Variational Measurement-based Quantum Computation
Dr. Hendrik Poulsen Nautrup & Dr. Sofiène Jerbi (Universität Innsbruck Institut für Theoretische Physik)

Measurement-based quantum computation (MBQC) offers a fundamentally unique paradigm to design quantum algorithms. Indeed, due to the inherent randomness of quantum measurements, the natural operations in MBQC are not deterministic and unitary, but are rather augmented with probabilistic byproducts. Yet, the main algorithmic use of MBQC so far has been to completely counteract this probabilistic nature in order to simulate unitary computations expressed in the circuit model.

In this talk, we are going to introduce MBQC as an ansatz for parameterized learning models that embraces this inherent randomness and treat random byproducts in MBQC as a resource for computation. We demonstrate numerically, that such models can lead to significant gains in learning performance in certain generative modeling tasks. We finish with a proposal for an experimental implementation of such an MBQC-based learning model for shuttling-based ion traps.