6 citations · 14 across the 8 of their papers we have counts for
8 papers
Strengthening the quantum data processing inequality for maximal -divergences via unraveling
Marcos Ruibal Ortigueira, Robert de Keijzer, Luke Visser +2
Maximal -divergences, among them the Belavkin--Staszewski relative entropy, are non-increasing under completely positive trace-preserving maps, which is the quantum data process…
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…
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…
Qubit fidelity under stochastic Schrödinger equations driven by colored noise
Robert de Keijzer, Luke Visser, Oliver Tse +1
Environmental noise on a controlled quantum system is generally modeled by a dissipative Lindblad equation. This equation describes the average state of the system via the density…
Optimal control formulation of transition path problems for Markov Jump Processes
Yuan Gao, Jian-Guo Liu, Oliver Tse
We formulate the transition path problem for Markov jump processes as a stochastic optimal control problem on path space. Transitions between metastable sets are induced by an unbo…
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…
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…