From the 2 of 14 linked papers with an AI index.
14 papers
Spectrum Estimation is Almost as Hard as Tomography
Marco Fanizza, Ryan O'Donnell, Chirag Wadhwa
We study the sample complexity of estimating and testing fundamental unitarily invariant properties of unknown quantum states; namely, the tasks of spectrum estimation, von Neumann…
Bosonic quantum communication beyond the thermal threshold
Francesco Anna Mele, Giuseppe Catalano, Marco Fanizza +2
The paper proves that non‑Gaussian input states can achieve a positive quantum capacity for bosonic thermal attenuator channels in regimes where Gaussian inputs give zero coherent…
Optimal tomography of bosonic and fermionic Gaussian states
Senrui Chen, Marco Fanizza, Filippo Girardi +4
The paper determines the exact sample complexity for learning bosonic and fermionic Gaussian quantum states, showing that a number of copies scaling quadratically with the number o…
Complete entanglement detection using polynomial invariants
Thomas C. Fraser, Vjosa Blakaj, Roberto Rubboli +2
Existing methods for deciding whether a bipartite quantum state is separable or entangled typically fall into one of two categories: they are either complete but require access to…
Random Stinespring superchannel: converting channel queries into dilation isometry queries
Filippo Girardi, Francesco Anna Mele, Haimeng Zhao +2
The recently introduced random purification channel, which converts copies of an arbitrary mixed quantum state into copies of the same uniformly random purification, has em…
Convex combinations of bosonic pure-loss channels
Giuseppe Catalano, Marco Fanizza, Francesco Anna Mele +2
The pure-loss channel is a fundamental model for describing noise in bosonic quantum platforms. It is characterised by a single parameter, the transmissivity, which quantifies the…