Vedran Dunjko

Quantum agents in the Gym: a variational quantum algorithm for deep Q-learning

2021 · arXiv (Cornell University)

Quantum machine learning (QML) has been identified as one of the key fields that could reap advantages from near-term quantum devices, next to optimization and quantum chemistry. Research in this area has focused primarily on …

Approximation and Generalization Capacities of Parametrized Quantum Circuits for Functions in Sobolev Spaces

2023 · arXiv (Cornell University)

Parametrized quantum circuits (PQC) are quantum circuits which consist of both fixed and parametrized gates. In recent approaches to quantum machine learning (QML), PQCs are essentially ubiquitous and play the role analogous to classical neural …

Compilation of product-formula Hamiltonian simulation via reinforcement learning

2023 · arXiv (Cornell University)

Hamiltonian simulation is believed to be one of the first tasks where quantum computers can yield a quantum advantage. One of the most popular methods of Hamiltonian simulation is Trotterization, which makes use of the …

Trainability maximization using estimation of distribution algorithms assisted by surrogate modelling for quantum architecture search

2024 · EPJ Quantum Technology

Abstract Quantum architecture search (QAS) involves optimizing both the quantum parametric circuit configuration but also its parameters for a variational quantum algorithm. Thus, the problem is known to be multi-level as the performance of a …