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
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
Files
(2.6 MB)
| Name | Size | |
|---|---|---|
|
data.zip
md5:ccc64a55e3f4533dfb73802e4d06129a |
2.5 MB | Download |
|
DataUpload.pdf
md5:c13f945561bff1253178e62fcce620fe |
58.7 kB | Download |
- Publication date:
- October 6, 2025
- DOI:
-
- Keyword(s):
- Computational Fluid Dynamics Variational Quantum Algorithms Non-Unitary Operators Quantum Computing
- Related identifiers:
- Supplement to:
https://arxiv.org/abs/2502.04425 - Communities:
- License (for files):
- Creative Commons Attribution 4.0 International