6 papers
Quantum relative entropy for unravelings of master equations
Marcos Ruibal Ortigueira, Robert de Keijzer, Luke Visser +2
This work explores connections between the quantum relative entropy of two faithful states (i.e. full-rank density matrices) and the Kullback-Leibler divergences of classic…
Evolution of Gaussians in the Hellinger-Kantorovich-Boltzmann gradient flow
Matthias Liero, Alexander Mielke, Oliver Tse +1
This study leverages the basic insight that the gradient-flow equation associated with the relative Boltzmann entropy, in relation to a Gaussian reference measure within the Hellin…
Consensus-based qubit configuration optimization for variational algorithms on neutral atom quantum systems
Robert de Keijzer, Luke Visser, Oliver Tse +1
In this work, we report an algorithm that is able to tailor qubit interactions for individual variational quantum algorithm problems. Here, the algorithm leverages the unique abili…
Variational method for learning Quantum Channels via Stinespring Dilation on neutral atom systems
L. Y. Visser, R. J. P. T. de Keijzer, O. Tse +1
Real-world quantum systems interact with their environments, leading to the irreversible dynamics described by the Lindblad equation. Solutions to the Lindblad equation give rise t…
Fidelity-Enhanced Variational Quantum Optimal Control
Robert de Keijzer, Luke Visser, Oliver Tse +1
Creating robust quantum operations is a major challenge in the current noisy intermediate-scale quantum computing era. Recently, the importance of noise-resilient control methods h…
Accelerating optimization over the space of probability measures
Shi Chen, Qin Li, Oliver Tse +1
The acceleration of gradient-based optimization methods is a subject of significant practical and theoretical importance, particularly within machine learning applications. While m…