Quantum Artificial Neural Network Model with Exponential Speedup | NextBigFuture.com

Researchers have proposed a model for perceptrons to be directly implemented on near-term quantum processing devices, and we have experimentally tested it on a 5-qubits IBM quantum computer based on superconducting technology. Our algorithm presents an exponential advantage over classical perceptron models, as we have explicitly shown by representing and classifying 4 bits strings using 2 qubits, and 16 bits strings using only 4 qubits. It might then be possible to design a version of our proposed quantum perceptron algorithm working with approximated encoding quantum states instead of exact ones, which would have the potential to scale exponentially better than The post Quantum Artificial Neural Network Model with Exponential Speedup appeared first on NextBigFuture.com.