112 citations · 985 across the 32 of their papers we have counts for
5 papers · 1 filter
Reinforcement learning of quantum circuit architectures for molecular potential energy curves
Maureen Krumtünger, Alissa Wilms, Paul K. Faehrmann +4
Quantum chemistry and optimization are two of the most prominent applications of quantum computers. Variational quantum algorithms have been proposed for solving problems in these…
Digitized Counterdiabatic Quantum Sampling
Narendra N. Hegade, Nachiket L. Kortikar, Balaganchi A. Bhargava +9
We propose digitized counterdiabatic quantum sampling (DCQS), a hybrid quantum-classical algorithm for efficient sampling from energy-based models, such as low-temperature Boltzman…
Speeding up thermalization and quantum state preparation through engineered quantum collisions
Sofia Sgroi, Salvatore Lorenzo, Luca Innocenti +3
We realize fast thermalization and state preparation of a single mode cavity field using a collision model-like approach, where a sequence of qubits or three level system ancillae,…
Partitioning the electronic wave function using deep variational Monte Carlo
Matěj Mezera, Paolo A. Erdman, Zeno Schätzle +2
We propose a novel wave function partitioning method that integrates deep-learning variational Monte Carlo with ansätze based on generalized product functions. This approach effect…
Deep quantum Monte Carlo approach for polaritonic chemistry
Yifan Tang, Gian Marcello Andolina, Alica Cuzzocrea +5
Recent years have witnessed a surge of experimental and theoretical interest in controlling the properties of matter, such as its chemical reactivity, by confining it in optical ca…