We have mapped the 12 CO(3-2) line emission around the Mira AB system at 0. 5 resolution using the Atacama Large Millimeter/submillimeter Array (ALMA). The CO map shows amazing complexity. The circumstellar gas has been shaped by different dynamical actors during the evolution of the system, and several morphological components can be identified. The companion is marginally resolved in continuum emission and is currently at 0. 487 ± 0. 006 separation. In the main line component, centered on the stellar velocity, spiral arcs around Mira A are found. The spiral appears to be relatively flat and oriented in the orbital plane. An accretion wake behind the companion is clearly visible, and the projected arc separation is about 5 . In the blue wing of the line emission, offset from the main line, several large (∼5-10 ) opposing arcs are found. We tentatively suggest that this structure is created by the wind of Mira B blowing a bubble in the expanding envelope of Mira A.
In this second paper in a series of papers based on the most-up-to-date catalogue of symbiotic stars (SySts), we present a new approach for identifying and distinguishing SySts from other H α emitters in photometric surveys using machine learning algorithms such as classification tree, linear discriminant analysis, and K-nearest neighbour. The motivation behind of this work is to seek for possible colour indices in the regime of near-and mid-infrared covered by the 2MASS and WISE surveys. A number of diagnostic colour-colour diagrams are generated for all the known Galactic SySts and several classes of stellar objects that mimic SySts such as planetary nebulae, post-AGB, Mira, single K and M giants, cataclysmic variables, Be, AeBe, YSO, weak and classical T Tauri stars, and Wolf-Rayet. The classification tree algorithm unveils that primarily J-H, W1-W4 and K s -W3 and secondarily H-W2, W1-W2 and W3-W4 are ideal colour indices to identify SySts. Linear discriminant analysis method is also applied to determine the linear combination of 2MASS and AllWISE magnitudes that better distinguish SySts. The probability of a source being a SySt is determined using the K-nearest neighbour method on the LDA components. By applying our classification tree model to the list of candidate SySts (Paper I), the IPHAS list of candidate SySts, and the DR2 VPHAS+ catalogue, we find 125 (72 new candidates) sources that pass our criteria while we also recover 90 per cent of the known Galactic SySts.
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