Detecting and quantifying stellar magnetic fields

Carroll, T. A.; Strassmeier, K. G.

doi:10.1051/0004-6361/201322825

Cited by 11 publications

(14 citation statements)

References 57 publications

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“…Similar results have been previously presented in Carroll & Strassmeier (2014). In this work the noise treatment is done adopting a sparsity representation of the data using an Ortogonal Match Pursuit (OMP) algorithm.…”

Section: Caracterizing the Techniquementioning

confidence: 68%

Using machine learning algorithms to measure stellar magnetic fields

Ramírez-Vélez

Yáñez-Márquez²,

Cordova-Barbosa³

2018

A&A

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Context. Regression methods based in Machine Learning Algorithms (MLA) have become an important tool for data analysis in many different disciplines. Aims. In this work, we use MLA in an astrophysical context; our goal is to measure the mean longitudinal magnetic field in stars (H eff ) from polarized spectra of high resolution, through the inversion of the so-called multi-line profiles. Methods. Using synthetic data, we tested the performance of our technique considering different noise levels: In an ideal scenario of noise-free multi-line profiles, the inversion results are excellent; however, the accuracy of the inversions diminish considerably when noise is taken into account. In consequence, we propose a data pre-process in order to reduce the noise impact, which consists in a denoising profile process combined with an iterative inversion methodology. Results. Applying this data pre-process, we have found a considerable improvement of the inversions results, allowing to estimate the errors associated to the measurements of stellar magnetic fields at different noise levels. Conclusions. We have successfully applied our data analysis technique to two different stars, attaining by first time the measurement of H eff from multi-line profiles beyond the condition of line autosimilarity assumed by other techniques.

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Section: Caracterizing the Techniquementioning

confidence: 68%

Using machine learning algorithms to measure stellar magnetic fields

Ramírez-Vélez

Yáñez-Márquez²,

Cordova-Barbosa³

2018

A&A

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“…How does one convert the observed Stokes V signal into a local magnetic field density (strength)? This is a non-trivial question and, so far, was implicitly answered through the assumption of the weak-field approximation (Stenflo 1994;Carroll & Strassmeier 2014) from which we derive the effective and apparent longitudinal magnetic field. Due to the a. b.…”

Section: Image Robustnessmentioning

confidence: 99%

Warm and cool starspots with opposite polarities

Strassmeier

Carroll

Ilyin

2019

A&A

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Aims. We present a temperature and a magnetic-field surface map of the K2 subgiant of the active binary II Peg. Employed are high resolution Stokes IV spectra obtained with the new Potsdam Echelle Polarimetric and Spectroscopic Instrument (PEPSI) at the Large Binocular Telescope (LBT). Methods. Fourteen average line profiles are inverted using our iMap code. We have employed an iterative regularization scheme without the need of a penalty function and incorporate a physical 3D description of the surface field vector. The spectral resolution of our data is 130 000 which converts to 20 resolution elements across the disk of II Peg. Results. Our main result is that the temperature features on II Peg closely correlate with its magnetic field topology. We find a warm spot (350 K warmer with respect to the effective temperature) of positive polarity and radial field density of 1.1 kG coexisting with a cool spot (780 K cooler) of negative polarity of 2 kG. Several other cool features are reconstructed containing both polarities and with (radial) field densities of up to 2 kG. The largest cool spot is reconstructed with a temperature contrast of 550 K, an area of almost 10% of the visible hemisphere, and with a multipolar magnetic morphology. A meridional and an azimuthal component of the field of up to ±500 G is detected in two surface regions between spots with strong radial fields but different polarities. A force-free magnetic-field extrapolation suggests that the different polarities of cool spots and the positive polarity of warm spots are physically related through a system of coronal loops of typical height of ≈2 R⋆. While the Hα line core and its red-side wing exhibit variations throughout all rotational phases, a major increase of blue-shifted Hα emission was seen for the phases when the warm spot is approaching the stellar central meridian indicating high-velocity mass motion within its loop. Conclusions. Active stars such as II Peg can show coexisting cool and warm spots on the surface that we interpret resulting from two different formation mechanisms. We explain the warm spots due to photospheric heating by a shock front from a siphon-type flow between regions of different polarities while the majority of the cool spots is likely formed due to the expected convective suppression like on the Sun.

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“…The mean longitudinal magnetic field is the line-of-sight magnetic field component integrated over the stellar disk. Following Carroll & Strassmeier (2014), an estimate of this quantity can be calculated directly from the LSD line profile:…”

Section: Circular Spectropolarimetrymentioning

confidence: 99%

The rotationally modulated polarization of ξ Boo A

Cotton

Evensberget

Marsden

et al. 2018

Monthly Notices of the Royal Astronomical Society

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We have observed the active star ξ Boo A (HD 131156A) with high precision broadband linear polarimetry contemporaneously with circular spectropolarimetry. We find both signals are modulated by the 6.43 day rotation period of ξ Boo A. The signals from the two techniques are 0.25 out of phase, consistent with the broadband linear polarization resulting from differential saturation of spectral lines in the global transverse magnetic field. The mean magnitude of the linear polarization signal is ∼4 ppm/G but its structure is complex and the amplitude of the variations suppressed relative to the longitudinal magnetic field. The result has important implications for current attempts to detect polarized light from hot Jupiters orbiting active stars in the combined light of the star and planet. In such work stellar activity will manifest as noise, both on the time scale of stellar rotation, and on longer time scales -where changes in activity level will manifest as a baseline shift between observing runs.

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Detecting and quantifying stellar magnetic fields

Cited by 11 publications

References 57 publications

Using machine learning algorithms to measure stellar magnetic fields

Using machine learning algorithms to measure stellar magnetic fields

Warm and cool starspots with opposite polarities

The rotationally modulated polarization of ξ Boo A

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