We present X-ray and spectropolarimetric observations of the WN+O binaries WR71 and WR97, which are analogs of the well-studied V444 Cygni. The combined results have the potential to constrain the locations and properties of wind interaction regions in these binaries, give clues to their subsequent evolution, and address the commonalities among WR+O systems.

The emission line spectra of WR stars are often formed completely in the optically thick stellar wind. Hence, any assumption on the wind velocity law in a spectral analysis has a profound impact on the determination of the stellar parameters. By comparing Potsdam Wolf-Rayet (PoWR) model spectra calculated with different β laws, we show that the velocity field heavily influences the spectra: by using the appropriate β laws, the entire range of late and early types can be covered with the same stellar model.

Next-generation spectro-polarimetric broadband surveys will probe cosmic magnetic fields in unprecedented detail, using the magneto-optical effect known as Faraday rotation. However, non-parametric methods such as RMCLEAN can introduce non-observable linearly polarised flux into a fitted model at negative wavelengths squared. This leads to Faraday rotation structures that are consistent with the observed data, but would be impossible or difficult to measure. We construct a convex non-parametric QU-fitting algorithm to constrain the flux at negative wavelengths squared to be zero. This allows the algorithm to recover structures that are limited in complexity to the observable region in wavelength squared. We verify this approach on simulated broadband data sets where we show that it has a lower root mean square error and that it can change the scientific conclusions for real observations. We advise using this prior in next-generation broadband surveys that aim to uncover complex Faraday depth structures. We provide a public Python implementation of the algorithm at https://github.com/Luke-Pratley/Faraday-Dreams.

Faraday complexity describes whether a spectropolarimetric observation has simple or complex magnetic structure. Quickly determining the Faraday complexity of a spectropolarimetric observation is important for processing large, polarised radio surveys. Finding simple sources lets us build rotation measure grids, and finding complex sources lets us follow these sources up with slower analysis techniques or further observations. We introduce five features that can be used to train simple, interpretable machine learning classifiers for estimating Faraday complexity. We train logistic regression and extreme gradient boosted tree classifiers on simulated polarised spectra using our features, analyse their behaviour, and demonstrate our features are effective for both simulated and real data. This is the first application of machine learning methods to real spectropolarimetry data. With 95% accuracy on simulated ASKAP data and 90% accuracy on simulated ATCA data, our method performs comparably to state-of-the-art convolutional neural networks while being simpler and easier to interpret. Logistic regression trained with our features behaves sensibly on real data and its outputs are useful for sorting polarised sources by apparent Faraday complexity.

We develop a polarimetry-based remote-sensing method for detecting and identifying life forms in distant worlds and distinguishing them from non-biological species. To achieve this we have designed and built a bio-polarimetric laboratory experiment BioPol for measuring optical polarized spectra of various biological and non-biological samples. Here we focus on biological pigments, which are common in plants and bacteria that employ them either for photosynthesis or for protection against reactive oxygen species. Photosynthesis, which provides organisms with the ability to use light as a source of energy, emerged early in the evolution of life on Earth. The ability to harvest such a significant energy resource could likely also develop on habited exoplanets. Thus, we investigate the detectability of biomolecules that can capture photons of particular wavelengths and contribute to storing their energy in chemical bonds. We have carried out laboratory spectropolarimetric measurements of a representative sample of plants containing various amounts of pigments such as chlorophyll, carotenoids and others. We have also measured a variety of non-biological samples (sands, rocks). Using our lab measurements, we have modelled intensity and polarized spectra of Earth-like planets having different surface coverage by photosynthetic organisms, deserted land and ocean, as well as clouds. Our results demonstrate that linearly polarized spectra provide very sensitive and rather unambiguous detection of photosynthetic pigments of various kinds. Our work paves the path towards analogous measurements of microorganisms and remote sensing of microbial ecology on the Earth and of extraterrestrial life on other planets and moons.

A limited list of new results of the searches for the new magnetic stars among late B and early A stars is in this work. Continual observations with spectroscopic devices of the 6m Russian telescope BTA led to successful detection of about 10 new magnetic stars that occupy different parts of evolutional tracks for the stars of 2–3 solar masses. Measurements of the longitudinal magnetic field show weak and medium strength magnetic field in all program stars.

We present the preliminary results of the measurements of longitudinal magnetic field of the massive white dwarf 1658+441. This star have an hydrogen pure atmosphere (e.g. Dupuis & Chayer, 2003). We have observed the target in a total of 18 hrs during 3 consecutive nights in June 2010 and one more in May 2011. The data was acquired with a prototypical spectropolarimeter at the San Pedro Martir Telescope in Mexico. We have tested the magnetic field measurements with our instrument using the famous Babcock's star obtaining consistent results with previous studies. For our object of study, the WD 1658+441, we have measured variable intensities of the longitudinal magnetic field of Blong = 720 kG that oscillates with an amplitude of 130 kG.

Using spectropolarimetric data acquired with the ESPaDOnS and NARVAL instruments at CFHT and at TBL, we present a detailed spectral synthesis analysis of HD 232 862, a field giant classified as a G8II star hosting a magnetic field. This star is the first lithium-rich field giant hosting a magnetic field. Stellar evolution models suggest that HD 232 862 should be a 1.5 to 2.0 M⊙ star at the bottom of the red giant branch. Its unsually high lithium content (A(Li) = 2.45 ± 0.25 dex) is even more puzzling and challenges our understanding of the evolution of this star.