Tensor Network Based Efficient Quantum Data Loading of Images

Understand

Image-based data is a popular arena for testing quantum machine learning algorithms.

• A crucial factor in realizing quantum advantage for these applications is the ability to efficiently represent images as quantum states.
• Here we present a novel method for creating quantum states that approximately encode images as amplitudes, based on recently proposed techniques that convert matrix product states to quantum circuits.
• The numbers of gates and qubits in our method scale logarithmically in the number of pixels given a desired accuracy, which make it suitable for near term quantum computers.