首页|Reports on Machine Learning Findings from State University of New York (SUNY) Bu ffalo Provide New Insights (Optimized higherorder photon state classification b y machine learning)
Reports on Machine Learning Findings from State University of New York (SUNY) Bu ffalo Provide New Insights (Optimized higherorder photon state classification b y machine learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Data detailed on artificial intelligen ce have been presented. According to news originating from Buffalo, New York, by NewsRx correspondents, research stated, "The classification of higher-order pho ton emission becomes important with more methods being developed for determinist ic multiphoton generation." Our news journalists obtained a quote from the research from State University of New York (SUNY) Buffalo: "The widely used second-order correlation g(2) is not sufficient to determine the quantum purity of higher photon Fock states. Traditi onal characterization methods require a large amount of photon detection events, which leads to increased measurement and computation time. Here, we demonstrate a machine learning model based on a 2D Convolutional Neural Network (CNN) for r apid classification of multiphoton Fock states up to |3 with an overAll accuracy of 94%."
State University of New York (SUNY) Buff aloBuffaloNew YorkUnited StatesNorth and Central AmericaCyborgsEmerg ing TechnologiesMachine Learning
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