David Wierichs
David Wierichs
Quantum Scientist, Xanadu Quantum Technologies
Verified email at
Cited by
Cited by
General parameter-shift rules for quantum gradients
D Wierichs, J Izaac, C Wang, CYY Lin
Quantum 6, 677, 2022
Avoiding local minima in variational quantum eigensolvers with the Natural gradient optimizer
D Wierichs, C Gogolin, M Kastoryano
Physical Review Research 2 (2), 043246, 2020
Training quantum embedding kernels on near-term quantum computers
T Hubregtsen, D Wierichs, E Gil-Fuster, PJHS Derks, PK Faehrmann, ...
Physical Review A 106 (4), 042431, 2022
Local, Expressive, Quantum-Number-Preserving VQE Ansatze for Fermionic Systems
GL Anselmetti, D Wierichs, C Gogolin, RM Parrish
New Journal of Physics, 2021
Demonstration of coupling correction below the per-mil limit in the LHC
EH Maclean, DA Wierichs, PK Skowronski, R Tomas Garcia, S Fartoukh, ...
Suppression of Amplitude dependent closest tune approach and first tests of the ADT as an AC-dipole (MD 1412)
THB Persson, EH Maclean, DA Wierichs, R Tomas Garcia, M Gasior, ...
Backpropagation scaling in parameterised quantum circuits
J Bowles, D Wierichs, CY Park
arXiv preprint arXiv:2306.14962, 2023
Here comes the SU (N): multivariate quantum gates and gradients
R Wiersema, D Lewis, D Wierichs, J Carrasquilla, N Killoran
Quantum 8, 1275, 2024
Symmetric derivatives of parametrized quantum circuits
D Wierichs, RDP East, M Larocca, M Cerezo, N Killoran
arXiv preprint arXiv:2312.06752, 2023
Rocky Raccoon: Automated quantum circuit optimization using graph-based deep reinforcement learning
A Abhishek, O Di Matteo, D Wierichs, N Killoran
Bulletin of the American Physical Society, 2024
Estimation of gradients and analysis of gradient-based optimizers for variational quantum algorithms
D Wierichs
Universität zu Köln, 2023
The system can't perform the operation now. Try again later.
Articles 1–11