activity
20072023
most citedAnalysis of the emission of very small dust particles from Spitzer spectro-imagery data using blind signal separation methods

218 citations · 301 across the 17 of their papers we have counts for

collaborators

18 papers

quant-ph2023★ 2 cited

Unitary quantum process tomography with unreliable pure input states

François Verdeil, Yannick Deville

Quantum process tomography (QPT) methods aim at identifying a given quantum process. The present paper focuses on the estimation of a unitary process. This class is of particular i…

quant-ph2022★ 7 cited

Pure state tomography with parallel unentangled measurements

François Verdeil, Yannick Deville

Quantum state tomography (QST) aims at estimating a quantum state from averaged quantum measurements made on copies of the state. Most quantum algorithms rely on QST at some point…

quant-ph2022★ 2 cited

Beyond the density operator and Tr(ρA): Exploiting the higher-order statistics of random-coefficient pure states for quantum information processing

Yannick Deville, Alain Deville

Two types of states are widely used in quantum mechanics, namely (deterministic-coefficient) pure states and statistical mixtures. A density operator can be associated with each of…

quant-ph2022

Random-coefficient pure states, the density operator formalism and the Zeh problem

Alain Deville, Yannick Deville

Quantum electronics is significantly involved in the development of the field of quantum information processing. In this domain, the growth of Blind Quantum Source Separation and B…

quant-ph2021★ 1 cited

Statistical intrusion detection and eavesdropping in quantum channels with coupling: Multiple-preparation and single-preparation methods

Yannick Deville, Alain Deville, Ali Mansour +2

Classical, i.e. non-quantum, communications include configurations with multiple-input multiple-output (MIMO) channels. Some associated signal processing tasks consider these chann…

quant-ph2021★ 21 cited

Single-preparation unsupervised quantum machine learning: concepts and applications

Yannick Deville, Alain Deville

The term "machine learning" especially refers to algorithms that derive mappings, i.e. intput/output transforms, by using numerical data that provide information about considered t…