Comparison of fault-tolerant thresholds for planar qudit geometries






We introduce and analyze a new type of decoding algorithm called General Color Clustering (GCC), based on renormalization group methods, to be used in qudit color codes. The performance of this decoder is analyzed under depolarizing and generalized bit flip noise models, and is used to obtain the first fault-tolerant threshold estimates for qudit 6-6-6 color codes. The proposed decoder is compared with similar decoding schemes for qudit surface codes as well as the current leading qubit decoders for both sets of codes…

Examining the Effects of Simplified Neural Net Structure on Jet Identification





The summer after my freshman year at Yale, I worked under Tobias Golling in the Yale ATLAS High Energy Research Group. At CERN, particles are accelerated and collided in the Large Hadron Collider (LHC), forming “jets” of subatomic particles. In these collision events, each particle gives off unique signatures, which are measured by calorimeters, spectrometers, and magnets in the detector. Continue reading “Examining the Effects of Simplified Neural Net Structure on Jet Identification”