Quantum chip predicts time series with a feedback loop

Nearly four decades passed between the 1971 postulation of the memristor and its eventual demonstration in 2008. The memristor functions as the primary example of neuromorphic components due to its ability to retain memory through hysteresis, mirroring how synapses function in the human brain. This work explores integrating the memristor with quantum computing to create more efficient machine learning platforms. The implementation of a quantum reservoir computing system using single photon states marks a first for the field, according to work detailed in a recent publication. Researchers designed the device to update its internal phase via feedback based on measurements at one output mode. The reservoir’s output then undergoes processing by a linear regression model, calculating a weighted sum to produce a final result. To test the system’s efficacy, the team addressed four distinct tasks: predicting a smooth nonlinear function and forecasting three random time series, NARMA, Mackey-Glass and Santa…