Dataset Open Access

Dataset Tensor-Programmable Quantum Circuits for Solving Differential Equations

Pia Siegl; Greta Sophie Reese; Tomohiro Hashizume; Nis-Luca van Hülst; Dieter Jaksch


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{"DOI":"10.25592/uhhfdm.18010","abstract":"<p>We used a self-written Julia library to find unitary approximations of</p>\n\n<p>matrix product operators (MPO). We implemented the variational quantum algorithms in python,</p>\n\n<p>using pennylane, pyTorch and Jax.</p>\n\n<p>&nbsp;</p>\n\n<p>This dataset contains:&nbsp;</p>\n\n<p>- Unitaries that represent the MPO operators</p>\n\n<p>- Weights for all time steps parametrizing the solution of the linear Euler equation, the Burgers&rsquo;</p>\n\n<p>&nbsp; equation and the Advection-Diffusion equation.</p>\n\n<p>- Weights encoding the initial condition for the the Burgers&rsquo; equation and the Advection-Diffusion&nbsp;</p>\n\n<p>&nbsp;&nbsp;&nbsp;equation.</p>\n\n<p>- Data used for Fig.4, Fig.7 , Fig.8</p>","author":[{"family":"Pia Siegl"},{"family":"Greta Sophie Reese"},{"family":"Tomohiro Hashizume"},{"family":"Nis-Luca van H\u00fclst"},{"family":"Dieter Jaksch"}],"id":"18010","issued":{"date-parts":[[2025,10,6]]},"language":"eng","title":"Dataset Tensor-Programmable Quantum Circuits for Solving Differential Equations","type":"dataset","version":"2"}

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