120 citations · 122 across the 5 of their papers we have counts for
5 papers
Molecular Design beyond Training Data with Novel Extended Objective Functionals of Generative AI Models Driven by Quantum Annealing Computer
Hayato Kunugi, Mohsen Rahmani, Yosuke Iyama +8
Deep generative modeling to stochastically design small molecules is an emerging technology for accelerating drug discovery and development. However, one major issue in molecular g…
Comparing Quantum Annealing and BF-DCQO
Pau Farré, Erika Ordog, Kevin Chern +1
Recent work [1] has claimed that a gate-model quantum-classical hybrid algorithm called bias-field digitized counterdiabatic quantum optimization (BF-DCQO) [2] outperforms D-Wave's…
Optimised Annealed Sequential Monte Carlo Samplers
Saifuddin Syed, Alexandre Bouchard-Côté, Kevin Chern +1
Annealed Sequential Monte Carlo (ASMC) samplers are special cases of SMC samplers where the sequence of distributions can be embedded in a smooth path of distributions. Using this…
A comment on comparing optimization on D-Wave and IBM quantum processors
Catherine C. McGeoch, Kevin Chern, Pau Farré +1
Recent work [Sachdeva et al.] presented an iterative hybrid quantum variational optimization algorithm designed by Q-CTRL and executed on IBM gate-based quantum processing units (Q…
Beyond-classical computation in quantum simulation
Andrew D. King, Alberto Nocera, Marek M. Rams +60
Quantum computers hold the promise of solving certain problems that lie beyond the reach of conventional computers. However, establishing this capability, especially for impactful…