quant-ph · 2026-08-31 · No. 101
Quantum Physics, 2026-08-31.
1 new papers in quant-ph. Titles, authors,
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01 — The papers
1 entries-
01
Quantum Federated Learning Based on Bures--Uhlmann Geometry for Heterogeneous Noisy Clients
Haruki Emori, Masaki Uchihara, Yuuki Tokunaga
quant-ph · cs.LG
Quantum federated learning enables collaborative model training across quantum devices without sharing raw data, and it faces the data and hardware heterogeneity inherent to noisy quantum devices. Utilizing the quantum geometric tensor is a natural remedy, yet pure-state approaches and diagonal approximations discard the correlations that encode parameter incompatibility. To address this, we extend the parameter-space geometry to the mixed...
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