Improved variational quantum eigensolver via quasi-dynamical evolution
Manpreet Singh Jattana, Fengping Jin, Hans De Raedt, Kristel, Michielsen

TL;DR
This paper introduces an enhanced variational quantum eigensolver (VQE) that incorporates a quasi-dynamical evolution inspired by quantum annealing, improving ground state energy estimation on near-term quantum devices and scaling towards quantum advantage.
Contribution
It proposes a novel heuristic supplementing VQE with quasi-dynamical evolution, enabling efficient initial state preparation and better scaling for larger quantum systems.
Findings
Avoids barren plateaus and local minima
Works with low-depth circuits
Enables estimation beyond 50 qubits
Abstract
The variational quantum eigensolver (VQE) is a hybrid quantum-classical algorithm designed for current and near-term quantum devices. Despite its initial success, there is a lack of understanding involving several of its key aspects. There are problems with VQE that forbid a favourable scaling towards quantum advantage. In order to alleviate the problems, we propose and extensively test a quantum annealing inspired heuristic that supplements VQE. The improved VQE enables an efficient initial state preparation mechanism, in a recursive manner, for a quasi-dynamical unitary evolution. We conduct an in-depth scaling analysis of finding the ground state energies with increasing lattice sizes of the Heisenberg model, employing simulations of up to qubits that manipulate the complete state vector. For the current devices, we further propose a benchmarking toolkit using a mean-field model…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Quantum Information and Cryptography · Quantum and electron transport phenomena
