TFM Astrosismologia K2

Variability Characterization of Massive B-Type
Stars in K2 Space Mission.
TFM en Astronom´ıa y Astrof´ısica
MSc. Felipe Meza (VIU)
Dr. Ehsan Moravveji (KU Leuven)
Valencian International University
May 17, 2017
Felipe Meza fmezacr@gmail.com Valencian International University
TFM Astronom´ıa y Astrof´ısica 1

Agenda
1 Objectives
2 Introduction
3 Methodology
4 Results
5 Future Work

Objectives
• Get familiar with at least three tools/methods to reproduce
accurate and precise K2 light curves devoid of instrumental
eﬀects or trends and choose one of them for the analysis.
• Perform a Fourier analysis of the photometric timeseries (light
curves) using IvS python programming.
• Identify gravity g-mode pulsators at low frequencies and
pressure p-mode pulsators at higher frequencies, or hybrid
pulsators that simultaneously exhibit p- and g-modes, in the
resulting periodograms.
• Characterize the database of candidate stars according to the
presence of modes in speciﬁc ranges of frequency.

Introduction - Star Oscillations
“Stellar oscillations enables the study of stellar interior because
diﬀerent modes penetrate to diﬀerent depths inside the star”
“Asteroseismology is the study of stellar oscillations”

STAR

Introduction - Star Oscillations ( m n)
( ,m) = (3,0)
( ,m) = (3,±1)
( ,m) = (3,±2)
( ,m) = (3,±3)

Introduction - B type massive stars

Christensen-Dalsgaard, 2003
• Masses above 3M
• Examples: β Cep, SPB and
hybrids.
• Challenges:
• Inﬂuence of processes in the
stellar atmosphere.
• Rotation eﬀects such as mass
loss and asymmetry.

Introduction - K2 Space Mission
• In 2014, Kepler lost 2 gyroscopes.
• Telescope pointing is now controlled by solar photon ﬂux.
• The pointing is limited to the ecliptic plane only.
• Precision has degraded from 1 to 50 ppm
• Observation campaigns of 80 days.
Howell, 2014

Methodology - Data Selection
• International researchers have proposed observation of OB
type stars with K2: Moravveji, Aerts, Papics, Buysschaert, De
Cat, Balona, Gies.

Methodology - Data Size
CAMPAIGN # STARS
C0 281
C1 1
C2 116
C3 79
C4 21
ALL 498

Methodology - Python Analysis Interface
• Anaconda IDE (Python 2.7)
• astropy (FITS ﬁles) and matplotlib (curves)
• reportlab (generation of PDF ﬁles)
• IvS (lib KU Leuven - Frequency Analysis)

Methodology - Classiﬁcation
MODE TYPE FREQUENCY (day−1) VAR. CLASS1
High Order g 0-3 SPB
Low Order g and p 2 3-6 βCep
High Order p 2 6-25 βCep
All the modes above 0-25 Hybrid 3
1
variability class according to Aerts et al,“Astereoseismology”, 2010.
2
simultaneously.
3
according to Balona, 2011.

Results - General Scheme

Results - Tools for Reduction (PYKE)
• Set of tools for light curve reduction.
• Based on Python, part of PyRAF.
• Example of ﬁles: SAP, TPF, PDCSAP and CBV.
• Total control of reductions.
Still-Barclay, 2012

Results - Tools for Reduction (K2SFF)
• Developed by Andrew Vanderburg at Hardvard.
• The method correlates the ﬂux measurements with the
satellite pointing and according to the results, the dependence
is extracted.
• Data available online at cfa.hardvard.edu
Vanderburg, A. and Johnson, 2014

Results - Tools for Reduction (K2P2-KASOC)
• Based on KASOC ﬁlter (removed long term instrumental
eﬀects, planetary signals, among others)
• Uses TPF’s, masks and statistical operations.
• Data available online at KASOC database.
Lund, 2015

Results - General Scheme (LSP)
PLS(v) = 1
2
( N
i=1 x(ti)cos[2πv(ti−τ)])2
N
i=1 cos2[2πv(ti−τ)]
+
( N
i=1 x(ti)sin[(2πv(ti−τ)])2
N
i=1 sin2[(2πv(ti−τ)]

Results - General Scheme (Pre-Whitening)

Results - General Scheme (Freq. Comb.)

Results - Programming Workﬂow
Complete script available at: https://github.com/fmezacr/K2BTMS

Results - The Journal (https://goo.gl/qZ78o5)

Results - Variability Characterization (SPB, βCep, Hybrid)

Results - Variability Characterization (RMA)
Application of Spectral Energy Distribution (SED) ﬁtting, to get
photometric calibration of eﬀective temperature and surface gravity for
the most promising candidates.

Results - Characterization

Future Work
• Complete the missing phases and according to the ﬁnal results
evaluate the creation of a paper.

Future Work - Asteroseismology Analysis
Period Spacing
Van Reeth, 2015a
Rotation Frequency
Ouazzani, 2017
Diﬀerential Rotation
Kurtz, 2014

Future Work
• WEB version of the tool to generate pulsation modes reports
from the .fits light curves.
Program progress: https://github.com/fmezacr/K2BTMS_WEB

Future Work
• Future space projects such as NASA-TESS and ESA-PLATO
2.0 missions will provide more data to be used for similar
analysis with our automated classiﬁcation tool.
• Use of the code in future K2 campaigns (e.g. C11 and C14,
C16) which contain massive stars.

Future Work - TESS
• Transiting Exoplanet Survey Satellite (TESS)
• The TESS launch date is NLT June 2018 (Falcon 9).
• Will survey almost the entire sky.
Ricker et al, 2014

Questions?
Felipe Meza - fmezacr@gmail.com

ANEXO 1

TFM Astrosismologia K2

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