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Found 2 papers, 1 papers with code
Compilation of product-formula Hamiltonian simulation via reinforcement learning
In some cases this order is fixed by the desire to minimise the error of approximation; when it is not the case, we propose that the order can be chosen to optimize compilation to a native quantum architecture.
Reinforcement learning for optimization of variational quantum circuit architectures
The study of Variational Quantum Eigensolvers (VQEs) has been in the spotlight in recent times as they may lead to real-world applications of near-term quantum devices.
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