Nikolay Walters | Searcharxiv

arXiv2026

The Complex Magnetic Anatomy of a White Dwarf Chromosphere

This study presents phase-resolved spectroscopy and spectropolarimetry of the DAHe white dwarf LP 705-64. Here, two apparently discrete chromospheric regions are observed to alternate in visibility and magnetic polarity with rotation, with field strengths of 9.5 and 22 MG based on the measured Zeeman splitting in Hα. As in the class prototype GD 356, emission line equivalent widths vary in antiphase with the broadband light curve. The 9.5 MG field is visible for 60 per cent of the stellar rotation and stays nearly constant, whereas the 22 MG field increases modestly during the remaining phases. Notably, the time-series transitions between magnetic regions are abrupt and transit-like in morphology, requiring at least one magnetic region to be highly localised and significantly smaller than the areas inferred for the dark surface spots. Both the intensity and the Stokes V/I spectra indicate a field configuration significantly more complex than an offset dipole, but higher-cadence data are necessary to distinguish between a global field and localised magnetic regions. All data are consistent with magnetic, chromospheric, and dark surface regions that are co-located and thus physically related. These findings support a model of chromospheric emission that is intrinsic and localised, consistent with predictions of dynamo-driven electrical currents that heat the upper atmosphere near magnetic poles.

astro-ph.SR↗

arXiv2021

White dwarfs identified in LAMOST Data Release 5

In this paper, we report white dwarfs identified in the 5th Data Release of the Large Area Multi-Object fibre Spectroscopic Telescope, including spectral types of DA, DB, DC, DZ, and so on. There are 2 625 DA spectra of 2 281 DA stars, 182 DB spectra of 166 DB stars, 62 DC spectra of 58 DC stars, 36 DZ spectra of 33 DZ stars and many other types identified, in addition to our previous paper (Data Release 2). Among those sources, 393 DA stars and 46 DB stars are new identifications after cross-matching with the literature. In order to select DA candidates, we use the classification result from the LAMOST pipeline, colour-colour cut method and a random forest machine learning method. For DBs, since there is no template for DB in the pipeline model, a random forest machine learning method is chosen to select candidates. All the WD candidates have been visually checked individually. The parameters of effective temperature, surface gravity, mass, and cooling age have been estimated for relatively high signal-to-noise ratio DAs and DBs. The peaks of the DA and DB mass distributions are found to be around 0.62Msun and 0.65Msun, respectively. Finally, the data and method we used to select white dwarf candidates for the second phase of LAMOST survey are also addressed in this paper.

astro-ph.SR↗