5 papers
Quantum Lattice Boltzmann with Denoising Collision Operators
Trong Duong, Matthias Möller, Norbert Hosters
The Lattice Boltzmann method (LBM) is a well-established mesoscopic approach for simulating fluid dynamics by evolving particle distribution functions on discrete lattices. While t…
Performance Comparison of Gate-Based and Adiabatic Quantum Computing for AC Power Flow Problem
Zeynab Kaseb, Matthias Moller, Peter Palensky +1
We present the first direct comparison between gate-based quantum computing (GQC) and adiabatic quantum computing (AQC) paradigms for solving the AC power flow (PF) equations. The…
Power flow and optimal power flow using quantum and digital annealers: a computational scalability analysis
Zeynab Kaseb, Matthias Moller, Pedro P. Vergara +1
This study further explores reformulating power flow (PF) analysis as a discrete combinatorial optimization problem, proposed in our earlier study using the Adiabatic Quantum Power…
A Framework for Solving Continuous Energy and Power System Problems using Adiabatic Quantum Computing
Zeynab Kaseb, Matthias Moller, Peter Palensky +1
The increasing scale and nonlinearity of modern energy and power system problems pose significant challenges to classical numerical solvers. In parallel, advances in quantum and qu…
NN-AE-VQE: Neural network parameter prediction on autoencoded variational quantum eigensolvers
Koen Mesman, Yinglu Tang, Matthias Moller +2
A longstanding computational challenge is the accurate simulation of many-body particle systems. Especially for deriving key characteristics of high-impact but complex systems such…