1 citations · 1 across the 5 of their papers we have counts for
8 papers · 1 filter
Quantum machine learning models for graphs
Frédéric Sauvage, Pranav Kalidindi, Frederic Rapp +1
Geometric Machine Learning (GML) successes have been achieved through the thorough study and design of new equivariant neural networks. In comparison, geometric quantum machine lea…
Exact log-depth preparation of highly entangled matrix product states
Keisuke Murota, Frédéric Sauvage, Marco Ballarin +2
Preparing matrix product states (MPS) on a quantum device is a key subroutine in many quantum algorithms. The most competitive methods, based on the renormalisation group, prepare…
Unbiased Hamiltonian Simulation by Reversing Trotter Error Dynamics
Keisuke Murota, Yuta Kikuchi, Enrico Rinaldi +2
Owing to their simplicity and low overhead, Suzuki-Trotter formulas remain the de facto Hamiltonian simulation methods on current quantum computing platforms. Systematic Trotter er…
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…
More buck-per-shot: Why learning trumps mitigation in noisy quantum sensing
Aroosa Ijaz, C. Huerta Alderete, Frédéric Sauvage +3
Quantum sensing is one of the most promising applications for quantum technologies. However, reaching the ultimate sensitivities enabled by the laws of quantum mechanics can be a c…
Classical shadows with symmetries
Frederic Sauvage, Martin Larocca
Classical shadows (CS) have emerged as a powerful way to estimate many properties of quantum states based on random measurements and classical post-processing. In their original fo…