Transient behaviour of three SU UMa-type dwarf novae: AR Pic, QW Ser, and V521 Peg

Abstract

Changes in the supercycle lengths of some SU UMa-type dwarf novae have been detected by other studies, and indicate that the mass transfer rates noticeably decrease over time. We investigated the supercycle lengths of three SU UMa-type dwarf novae: AR Pic, QW Ser, and V521 Peg, to determine if they have detectable changes in their supercycles. We present the results of optical spectroscopic and photometric observations of these sources. Our observations were conducted in 2016 and 2017 at the Boyden Observatory and the Sutherland station of the South African Astronomical Observatory. The quiescent results indicated that all three sources are typical SU UMa-type dwarf novae. We also present results of AR Pic and QW Ser in outburst and of V521 Peg during a precursor outburst and superoutburst. Light curves were supplemented by the Catalina Real-Time Transient Survey, the ASAS-3 and ASAS-SN archives, and the AAVSO International Database in order to investigate the long-term behaviour of these sources. Our results combined with catalogued properties for all short-period dwarf novae show a possible relationship between the supercycle time in SU UMa systems and their orbital periods, which is interpreted as the decline in the mass transfer rate as systems evolve towards and away from the ‘period minimum’. At the shortest orbital periods, SU UMa systems are almost indistinguishable from WZ Sge systems. However, we propose that the scaleheight between the secondary’s photosphere and L1 may be a factor that distinguish the SU UMa subclasses.

Machine learning-based search for cataclysmic variables within Gaia Science Alerts

“…This data should provide the necessary information to identify subclasses within the CV population and pick out rare varieties that further our understanding of binary evolution. For example, the ∼2 day cadence provides the sampling necessary to recognise the defining characteristics of DNe subtypes, such as the superoutbursts of SU UMa systems (e.g., Szegedi et al 2022) and the standstills of Z Cam systems (Simonsen et al 2014); and identify characteristics present in outbursting AM CVns, such as the short duration rebrightenings on the fading tail of a superoutburst (Kato & Kojiguchi 2021). Our ability to automatically distinguish between the different CV subtypes will depend upon several factors, one of which is the quality of features.…”