X-ray Variability in the X-ray Emitting Symbiotic RT Cru

e-Talk (abstract id.HH00.02) presented at the American Physical Society (APS) April Meeting, Sacramento, CA, USA, April 5, 2024
https://doi.org/10.6084/m9.figshare.26121766

1. Ashkbiz (Ash) Danehkar
Eureka Scientific, Oakland, CA, USA
[email protected]
In Collaborations with: Jeremy J. Drake & Gerardo Juan M. Luna
APS April Meeting, Sacramento, CA, 5 April 2024
X-ray Variability in
the X-ray Emitting Symbiotic RT Cru:
Principal Component Analysis
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Symbiotic Stars
Symbiotics: interacting binaray system
–A Hot accreting compact object (WD)
–A Cool red giant star
A White dwarf (WD) accreting
materials from red giant,
typically having a soft or
supersoft X-ray emission
However, a few of them
show hard X-ray emission,
so called Hard X-ray Emitting Symbiotics
Credit: Atrononomy.com, Kavli IPMU

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Hard X-ray Emitting Symbiotics
Hard X-ray Symbiotics:
–RT Cru
–CH Cyg
–T CrB
–CD-57 3057 (SS73 17)
–MWC 560
RT Cru:
•Soft thermal emission ~ 1.3 keV
•Hard thermal emission ~ 10 keV
Ducci et al. 2016
RT Cru

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Timing Analysis
Changes hard and soft state
–Soft (S: 0.4–1.1 keV)
–Medium (M: 1.1–2.6 keV)
–Hard (H: 2.6–10 keV)
Danehkar et al. 2024

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Hardness Analysis
Changes hard and soft state
–Soft (S: 0.4–1.1 keV)
–Medium (M: 1.1–2.6 keV)
–Hard (H: 2.6–10 keV)
Danehkar et al. 2024

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Principal Component Analysis (PCA)
Singular Value Decomposition (SVD):
PCA: Python code (Mike Parker 2015)
https://www.michaelparker.space/
SVD of the linear algebra in NumPy
Press + 1997, Numerical Recipes in Fortran 77
A=U⋅Σ⋅V
T
A: matrix (m ⨯ n), a time-sliced spectra of n time-stacked data binned with m energies,
U: unitary matrix (m ⨯ m), PCA components, energy-binned spectra fi(E),
Σ: diagonal matrix (m ⨯ n), PCA eigenvalues, variability fractions λi,
V: square matrix (n ⨯ n), PCA eigenvectors, time-binned lightcurves Ai(t).

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Principal Component Analysis (PCA)
absorbing column
continuum
thermal emission
thermal emission
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eigenvalues
Li, Machine Learning Methods, Springer 2024
eigenvalues
A=U⋅Σ⋅V
T
eigenvectors
Unitary
matrix
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Principal Component Analysis (PCA)
thermal emission
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Principal Component Analysis (PCA)
absorbing column
continuum
thermal emission
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Bayesian Statistic Analysis
Soft thermal emission ~ 1.3 keV
Hard thermal emission ~ 10 keV
Danehkar et al. 2021

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X-ray Soft Thermal Emission
Soft and Hard thermal components in Hard X-ray Emitting Symbiotics:
RT Cru
–1.3 keV (Danehkar et al 2021)
–9.6 keV (Luna & Sokoloskil 2007; Danehkar et al 2021)
CH Cyg:
–0.2, 0.7 & 7.3 keV (Ezuka et al 1998)
MWC 560:
–0.18 & 11.26 keV (Stute & Sahai 2009)
SS73 17 (CD-57 3057):
–1.12 & 9.9 keV (Eze et al. 2010)
Soft component likely from a colliding wind

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Summary
Hard X-ray Symbiotic Star RT Cru
–Soft Themal Emission ~1 keV from Bayesian Statistics (Danehkar + 2021)
–Hard Thermal Emission ~10 keV (Luna & Sokoloskil 2007; Danehkar + 2021)
Timing Analysis:
–Stochastic Variability in XMM-Newton and Suzaku
Hardness Analysis:
–Spectral Transition in Suzaku
Variability in Principal Component Analysis (PCA):
–Mostly from Absorbing Material (50%)
–Partially from Source Continuum (20%)
–Likely from Soft Thermal Emission (9%) of a Colliding Wind

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AD thanks NASA grant 80NSSC22K0626.
GJML thanks grant ANPCYT-PICT 0901/2017.
Contact: [email protected]