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The regions around the celestial poles offer the ability to find andcharacterize long-term variables from ground-based observatories. We usedmulti-year Evryscope data to search for high-amplitude (~5% or greater)variable objects among 160,000 bright stars (Mv < 14.5) near the SouthCelestial Pole. We developed a machine learning based spectral classifier toidentify eclipse and transit candidates with M-dwarf or K-dwarf host stars -and potential low-mass secondary stars or gas giant planets. The largeamplitude transit signals from low-mass companions of smaller dwarf host starslessens the photometric precision and systematics removal requirementsnecessary for detection, and increases the discoveries from long-termobservations with modest light curve precision. The Evryscope is a robotictelescope array that observes the Southern sky continuously at 2-minutecadence, searching for stellar variability, transients, transits around exoticstars and other observationally challenging astrophysical variables. In thisstudy, covering all stars 9 < Mv < 14.5, in declinations -75 to -90 deg, werecover 346 known variables and discover 303 new variables, including 168eclipsing binaries. We characterize the discoveries and provide the amplitudes,periods, and variability type. A 1.7 Jupiter radius planet candidate with alate K-dwarf primary was found and the transit signal was verified with thePROMPT telescope network. Further followup revealed this object to be a likelygrazing eclipsing binary system with nearly identical primary and secondary K5stars. Radial velocity measurements from the Goodman Spectrograph on the 4.1meter SOAR telescope of the likely-lowest-mass targets reveal that six of theeclipsing binary discoveries are low-mass (.06 - .37 solar mass) secondarieswith K-dwarf primaries, strong candidates for precision mass-radiusmeasurements.

Variables in the Southern Polar Region Evryscope 2016 Dataset