Young stars in gas-dust disks. II. Vega (α Lyr) and β Pic
Transcript of Young stars in gas-dust disks. II. Vega (α Lyr) and β Pic
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YOUNG STARS IN GAS-DUST DISKS. II. Vega (ααααα Lyr) and βββββ Pic
E. V. Ruban and A. A. Arkharov
Observational data for Vega, α Lyr in the 325-1080 nm range from various years are studied using
material stored at the Pulkovo Spectrophotometric Data Base (PSDB). It is shown that the
spectrophotometric temperature of the star was lower than the effective temperature according to data
from all the observational seasons. Possible reasons for this are examined: light scattering by small
particles in the ultraviolet and reflection by large particles at longer wavelengths. A difference of 0m.01-
0m.02 in the quasimonochromatic magnitudes of the star is obtained for observations in different seasons.
This difference may related to a large-scale inhomogeneity in the distribution of dust and gas in the disk.
Photometric data for the star β Pic in the Hipparcos catalog reveal periodic variations in the Vt magnitude
with a period of 4.46 d and an amplitude of 0m.0085. Three assumptions are made to explain this result:
pulsations in the star’s photosphere, a planet at a distance of ~0.1 a.u., and a region with an elevated
density of particles in the circumstellar disk that periodically eclipses the star as it undergoes Kepler
rotation. These assumptions require further confirmation.
Keywords: Vega; β Pic; spectrophotometry; photometry; microvariability
1. Introduction
The second part of this paper is a study of spectrophotometric and photometric data from observations of Vega
(α Lyr, HD 172167, BS 7001) and β Pic (HD 39060, BS 2020), which are surrounded by extended gas-dust clouds.
As noted in the first part of this paper, there is a planet in the disk of β Pic. The giant planet β Pictoris b with a
mass of 7-10 times that of Jupiter was discovered in 2010. It lies at a distance of 8-15 a.u. from the star and orbits
Astrophysics, Vol. 55, No. 2, June , 2012
0571-7256/12/5502-0156 ©2012 Springer Science+Business Media, Inc.
Original article submitted September 28, 2011; accepted for publication April 4, 2012. Translated fromAstrofizika, Vol. 55, No. 2, pp. 175-188 (May 2012).
Main (Pulkovo) Astronomical Observatory, Russian Academy of Sciences, Russia; e-mail: [email protected] [email protected]
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it with a period of ~17 years [1,2]. No planet has yet been found near Vega, but the large, solid particles made up
of primordial gas and dust in the disk surrounding the star suggest that its gas-dust disk is similar to the disk
surrounding β Pic, which is a protoplanetary system.
As noted in the first part of this paper, these studies are based on Vt- and Bt-band photometric data contained
in the Hipparcos catalog [3] and on spectrophotometric data in the 325-1080 nm range stored in the Pulkovo
Spectrophotometric Data Base (PSDB), which has served as the basis for compiling the Pulkovo Spectrophotometric
Catalog (PSC) [4,5].
2. Vega
2.1. Results of the spectrophotometric observations. The study of observational data on Vega ( α Lyr,
BS = HR 7001 [6], HD 172167) in this paper is based only on spectrophotometric data from the PSDB, since no Vt
and Bt photometric data for Vega are given in the Hipparcos catalog [3]. The H-band data given there also have
systematic errors, which we detected but could not eliminate owing to their complicated character, as opposed to the
systematic errors in the Vt and Bt bands for Fomalhaut [7], which we were able to eliminate. In addition, the H-band
is too broad for studying subtle effects of the sort examined here.
It has been repeatedly noted that the results of spectrophotometric observations are stored in the PSDB in the
form of individual seasonal catalogs. Each catalog combines the observational data obtained during a single season
for all the stars observed in that season.
The duration of a season was determined by the fixed observation site, telescope, spectral range, and detection
system and could range from a few months to several years. Data on the quasimonochromatic flux E(λ) of a star, after
eliminating the effect of the earth’s atmosphere and accounting for the spectral sensitivity of the apparatus, are given
in absolute energy units of erg/cm2/s/cm.
In seasonal catalog k, the following data are given at each wavelength λ within the spectral band being studied
with a step size of 2.5 nm (see Table 1): the quasimonochromatic magnitude of the star averaged over all observations
(i is the series number of an observation, Nk is the number of observations), i.e., ( ) ( ) k
N
ik Nmmk
∑ λ=λ1
, where
( ) ( )λ−=λ ii E.m log52 ; as well as the mean square (standard) error of the average magnitude, ( ) ( ) kNk NSSk
λ=λ ,
where ( )λkNS is the standard error for a single observation.
The mean weighted magnitudes of each star obtained from the data in the seasonal catalogs and the mean
square error of these magnitudes are listed the PSC [4,5].
It is evident that the error in the observations will be determined both by random factors and by the variability
in the emission when microvariability is present.
In this paper we study the microvariability factor. For the chosen stars, in order to monitor the presence of
possible systematic errors, we have used data obtained in the same seasons. Large systematic errors (>0m.02) were
eliminated in the course of analyzing the data and creating the PSC [4,5]. Small errors ( 020m.≤ ) were not considered
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k Years λλ , nm Telescope Nk
Group
1 1971-1973 325-737,5 AZT-7 124
4 1985-1986 " " 16 I
9 1990-1991 " " 22
16 1987e 510-1080 Zeiss-600 28
17 1988 " " 47 II
19 1989 " " 22
TABLE 1. Observational Seasons
λ, nm
mλ
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Fig. 1. Average continuum energy distributions,
)(λλm , of Vega in the ultraviolet (a) and infrared (b)
segments of the spectrum obtained in seasons k; theerror bars indicate the error in the averagemagnitudes; the different plot points show the
theoretical values of λm for different temperatures T
(normalized to λ = 555 nm).
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then. Now, as we are studying microvariability, it is important to protect ourselves against these errors.
Table 1 lists the series numbers k of the selected seasons [7] in which Vega was observed. Also indicated there
are the observation years (“e” denotes the second half of a year), the spectral ranges λλ, the telescopes, the number
Nk of observations of the star during a given season, and the groups combining the catalogs.
The seasonal average magnitudes mk(λ) are plotted in Fig. 1 as functions of the real continuum wavelength
in the ultraviolet (a) and infrared (b) parts of the spectrum. The plot points are joined smoothly by curves of various
types for the different seasons k. The error bars indicate the errors in the average magnitudes (the other notation is
discussed below).
2.2. Effect of the variability factor. The influence of the variability factor is quite evident from the difference
in the average magnitudes obtained in different seasons (see Fig. 1b). The spread in the magnitudes within the seasons
shown here was random according to the Fischer criterion (Eq. (6) in Ref. 7).
Fig. 2. Average continuum energy distributions,
)(λλm , in the infrared obtained in seasons k for the
stars (a) BS 1791 and (b) BS 7557. The parenthesesindicate the number of observations and the errorbars indicate the error in the average magnitudes.
λ, nm
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k = 16(5)k = 17(5)k = 19(2)
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mλ
mλ
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BS 1791a
k = 16(26)k = 17(60)k = 19(30)
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It can be seen that the data from the 17-th season differ substantially from the others: the fluxes of monochromatic
light from Vega in the 17-th season are systematically higher, by ~2%, than the fluxes observed in the other seasons.
For comparison with other stars, Fig. 2 shows the corresponding infrared data for the stars BS 1791 (a) and
BS 7557 (b) observed in the same seasons. The parentheses indicate the number of observations of the star and the
other notation is the same. Clearly, here there are no systematic differences among the data from different seasons.
The significance of the differences in the average magnitudes for Vega in seasons 16 and 17, as well as 19
and 17, was verified using Student’s criterion [8]. According to this test, if the difference in th average magnitudes
exceeds T (Eq. (2) of Ref. 7), then the difference is significant. The following quantiles of the Student distribution
were used for calculating T with a confidence of 95%: t0.95
(27) = 2.05, t0.95
(46) = 2.02, t0.95
(21) = 2.08. The values of T16,17
and T19,17
calculated using Eq. (2) of Ref. 7 at each point of the real continuum and averaged over wavelength
are 0140m,1716 .T ≈ and 0190m
,1719 .T ≈ . The differences in the average magnitudes obtained for the same seasons and
averaged over wavelength are ( ) ( ) 03201716 m.mm ≈− and ( ) ( ) 02801719 m.mm ≈− . Therefore, m(k) - m(17) > Tk,17
for
k = 16 and k = 19; that is, the difference in the averaged magnitudes is significant with 95% confidence.
2.3. Microvariability. The variability factor, which influences the average magnitudes, also affects the
dispersion in the results when they are combined over several seasons. An approximate estimate of this influence was
made using single-factor dispersion analysis [8], which decomposes the total dispersion into separate components
characterizing the random factor and the variability factor.
In part I [7] the random component of the dispersion, ( )λ20S , was determined for the two groups of seasons
listed in Table 1. The number of degrees of freedom for the random dispersion in these groups are fI
= 275
(group I) and fII
= 143 (group II).
TABLE 2. Variations in Stellar Magnitude, λ± ,MS , for Group I
λ, nm meanm ,λ λ± ,MS λ, nm meanm ,λ λ± ,MS
325.0 1.282 0.014 460.0 0.616 0.012
327.5 1.277 0.017 580.0 1.328 0.009
417.5 0.334 0.009 582.5 1.339 0.007
425.0 0.379 0.014 600.0 1.423 0.010
445.0 0.517 0.013 627.5 1.567 0.012
447.5 0.540 0.015 630.0 1.585 0.017
450.0 0.552 0.012 635.0 1.601 0.008
452.5 0.563 0.010 675.0 1.798 0.009
455.0 0.587 0.014 680.0 1.829 0.009
457.5 0.600 0.012 687.5 1.879 0.020
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TABLE 3. Variations in Stellar Magnitude, λ± ,MS , for Group II
λ, nm meanm ,λ λ± ,MS
1 2 3
510.0 0.922 0.012
512.5 0.932 0.012
515.0 0.942 0.009
517.5 0.951 0.008
520.0 0.964 0.010
522.5 0.979 0.014
525.0 0.997 0.020
527.5 1.012 0.016
530.0 1.021 0.012
532.5 1.034 0.010
535.0 1.051 0.012
537.5 1.065 0.016
540.0 1.075 0.007
542.5 1.094 0.019
545.0 1.108 0.018
547.5 1.123 0.016
550.0 1.132 0.013
552.5 1.146 0.011
555.0 1.162 0.010
557.5 1.184 0.012
560.0 1.197 0.006
562.5 1.212 0.006
565.0 1.229 0.008
567.5 1.243 0.011
570.0 1.259 0.009
572.5 1.274 0.006
575.0 1.288 0.009
577.5 1.299 0.007
580.0 1.310 0.007
585.0 1.337 0.008
587.5 1.350 0.009
590.0 1.361 0.011
592.5 1.372 0.013
595.0 1.384 0.012
597.5 1.398 0.007
λ, nm meanm ,λ λ± ,MS
1 2 3
600.0 1.413 0.010
602.5 1.417 0.014
605.0 1.432 0.014
607.5 1.445 0.014
610.0 1.462 0.017
612.5 1.474 0.014
615.0 1.489 0.013
617.5 1.500 0.012
620.0 1.512 0.012
622.5 1.520 0.014
625.0 1.538 0.010
627.5 1.558 0.016
630.0 1.572 0.013
632.5 1.577 0.013
635.0 1.587 0.012
637.5 1.595 0.008
640.0 1.606 0.013
642.5 1.618 0.011
645.0 1.634 0.016
675.0 1.800 0.012
677.5 1.812 0.008
682.5 1.834 0.013
685.0 1.856 0.013
687.5 1.863 0.014
697.5 1.919 0.008
702.5 1.941 0.017
705.0 1.953 0.011
707.5 1.962 0.010
710.0 1.976 0.017
712.5 1.997 0.010
715.0 2.006 0.010
737.5 2.127 0.006
740.0 2.137 0.008
742.5 2.145 0.015
745.0 2.157 0.016
λ, nm meanm ,λ λ± ,MS
1 2 3
747.5 2.166 0.016
777.5 2.286 0.012
780.0 2.293 0.015
782.5 2.304 0.015
785.0 2.316 0.013
787.5 2.325 0.013
790.0 2.344 0.013
792.5 2.355 0.015
795.0 2.362 0.017
797.5 2.371 0.011
800.0 2.381 0.012
802.5 2.392 0.016
805.0 2.405 0.015
807.5 2.410 0.009
825.0 2.488 0.011
827.5 2.492 0.014
830.0 2.503 0.016
832.5 2.511 0.016
835.0 2.518 0.018
837.5 2.530 0.014
840.0 2.533 0.010
842.5 2.535 0.009
845.0 2.543 0.011
847.5 2.550 0.011
850.0 2.556 0.007
852.5 2.564 0.010
855.0 2.571 0.010
857.5 2.578 0.013
860.0 2.581 0.012
862.5 2.585 0.011
865.0 2.590 0.014
877.5 2.609 0.013
880.0 2.603 0.012
882.5 2.629 0.007
885.0 2.655 0.008
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In order to estimate the dispersion owing to variability, it is necessary to determine the dispersion in the
average magnitudes. The dispersion ( )λ2AS in the average magnitudes for Vega was estimated using Eq. (5) of Ref.
7 with the numbers of catalogs and observations, k and Nk, given in Table 1. The calculated dispersion had f
I = 2
(group I) and fII
= 2 (group II) degrees of freedom. The significance of the ratio ( ) ( )λλ 20
2 SSA of the dispersions was
tested in each group using the Fisher test (Eq. (6) of Ref. 7): ( ) ( ) ( )095020
2 , ffFSS A.A >λλ . The Fisher quantiles for
a 95% confidence for both groups are roughly equal, with ( ) ( ) 0314322752 950950 ..F.F .. ≈≈ . The ratio ( ) ( )λλ 20
2 SSA
of the dispersions (on the average, over all wavelengths) for group I is ~7 and for group II, ~16; that is, the
inequality ( ) ( ) 0320
2 .SSA >λλ was satisfied for both groups. This means that the variability factor had a significant
effect on the dispersion in the average magnitudes with a probability >95%.
Therefore, the variability in the light was found, with high probability, to have an influence on the average
magnitudes of the star and on the dispersion in these magnitudes according to both the Student and Fisher tests.
For those wavelengths at which the inequality (6) of Ref. 7 was satisfied, we estimated the dispersion in the
variability factor, ( )λ2MS , using the approximation (7) of Ref. 7. The square root of these dispersions give the
variations in the star’s emission, λ± ,MS . These dispersions are given in magnitudes (m) in Table 2 for group I and
in Table 3 for group II. The mean square magnitudes meanm ,λ of Vega in these groups are also listed in these tables.
The results in Tables 2 and 3 are illustrated in Fig. 3. The observed mean weighted magnitudes meanm ,λ for
both groups of catalogs are plotted in Fig. 3a. The variations λ± ,MS in the observed magnitudes for the same groups
are plotted in Fig. 3b. The other notation is discussed below.
We now analyze these results.
TABLE 3. (Conclusion)
λ, nm meanm ,λ λ± ,MS
1 2 3
932.5 2.748 0.022
970.0 2.880 0.023
972.5 2.885 0.026
975.0 2.895 0.031
977.5 2.897 0.023
980.0 2.896 0.018
982.5 2.902 0.016
985.0 2.906 0.017
987.5 2.913 0.015
990.0 2.922 0.014
992.5 2.928 0.018
995.0 2.936 0.016
λ, nm meanm ,λ λ± ,MS
1 2 3
1022.5 3.018 0.023
1025.0 3.025 0.025
1027.5 3.032 0.025
1030.0 3.041 0.022
1032.5 3.049 0.020
1035.0 3.057 0.026
1037.5 3.065 0.022
1040.0 3.074 0.019
1042.5 3.083 0.019
1045.0 3.085 0.016
1047.5 3.101 0.021
1050.0 3.112 0.019
λ, nm meanm ,λ λ± ,MS
1 2 3
1052.5 3.121 0.021
1055.0 3.130 0.022
1057.5 3.135 0.018
1060.0 3.142 0.014
1062.5 3.157 0.022
1065.0 3.166 0.019
1067.5 3.175 0.017
1070.0 3.183 0.014
1072.5 3.194 0.013
1075.0 3.206 0.018
1077.5 3.216 0.015
1080.0 3.221 0.020
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2.4. Spectrophotometric temperature. Besides the observational results, theoretical monochromatic magnitudes
mλ for temperatures of 9000, 9500, and 10000 K according to the data of Kurucz [9] are plotted in Figures 1 (a and
b) and 3a. (Here and in the following, the data are normalized to the averaged observed magnitude at a wavelength
of λ = 555 nm.)
A comparison of the observed and theoretical curves in Fig. 3a shows that the energy distribution in the
continuum spectrum of Vega corresponds to the theoretical curve for a temperature of ~9000 K. According to the
latest data [10], the rapidly rotating Vega, with its pole oriented toward the observer, has a polar temperature of 10000
K, and an average of ~9650 K. Spectrophotometric observations, in which the luminous flux from the entire star is
measured at each wavelength, should yield a temperature close to the average. But here the spectrophotometric
Fig. 3. (a) Mean-weighted continuum energy
distributions of Vega, )( , λλ meanm , for groups I and II
and theoretical values of mλ for temperatures T(normalized to λ = 555 nm); (b) variations in the
emission from Vega, λ ,MS , for groups I and II and
theoretical variations in the magnitudes, λΔ m , when
the temperature is varied by ΔT.
λ, nm
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T=10000K T=9500K T=9000K
(I)mmean ,λ
(II)mmean ,λ
(I)S M, λ
(II)S M, λ
500KT −=Δ500KT +=Δ
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temperature of Vega turned out to be lower than the effective temperature. Furthermore, it differs in different parts
of the spectrum (cf. Figs. 1a and 1b). Thus, non-temperature factors have had an influence on the spectral energy
distribution.
In order to check whether the change in the monochromatic magnitudes at different wavelengths is caused
by changes in the temperature of the photosphere, theoretical variations in the magnitudes, λΔ+ m , were calculated
for temperature changes of ±500 K and are plotted in Fig. 3b. The plotted dependences of the observed
variations ( )λ± λ ,MS in the magnitudes are symmetric with respect to the horizontal axis, in the directions of both
increased and decreased radiative flux. The resulting symmetry is related to the method used for determining the
variations, i.e., taking the square root of the dispersions. However, the theoretical dependences are, strictly speaking,
not symmetric. We can still assume that the asymmetry is small for small temperature variations.
A comparison of the curves in Fig. 3b shows that the observed dependence ( )λλ ,MS does not agree with the
theoretical dependence ( )λΔ λm as the temperature is varied: in the theoretical curve, as opposed to the observed data,
the variation in the magnitude increases toward shorter wavelengths. This implies that the variations in the observed
magnitudes are not related to variations in the photospheric temperature.
2.5. Effect of a surrounding gas-dust disk. A drop in the spectrophotometric temperature indicates that layers
outside the photosphere are acting on the photospheric emission. These layers can be layers from a gas-dust disk
surrounding the star. Layers of the disk can also absorb or scatter light from the star [7]. Absorption by the gas, as
in the case of Fomalhaut, can show up as a reduction in the continuum level in the extreme ultraviolet portions of
the spectrum (see Fig. 3a) and may be related to bunching of faint absorption lines of ionized atoms. Here, given
the small variations in the emission in this region (see Fig. 3b), we may assume that the density of the gas along
the line of sight varies between different observational seasons. Given the high temperature of Vega, we may assume
that there are quite a lot of ionized atoms in the disk. However, because of the orientation of the disk in the plane
of the figure, there are not enough of them along the line of sight, so that absorption by the gas has negligible effect
on the observational results.
Fine particles with radii 10.≤ mm contribute the most to the scattering of light in the visible and near
ultraviolet regions of the spectrum with λ < 650 nm [11]. This kind of scattering can obviously explain the reduction
in the observed light flux from the star relative to the theoretical level in the ultraviolet (see Fig. 1a).
At long wavelengths λ > 650 nm, the main contribution is from large particles with radii 1≥ mm [11]. The
increased flux from the star observed at long wavelengths (see Fig. 1b) is most likely related to the superposition
of light reflected from the dust disk on the light from the star. The fraction of reflected light is obviously determined
by the albedo of the particles and the amount of these particles (the density of the medium). A difference in the
contributions from reflected light in different seasons may be caused by a large-scale inhomogeneity in the distribution
of dust over the disk and to the participation of the dust in Kepler rotation.
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3. βββββ Pic
3.1. Results of the spectrophotometric observations. The star b Pic appears in the PSDB only in one season,
k = 1. The number of observations was 4 (Nk = 4). The real continuum wavelength-averaged standard error for a single
observation of the star, S1, is equal to 0m.0239. The random error, S
0(λ), in the observational results in the season for
group I was determined in the first part of Ref. 7. On the average, it is 0m.0345. Clearly, S1
< S0. Thus, no factors other
than random are involved in the spread in the data.
The average energy distribution in the real continuum of the star obtained in season 1 is plotted in Fig. 4.
The error bars indicate the errors in the average magnitudes. Also shown here are the theoretical monochromatic
magnitudes at different wavelengths for temperatures T = 8000 and 9000 K according to the data of Kurucz [9]. The
effective temperature of the star is 8073 K [12]. It is clear in the figure that the star’s spectral energy distribution
is essentially the same as the theoretical curve for the corresponding temperature.
3.2. Results of the photometric observations. In the Hipparcos catalog [3], the series of observational data
for the star β Pic in the Bt and Vt bands includes 164 terms. Fourier analysis was used to search for microperiodicity
in the series. Figure 5a is a power spectrum 105PW for the Vt series. The maximum peak (indicated by a dashed vertical
line) corresponds to a period p = 4.462 d and exceeds the noise level by a factor of 6.54. The error in the period
determined from the width of the peak is ±0.03 d. A phase curve for a period of 4.62 d is shown in Fig. 5b. The abscissa
is the phase ph, and the ordinate is the difference Vt – Vtmean
(Vtmean
is the average magnitude in the series of
observations). A sinusoidal regression fit with an amplitude of 0m.0085 is drawn through the points. The correlation
ratio determining the strength of the coupling of the points to the regression curve is 0.281; that is, the coupling
is significant with a confidence exceeding 95% [8]. (The power spectrum in the Bt band contained several peaks,
Fig. 4. The continuum spectral energy distribution ofβ Pic obtained in the first (k = 1) season, mλ(λ), andtheoretical magnitudes mλ for temperatures T; the errorbars indicate the errors in the average magnitudes.
λ, nm
mλ
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T=8000KT=9000K
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166
among which a main peak could not be distinguished, so it is not shown here.)
4. Discussion
4.1. An unknown planet? The period of the microvariability obtained for β Pic is p = 4.46±0.03 d with an
amplitude of 0m.0085. If this variability were associated with a planet orbiting the star, then, according to Kepler’s
third law, the planet would be at a distance of ~0.098 a.u. from the star. Its orbital velocity would be ~240 km/s.
However, in a study of radial velocities [13] no inner planets of the star were observed at distances ranging from 0.03
to 1.2 a.u. Recall that the only planet discovered so far [1,2], β Pic b, is at a distance of 8-15 a.u.
Fig. 5. (a) A power spectrum 105PW(Vt) for β Pic. ν isthe frequency in d-1. (b) The phase dependence of Vt– Vt
mean. p is the period and ph, the phase.
ph, p = 4.462d
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4.2. Pulsations? It might be supposed that the observed microvariability is related to pulsations of β Pic. The
existence of pulsations of the star was suggested in the above cited paper [13]. The period of the pulsations obtained
there, ~30 min, led the authors to compare them with the pulsations of type δ Scu stars. On the other hand, if pulsations
do exist, the ones obtained in the present work have a longer period, 4.46 d, than in δ Scu stars. (The period in δ
Scu stars is 0.01-0.2 d [14].) In addition, the positions of the (Vt-Vtmean
) points in the phase plot for β Pic Fig. 5b
recall the asymmetric light curve of δ Cep stars: a slow decrease in brightness and a rapid rise (the sinusoid is only
an approximation to the phase dependence). However, the pulsations of β Pic have a very low amplitude (0m.0085)
compared to those of δ Cep stars.
4.3. Large-scale inhomogeneity in the circumstellar disk? There may be a third reason for the variability
of β Pic: periodic eclipsing of the star by regions of a circumstellar disk with an elevated concentration of particles.
The existence of large-scale inhomogeneity in the surrounding disks is suggested by an analysis of observational data
from Fomalhaut and Vega. Confirmation of an inhomogeneity in the disk of β Pic will require further study.
5. Conclusion
A study of data from photometric observations of Vega at wavelengths of 325-1080 nm obtained in different
years has shown that its spectral energy distribution is influenced by a gas-dust disk surrounding the star. The effect
of the disk shows up through scattering of light in the ultraviolet by small particles, as well as in an enhanced
luminous flux at longer wavelengths owing to reflection of the star’s light by large particles. As a result, the
spectrophotometric temperature of the star turned out to be lower than the star’s effective temperature.
A microvariability of roughly 0m.01-0m.02 in the quasimonochromatic magnitudes of the star has been
detected. This variability was not associated with pulsations of the star, but was apparently determined by a large-
scale inhomogeneity in the distribution of dust and gas across the disk, where absorbing and scattering matter is
concentrated in clouds.
Because of the small number of spectrophotometric observations, the effect of a gas-dust disk surrounding the
star could not be detected in the observational data for β Pic. On the other hand, photometric observations of this
star reveal periodic variations in the Vt magnitude with a period of 4.46 d and an amplitude of 0m.0085. Three
assumptions were made to interpret this result: the existence of pulsations in the star’s photosphere, of a planet at
a distance of ~0.1 a.u., and of a region with an elevated particle density in the circumstellar disk, which periodically
eclipses the star as it participates in Kepler rotation. All three of these assumptions require confirmation.
To conclude, we note the main result of this work: a gas-dust disk surrounding the star has an effect on the
spectral energy distributions of Fomalhaut and Vega. It reduces the spectrophotometric temperature of the stars by
acting in different ways on different regions (UV and IR) of the spectrum. This interaction is nonthermal. The
difference in the effect during different seasons indicates that the disks have a large scale inhomogeneity.
168
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