used in the literature [2]. We will suppose that both
walls are fixed (one of them is fixed at and the other one is fixed at ), but that, when the particle suffers a
collision with one of then (say, with the one at ), the particle exchanges momentum and energy
as if the wall was moving. This simplification carries a great advantage of
allowing us to speed up our numerical simulations when compared to the complete
version of the model. Such a simplification also retains the nonlinearity of
the problem. Considering the same dimensionless variables defined for the
complete model, the map for the simplified hybrid Fermi-Ulam-bouncer model can
be written asThe modulus function used in the
equation of the velocity on the mapping (2.8) was introduced to preserve the
particle into the region between the walls. The expressions for depend on the following conditions:
(1) collision without reflection in the upper
wall. Such a condition is verified if .
In this case, the particle rises and decelerates due to the gravitational field
only until reaches instantaneously the rest. Then the particle is accelerated
downward until it collides with the wall at .
Thus, is given by(2) Collision with reflection in the upper wall.
For such a collision, the condition that must be observed is .
In this case, the particle goes in the upward direction and hits the upper
wall. It is then reflected downward and is also accelerated by the gravitational
field. The expression for is written as
The mapping (2.8) preserves the phase space measure since that .
The phase space for the mapping (2.8) is shown in Figure 2(a) for the same control parameters used in Figure 1. We have also evaluated numerically the positive Lyapunov exponent for
the chaotic sea of Figure 2(a). It is well known that the Lyapunov exponent has
great applicability as a practical tool that can quantify the average expansion
or contraction rate for a small volume of initial conditions. As discussed in
[41], the Lyapunov
exponents are defined aswhere are the eigenvalues of and is the Jacobian matrix evaluated over the
orbit .
However, a direct implementation of a computational algorithm to evaluate (2.11)
has a severe limitation to obtain .
Even in the limit of short ,
the components of can assume very different orders of magnitude
for chaotic orbits and periodic attractors, yielding impracticable the
implementation of the algorithm. In order to avoid such problem, we note that can be written as where is an orthogonal matrix and is a right triangular matrix. Thus, we rewrite as ,
where .
A product of defines a new .
In a next step, it is easy to show that .
The same procedure can be used to obtain and so on. Using this procedure, the problem
is reduced to evaluate the diagonal elements of : .
Finally, the Lyapunov exponents are now given byIf at least one of the is positive, then the orbit is classified as
chaotic. Figure 2(b) shows the behavior of the positive Lyapunov exponent
plotted against the number of collisions with the wall located at for 10 different initial conditions on the
chaotic sea. The control parameters used in the construction of Figure 2 were and .
The average of the positive Lyapunov exponent for the ensemble of the 10-time
series gives where the value corresponds to the standard deviation of the
ten samples. Finally, in Figure 2(c), we present the behavior of the average
energy of the particle for the simplified model.
Figure 2: (a) Phase space generated from iteration of mapping (
2.8) for the control
parameters
and
.
(b) Behavior of the positive Lyapunov exponent of the chaotic sea for the same
control parameters used in (a). The average value obtained was
where the error
corresponds to the standard deviation of the
10 samples. (c) Behavior of the average energy,
,
as function of
3. Scaling Analysis
The main goal of this section is to describe a scaling
present in the low-energy regime. We discuss in full detail the investigation
for the simplified and then, at the end of section, we present the
corresponding results for the complete version. Thus, we now discuss the
procedures used to obtain the average velocity on the chaotic low-energy
region. The average velocity (average along an orbit) is defined
asSince we obtain the average
velocity, it is also easy to obtain the deviation of the average velocity,
sometimes also called as the second momenta of .
It is defined aswhere the sum on refers to an average over an ensemble of different initial conditions. In order to
iterate (3.2) for the simplified version of the model, we evolved our
simulations considering an ensemble of different initial conditions. Figure 3 shows
the behavior of the deviation around the average velocity for the simplified
model as function of for three different control parameters, as
labelled in the figures. It is easy to see in Figure 3 two different kinds of
behaviors. For short ,
the deviation of the average velocity grows according to a power law and
suddenly it bends toward a regime of saturation for long enough values of .
The changeover from growth to the saturation is marked by a cross-over
iteration number .
It must be emphasized that different values of the parameter generate different behaviors for short .
However, applying the transformation coalesces all the curves at short ,
as shown in Figure 3(b). We can see that different values of yield each curve to saturate at distinct
values, thus we can suppose that
Figure 3: (a) Behavior of the deviation of the average velocity
for different values of the control parameter for the simplified model. (b) Their initial
collapse after the transformation for the simplified model. The control parameter was fixed as .
(1) when the deviation of the average velocity grows
according towhere the exponent is a critical exponent;(2) as the iteration number increases, ,
the deviation of the average velocity approaches a regime of saturation, that
is described aswhere the exponent is also a critical exponent;(3) the cross-over iteration number that marks the
change from growth to the saturation is written aswhere is a dynamic exponent.
After considering these three initial suppositions, we
are now able to describe the deviation of the average velocity in terms of a
scaling function of the typewhere is the scaling factor, and are scaling exponents. If we chose properly
the scaling factor we can relate the scaling exponents and with the critical exponents , and .
We begin considering that .
Thus, (3.6) is rewritten aswhere the function is assumed to be constant for .
Comparing (3.3) and (3.7), we obtain .
Choosing now ,
we have and (3.6) is given bywhere the function is defined as .
It is also assumed as constant for .
An immediate comparison of (3.4) and (3.6) gives us .
Given the two different expressions of the scaling factor ,
we obtain a relation for the dynamic exponent ,
that is, given by
Note that the scaling exponents are determined if the
critical exponents and were numerically obtained. The exponent is obtained from a power law fitting for the
deviation of the average velocity curves for the parameter for short iteration number. Thus, the average
of these values gives that .
Figure 4 shows the behaviors of (a) and (b) .
Applying power law fittings on the figure, we obtain and .
We can also obtain the exponent considering (3.9) and the previous values of
both and ;
we found that .
Such result indeed agrees with our numerical result. In order to confirm the initial hypotheses,
and since the values of the scaling exponents , and are now known, we will collapse all the curves
onto a single and universal plots, as demonstrated in Figure 5. With this good collapse of all the curves of
the deviation of the average velocity and considering that the critical
exponents are , and ,
we can conclude that the hybrid Fermi-Ulam-bouncer model belongs to the same
class of universality of a periodically corrugated waveguide [42]. It also belongs to the
same class of universality of the Fermi-Ulam [43, 44] itself and that the
presence of a gravitational field does not seem to create a new universality
class, at least for the control parameters considered in the present study.
Figure 4: (a) Plot of as function of the control parameter for the simplified model. (b) Behavior of the
cross-over number against for the simplified model.
Figure 5: (a) Different curves of the for four different control parameters for the
simplified model. (b) Their collapse onto a single and universal plots.
Let us now discuss our numerical results for the
complete version of the model. Once the equations of the mapping now be solved
numerically, we have considered an ensemble of less different initial
conditions. Such a consideration is mainly to produce a simulation not so
longer. However, it is still relevant to characterize statistical properties of
the model. For the complete version of the model, we have considered an
ensemble of different initial conditions. The behavior of for the complete version is rather similar to
that observed for the simplified version of the model. After an extensive
simulation, we obtain that the critical exponents are , and .
Evaluating (3.9), we found that .
These critical exponents also allow us to produce a good collapse of all the
curves of onto a single and universal plots, as shown in
Figure 6. Thus, we can conclude that the scaling
properties are unaffected by considering the simplified or complete versions of
the model.
Figure 6: (a) Different
curves of the for three different control parameters for the
complete model. (b) Their collapse onto a single and universal plots.
4. Final Remarks
As a final
remark of the present paper, we have studied a simplified and the complete
version of the hybrid Fermi-Ulam-bouncer model considering elastic collisions
with the walls. We show that the average energy as well as the deviation around
the average velocity for chaotic orbits for both the complete and simplified
versions of the model exhibit scaling properties with the same critical
exponents. Moreover, we have shown that there is an analytical relation between
the critical exponents , and .
Our scaling hypotheses are confirmed by a good collapse of all the curves of onto a single and universal plot, therefore,
confirming that this model also belongs to the same class of universality of
the Fermi-Ulam model [43], for the range of control parameters studied, and the
periodically corrugated waveguide [42].
Acknowledgment
D. F. M. Oliveira and R. A. Bizão are grateful to CNPq; E. D. Leonel thanks FAPESP, FUNDUNESP, and CNPq for financial support.