Quantum Recurrent Architectures for Text Classification

Wenduan Xu, Douglas Brown, Gabriel Matos, Konstantinos Meichanetzidis

Abstract:

We develop quantum RNNs with cells based on
Parametrised Quantum Circuits (PQCs). PQCs
can provide a form of hybrid quantum-classical
computation where the input and the output
is in the form of classical data. The previous
“hidden” state is the quantum state from the previous time-step, and an angle encoding is used
to define a (non-linear) mapping from a classical word embedding into the quantum Hilbert
space. Measurements of the quantum state provide classical statistics which are used for classification. We report results which are competitive with various RNN baselines on the Rotten
Tomatoes dataset, as well as emulator results
which demonstrate the feasibility of running
such models on quantum hardware.