249 citations · 670 across the 6 of their papers we have counts for
6 papers
Parallel quantum trajectories via forking for sampling without redundancy
Daniel K. Park, Ilya Sinayskiy, Mark Fingerhuth +2
The computational cost of preparing a quantum state can be substantial depending on the structure of data to be encoded. Many quantum algorithms require repeated sampling to find t…
Molecular Docking with Gaussian Boson Sampling
Leonardo Banchi, Mark Fingerhuth, Tomas Babej +2
Gaussian Boson Samplers are photonic quantum devices with the potential to perform tasks that are intractable for classical systems. As with other near-term quantum technologies, a…
Open source software in quantum computing
Mark Fingerhuth, Tomáš Babej, Peter Wittek
Open source software is becoming crucial in the design and testing of quantum algorithms. Many of the tools are backed by major commercial vendors with the goal to make it easier t…
Coarse-grained lattice protein folding on a quantum annealer
Tomáš Babej, Christopher Ing, Mark Fingerhuth
Lattice models have been used extensively over the past thirty years to examine the principles of protein folding and design. These models can be used to determine the conformation…
A quantum alternating operator ansatz with hard and soft constraints for lattice protein folding
Mark Fingerhuth, Tomáš Babej, Christopher Ing
Gate-based universal quantum computers form a rapidly evolving field of quantum computing hardware technology. In previous work, we presented a quantum algorithm for lattice protei…
Implementing a distance-based classifier with a quantum interference circuit
Maria Schuld, Mark Fingerhuth, Francesco Petruccione
Lately, much attention has been given to quantum algorithms that solve pattern recognition tasks in machine learning. Many of these quantum machine learning algorithms try to imple…