Blazhko RR Lyrae light curves as modulated signals
ABSTRACT We present an analytical formalism for the description of Blazhko RR Lyrae
light curves in which employ a treatment for the amplitude and frequency
modulations in a manner similar to the theory of electronic signal
transmitting. We assume monoperiodic RR Lyrae light curves as carrier waves and
modulate their amplitude (AM), frequency (FM), phase (PM), and as a general
case we discuss simultaneous AM and FM. The main advantages of this handling
are the following: (i) The mathematical formalism naturally explains numerous
light curve characteristics found in Blazhko RR Lyrae stars such as mean
brightness variations, complicated envelope curves, nonsinusoidal frequency
variations. (ii) Our description also explains properties of the Fourier
spectra such as apparent higherorder multiplets, amplitude distribution of the
side peaks, the appearance of the modulation frequency itself and its
harmonics. In addition, comparing to the traditional method, our light curve
solutions reduce the number of necessary parameters. This formalism can be
applied to any type of modulated light curves, not just for Blazhko RR Lyrae
stars.

Article: Fitting Blazhko light curves
[Show abstract] [Hide abstract]
ABSTRACT: The correct amplitude and phase modulation formalism of the Blazhko modulation is given. The harmonic order dependent amplitude and phase modulation form is equivalent with the Fourier decomposition of multiplets. The amplitude and phase modulation formalism used in electronic transmission technique as introduced by Benk\H{o}, Szab\'o and Papar\'o (2011, MNRAS 417, 974) for Blazhko stars oversimplifies the amplitude and phase modulation functions thus it does not describe the light variation in full detail. The results of the different formalisms are compared and documented by fitting the light curve of a real Blazhko star, CM UMa.Monthly Notices of the Royal Astronomical Society 06/2012; 424(4). · 5.52 Impact Factor  SourceAvailable from: journals.cambridge.org[Show abstract] [Hide abstract]
ABSTRACT: We modelled the light curves of modulated multiperiodically pulsating stars by a simple doublemode pulsation with combined amplitude and frequency modulations. The synthetic light curves and their spectra show similar features to those we found and discussed for monoperiodic stars. Comparing the synthetic light curves and their spectra with the observed ones helps us to classify the modulations and to distinguish between longperiod modulation (Blazhko effect) and the other types of amplitude and/or period changes.Proceedings of the International Astronomical Union 04/2012; 7(S285):286288.  [Show abstract] [Hide abstract]
ABSTRACT: This study investigates periodic modulation of the light curve of the RRc star TV Boo and its physical parameters based on photometric data. This phenomenon, known as the Blazhko effect, is quite rare among RRc stars. The frequency analysis based on the data gathered at the Masaryk University Observatory (MUO) and also using SuperWASP data revealed symmetrically structured peaks around the main pulsation frequency and its harmonics, which indicate two modulation components of the Blazhko period. The main modulation periodicity was found to be 9.7374 ± 0.0054 d. This is one of the shortest known Blazhko periods among RRc stars. The second modulation period (21.5 ± 0.2 d) causes changes of the Blazhko effect itself. Some indices show that TV Boo could be affected by longterm changes of the order of years. Basic physical parameters were estimated via an MUO V lightcurve solution using Fourier parameters. TV Boo seems to be a lowmetallicity star with [Fe/H] = 1.89.Monthly Notices of the Royal Astronomical Society 01/2013; 428(2):14421448. · 5.52 Impact Factor
Page 1
Mon. Not. R. Astron. Soc. 000, 1–18 (2011)Printed 27 June 2011(MN LATEX style file v2.2)
Blazhko RRLyrae light curves as modulated signals
J. M. Benk˝ o?, R. Szab´ o, and M. Papar´ o
Konkoly Observatory, Konkoly Thege M. u. 1517., H1121 Budapest, Hungary
Accepted 2011 June 23. Received 2011 June 23; in original form 2011 April 28
ABSTRACT
We present an analytical formalism for the description of Blazhko RRLyrae light curves in
which employ a treatment for the amplitude and frequency modulations in a manner similar to
the theory of electronic signal transmitting. We assume monoperiodic RR Lyrae light curves
as carrier waves and modulate their amplitude (AM), frequency (FM), phase (PM), and as
a general case we discuss simultaneous AM and FM. The main advantages of this handling
are the following: (i) The mathematical formalism naturally explains numerous light curve
characteristics found in Blazhko RRLyrae stars such as mean brightness variations, compli
cated envelope curves, nonsinusoidal frequency variations. (ii) Our description also explains
properties of the Fourier spectra such as apparent higherorder multiplets, amplitude distribu
tion of the side peaks, the appearance of the modulation frequency itself and its harmonics. In
addition, comparing to the traditional method, our light curve solutions reduce the number of
necessary parameters. This formalism can be applied to any type of modulated light curves,
not just for Blazhko RRLyrae stars.
Key words: methods: analytical — methods: data analysis — stars: oscillations — stars:
variables: general — stars: variables: RR Lyrae
1INTRODUCTION
The Blazhko effect (Blazhko 1907) is a periodic amplitude and
phase variation of the RRLyrae variable stars’ light curve. The typ
ical cycle lengths of these variations are about of 10100 times
longer than the main pulsation periods (0.3−0.7 d). Almost half
of the RRLyrae stars pulsating in their fundamental mode (type
RRab) and a smaller but nonnegligible fraction of the first over
tone mode pulsating stars (type RRc) show the effect (Jurcsik et
al. 2009c; Chadid et al. 2009; Kolenberg et al. 2010; Benk˝ o et
al. 2010). It is usually interpreted as a modulation or a beating
phenomenon, but both hypotheses have their own problems. The
beating picture describes the main feature of the light curves and
Fourier spectra well (see Breger & Kolenberg 2006; Kolenberg et
al. 2006), but reproducing phase variations, multiplet structures
found in certain stars’ Fourier spectra (Jurcsik et al. 2008; Chadid
et al. 2010) in this framework is not possible. On the other side,
the stars showing doublet structures in their Fourier spectra (Al
cock et al. 2000, 2003; Moskalik & Poretti 2003) seemed to be
contradicted with the modulation picture.
In this paper we describe the Blazhko effect as a modulation,
and derive the mathematical consequences of this assumption by
developing a consistent analytical framework. Using this frame
work we demonstrate that many light curve characteristics are nat
urally identified as mathematical consequences of the modulation
assumption. By disentangling these features we get closer to the
physics behind the Blazhko effect.
?Email: benko@konkoly.hu
The possibility of the modulation/Blazhko effect have been
raised for many types of pulsating stars from Cepheids to δ Scuti
stars (see e.g. Koen 2001; Henry, Fekel & Henry 2005; Moska
lik & Kołaczkowski 2009; Breger 2010; Poretti et al. 2011). The
main motivation of this paper is the mathematical description of the
Blazhko RRLyrae stars’ light curves and investigate their proper
ties. Most of our results can be applied directly to any other types
of variable stars, where modulation is suspected. Our deduced for
mulae and the related phenomena may help to prove or reject the
modulation hypothesis.
The basic idea of this paper was raised in Benk˝ o et al. (2009).
Modulation is a technique that has been used in electronic commu
nication for a long time, mostly for transmitting information signal
via a radio carrier wave. In those cases, the carrier wave is a sinu
soidal electromagnetic (radio) wave that is modulated by a (gener
ally nonperiodic) information signal (e.g. speech, music). In this
paper the formalism developed by engineers for broadcasting radio
signals has been modified such a way that we assumed a monope
riodic nonmodulated RRLyrae light variation as a carrier wave.
While for communication usually only one type of modulation is
applied we allow both types of modulations (amplitude and angle).
In Section 2 we present a collection of classical formulae
that are wellknown in physics of telecommunications (Carson
1922; van der Pol 1930; Roder 1931). Some of the more com
plicated cases (multiple modulations, recursive or cascade modula
tions) were investigated by mathematicians who developed the the
ory of electric sound synthesizers in the years of 1960s and ’70s.
Theformulaearemodifiedtodescribethemodulatedlightcurvesin
Sec. 3 and investigated by a stepbystep process from the simplest
arXiv:1106.4914v1 [astroph.SR] 24 Jun 2011
Page 2
2Benk˝ o et al.
cases to the more complex ones. Section 4 compares the numerical
behaviour of the traditional method and this one. Section 5 summa
rizes our results.
2BASIC FORMULAE
In this section we briefly review some classical definitions and for
mulae (see e.g. Newkirk& Karlquist 2004;Schottstaedt 2003) that
will be used through the next sections. The simplest periodic signal
is a sinusoidal function. It has three basic parameters: amplitude,
frequency and phase and any of these can be modulated.
2.1Amplitude modulation
The amplitude modulation (AM) is the simplest of the three cases.
Let the carrier wave c(t) be a simple sinusoidal signal as
c(t) = Ucsin(2πfct + ϕc),
(1)
where Uc, fc and ϕc constant parameters are the amplitude, fre
quency and initial phase of the carrier wave, respectively.
Let Um(t) represent an arbitrary waveform that is the mes
sage to be transmitted. The transmitter uses the information signal
Um(t) to vary the amplitude of the carrier Uc to produce a modu
lated signal:
UAM(t) = [Uc+ Um(t)]sin(2πfct + ϕc).
(2)
In the simplest case, where the modulation is also sinusoidal
Um(t) = UA
msin(2πfmt + ϕA
m).
(3)
Substituting Eq. (3) into (2) and using basic trigonometrical identi
ties, expression (2) can be rewritten as
UAM(t) = Ucsin(2πfct + ϕc) +
UA
m
2
?sin?2π (fc− fm)t + ϕ−?+ sin?2π (fc+ fm)t + ϕ+??,
(4)
where ϕ−= ϕc−ϕA
shifts (±π/2) appear because we used (through all this paper) a
sinusoidal representation instead of sin and cos functions.
The exact analytical Fourier transformation of (4) is given in
Appendix A, however, the basic structure of the frequency spec
trum can be easily read off from Eq. (4). Since the Fourier spectrum
of a single sinusoidal function shows a peak at the frequency of
the sinusoid, from the above expression (4) the wellknown triplet
structure composed of the peaks fcand fc± fmcan be seen. The
amplitude of the sidepeaks fc±fmare always equal. The Fourier
amplitude of the carrier wave (π√2πUc), that represents the energy
at the carrier frequency, is constant.
The ratio of the carrier wave amplitude A(fc) and the side
peaks A(fc ± fm) are connected to the modulation depth. We
rewrite Eq. (2) as
?
If Um(t) is a bounded function, let Umax
value of this modulation function, then modulation depth is de
fined as h = Umax
m
/Uc. In the above discussed sinusoidal case
h = UA
amplitude of the central peak is twice of the side peak highs.
m+π/2 and ϕ+= ϕc+ϕA
m−π/2. The initial
UAM(t) =1 +Um(t)
Uc
?
represent the maximum
c(t).
(5)
m
m/Uc and A(fc ± fm)/A(fc) =
1
2h. In other words, the
2.2Angle modulations
The phase and frequency modulations together are called angle
modulations. Since, when we assume the sinusoidal carrier wave
Eq. (1) as c(t) = Ucsin[Θ(t)], the Θ(t) = 2πfct+ϕcdenotes the
angle part of the function.
Phase modulation (PM) changes the phase angle of the carrier
signal. Suppose that the modulating or message signal is Um(t),
then Θ(t) = 2πfct + [ϕc + Um(t)]. Let Um(t) be again a
bounded function. In this case we can define a constant as: kPM =
Umax
UPM(t) = Ucsin2πfct + kPMUP
m
(t)/2. This transforms the modulated signal
?
where UP
signal is
m(t) + ϕc
?
,
(6)
m(t) ? 1. The instantaneous frequency of the modulated
f(t) =dΘ
dt
= fc+ kPMdUP
m(t)
dt
.
(7)
Frequency modulation (FM) uses the modulation signal
Um(t) to vary the carrier frequency. Θ(t) = 2πf(t)t + ϕc and
here the instantaneous frequency f(t) is modulated by the signal
of kFMUF
m(t) as
f(t) = fc+ kFMUF
m(t).
(8)
In this equation kFM is the frequency deviation, which represents
the maximum shift from fc in one direction, assuming UF
limited to the range (−1,...,+1). Using the definitions of the in
stantaneous frequency and phase, expression (8) can be rewritten as
Θ(t) = 2πfct+2πkFM
is
?
This definition of FM is the least intuitive of the three Eqs (2, 6
and 9). If we compare Eqs (6) and (9) we realize that the modu
lation signals are in derivativeintegral connection with each other.
In practice, we have modulating signals that can be represented by
analytical functions. Therefore, when we detect an FM or PM sig
nal without any previous knowledge about them, it is impossible to
distinguish between FM and PM signals.
First, let the modulating signal be represented by a sinusoidal
wave with a frequency fm. The integral of such a signal is
m(t) is
?t
0UF
m(τ)dτ +ϕc. The modulated signal
UFM(t) = Ucsin2πfct + 2πkFM
?t
0
UF
m(τ)dτ + ϕc
?
. (9)
UF
m(t) =
UF
2πfmsin
m
?
2πfmt + ϕF
m
?
.
(10)
Thus, in this case Eq. (9) gives
UFM(t) = Ucsin
?
2πfct + η sin
?
2πfmt + ϕF
m
?
+ ϕc
?
, (11)
where the modulation index is defined as η = (kFMUF
Eq. (11) can be deduced from Eq. (6) as well. The only difference
is the value of η = kPMUP
lation frequency fm. Let us transcribe Eq. (11) using relations for
trigonometricalandBesselfunctions(Abramowitz&Stegun 1972)
as:
?
where Jk(η) is the Bessel function of first kind with integer order
k for the value of η (Fig. 1); ϕm denotes either ϕF
formula is known as the Chowning relation (Chowning 1973). Al
though it had been deduced by many different authors formerly,
m)/fm.
m, which is independent of the modu
UFM(t) = Uc
∞
k=−∞
Jk(η)sin[2π (fc+ kfm)t + kϕm+ ϕc],
(12)
mor ϕP
m. This
Page 3
Blazhko RRLyrae light curves as modulated signals3
0.60.6 0.60.6
0.4 0.40.40.4
0.20.2 0.20.2
0 0 0 0
0.2 0.2 0.2 0.2
0.4 0.4 0.4 0.4
0.6 0.6 0.6 0.6
0.8 0.8 0.8 0.8
1 1 1 1
0 0 0 0 5 5 5 5 10 10 10 10 15
xxxx
20 20 20 20 25 25 25 25 30 30 30 30
f(x) f(x)f(x)f(x)
15 15 15
Figure 1. The graph of the first three and the 10th Bessel functions of first
kind with integer order k for the value of x. J0(x) – (red) continuous line,
J1(x) – (green) dashed line, J2(x) – (blue) dotted line, J10(x) – (purple)
dashdotted line.
Chowning recognized its key role in the electronic sound creation
method called FM synthesis.
Similarly to Eq. (4) expression (12) also helps to imagine the
spectrum. It is made up of a carrier at fcand symmetrically placed
side peaks separated by fm. The amplitudes follow the Bessel func
tions. The behavior of the Bessel functions is well known: except
for small arguments (x < k), they behave like damped sine func
tions (see also, Fig. 1). For higher indices the higher order side
peaks gradually become more and more important. As a conse
quence, the amplitude of the central peak gets reduced. The fre
quency spectrum of an actual FM signal has an infinite number of
side peak components, although they become negligibly small be
yond a point.
If η ? 1, we find that J0(η) ≈ 1, J±1 = η/2 and Jk ≈ 0
for k > 1. That is, the spectrum can be approximated with an
equidistant triplet similarly to AM, but the character of the sig
nal differs from AM: the total amplitude of the modulated wave
remains constant. When η increases the amplitude of side peaks
also increases, but the Fourier amplitude of the carrier decreases.
In other words, the side peaks could be larger than the central peak,
on the other hand higher order side frequencies could also be of
larger amplitude than the lower order ones.
A more general case is formulated by Schottstaedt (1977)
UFM(t) = Ucsin
?
2πfct +
q
?
q
?
?
p=1
U(p)
m sin
?
2πf(p)
m t + ϕ(p)
m
?
+ ϕc
?
= Uc
∞
?
kp=−∞
···
∞
?
?
k1=−∞
?
p=1
Jkp(U(p)
m )
?
sin
?
2πfct +
q
p=1
kp
2πf(p)
m t + ϕ(p)
m
?
+ ϕc
?
.
(13)
Here the modulating signal is assumed to be a linear combination
of a finite number of sinusoidal functions with arbitrary frequen
cies f(p)
spectrum contains equidistant frequencies on both sides of the car
rier frequency. The amplitudes of the side peaks fc ± kpf(p)
determined by products of Bessel functions.
m , amplitudes U(p)
m and phases ϕ(p)
m , p = 1,2,...,q. The
m
are
2.3Combined modulation
In practice, the electronic circuits that generate modulated signals
generally produce a mixture of amplitude and angle modulations.
This combined modulation is disliked in radio techniques but wel
comed in sound synthesis and as we will see they appear in the case
of Blazhko RRLyrae stars, as well. Let us overview the basic phe
nomena of combined modulations following Cartianu (1966). We
start with the simplest case: both the AM and FM are sinusoidal
and their frequencies are the same.
UComb(t) = Uc(1 + hsin2πfmt)sin[2πfct+
η sin(2πfmt + φm) + ϕc].
(14)
By suitable choice of the starting epoch, without any restriction
of the general validity we can set ϕc = 0. Here φm is the rela
tive phase difference between the modulating FM and AM signals.
Other designations are the same as before. The third term of the
product (14) is the same as in Eq. (11), therefore, after applying the
Chowning relation (12)
UComb(t) = Uc(1 + hsin2πfmt)·
∞
?
This expression results in an infinite number of amplitude modu
lated waves. After trigonometrical transformations we get:
?
h
2Jk−1(η)sin
h
2Jk+1(η)sin
It can be seen that each terms consists of three sinusoidal functions
with different phases. On the basis of expression (16), the spectrum
of combined modulation (14) is comprehensible as a combination
of three FM spectra. The peaks are at the same places as the fre
quencies of the spectrum of (12), but the amplitudes of a pair of
side peaks are generally asymmetrical. Using some trigonometrical
identities, the rules of summation of parallel harmonic oscillations
and relations for Bessel functions we arrive to the expression for
the Fourier amplitudes of a certain frequency:
?
k=−∞
Jk(η)sin[2π (fc+ kfm)t + kφm].
(15)
UComb(t) = Uc
∞
?
?
2π (fc+ kfm)t + (k + 1)φm+π
k=−∞
2π (fc+ kfm)t + (k − 1)φm−π
Jk(η)sin[2π (fc+ kfm)t + kφm]+
2
?
+
?
2
??
.
(16)
A(fc+ kfm) ∼ Uc
J2
k(η)
?
1 −hk
η
sinφm
?2
+
h2
4cos2φm[Jk+1(η) − Jk−1(η)]2
?1
2
,
(17)
(k = 0,±1,±2,...). Introducing the power difference of the side
peaks as it was done by Szeidl & Jurcsik (2009) ∆l := A2(fc+
lfm)−A2(fc−lfm), where l = 1,2,3... and taking into account
formula (17), we get
∆l= −4hl
ηU2
cJ2
l(η)sinφm.
(18)
This formula is a direct generalisation of the formulae given by
Szeidl & Jurcsik (2009) for l = 1 and l = 2. It is evident, that
this asymmetry parameter depends only on φm, the relative phase
of AM and FM. The left hand side peaks are higher than the right
hand side ones (∆l< 0), if 0 < φm < π, otherwise the situation is
opposite: π < φm < 2π and ∆l > 0. In those very special cases,
Page 4
4Benk˝ o et al.
where φm = 0 or φm = π the side peaks’ amplitudes are equal.
We have to note that if one of the modulations from AM and FM
dominates in the combined case (h ? η or η ? 1), the amplitude
of the side peaks are almost the same.
3 BLAZHKO MODULATION
RRLyrae light curves traditionally are described by a Fourier series
of a limited number of terms. In Blazhko modulated RRLyrae stars
the sum builds up from terms of harmonics of the main pulsation
frequency, side peaks due to the modulation and the modulation
frequency and even its harmonics:
m(t) = A0+
N
?
i=1
Aisin[2πFit + Φi],
(19)
where either Fi = jf0, (j = 1,2,...,n); or Fi = kfm,
(k = 1,2,...,m); or Fi = j?f0 + k?fm, (j?= 1,2,...,n?,
k?= 1,2,...,m?); Fi = j??f0−k??fm, (j??= 1,2,...,n??, k??=
1,2,...,m??); f0and fmare the main pulsation frequency and the
modulation one, respectively. The amplitudes Ai and phases Φi
are considered as independent quantities and determined by a non
linear fit. The necessary number of parameters for a complete light
curve solution is 2N + 3 (amplitudes and phases and two frequen
cies and the zero point A0). The number of parameters can be as
high as 500600 for a long time series of good quality (see e.g.
Chadid et al. 2010).
Inthenextsubsectionsweshowhowthemodulationparadigm
can be applied and what advantages it has compared to this tradi
tional handling Eq. (19).
3.1Blazhko stars with AM
To start with, we discuss Blazhko stars’ light curves with pure AM
effect, although the recent spaceborn data suggest that all Blazhko
RRLyrae stars show amplitude modulation and simultaneous pe
riod changes (Chadid et al. 2010; Benk˝ o et al. 2010; Poretti et al.
2010). We follow a stepbystep generalization process that allows
us to separate effects more clearly. We note that the most striking
feature of a Blazhko RRLyrae light curve is the amplitude varia
tion, which is generally easy to find and in many cases the only
detectable modulation (see Stothers 2010 and references therein).
To apply the framework described in Sec. 2.1 to an RRLyrae
light curve the coursebook formulae need some extensions.
We choose a continuous, infinite, periodic function with a non
modulated RRLyrae shape as a “carrier wave”. This function is
described by the frequency f0 and its harmonics, that is c∗(t) :=
m(t) if Fi = jf0in Eq. (19).
Although, the exact analytical Fourier spectra of any of the
modulated signals discussed in this paper can be calculated with
out any problems, at least in theory (see also Appendix A), to illus
trate the different formulae synthetic light curves and their Fourier
spectra were also generated and plotted. An artificial light curve
was constructed as a carrier wave with typical RRLyrae parame
ters (f0 = 2 d−1and its 9 harmonics) on a 100 day long time span
sampled by 5 min (insert in Fig. 2). The Fourier transform of such
a signal is wellknown (Fig. 2): it consists of the transformed si
nusoidal components given in Eq. A2. (More precisely, due to the
finite length of the data set and its sampling, the Fourier transfor
mations should always be multiplied by the Fourier transform of
the appropriate window function.)
02468 1012141618 20
0
.1
.2
.3
.4
Frequency [d−1]
Amplitude [mag]
0 .2.4.6.811.21.4
.4
.2
0
−.2
−.4
−.6
−.8
−1
Time [days]
Brightness [mag]
Figure 2. Fourier amplitude spectrum of the artificial RRLyrae light curve
acting as a carrier wave of all modulated light curves constructed in this
paper (main panel), and a part of the light curve itself (insert).
Substituting c∗(t) carrier wave into the definition of AM in
Eq. (5):
?
?
j=1
m∗
AM(t) =1 +U∗
m(t)
U∗
c
?
c∗(t) =
[1 + m∗
m(t)]a0+
n
?
ajsin(2πjf0t + ϕj)
?
.
(20)
Expression (20) describes a general amplitude modulated RRLyrae
light curve, U∗
of the nonmodulated light curve. On the one hand, the nonzero
constant term of a0is obligatory from mathematical point of view,
otherwise the Fourier sum does not compose a complete set of
functions. On the other hand, this value represents the difference
between the magnitude and intensity means. More precisely, either
we use physical quantities (viz. positive definite fluxes) or we trans
form normalized fluxes into magnitude scale. In this latter case the
average of the transformed light curve differs from zero. In this
paper, for traditional purposes we use the second approach. For
RRLyrae stars the typical value of this difference is about some
hundredths of a magnitude (a0 ? 1). It is evident that this con
stant differs from the zero point of the light curve A0 given in the
apparent magnitude scale.
m(t) is the modulation signal, U∗
c is the amplitude
3.1.1Sinusoidal amplitude modulation
In the simplest case the modulation is sinusoidal:
U∗
m(t) = amsin(2πfmt + ϕm).
(21)
Sample light curves obtained with this assumption from Eq. (20)
are shown in Fig. 3. Introducing the modulation depth as h =
am/U∗
resulting in modulations symmetrical to an averaged value viz. a
horizontal line (left panels). Right panels show cases with higher
modulation depths (am > a0), where this symmetry is broken.
A common feature of these light curves is that the maxima and
minima of the envelope curves coincide in time. Furthermore, the
average brightness of all light curves vary with fm. It can be seen
directly from Eq. (20): the m∗
haviour. That is, the found mean brightness (V ) variations during
c the parameters were chosen as a0 ? U∗
c and am ? a0,
m(t)a0term is responsible for this be
Page 5
Blazhko RRLyrae light curves as modulated signals5
Time [days]
Brightness [mag]
.5
0
−.5
am <= a0
.5
0
−.5
0 20406080100
.5
0
−.5
.5
0
−.5
−1
am > a0
.5
0
−.5
−1
0204060 80100
.5
0
−.5
−1
Figure 3. Artificial light curves with a sinusoidal AM computed with the
formula Eq. (20). Left panels show symmetrical modulation (am ? a0;
a0 = 0.2), the right ones are asymmetrical (am > a0; a0 = 0.005).
The modulation depth h is increasing from the top to bottom as h =
0.1,0.2,0.4; fm= 0.05 d−1and ϕm= 270 deg are fixed.
Time [d]
Brightness [mag]
020406080100
1
0
−1
99.51010.511
1
.5
0
−.5
−1
−1.5
1919.520 20.521
.5
0
−.5
Figure 4. Bottom panel: Artificial light curve with a sinusoidal AM com
puted with the formula (20). The modulation depth is h = 1.2. Other pa
rameters are a0= 0.01, fm= 0.05 d−1and ϕm= 270 deg. Top panels:
Twoday zooms around a maximum (top left) and a minimum (top right) of
the modulation cycle.
the Blazhko cycle (Jurcsik et al. 2005) is a natural consequence of
the AM.
There is a fascinating case, when the modulation is very strong
i.e. when the modulation depth is h > 1. Beside the strong light
curve changes (Fig. 4) in some Blazhko phases the shape of the
light curve looks very unfamiliar (see top right panel in Fig. 4). The
relevance of this mathematical case is corroborated by the Kepler
observation of V445Lyr that shows similar characteristics (fig 2. in
Benk˝ o et al. 2010).
Using some trigonometrical relations, Eq. (20) with (21) can
be converted to a handy sinusoidal decomposition form from where
the Fourier spectrum is easily seen:
m∗
AM(t) = a0+ ha0sin(2πfmt + ϕm) +
Frequency [d−1]
Amplitude [mag]
02468101214161820
0
.02
.04
.06
.08
0.02.04.06.08.1.12.14.16.18.2
0
.001
.002
.003
1.51.61.71.81.922.12.22.32.42.5
0
.02
.04
.06
.08
Figure 5. Fourier amplitude spectrum of the artificial sinusoidal AM light
curve in bottom right panel of Fig. 3 after the data are prewhitened with the
main frequency and its harmonics. Inserts are zooms around the positions
of the main frequency f0 = 2 d−1(top), and the modulation frequency
fm= 0.05 d−1(bottom), respectively.
n
?
j=1
ajsin(2πjf0t + ϕj) +
h
2
n
?
j=1
aj
?sin?2π (jf0− fm)t + ϕ−
sin?2π (jf0+ fm)t + ϕ+
= ϕj − ϕm + π/2, ϕ+
Fourier spectrum of such an AM signal is familiar for RRLyrae
stars’ experts (see also Fig. 5). It consists of the spectrum of the
nonmodulated star (third term) as in Fig. 2 and two equidistant
side peaks around each harmonic (last term). The amplitudes of the
pairs of side peaks are always equal: A(jf0± fm) ∼ ajh/2. The
second term in Eq. (22), that causes the average brightness varia
tion, produces the frequency fmitself in the spectrum. The Blazhko
modulation frequency is always found in observed data sets ex
tended enough (see e.g. Kov´ acs 1995; Nagy 1998; Jurcsik et al.
2005, 2008; Chadid et al. 2010; Poretti et al. 2010; Kolenberg et
al. 2011).
It is a longstanding question whether there is any Blazhko
phase where the modulated light curve is identical to the unmod
ulated one (see Jurcsik, Benk˝ o & Szeidl 2002 and further refer
ences therein). In this simplest case the answer is easy. It happens
if the second and fourth terms in (22) disappear simultaneously,
namely, in the zero points of the modulated sinusoidal function at
t = (kπ − ϕm)/(2πfm), k is an arbitrary integer.
The number of used parameters for solving such a light curve
(Fig. 3) in the traditional way (according to Eq. 19) is 6n + 5,
where n denote the number of detected harmonics including the
main frequency. The necessary number of parameters in our han
dling is 2n + 5. The modulation is described by 3 parameters (fm,
am, ϕm) as opposed to the traditional framework where this num
ber is 4n + 3.
j
?+
j
??,
(22)
where ϕ−
jj
= ϕj + ϕm − π/2. The
Page 6
6Benk˝ o et al.
3.1.2Nonsinusoidal AM
As a next step, we assume the modulation function m∗
an arbitrary periodic signal represented by a Fourier sum with a
constant frequency fm. Substituting it into Eq. (20) we get
?
p=1
m(t) to be
m∗
AM(t) =aA
0+
q
?
aA
psin
?
0 = 1 + (am
2πpfmt + ϕA
p
??
c∗(t),
(23)
where constants are defined by aA
am
ters. Some typical light curves are shown is Fig. 6. It is evident that
their envelope curves are nonsinusoidal and their shapes depend
on the actual values of aA
these envelope curves occur, however, at the same Blazhko phase
as in the previous sinusoidal cases. Rewriting of (23) similarly to
Eq. (22) but in a more compact form yields
0/U∗
c), and aA
p =
p/U∗
c. From now on, the upper index A denotes the AM parame
p and ϕA
p. The maxima and minima of
m∗
AM(t) =
q
?
p=0
n
?
j=0
aA
p
2ajsin?2π (jf0± pfm)t + ϕ±
jp
?,
(24)
where the two sinusoidal terms appearing analogously to Eq. (22)
are formally unified into one formula and denoted by ± signs;
ϕ+
constants are chosen to be ϕA
By investigating the Fourier amplitude of the side peaks we
found that A(jf0±pfm)/A(jf0) ∼ aA
the side peaks of a given order and the central peak is constant. (ii)
ThecommonlyusedamplituderatioA(jf0±pfm)/A(f0±pfm) ∼
aj/a1vs. harmonic order is the same as the amplitude ratio of the
main frequency A(jf0)/A(f0) ∼ aj/a1 vs. harmonic order. (iii)
Since the same coefficient aA
the amplitudes of lefthandside and righthandside peaks are the
same. According to this, the generated Fourier spectrum (Fig 7)
now shows symmetrical multiplet structure of peaks around the
main frequency and its harmonics (jf0 ± pfm). Each multiplet
structure is the same at each harmonic order, that is the number
of the side peaks, their frequency differences and amplitude ratios
to their central peaks are the same. It is important to note that the
number of side peaks (in one side) is equal to p. In addition, the har
monic components of the modulation frequency pfm also appear.
(This can be obtained from Eq. (24) if j = 0.)
Such a phenomenon was undetected in the observed data of
Blazhko stars until recently. Hurta et al. (2008) found equidistant
quintuplets in the spectrum of RVUMa for the first time. Besides
triplets and quintuplets, sextuplet structures were also found by Ju
rcsik et al. (2008) in the spectrum of MWLyr, while Chadid et
al. (2010) detected even 8th order (sepdecaplet) multiplet frequen
cies in the spectrum of CoRoT data of V1127Aql. According to
Sec.2.2,theanglemodulationscauseinfinitenumbersofsidepeaks
around each harmonic, therefore, the origin of the observed multi
plets as a nonsinusoidal amplitude modulation is certain for those
cited cases (e.g. MWLyr and V1127Aql), where the harmonics of
the modulation frequency are also detected.
In searching for a Blazhko phase where the modulated and
carrier waves are identical we concluded that the modulation
terms can only be entirely disappearing from the formula (24) if
aA
ists. This necessary condition is complemented by an additional
one: the modulation virtually disappears in the moments when
?q
the parameters aA
jp= ϕj + ϕA
p− π/2; ϕ−
jp= ϕj − ϕA
0:= ϕ0 := π/2.
p+ π/2. The arbitrary
p. (i) The amplitude ratio of
pbelongs to both side peaks (at ±p),
0 = 1 (am
0 = 0) is true, otherwise no such Blazhko phase ex
p=1ajapsin[2π(jf0± pfm)t + ϕ∓
zero or infinite numbers of zero points depending on the values of
p, ϕA
jp] = 0. The sum has either
p. That is, generally there are no such phases
Brightness [mag]
.5
0
−.5
−1
.5
0
−.5
−1
.5
0
−.5
−1
.5
0
−.5
−1
020406080 100
.5
0
−.5
−1
Time [days]
Figure 6. Synthetic light curves of nonsinusoidal AM signals computed
by the formula (23). A twoterm sum of modulation signal was assumed:
aA
the second modulation term varies from top to bottom as: ϕA
220, 270, 360, respectively.
1= 0.01, aA
2= 0.2 mag; ϕA
1= 270 deg are fixed and the phase of
2= 110, 140,
Frequency [d−1]
Amplitude [mag]
0246810 1214 1618 20
0
.02
.04
.06
.08
0 .02.04 .06.08.1.12 .14.16 .18.2
0
.001
.002
.003
1.51.6 1.71.8 1.92 2.12.2 2.32.4 2.5
0
.02
.04
.06
.08
Figure 7.
AM light curves in Fig. 6 after the data were prewhitened with the main
frequency and its harmonics. Inserts are zooms around the positions of
the main frequency f0 = 2 d−1(top), and the modulation frequency
fm= 0.05 d−1(bottom), respectively.
Fourier amplitude spectrum of the synthetic nonsinusoidal
Page 7
Blazhko RRLyrae light curves as modulated signals7
where a nonsinusoidal AM light curve and its carrier wave are
identical.
The necessary number of the parameters for a light curve fit of
(19) and (23) is (2q+1)2n+2q+3 and 2n+2q+3, respectively.
Here n denotes the total number of used harmonics including the
main frequency and q is the order of side peak structures as above,
(i.e. q = 1 means triplets, q = 2 quintuplets, etc). In the traditional
description each additional side peak order increased the number
of terms by 4n+2 as opposed to our method, where this increment
is only 2.
3.1.3Parallel AM modulation
Multiperiodic modulation was suspected in XZCyg (LaCluyz´ e et
al. 2004), UZUMa (S´ odor et al. 2006), SUCol (Szczygieł & Fab
rycky 2007), and LSHer (Wils, Kleidis & Broens 2008). The
Blazhko RR Lyrae stars of the MACHO and OGLE surveys (Al
cock et al. 2000; Moskalik & Poretti 2003) that have unequally
spaced triplet structures in their Fourier spectra are possibly also
multiperiodically modulated variables. CZLac (S´ odor et al. 2011)
is the first Blazhko star with multiperiodic modulation where both
modulation periods are identified. Not only modulation side peaks
but linear combinations of the modulation frequencies also appear.
Signs of multiple modulation were discovered in Kepler data of
V445Lyr (Benk˝ o et al. 2010). There are numerous possibilities for
creating a multiply modulated light curve. Let us review some of
them.
The most simple case is a natural generalization of Eq. (23)
when the modulation signal is assumed to be a sum of signals with
differentˆfr
signals be independent, i.e., the modulation signal consists of lin
early superimposed waves. In this case, Eq. (23) reads as:
?
r=1p=1
m, where r = 1,2,... signs constant frequencies. Let
m∗
AM(t) =ˆ a0+
s
?
qr
?
ˆ aprsin
?
2πpˆfr
mt + ˆ ϕpr
??
c∗(t),
(25)
where ˆ a0 = 1 +?s
are taken into account and the only varied parameter is the fre
quency of the second modulation isˆf2
frequencies are comparable (ˆf1
panel a the envelope shape of the light curve shows the wellknown
beatingphenomenon.Herethebeatingperiodis200days,albeitthe
modulation periods are close to the shortest known ones. It is easy
to understand that the observations taken on a moderate time span
often detect only the gradual increase or decrease of the amplitude
of the Blazhko cycles. In panel b of Fig. 8ˆf2
that is the ratio of the modulation frequencies is 4:3, similarly to
the case of CZLac during its second observed season in S´ odor et
al. (2011). The amplitude changes of the consecutive Blazhko cy
cles need wellcovered longterm time series observations, other
wise the interpretation becomes difficult. Panel c in Fig. 8 shows
the case where the frequency of the second modulation is half of
the first one (ˆf2
cause alternating higher and lower Blazhko cycles. The exact 2:1
ratio between the two modulation frequencies leads to the same re
sult as a twoterm nonsinusoidal modulation in Eq. (23) (see also
top panel in Fig. 6). The bottom panel in Fig. 8 shows a case where
the second modulation has a much longer period than the primary
Blazhko cycle. In a first inspection the top and bottom panels are
very similar apart from a phase shift.
To reveal the real situation we need to compare their Fourier
r=1am
0r/U∗
c, and ˆ apr = am
pr/U∗
c. This formula
is demonstrated in Fig. 8. In this figure, only two modulation waves
m. When the two modulation
m= 0.1 d−1andˆf2
m= 0.09 d−1in
mwas set to 0.075 d−1,
m = 0.05 d−1). These specially selected values
Brightness [mag]
Time [days]
.5
0
−.5
−1
a
.5
0
−.5
−1
b
.5
0
−.5
−1
c
0 204060 80100
.5
0
−.5
−1
d
Figure 8. Artificial light curves calculated with two independent sinusoidal
AM modulations according to the formula of (25). The fixed parameters
were a0= 0.01, ˆ a11= 0.5, ˆ a12= 0.2 mag,ˆf1
ˆ ϕ12= 120 deg, whereˆf2
and 0.01 d−1, respectively.
m= 0.1 d−1, ˆ ϕ11= 270,
mchanges from top to bottom as 0.09, 0.075, 0.05
spectra starting with
m∗
AM(t) =
s
?
r=1
qr
?
p=0
n
?
j=0
ˆ apr
2
ajsin
?
2π
?
jf0± pˆfr
m
?
t + ˆ ϕ±
jpr
?
.
(26)
Where the constants are chosen similarly to (24): ˆ ϕ−
ˆ ϕpr+ π/2; ˆ ϕ+
toseethattheFourierspectrumof expression (26)containsssetsof
side peaks shown in Fig. 7. The qualitative structure of these sets
is the same. It consists of the carrier’s spectrum (jf0), the peaks
of the different modulation frequencies and their harmonics (pˆfr
and the side peaks around the main frequency and its harmonics:
jf0± pˆfr
the independence of the modulation waves no further side peaks
appear.
jpr= ϕj −
jpr= ϕj+ ˆ ϕpr− π/2; ϕ0 = ˆ ϕ0r = π/2. It is easy
m),
m, where p = 1,2, ..., qr, and r = 1,2,...,s. Due to
3.1.4Modulated modulation – the AM cascade
It is hard to imagine, however, that in a real stars’s case, the dif
ferent modulating waves are independently superimposed without
any interactions. Let us investigate the possibility of the modulated
modulation: the cascade. In other words, the modulation signal is
composed of recursively modulated waves as
Page 8
8Benk˝ o et al.
f0−f1
m
f0+f1
m
f0−f2
m
f0+f2
m
f0−(f1
m+f2
m)
f0+(f1
m+f2
m)
f0−f1
m+f2
m
f0+f1
m−f2
m
1.71.81.92 2.1 2.22.3
0
.02
.04
.06
.08
.1
Frequency [d−1]
Amplitude [mag]
Figure9.FourieramplitudespectraoftheartificialcascadeAMlightcurves
with parameters of panel b in Fig. 8 – (black) dotted line – and its cascade
equivalent – (red) continuous line. The spectra show the interval around the
main pulsation frequency after the data are prewhitened with it. The (blue)
dashedlineshowsthespectrumofcascadecaseafterthesidepeaksf0±f1
f0± f2
are shifted with +0.01 and −0.01 mag, respectively).
m,
mare also removed (for better visibility the top and bottom spectra
c(1)(t) := c∗(t), m(1)
m(t) = m∗
m(t),
c(2)(t) := m(1)
AM(t) = [1 + m(1)
m(2)
m(t)]c(1)(t),
AM(t) = [1 + m(2)
m(s)
m(t)]c(2)(t),...,
AM(t) = [1 + m(s)
m(t)]c(s)(t).
(27)
m∗
AM(t) =
s
?
r=1
?
˜ a0r+
qr
?
p=1
˜ aprsin
?
2πp˜fr
mt + ˜ ϕpr
??
c∗(t),
(28)
where ˜ a0r = 1 + am
plitude of the rth carrier wave c(r)(t). On the basis of a visual in
spection,thereareimperceptibledifferencesamongthelightcurves
produced by this expression (28) and those that can be seen in
Fig. 8. The Fourier spectrum, however, contains additional peaks
at the linear combinations of f0and˜fr
understand this spectrum we generate Eq. (28) in a form similar to
Eq. (26).
sin2π
0r/U∗
cr, ˜ apr = am
pr/U∗
cr. U∗
crdenotes the am
mas it is shown in Fig 9. To
m∗
AM(t) =
s
?
r=1
qr
?
p=0
n
?
j=0
1
2
s
?
r??=r
?
˜ a0r?
r?=1
˜ a0r?
˜ apraj·
m
??
??
?
?
?
jf0± p˜fr
?
t + ˜ ϕ±
?
?
jpr
?
+
s
?
?
k=2
?
?
r∈Rk
qr
?
n
?
p=1
a0
r?∈RC
k
r
˜ apr
Sk(α)+
s
?
k=2
r∈Rk
qr
p=1
j=1
aj
r?∈RC
k
˜ a0r?
r
˜ apr
Sk+1(β),
(29)
˜ ϕ−
An index set Rsis defined so that it contains all r indices from r =
1,2,...,s. Index sets Rkmeans all subsets of Rswhat contains k
elements. Therefore, the total number of Rksets is?s
jpr= ϕj − ˜ ϕpr+ π/2; ˜ ϕ+
jpr= ϕj + ˜ ϕpr− π/2; ˜ ϕ0r = π/2.
k
?. The sums
over r ∈ Rkmean a sum over the all possible combinations of the
k number of different indices r. Similarly r?always runs over the
complement of a set RC
up sums of sinusoidal functions (see for the definition and further
details in Appendix B) of the linear combinations of k angles. Here
the components of the α and β vectors are αr = 2πp˜fr
r ∈ Rk, βk+1= 2πjf0t + ϕj and βr = αr.
For better comparison we present the formula in the form
of Eq. (29) instead of the most possible compact one. Although
Eq. (29) seems to be complicated, the meaning of each term is
simple: the first term can be directly compared to the linearly su
perimposed case Eq. (26). It produces all the peaks in the Fourier
spectrum appearing in that case: the main pulsation frequency and
its harmonics jf0, modulation frequencies and its harmonics p˜fr
the side frequencies around the main frequency and its harmonics
(jf0± p˜fr
all the possible linear combinations of p˜fr
is responsible for the many linear combination frequencies around
the main frequency and its harmonics (Fig. 9). The latter two types
of combination terms were detected by S´ odor et al. (2011) in the
Fourier spectrum of CZLac, the only wellstudied multiply modu
lated RRLyrae star.
Longterm secondary changes in Blazhko cycles can be ex
plained by the variable strength of the modulation. To formulate
this assumption we arrived at
AM(t) =?1 +?1 + m?
The formula (30) can be considered as a special case of (28) when
s = 2 and ˜ a01 = 0.
kof the actual Rk. The functions Skbuild
mt + ˜ ϕpr,
m,
m). The second sum in Eq. (29) belongs to the peaks of
m, whilst the last term
m∗
m(t)?m??
m(t)?c∗(t)
(30)
3.2Blazhko stars with FM
We remind the reader of the possible absence of real Blazhko stars
with pure AM that was mentioned in the introductory paragraphs
of Sec. 3.1. The only difference between pure AM and FM cases is
that RRLyrae stars showing pure PM/FM are much more rarely re
ported than pure AM ones, but there are some examples (e.g. Kurtz
et al. 2000; Derekas et al. 2004).
How can the formalism discussed in Sec. 2.2 be applied to
RRLyrae stars? Let us assume the same carrier wave as in the case
ofAM,butheretheinstantaneousfrequencyf(t)isdenotedasf0+
m∗
m(t), and m∗
m(t) is an arbitrary (bounded) modulation signal.
m∗
FM(t) = a0+
n
?
j=1
ajsin{2πj [f0+ m∗
m(t)]t + ϕj}.
(31)
Expression (31) describes a general frequency modulated RRLyrae
light curve.
3.2.1The sinusoidal FM
When the modulating function is sinusoidal and expressed in the
same form as (21), Eq. (31) becomes
m∗
FM(t) = a0+
?
where aF= am/fm, ϕF= ϕm+π/2 and the upper index F marks
theparametersofFM.Theamplitudeofthissignalisdeterminedby
the Fourier amplitudes aj of the carrier signal, hence no amplitude
changes are present. In the bottom panel of Fig. 10 a simulated light
n
j=1
ajsin
?
2πjf0t + jaFsin
?
2πfmt + ϕF?
+ ϕj
?
,
(32)
Page 9
Blazhko RRLyrae light curves as modulated signals9
Time [d]
Brightness [mag]
0 20406080 100
.5
0
−.5
−1
10.610.8 1111.2 11.4
.5
0
−.5
20.6 20.82121.221.4
Figure 10. Bottom: Artificial FM light curve produced with sinusoidal
modulation according to Eq. (32). Fourier parameters of the “carrier light
curve” are the same as before, aF= 0.279;ϕF= 0. Boxes show the lo
cations of the top panels. Top panels: Oneday zooms from two different
phases of the modulation cycle. The nonmodulated “carrier” light curve
is shown by a (red) continuous lines while (blue) dotted lines denotes FM
signal. The periodic phase shift (viz. PM) caused by FM can be clearly
identified.
Frequency [d−1]
Amplitude [mag]
02468101214161820
0
.02
.04
.06
15.615.81616.216.4
0
.002
.004
.006
.008
.01
1.61.822.22.4
0
.02
.04
.05 .1.15.2.25
0
.0002
.0004
Figure 11. Bottom: Fourier amplitude spectrum of the artificial sinusoidal
FM light curve in Fig. 10 after the data are prewhitened with the main fre
quency and its harmonics. Top panels are zooms around the positions of the
mainfrequencyf0= 2d−1(topleft),andits7thharmonics8f0= 16d−1
(top right), respectively. The modulation frequency fmis missing from the
spectrum (insert).
curve is shown. It is evident that there is no amplitude change. Two
day zooms from two different phases of the modulation cycle are
shown in the top panels. The periodic phase shift caused by FM can
be identified well: in the lefthandside panel the nonmodulated
light curve is to the left from the FM light curve whilst in the right
hand side panel the situation is opposite.
Using Chowning’s relation (12) we get from (32):
m∗
FM(t) = a0+
n
?
j=1
∞
?
k=−∞
ajJk
?
jaF?
sin
?
2π (jf0+ kfm)t + kϕF+ ϕj
?
(33)
.
This equation shows the main characteristics of the Fourier spec
trum (Fig. 11). It consists of peaks at f0 and at its harmonics
jf0 and each of them is surrounded by side peaks at jf0 ± kfm
with symmetrical amplitudes at the two sides. This symmetry of
the amplitudes can be seen from the expression of amplitude ra
tio A(jf0 ± kfm)/A(jf0) ∼ J±k(jaF), and it is known that
J−k(z) = (−1)kJk(z). It is worth to compare the AM spectra
in Figs. 5 and 7 to this FM spectrum. The Fourier amplitude of
the side peaks are proportional to the Bessel function, and an im
mediate consequence can be seen in the figure: the amplitude of
the triplet peaks are higher at 3f0 than at 2f0. (Although it is not
shown in the figure, the higher order j > 5 harmonics have also
smaller amplitudes than their side frequencies’ ones.) Since the ar
gument of the Bessel functions depends on the order of harmonics
j, higher order harmonics “feel” larger modulation index, which
results in more side peaks around the higher order harmonics (see
inserts in Fig. 11). This effect was found for V1127Aql from its
CoRoT data by Chadid et al. (2010). A further remarkable flavour
of this Fourier spectrum is, that it does not include fmas opposed
to any of the AM spectra (insert in Fig. 11).
Let us return to the question whether there is any phase in the
modulation cycle where the light curve is identical to the monope
riodic light curve (carrier signal). As it was shown in the case of
sinusoidal AM modulation, there are some such possible phases.
Looking at the formula (32) it can be realised that the modulation
disappears at the moments of time if t = (lπ−ϕF)/(2πfm), where
l is an arbitrary integer.
Estimating the number of the necessary parameters for a light
curve fit the traditional description Eq. (19) needs ≈ 2n + 3 +
4?n
well. At the same time, Eq. (32) requires only 2n+5 parameters, no
more than in the sinusoidal AM case. For a typical case plotted in
Fig. 10 (n = 10 and aF= 0.27), the difference is 143 parameters
versus 25.
j=1[int(jaF)+1], where “int” means the integer function, and
n is the number of all harmonics including the main frequency as
3.2.2The case of nonsinusoidal FM
Assuming an arbitrary periodic modulation with a fixed frequency
wesubstituteaFouriersumrepresentingthismodulationsignalinto
Eq. (31) and get
m∗
FM(t) = a0+
n
?
j=1
ajsin
?
2πjf0t +
j
q
?
p=1
aF
psin
?
2πpfmt + ϕF
p
?
+ φj
?
,
(34)
where the constant terms are contracted as φj = jaF
the previous sinusoidal case the equation can be rewritten as
0+ ϕj. As in
m∗
FM(t) = a0+
n
?
j=1
∞
?
k1,k2,...,kp=−∞
q
?
aj
?
q
?
p=1
Jkp(jaF
p)
?
·
sin
?
2π
?
jf0+
p=1
kppfm
?
t +
q
?
p=1
kpϕF
p+ φj
?
.
(35)
Page 10
10Benk˝ o et al.
Frequency [d−1]
Amplitude [mag]
02468 101214161820
0
.02
.04
.06
15.615.816 16.216.4
0
.002
.004
.006
.008
.01
1.61.82 2.22.4
0
.02
.04
Figure 12. Bottom: Fourier amplitude spectrum of an artificial non
sinusoidal FM light curve calculated by the formula of (34) after the data
are prewhitened with the main frequency and its harmonics. Parameters of
the generated light curve were the same as for the light curve in Fig. 10, and
p = 2, aF
positions of the main frequency f0= 2 d−1(top left), and its 7th harmonic
8f0= 16 d−1(top right), respectively.
2= −0.1 mag, ϕF
2= π/4. Top panels are zooms around the
In one sense, this formula is a generalisation of (13) to the case
for a nonsinusoidal carrier wave, in the other sense however, the
modulation frequencies are chosen specially as fp
Comparing equation (35) with (33) it can be realised that the
structure of both Fourier amplitude spectra should be similar (cf.
also Fig. 11 and Fig. 12), although there are significant differences,
as well. First of all, besides the same values of common Fourier pa
rameters of a sinusoidal and a nonsinusoidal case, the detectable
side peaks are more numerous than for the nonsinusoidal case. The
reason is simple: the higher order terms in the modulation signals’
sum increase the “effective modulation index”. The most notewor
thy difference is the disappearance of the symmetry between the
amplitude of the side peaks from the lower and higher frequency
parts.
To understand this let us investigate the simplest non
sinusoidal case, if q = 2 and concentrate only on the side peaks
around the main pulsation frequency (j = 1). Then the above ex
pression (35) is simplified to
m:= pfm.
∞
?
?
k1=−∞
sin
∞
?
k2=−∞
a1Jk1(aF
1)Jk2(aF
2)·
2π [f0+ (k1+ 2k2)fm]t + k1ϕF
1+ k2ϕF
2+ φ1
?
.
(36)
For calculating the amplitude of the triplet’s side peaks A(f0±fm)
we have to sort out the corresponding terms from the above infinite
sum such as k1 = 1 − 2k2 and k1 = −(2k2+ 1), for the right
handside and lefthandside peaks, respectively (k2is an arbitrary
integer). It can be seen, that both sums include the same elements,
because J−3(aF
J5(aF
ences have the same values with an opposite sign. The only dif
fering terms contain J1(aF
J−1(aF
sponsible for the asymmetry of the side peaks. Introducing power
1)J1(aF
2),... for each pair and the relative phase differ
2) = J3(aF
1)J−1(aF
2), J−5(aF
1)J2(aF
2) =
1)J−2(aF
1)J0(aF
2) in the sum of A(f0+ fm) and
1)J0(aF
2) in the sum of A(f0 − fm). These terms are re
Harmonic order
Logarithm of the amplitude ratio
−3
−2
−1
0
1
2
0123456789
−2
−1
0
1
Figure 13. Amplitude ratios of the harmonic components of the main pul
sation (A(jf0)/A(f0)) plotted on decimal logarithmic scale compared to
theamplituderatiosofthemodulationcomponents:A(jf0+pfm)/A(f0+
pfm). Top: sinusoidal FM case; p = 0, 1, 2 and 3 (black) asterisks, (red)
circles, (blue) triangles and (green) squares, respectively. Bottom: non
sinusoidal FM; shape of the symbols denotes p as in the top panel, but
filled symbols mark positive ps (higher frequency side peaks) while the
open symbols show negative ps (lower frequency side peaks).
difference of the side peaks as in Sec. 2.3 we get
∆1 = 4ˆ A1J1(aF
1)J0(aF
2)cos(ˆΦ1− ϕF
1).
(37)
Hereˆ A1 andˆΦ1 indicate the amplitude and phase of a sinusoidal
oscillation obtained by summing all the terms in (36) except the
different ones. The asymmetry of the higher order side peaks (k1+
2k2 > 1) can be verified in a similar manner.
This asymmetry has a further consequence. The functions of
amplitude ratio vs. harmonic orders belonging to a given pair of
side peaks are diverge from each other (Fig. 13). This behaviour
is wellknown from the similar diagrams of observed Blazhko
RRLyrae stars (Jurcsik et al. 2009b; Chadid et al. 2010; Kolen
berg et al. 2011). It can also be seen that the actual character of the
asymmetry can change with the harmonic order j or even within a
given order with the different p. For example, in Fig. 13 if p = 1
(triplets), the righthandside peaks are always higher than the left
handside ones and the difference between the pairs are increas
ing with harmonic orders. Meanwhile, if p = 3 (septuplets) the
situation is the opposite. In the case of p = 2 (quintuplets) the
lower frequency peaks have higher amplitude around the lower or
Page 11
Blazhko RRLyrae light curves as modulated signals 11
Epoch
O−C [d]
0 20 4060 80100120140160180200
−.1
−.08
−.06
−.04
−.02
0
.02
.04
Figure 14. OC diagram of the maxima of FM light curves with sinusoidal
– (blue) filled circles – and nonsinusoidal – (red) empty circles – modu
lations, respectively. The input light curves are generated from the formu
lae of (32) and (34) with the same parameters as the light curve shown in
Fig. 10 (sinusoidal case) and Fourier plot in Fig. 12 (nonsinusoidal case).
(For better visibility the nonsinusoidal curve is shifted by −0.05.)
der (j < 5) harmonics, for higher harmonics (j > 7) the amplitude
ratios of the pairs of side peaks reversed.
As it was discussed in the introductory Section 2.3 simulta
neous and sinusoidal amplitude and phase modulations result in
an asymmetrical spectrum, therefore, the asymmetry of the ampli
tude spectrum alone is not a good criterion for detecting a non
sinusoidal FM. The classical O−C diagram is an ideal tool for this
purpose (see e.g. Sterken 2005). Fig. 14 illustrates the O−C dia
grams of the maxima for two artificial FM light curves: a sinusoidal
and a simple nonsinusoidal one.
At the end of this section we compare the necessary param
eters of a potential fit based on the classical description (19) and
the present (31) one. In the latter case this value is 2n + 2q + 3,
where n and q are defined in (31). The expression is the same as
in the case of a nonsinusoidal AM. The traditional formula needs
≈ 2n + 3 + (4?n
values are 27 and 163, respectively.
j=1[int(j?q
p=1aF
p) + 1]) parameters. For the
1 = 0.27, aF
case showed in Fig. 12 (n = 10, aF
2 = 0.1) these
3.2.3Parallel FM
We continue the discussion as in the case of AM. The next step
is the multiply modulated FM with independently superimposed
modulation signals (parallel modulation). As has already been
noted, the chance of such a scenario is very low for stars, but this
case shows a new phenomenon, which is why it is worth to have a
look at it.
?
?
r=1p=1
ˆ m∗
FM(t) = a0+
n
?
qr
?
j=1
ajsin2πjf0t +
j
s
?
0r+ϕj. The formula (38) can easily be transformed
with the help of Eqs. (13) and (35) to
ˆ aF
prsin
?
2πpˆfr
mt + ˆ ϕF
pr
??
+ˆφj
?
.
(38)
Hereˆφj := jˆ aF
f0−2f1
m
f0+2f1
m
f0−f1
m−f2
m
f0+f1
m+f2
m
f0−f1
m+f2
m
f0+f1
m−f2
m
f0−2f2
m
f0+2f2
m
1.71.8 1.92 2.12.2 2.3
0
.005
.01
.015
.02
Frequency [d−1]
Amplitude [mag]
Figure 15. Fourier amplitude spectra of the artificial light curves containing
two parallel FM modulations in formula (38). The figure shows a zoom
around the main pulsation frequency after the data are prewhitened with it
and the triplet components f0±ˆf1
quintuplet frequencies (f0±2ˆf1
frequencies. (The used parameters are:ˆf1
ˆ aF
m, f0±ˆf2
m, f0±2ˆf2
m. The highest peaks are at the
m) and at the linear combination
m= 0.1 d−1,ˆf2
m= 0.01 d−1,
11= 0.5 mag, ˆ aF
12= 0.2 mag.)
ˆ m∗
FM(t) = a0+
n
?
s
?
j=1
∞
?
k11,k12,...,kqss=−∞
qr
?
aj
?
s
?
r=1
qr
?
p=1
Jkpr(jˆ aF
pr)
?
·
sin
?
2π
?
jf0+
r=1p=1
kprpˆfr
m
?
t +
s
?
r=1
qr
?
p=1
kprˆ ϕF
pr+ˆφj
?
.
(39)
There is a fundamental difference between the construction of
FourierspectraofparallelAMandFMsignals.WhiletheAMspec
tra build up from a simple sum of the component spectra belonging
to a given modulation frequencyˆfr
ble linear combinations ofˆfr
sation frequency jf0. This is illustrated in Fig. 15. In practice, this
effect complicates distinguishing Fourier spectra from the cascade
AM and parallel FM.
m, FM spectra contain all possi
mand the harmonics of the main pul
3.2.4 The FM cascade
Although a parallel FM modulation results in a more complex
Fourier spectrum than either a parallel or even a cascade AM, our
former statement is still true. There is a very low chance for in
dependently superimposed modulation signals in real stars. Let us
turn to the FM cascade (viz. the modulated modulation) case now!
?
where
˜ m∗
FM(t) = a0+
n
j=1
ajsin
?
2πjf0t + j˜CFM(t) +˜φj
?
,
(40)
˜CFM(t) := m(1)
FM(t) =
q1
?
?
p=1
˜ aF
p1sin
?
2πp˜f1
mt + pm(2)
FM(t) + ˜ ϕF
p1
?
,
m(2)
FM(t) =
q2
?
p=1
˜ aF
p2sin2πp˜f2
mt + pm(3)
FM(t) + ˜ ϕF
p2
?
,...,
m(s)
FM(t) =
qs
?
p=1
˜ aF
pssin
?
2πp˜fs
mt + ˜ ϕF
ps
?
,
(41)
Page 12
12Benk˝ o et al.
and˜φj = j˜ aF
of a modulation cascade with s elements, where all elemental mod
ulation functions m(r)
That is, they are assumed to be independent periodic signals with
the frequencies˜fr
infinite series of sinusoidal functions (see Chowning relation), it is
not a surprise that the sinusoidal decomposition of the expression
(40) is very similar to the parallel case (39). Namely
01+ ϕj. As we can see, the function˜CFM(t) consists
FM(t) are represented by finite Fourier sums.
m. Since an FM modulation can be reproduced by
˜ m∗
FM(t) = a0+
n
?
?
?
j=1
∞
?
qr
?
?
k11,k12,...,kqss=−∞
?
aj·
?q1
p=1
?
?
Jkp1
j˜ aF
p1
s
?
r=2p=1
Jkpr
?
s
kp−1,r˜ aF
pr
??
·
sin
?
2πjf0+
s
?
r=1
qr
p=1
kprp˜fr
m
t +
?
r=1
qr
?
p=1
kpr˜ ϕF
pr+˜φj
?
.
(42)
The frequency content is exactly the same as in the parallel case,
only the values of amplitudes and phases are different.
3.3The case of PM
Here we discuss the phase modulation. As we stated in the Sec. 2
there is no chance to distinguish between FM and PM phenomena
onthebasisoftheirmeasuredsignals(inverseproblem),ifthemod
ulation function m∗
same time, if the basic physical parameters such as effective tem
perature, radius and logg are changing during the Blazhko cycle as
was found recently (S´ odor, Jurcsik & Szeidl 2009; Jurcsik et al.
2009a,b) the cyclic variation of the fundamental pulsation period
(vis. frequency) that results in FM would be a plausible explana
tion for observed effects. There is an additional possible argument
against the existence of PM in RRLyrae stars.
If we assume that the modulating function m∗
plicit time variation – as in the usual definition for PM modulation
in electronics – Eq. (31) reads as
m(t) in Eq. (31) is allowed to be arbitrary. At the
mcontains no ex
m∗
PM(t) = a0+
n
?
j=1
ajsin[2πjf0t + m∗
m(t) + ϕj].
(43)
When this formula is expressed as Eq. (33) or Eq. (35) according
to a sinusoidal or an arbitrary periodic modulating function, respec
tively, the arguments of Bessel functions are independent from the
harmonic order j as opposed to the case of FM. It causes a sys
tematic difference between Fourier spectra of FM and PM. While
the number of detectable side peaks in FM increases with the order
of harmonics, for PM the number of side peaks is the same for all
harmonics.
There are two Blazhko RRLyrae stars that show both strong
phase variations and their data are precise enough, these are the
CoRoT targets V1127Aql and CoRoT 105288363 (Chadid et al.
2010; Guggenberger et al. 2011). The spectrum of V1127Aql
clearly shows the existence of FM: 3rd order side frequencies
are detected around the main pulsation frequency while order of
8th around the 19th harmonic. The Fourier analysis of separate
Blazhko cycles of CoRoT 105288363 showed that with the increas
ing strength of phase variation, the number of detected side peaks
around higher order harmonics are also increased (Guggenberger
et al. 2011). It is an evidence of (changing) FM.
3.4 Real Blazhko stars with simultaneous AM and FM
In this section we discuss the general combined case, when both
types of modulations occur simultaneously. As it was mentioned
before both AM and FM type modulations were detected for all
observed Blazhko RRLyrae stars if the observed data sets were
precise and long enough. This is the situation for groundbased
(Jurcsik et al. 2009c; and references therein) and spaceborn ob
servations of CoRoT and Kepler (Chadid et al. 2010; Poretti et al.
2010; Benk˝ o et al. 2010; Kolenberg et al. 2011) as well.
Generalising the sinusoidal case of combined modulation
Eq. (14) discussed in Sec. 2.3 we get
m∗
Comb(t) = [1 + m∗
m(t)]m∗
FM(t),
(44)
where m∗
Eq. (31). Since all observed Blazhko stars show AM and FM with
the same frequency, we have investigated only those cases where
this assumption is fulfilled.
FM(t) is the general modulated FM function defined by
3.4.1Combined modulations with sinusoidal functions
The simplest case similarly to the pure AM and FM cases is the
simultaneous but sinusoidal modulations.
m∗
Comb(t) = (1 + hsin2πfmt)·
n
?
?
a0+
j=1
ajsin
?
2πjf0t + jaFsin(2πfmt + φm) + ϕj
??
,
(45)
where the notations are the same or directly analogous with the
previously defined ones: h = am/U∗
of the second term (the FM modulated “carrier wave”). The relative
phase between AM and FM signals is φm = ϕF− ϕm.
According to the schema of (16) expression (45) can be refor
mulated into
FMand U∗
FMis the amplitude
m∗
?
h
2Jk−1(jaF)sin?2π (f0+ kfm)t + (k − 1)φm+ ϕ−
h
2Jk+1(jaF)sin?2π (f0+ kfm)t + (k + 1)φm+ ϕ+
Comb(t) = a0+ a0hsin2πfmt+
?
n
j=1
∞
k=−∞
aj
?
Jk(jaF)sin[2π (f0+ kfm)t + kφm+ ϕj]+
j
?+
j
??
,
(46)
where ϕ±
in Fig. 16 can be interpreted as a sum of the combined modulation
with sinusoidal carrier wave (16) with an additional term describ
ing the modulation frequency itself (insert in bottom panel). Each
harmonic is surrounded by a multiplet structure of peaks just like
the main frequency. The number of side peaks increases with the
harmonic order j similarly for FM (Sec. 3.2.1).
The asymmetrical amplitudes of pairs of side frequencies be
longing to a given harmonic can be characterised similarly to the
sinusoidal carrier wave case (18) as
j= ϕj ± π/2. Based on Eq. (45) the Fourier spectrum
∆jl= −4hl
jaFa2
jJ2
l(jaF)sinφm.
(47)
Here ∆jl = A2(jf0+ lfm) − A2(jf0− lfm) is the power dif
ference of the lth side peaks at the jth harmonics (l = 1,2,...).
Similarly to the course book case discussed in Sec. 2.3 the asym
metry depends on the actual value of h and aF, (viz. the relative
Page 13
Blazhko RRLyrae light curves as modulated signals 13
Frequency [d−1]
Amplitude [mag]
0246810 1214 1618 20
0
.02
.04
.06
.08
.1
15.615.81616.2 16.4
0
.002
.004
.006
.008
.01
1.61.822.2 2.4
0
.02
.04
.06
.08
.1
.05.1.15 .2 .25
0
.001
.002
.003
Figure 16. Bottom: Fourier amplitude spectrum of an artificial com
bined (AM & FM) light curve computed from Eq. (45) after the data are
prewhitened with the main frequency and its harmonics. Top panels are
zooms around the positions of the main frequency f0 = 2 d−1(top left),
and its 7th harmonics 8f0= 16 d−1(top right), respectively. The relative
phase between AM and FM is set to φm= 270 deg.
strengths of AM and FM) and the relative initial phase angle φm.
The most extreme possibility is when one of the side peaks com
pletely disappears. The necessary conditions are φm = ±π/2 and
jaF= hl. The asymmetry decreases with the increasing harmonic
order j (see also top panels in Fig. 16), because all the Bessel func
tions quickly converge to zero with increasing arguments, therefore
dominate the right hand side of expression (47).
Nonequidistant sampling and large gaps in the observed time
series can cause significant differences between sidepeak ampli
tudes (see Jurcsik et al. 2005). Such sampling effects, however,
can not explain huge differences, such as when side peaks com
pletely disappear in one side and the spectra show doublets, though
numerous examples were found by large surveys as MACHO and
OGLE (Alcock et al. 2000, 2003; Moskalik & Poretti 2003). But
as illustrated by Fig. 16, highly asymmetrical side peaks can eas
ily be generated by (45). This asymmetry effect can be a possible
explanation for the observed doublets (RRν1 stars) and even for
triplets (RRν2 stars). In the latter case the two side frequencies
can originate from a quintuplet structure (equidistant triplet on one
side) or from a multifrequency modulation (nonequidistant triplet
on one side).
Searching for phases where the modulated and nonmodulated
light curves are identical we conclude that such phases exist only
if φm = (k1− k2)π; (k1, k2 are integers) and then the moments
of the coincidences are t = k2/2fm. Assuming all Blazhko stars
showing both AM and FM this conclusion supports the finding of
Jurcsik, Benk˝ o & Szeidl (2002), who studied light and radial ve
locity curves of Blazhko RRLyrae stars,
The amplitude ratio vs. harmonic order diagrams show sim
ilar shapes and relative positions as were discussed in Sec. 3.2.2
with the connection of Fig. 13. Let us look at the maximum bright
ness vs. maximum phase diagrams, a classical tool for analysing
Blazhko RRLyrae stars. Such diagrams are plotted in Fig. 17 for
synthetic light curves generated from the formula of (45). All
diagrams have a simple round shape. They reflect the relative
strength of AM and FM components. In panels A and B the rel
Maximum phase
Maximum brightness [mag]
φm=90
A
−.6
−.7
−.8
−.9
φm=120
C
−.6
−.7
−.8
−.9
φm=60
E
−.020 .02
−.6
−.7
−.8
−.9
φm=90
B
φm=240
D
φm=300
F
−.020 .02
Figure17. Maximumbrightnessvs.maximumphasediagramsforsomear
tificial light curves with combined sinusoidal modulations. Between panels
A and B the relative strengths of AM and FM are changed as (A) h = 0.1
and aF= 0.2 and (B) h = 0.2 and aF= 0.1, respectively. From panel
B to F the amplitudes are fixed and only the relative phase φmis changed
as shown at the upper left corner in each panel. The arrows in panels CF
indicate the direction of motion.
ative strengths are opposite 2h = aFand h = 2aF, respec
tively. As a consequence, the loop is deformed vertically or hor
izontally. When the angle φm differs from the special values of
lπ/2, (l = 0,1,2,3,4), the axes of the loops are inclined to the ver
tical horizontal position. This angle also determines the direction of
motion. If 0 < φm < π it is clockwise, whilst if π < φm < 2π
it is anticlockwise. (These conditions are the same as it was found
by Szeidl & Jurcsik 2009 for sinusoidal carrier waves.) It is note
worthy, that the same ranges of φmalso determine the character of
power difference of the side peaks: if the right hand side peaks are
higher than the left hand side ones then the direction of motion is
anticlockwise and vice versa.
3.4.2 Nonsinusoidal combined modulation
On the basis of the previous sections it is easy to define the light
curves which are modulated by general periodic signals simultane
ously both in their amplitudes and phases:
Comb(t) =m∗
c∗(t)
where the functions m∗
and (34), respectively. Since the two modulations are described
m∗
AM(t)
m∗
FM(t),
(48)
AM(t) and m∗
FM(t) are defined by Eqs. (23)
Page 14
14Benk˝ o et al.
by different functions (they are represented by different order of
Fourier sums), no such simple relative phase can be defined as φm
for the sinusoidal case in Sec.3.4.1. Therefore, we obtain for the
mathematical form of such a generally modulated light curve:
p?=1
?
j=1
?
where the notations are the same as in Eqs. (23) and (34). This
expression describes all the discussed phenomena of a light curve
modulated regularly with a single frequency fm. The envelopes
of these light curves are very similar to the envelopes of non
sinusoidal AM light curves shown in Fig. 6. The light curves show
nonsinusoidal phase variation as well (see also Figs. 10 and 14).
As in the former simpler cases, the Fourier spectrum can also
be constructed analytically with the help of the sinusoidal decom
position of (49):
m∗
Comb(t) =
aA
0+
q?
?
?
aA
p? sin
?
?
2πp?fmt + ϕA
p?
?
·
a0+
n
ajsin2πjf0t+
j
q
?
p=1
aF
psin2πpfmt + ϕF
p
?
+ φj
??
,
(49)
m∗
Comb(t) = a0aA
0+
q?
?
∞
?
?
p=1
p?=1
a0aA
p? sin
?
?
?
2πp?fmt + ϕA
p?
?
+
n
?
j=1
q?
?
p?=0
k1,k2,...,kq=−∞
aA
p?
2aj
q
?
p=1
Jkp(jaF
p)
?
?
·
sin
?
2π
?
jf0+
q
?
kpp ± p?
fm
?
t + ψ±
pp?j
.
(50)
Here the ψ±
constant is chosen as ϕA
spectrum is simple and wellunderstandable on the basis of the pre
viously discussed cases. The second term is responsible for the
appearance of the modulation frequency and its higher harmon
ics (see insert in Fig. 7). The next (infinite number of) terms de
scribe a spectrum which is similar to the nonsinusoidal FM spec
trum (Fig. 12) but it also shows the AM splitting which is present
in the sinusoidal combined case. These effects make the calcula
tion of the peaks’ amplitude complicated. The asymmetry between
each pair from a multiplet around a given harmonic is determined
by two factors: one of them is the the nonsinusoidal nature of the
FM (Sec. 3.2.2) and the other one is the combination of AM and
FM (Sec. 3.4.1).
The maximum brightness vs. maximum phase diagrams gen
erally show complicated shapes. They could form knots, loops and
other nontrivial features. A collection of such diagrams is plotted
in Fig. 18. The direction of the motion can arbitrarily change by
tuning the initial phases.
pp?j:=?q
p=1kpϕF
0 := π/2. The qualitative structure of this
p± ϕA
p? + φj ∓ π/2, the arbitrary
3.4.3Combined multifrequency modulations
A combined modulation with multiperiodic AM or FM or both can
be handled analogously to the simpler presented cases. We can
substitute m∗
fined by Eq. (25) (parallel AM) or Eq. (28) (AM cascade). Writ
ing m∗
m(t) into the general expression (44) as it was de
FM(t) as Eq. (38) (parallel FM) or Eq. (40) (FM cascade) in
Maximum phase
Maximum brightness [mag]
G
−.020.02
−.6
−.7
−.8
−.9
H
−.020 .02
I
−.020 .02
D
−.6
−.7
−.8
−.9
EF
A
−.6
−.7
−.8
−.9
BC
Figure 18. Some typical maximum brightness vs. maximum phase dia
gramsforsyntheticlightcurveswithcombinednonsinusoidalmodulations.
The relative strength, initial phases and number of used harmonics of AM
and FM has been varied.
principle is straightforward. In practice, however, calculating co
efficients (amplitudes, phases) is more complicated. The resulting
light curves and Fourier spectra can be interpreted on the basis of
their constituents. They do not show new features except their max
imum brightness vs. maximum phase diagrams which show time
dependent and generally nonclosed curves as opposed to those in
Fig 18. If the ratio of modulating frequencies are commensurable,
the curve is closed, otherwise it has a nonrepetitive behaviour. The
reason is that if the modulation is described by N independent fre
quencies the proper diagram would be 2Ndimensional and the
classical one is only a 2D projection of it.
4 PRACTICAL APPLICATION – A CASE STUDY
To demonstrate how our formalism works in practice, we gener
ated two artificial light curves with simultaneous nonsinusoidal
AM (with two harmonics, p?= 2) and FM (with three harmon
ics, p = 3). The light curves are 100days long and sampled by
5minutes in the same manner as the all synthetic light curves in
the paper. We added Gaussian noise to the light curves either with
rms=0.01 mag (model A) or 10−4mag (model B), respectively.
The model A is similar to a good quality groundbased observation,
while the model B simulates a typical spaceborne data set. These
two artificial light curves (top panels in Fig. 19) were analysed with
a blind test (i.e. without knowledge about frequencies, amplitudes
and phases) both by the traditional way and by our method.
4.1Classical light curve analysis
Constructing the mathematical model Eq. (19) of the light curves
in the traditional analysis is a successive prewhitening process. It
consists of Fourier spectra building, fitting the data with the param
eters of the highest peak(s) in the spectrum by a nonlinear algo
rithm, and subtracting the fitted function from the data and so on.
The process continues as long as significant peaks are detected. At
the end of this analysis the noise of the residual data reaches the
observational scatter.
Page 15
Blazhko RRLyrae light curves as modulated signals15
Brightness [mag]
Amplitude [mag]
.5
0
−.5
−1
Model A
0
.1
.2
.3
.4
(σ=0.01)
−.06
.04
−.04
−.02
0
.02
.04
0
.0005
.001
020 40 60 80 100
Time [days]
−.06
−.04
−.02
0
.02
05101520
0
.0005
.001
Frequency [d−1]
.5
0
−.5
−1
Model B
0
.1
.2
.3
.4
(σ=0.0001)
−.004
.004
−.002
0
.002
.004
0
10−4
.0002
0 20 40 60 80 100
Time [days]
−.004
−.002
0
.002
05101520
0
10−4
.0002
Frequency [d−1]
Figure 19. Artificial light curves with Gaussian noise and their Fourier spectra. Model A (σ = 10−2) is plotted in the left, model B (σ = 10−4) in the right.
The residual light curves and their spectra after the traditional fitting process (middle panels) and the present one (bottom panels). (Residuals and their spectra
are in different scales for the two models.)
In the case of model A the highest peaks belong to the main
frequency f0 and its harmonics. In the further prewhitening steps
the triplets (f0±fm), quintuplets (f0±2fm), septuplets (f0±3fm),
nonuplets (f0 ± 4fm) and the modulation frequency (fm) were
found and fitted. The significance level was chosen at S/N = 4,
where signaltonoise ratio (S/N) is estimated as Breger et al.
(1993). To remove all significant peaks from the spectrum five from
the undecaplet peaks (f0+ 5fm) and two aliases have to be fitted
andsubtracted.(Wenotethatthefrequency2fmwasdetectable,but
under the significance level, therefore it was not fitted.) The resid
ual light curve of this process and its Fourier spectrum are plotted
in the middle panels of Fig. 19. The rms of the residual light curve
is 10−2, so we got back the input noise value. The number of fit
ted frequencies are 103 and used parameters in this successive fit is
201. If the frequency of the side peaks are also fitted independently
(“let it free approach”) this value increases to 286.
The process works similarly in the case of model B as well.
Naturally, many more significant peaks are detectable. From the
highest peaks to the lowest: f0, its harmonics, the side peaks up
their orders of six (f0 ± 6fm), the modulation frequency and its
harmonic (fm, 2fm) are significant. Many alias peaks originating
from the finite data length are also detectable: 46 such frequencies
were removed up to the significance level of the sixth order of side
peaks. We stopped the analysis here at S/N ≈ 40, because we
already found 168 frequencies and used 368 parameters (or 478 if
we fit each frequency independently). The resulted light curve and
its Fourier spectrum are shown in the middle panels of Fig. 19. The
rms of this light curve is 10−3an order of magnitude higher than
the input noise parameter is.
4.2Light curve analysis in our framework
When we apply the approach of this work we need to calculate only
oneFourierspectrumandasinglenonlinearfitforeachlightcurve.
The Fourier spectrum and the characteristics of the light curve help
us to choose the proper fitting formula and to determine the initial
values of the fit.
The Fourier spectrum for any of the light curves A and B pro
vide us with the necessary parameters (f0, j, a0, aj, ϕj) of the
carrier wave. The amplitude modulation and its nonsinusoidal na
ture in both light curves are apparent. Searching for peaks in the
low frequency range of the Fourier spectra results in good initial
values for fm, p?= 1,2, aA
detectable around the harmonics of the main frequency than the
number of harmonics of fm and the side peaks are asymmetrical,
an FM has to be assumed. To check its nonsinusoidal nature we
may prepare e.g. an O−C or maximum brightness vs. maximum
phase diagram. At the end of this preparatory work we can choose
the fitting formula (49). We note that to determine the correct initial
values of aF
quency variations. In the worst case, they can be estimated by some
numerical trials with the nonlinear fit. Using initial values that are
good enough the nonlinear fit converged fast for models A and B.
The algorithm reached the noise levels 10−2and 10−4within few
(less than 10) iterations automatically. The residual light curves and
their Fourier spectra are plotted in the bottom panels of Fig 19. The
number of fitted parameters for both models is only 33. Due to the
finite numerical accuracy the residual spectra always show a struc
ture reflecting the original spectra at very low levels.
In conclusion our method fits the light curves in a single step
with much less parameters than the traditional one. In addition we
avoid the timeconsuming alias fitting and subtracting processes.
The difference in the number of used parameters increases with the
increasing accuracy of the observed data sets. In our example the
number of regressed parameters is reduced from 6 times (model A)
to more than 10 times (model B). Our description has advantages in
the numerical fit of the groundbased observations as well, but its
advantages are outstanding in the analysis of the spaceborn time
series.
p? and ϕA
p?. While more side peaks are
pand ϕF
pdepends on the tool used for finding the fre
5DISCUSSION AND SUMMARY
In this paper we have investigated mathematical representation of
artificial light curves. These light curves are defined as modulated
signals where their carrier wave is a monoperiodic RRLyrae light
curve defined by its finite Fourier sum. Different types of periodic
functions are taken into account as modulation functions from the
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 Available from Robert Szabo · May 30, 2014
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