activity
20092026
most citedQuantum machine learning in feature Hilbert spaces

1.8k citations · 7.8k across the 50 of their papers we have counts for

collaborators

50 papers

quant-ph2026

Classical shadows with arbitrary group representations

Maxwell West, Frederic Sauvage, Aniruddha Sen +6

Classical shadows (CS) has recently emerged as an important framework to efficiently predict properties of an unknown quantum state. A common strategy in CS protocols is to paramet…

quant-ph2026

Parameter-optimal unitary synthesis with flag decompositions

Korbinian Kottmann, David Wierichs, Guillermo Alonso-Linaje +1

We introduce the flag decomposition as a central tool for unitary synthesis. It lets us carve out a diagonal unitary with degrees of freedom in such a way that the remaining…

quant-ph2025

Unitary synthesis with optimal brick wall circuits

David Wierichs, Korbinian Kottmann, Nathan Killoran

We present quantum circuits with a brick wall structure using the optimal number of parameters and two-qubit gates to parametrize , and provide evidence that these circuit…

quant-ph2025

Recursive Cartan decompositions for unitary synthesis

David Wierichs, Maxwell West, Roy T. Forestano +2

Recursive Cartan decompositions (CDs) provide a way to exactly factorize quantum circuits into smaller components, making them a central tool for unitary synthesis. Here we present…

quant-ph2024★ 6 cited

Geometric Quantum Machine Learning with Horizontal Quantum Gates

Roeland Wiersema, Alexander F. Kemper, Bojko N. Bakalov +1

In the current framework of Geometric Quantum Machine Learning, the canonical method for constructing a variational ansatz that respects the symmetry of some group action is by for…

quant-ph2023★ 2 cited

Symmetric derivatives of parametrized quantum circuits

David Wierichs, Richard D. P. East, Martín Larocca +2

Symmetries are crucial for tailoring parametrized quantum circuits to applications, due to their capability to capture the essence of physical systems. In this work, we shift the f…