Quantum algorithms for quantum dynamics: A performance study on the spin-boson model
Alexander Miessen, Pauline J. Ollitrault, Ivano Tavernelli

TL;DR
This study evaluates the efficiency and scalability of variational quantum algorithms for simulating quantum dynamics, specifically the spin-boson model, comparing them to traditional Trotter-based methods under realistic noise conditions.
Contribution
It provides a detailed performance assessment of a variational quantum algorithm for quantum dynamics, including noise effects and system size scaling, and offers insights into their potential and limitations.
Findings
Variational algorithms show good accuracy with a physically motivated ansatz.
They reduce quantum gate costs compared to Trotter methods.
Current implementations are unlikely to achieve quantum advantage for time-dependent problems.
Abstract
Quantum algorithms for quantum dynamics simulations are traditionally based on implementing a Trotter-approximation of the time-evolution operator. This approach typically relies on deep circuits and is therefore hampered by the substantial limitations of available noisy and near-term quantum hardware. On the other hand, variational quantum algorithms have become an indispensable alternative, enabling small-scale simulations on present-day hardware. However, despite the recent development of variational quantum algorithms for quantum dynamics, a detailed assessment of their efficiency and scalability is yet to be presented. To fill this gap, we applied a variational quantum algorithm based on McLachlan's principle to simulate the dynamics of a spin-boson model subject to varying levels of realistic hardware noise as well as in different physical regimes, and discuss the algorithm's…
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