3 papers
quant-ph2026
Learnt Attacks on Quantum Key Distribution under Channel Noise and Device Drift
Marcel Mordarski, Benjamin Gras, Abdelrahman Shehata +2
Quantum key distribution (QKD) links are provisioned from security analyses of stationary channels, whereas the devices that determine the channel drift between recalibrations. Whe…
quant-ph2026
Encryptability As a Coordinate Choice: Depth-One Homomorphic Federated Learning of Quantum Neural Networks
Marcel Mordarski, Nathan Mani, Arshad Patel +2
Encrypted training relies on keeping server-side updates low-degree. This constraint traditionally excludes models whose weights inhabit a compact Lie group (notably variational qu…
quant-ph2026
Quantitative Universal Approximation for Noisy Quantum Neural Networks
Lukas Gonon, Antoine Jacquier, Marcel Mordarski
We provide here a universal approximation theorem with precise quantitative error bounds for noisy quantum neural networks. We focus on applications to Quantitative Finance, where…