Work

Continuous variable quantum perceptron

Year: 2019

Type: article

Abstract: We present a model of Continuous Variable Quantum Perceptron (CVQP), also referred to as neuron in the following, whose architecture implements a classical perceptron. The necessary nonlinearity is obtained via measuring the output qubit and using the measurement outcome as input to an activation function. The latter is chosen to be the so-called Rectified linear unit (ReLu) activation function by virtue of its practical feasibility and the advantages it provides in learning tasks. The encoding of classical data into realistic finitely squeezed states and the use of superposed (entangled) input states for specific binary problems are discussed.

Source: International Journal of Quantum Information

DOI: 10.1142/s0219749919410090

Authors: F. Benatti, S. Mancini, S. Mangini

Institutions: University of Trieste, Istituto Nazionale di Fisica Nucleare, Sezione di Trieste, Università di Camerino, Istituto Nazionale di Fisica Nucleare, Sezione di Perugia

Language: English

Topic: Quantum Computing Algorithms and Architecture

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W2990893027

FWCI: 0.344

Cites: 13

Cited by: 10

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