Dataset Open Access
Pia Siegl;
Greta Sophie Reese;
Tomohiro Hashizume;
Nis-Luca van Hülst;
Dieter Jaksch
<?xml version='1.0' encoding='utf-8'?> <oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"> <dc:creator>Pia Siegl</dc:creator> <dc:creator>Greta Sophie Reese</dc:creator> <dc:creator>Tomohiro Hashizume</dc:creator> <dc:creator>Nis-Luca van Hülst</dc:creator> <dc:creator>Dieter Jaksch</dc:creator> <dc:date>2025-10-06</dc:date> <dc:description>We used a self-written Julia library to find unitary approximations of matrix product operators (MPO). We implemented the variational quantum algorithms in python, using pennylane, pyTorch and Jax. This dataset contains: - Unitaries that represent the MPO operators - Weights for all time steps parametrizing the solution of the linear Euler equation, the Burgers’ equation and the Advection-Diffusion equation. - Weights encoding the initial condition for the the Burgers’ equation and the Advection-Diffusion equation. - Data used for Fig.4, Fig.7 , Fig.8</dc:description> <dc:identifier>https://www.fdr.uni-hamburg.de/record/18010</dc:identifier> <dc:identifier>10.25592/uhhfdm.18010</dc:identifier> <dc:identifier>oai:fdr.uni-hamburg.de:18010</dc:identifier> <dc:language>eng</dc:language> <dc:relation>url:https://arxiv.org/abs/2502.04425</dc:relation> <dc:relation>doi:10.25592/uhhfdm.16775</dc:relation> <dc:rights>info:eu-repo/semantics/openAccess</dc:rights> <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights> <dc:subject>Computational Fluid Dynamics</dc:subject> <dc:subject>Variational Quantum Algorithms</dc:subject> <dc:subject>Non-Unitary Operators</dc:subject> <dc:subject>Quantum Computing</dc:subject> <dc:title>Dataset Tensor-Programmable Quantum Circuits for Solving Differential Equations</dc:title> <dc:type>info:eu-repo/semantics/other</dc:type> <dc:type>dataset</dc:type> </oai_dc:dc>