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Variability study of the high-resolution spectra of an O-star
Guilherme D. C. TeixeiraSupervisors: M. S. Nanda Kumar, M. J. P. F. G. Monteiro
Stellar Structure and Evolution
● Described and predicted by structure equations
∂m∂r
=4 π r2ρ
∂ P∂ r
=−Gm
r2ρ
∂ L∂ r
=4π r2ρε
∂T∂r rad
=−34ac
κρ
T 3
L
4 π r2
∂T∂r ad
=−(1−1γ )
μmhκ
Gm
r2
Mass conservation
Hydrostatic Equilibrium
Energy Equation
Radiative Transport
Adiabatic Convection
H-R diagram
Figure - The Hertzsprung-Russel diagram. Credits: ESO
Internal structures
● Internal structure of stars is dependent on mass
Figure - Heat transfer on stars. Credit: Sun.org - www.sun.org
O-stars
● Massive stars are rare(~1% of all stars).
● Short-lived (~106yrs).● Responsible for
synthesis of heavyelements via supernovae.
Figure - Number of stars in Eagle Nebula by mass bin. From Andrea Stolte - private communication.
Where to look for O-stars?
● Nearby star forming/HII regions
● The moleculargas is being ionizedby the embeddedO stars
● Orion, Monoceros,M8, Trifid are someof the regions wewill study
Figure - Color composite made by WISE, shows Orion. Bright red arc on bottom right is one of our targets, Sigma Orionis. Credit: NASA.
Getting R,M
● Photometric methods: – Mass-Luminosity relation (M)
– Interferometry (R)
– Evolutionary tracks (M, R)
● Spectroscopy:– Effective temperature (R)
– Logg (M)
– Spectral type (M, R)
● Asteroseismology– Gravity modes and pressure modes (R,M)
Asteroseismology
● Observes oscillations and variability on stellar flux and spectra
● Compares with models of stellar pulsations
● Different oscillation modes probe stellar interior at different depths
● Measures precise stellar parameters Figure - Principle of asteroseismic modelling.
From Aerts (2015).
p-modes and g-modes
● p-modes, or pressure modes, are present in convection dominated envelopes. Do not propagate in radiative zones.
● g-modes, or gravity modes, show up in radiative zones. Do not propagate in convective zones.
● mixed modes are combination of p- and g- modes
Difficulties of massive star asteroseismology
● Different internal structures from low- and intermediate-mass stars
● Fast rotation
● Mass loss from stellar winds
● Stronger magnetic fields
● Smaller number of sharp absorption lines
Macroturbulence
Credit David F. Gray
● Had-hoc velocity field that explains the shape of the wings of a spectral line (Struve 1952; Conti & Ebbets 1977; Howarth et al. 1997).
● No physical explanation for its presence
High-resolution spectra in O-stars
● Spectral lines are highly-broadened
● Show presence of macroturbulence
● Macroturbulence shown not to be product of large scale turbulence motions (Simón-Díaz et al. 2010).
Broadening and the Pulsational Hypothesis
● macroturbulence is a collective pulsational velocity broadening due to g-modes (Aerts et al. 2009; Simón-Díaz et al. 2010)
● Pulsational components have been confirmed on B-dwarfs (Aerts et al. 2009, Waelkens et al. 1998).
Figure - Noiseless pulsationally and rotationally broadened profiles (thin lines) compared with only rotational broadening (dashed). From Aerts et al. (2009).
Line variability in O-stars● Explored in Simón-Díaz (2015).● Observational strategy based on long-period variability.● Observed multi-periodic variability from high-order g-modes● Found correlation between the skewness of profile and
macroturbulent velocity
Figure - Line-profile variability of B star on the IACOB sample. From Simón-Díaz (2015).
Our targetSpectral Type ~ O9
Luminosity ~ 40000 Lsun
Mass ~ 20 Msun
Teff ~ 35000 K
age ~ 300 000 yrs
v sini ~ 140 km/s
radial velocity -29.45 km/s
visual magnitude ~ 4 mag
log g ~ 4.2 dex
Building a Linelist
● Stellar atmospheres depend on: age, mass, energy, chemical composition, and momentum of a given star
● One of primary tasks was to build a line list appropriate to young O-stars
Figure - Spectra for different spectral types. From Jacoby et al. (1984).
Studied lines
● Spectral lines based on careful study of the available spectra
● Selected lines with line depth >30% in synthetic spectra of O star
Observations● Used the PRL Advanced
Radial-velocity All-sky Search spectrograph at the 1.2m telescope at Mt. Abu, India
● Has a wavelength coverage of 3800-6900 Å
● Spectral Resolution of R~67000
Figure – Echelle spectra image.Credit: “PARAS First light”
Summary of observations
CCF
● Cross-correlation function (CCF) correlates the spectrum with a binary mask
Figure - Construction of CCF with template binary mask. From Melo (2001).
Temporal Variance Spectrum analysis
TVSi=1
N−1∑i=1
N
d ij2
TVS of He 4713 from Martins et al. 2010 TVS of He 4920 from Martins et al. 2010
CCF variability
CCF of 2015-01-17 for each pair of two observations. The black line represents the median of all days
The difference between the median CCF and the observation at each interval of 3 km/s
CCF variability
CCF of 2015-01-18 for each pair of two observations. The black line represents the median of all days
The difference between the median CCF and the observation at each interval of 3 km/s
CCF variability
CCF of 2015-01-19 for each pair of two observations. The black line represents the median of all days
The difference between the median CCF and the observation at each interval of 3 km/s
H-alpha variability (daily)
Variability of the H-alpha line in Jan of 2015. Each line represents a consecutive day and the black line represents the median of the month.
TVS of the H-alpha line in Jan of 2015. The dotted, dashed and full black lines represent, respectively the 1-sigma, 2-sigma and 3-sigma of the wings.
He-5875 variability (daily)
Variability of the He-5875 line in Jan of 2015. Each line represents a consecutive day and the black line represents the median of the month.
TVS of the He-5875 line in Jan of 2015. The dotted, dashed and full black lines represent, respectively the 1-sigma, 2-sigma and 3-sigma of the wings.
H-alpha vs He 5875
EW of H-alpha vs Ew of He 5875
Possible explanations for variability
● Short-lived prominences (Sudnik et al. 2016)
● Wind variability (Martins et al. 2015)
● Non-radial Pulsations (Fullerton et al. 1996)
Future work
● Implementing analysis based on the bisector method
● Further study the correlation between the variations of different lines
● Model and minimize the effect of winds
Figure - Bisector method. From Dravins (2008).
Summary
● We have found spectral variability in an O-star
● Variability is present in the timescale of days and hours
● We will further improve our study by modeling and minimizing other effects such as winds