The Born Supremacy: Quantum Advantage and Training of an Ising Born Machine

Understand

The search for an application of near-term quantum devices is widespread.

• Quantum Machine Learning is touted as a potential utilisation of such devices, particularly those which are out of the reach of the simulation capabilities of classical computers.
• In this work, we propose a generative Quantum Machine Learning Model, called the Ising Born Machine (IBM), which we show cannot, in the worst case, and up to suitable notions of error, be simulated efficiently by a classical device.
• We also show this holds for all the circuit families encountered during training.