Preparing the ground state of a Hamiltonian is a problem of great significance in physics with deep implications in combinatorial optimization. While the quantum adiabatic algorithm (QAA) is known to return the ground state for sufficiently long preparation times, the decoherence times of noisy, intermediate-scale quantum devices render the QAA infeasible. Variational approaches such as the quantum approximate optimization algorithm sparked intensive research interest, however, optimization of a multiparameter cost function requires billions of measurements already for a moderate number of qubits and can be prone to noise-induced barren plateaus, thus forsaking any practical quantum advantage. In our work, we aim at combining the strengths of the adiabatic and the variational approaches for fast and high-fidelity ground state preparation by keeping the number of measurements as low as possible, benchmarking our algorithm for a spin-1/2 transverse and longitudinal Ising chain (ZZXZ model) with N=100 sites. Our preliminary results already show a promising significant increase in the overlap with the ground state from 5.7% to 17.4% when compared to naive QAA for fixed total evolution time.

Faster adiabatic ground state preparation with few measurements in the NISQ era

QCQS-1: Quantum Computing and Quantum Simulation

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Quantum 2020

The Institute of Physics and IOP Publishing, in partnership with the Chinese Physical Society (CPS) and the University of Science and Technology of China (USTC) are proud to have brought together the international quantum science community online for this inaugural conference.

Early career and leading researchers from universities, industry and government worldwide came together to share, learn and collaborate on the latest research and emerging areas of high interest across quantum science and technology. 

Benjamin Schiffer

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Faster adiabatic ground state preparation with few measurements in the NISQ era

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