%0 Journal Article
%J Physical Review X
%D 2019
%T Unsupervised Classification of Quantum Data
%A Sentís, Gael
%A Monras, Alex
%A Muñoz-Tapia, Ramon
%A Calsamiglia, John
%A Bagan, Emilio
%B Physical Review X
%V 9
%P 041029
%8 Jan-11-2019
%U https://link.aps.org/doi/10.1103/PhysRevX.9.041029http://harvest.aps.org/v2/journals/articles/10.1103/PhysRevX.9.041029/fulltexthttps://link.aps.org/article/10.1103/PhysRevX.9.041029
%! Phys. Rev. X
%R 10.1103/PhysRevX.9.041029
%0 Journal Article
%J Physical Review Letters
%D 2018
%T Duality Games and Operational Duality Relations
%A Bagan, Emilio
%A Calsamiglia, John
%A Bergou, János A.
%A Hillery, Mark
%B Physical Review Letters
%V 120
%8 Jan-01-2018
%U https://link.aps.org/doi/10.1103/PhysRevLett.120.050402http://harvest.aps.org/v2/journals/articles/10.1103/PhysRevLett.120.050402/fulltexthttps://link.aps.org/article/10.1103/PhysRevLett.120.050402
%! Phys. Rev. Lett.
%R 10.1103/PhysRevLett.120.050402
%0 Journal Article
%J Journal of Physics A: Mathematical and Theoretical
%D 2018
%T A generalized wave-particle duality relation for finite groups
%A Bagan, Emilio
%A Calsamiglia, John
%A Bergou, János A
%A Hillery, Mark
%B Journal of Physics A: Mathematical and Theoretical
%V 51
%P 414015
%8 Dec-10-2018
%! J. Phys. A: Math. Theor.
%R 10.1088/1751-8121/aabb21
%0 Journal Article
%J Physical Review Letters
%D 2017
%T Discrimination Power of a Quantum Detector
%A Hirche, Christoph
%A Hayashi, Masahito
%A Bagan, Emilio
%A Calsamiglia, John
%B Physical Review Letters
%V 118
%8 Jan-04-2017
%U http://link.aps.org/doi/10.1103/PhysRevLett.118.160502http://harvest.aps.org/v2/journals/articles/10.1103/PhysRevLett.118.160502/fulltexthttp://link.aps.org/article/10.1103/PhysRevLett.118.160502
%! Phys. Rev. Lett.
%R 10.1103/PhysRevLett.118.160502
%0 Journal Article
%J Physical Review Letters
%D 2016
%T Quantum Change Point
%A Sentís, Gael
%A Bagan, Emilio
%A Calsamiglia, John
%A Chiribella, Giulio
%A Muñoz-Tapia, Ramon
%B Physical Review Letters
%V 117
%8 Jan-10-2016
%U http://link.aps.org/doi/10.1103/PhysRevLett.117.150502http://link.aps.org/article/10.1103/PhysRevLett.117.150502
%! Phys. Rev. Lett.
%R 10.1103/PhysRevLett.117.150502
%0 Journal Article
%J New Journal of Physics
%D 2012
%T Beating noise with abstention in state estimation
%A Gendra, Bernat
%A Ronco-Bonvehi, Elio
%A Calsamiglia, John
%A Muñoz-Tapia, Ramon
%A Bagan, Emilio
%B New Journal of Physics
%V 14
%P 105015
%U http://iopscience.iop.org/1367-2630/14/10/105015
%R 10.1088/1367-2630/14/10/105015
%0 Journal Article
%J Scientific Reports (Nature Publishing Group)
%D 2012
%T Quantum learning without quantum memory
%A Sentís, Gael
%A Calsamiglia, John
%A Muñoz-Tapia, Ramon
%A Bagan, Emilio
%X A quantum learning machine for binary classification of qubit states that does not require quantum memory is introduced and shown to perform with the minimum error rate allowed by quantum mechanics for any size of the training set. This result is shown to be robust under (an arbitrary amount of) noise and under (statistical) variations in the composition of the training set, provided it is large enough. This machine can be used an arbitrary number of times without retraining. Its required classical memory grows only logarithmically with the number of training qubits, while its excess risk decreases as the inverse of this number, and twice as fast as the excess risk of an “estimate-and-discriminate” machine, which estimates the states of the training qubits and classifies the data qubit with a discrimination protocol tailored to the obtained estimates.
%B Scientific Reports (Nature Publishing Group)
%I Nature Publishing Group
%V 2
%P 708
%8 10/2012
%U http://www.nature.com/srep/2012/121005/srep00708/full/srep00708.html
%R 10.1038/srep00708
%0 Journal Article
%J Physical Review A
%D 2010
%T Estimation of quantum finite mixtures
%A de Vicente, J. I.
%A Calsamiglia, John
%A Muñoz-Tapia, Ramon
%A Bagan, Emilio
%X We consider the problem of determining the weights of a quantum ensemble. That is to say, given a quantum system that is in a set of possible known states according to an unknown probability law, we give strategies to estimate the individual probabilities, weights, or mixing proportions. Such strategies can be used to estimate the frequencies at which different independent signals are emitted by a source. They can also be used to estimate the weights of particular terms in a canonical decomposition of a quantum channel. The quality of these strategies is quantified by a covariance-type error matrix. According with this cost function, we give optimal strategies in both the single-shot and multiple-copy scenarios. The latter is also analyzed in the asymptotic limit of large number of copies. We give closed expressions of the error matrix for two-component quantum mixtures of qubit systems. The Fisher information plays an unusual role in the problem at hand, providing exact expressions of the minimum covariance matrix for any number of copies.
%B Physical Review A
%V 81
%P 012332
%8 1/2010
%U http://link.aps.org/doi/10.1103/PhysRevA.81.012332
%R 10.1103/PhysRevA.81.012332
%0 Journal Article
%J Physica Scripta
%D 2010
%T Recycling of qubits
%A P Rapcan
%A Calsamiglia, John
%A Muñoz-Tapia, Ramon
%A Bagan, Emilio
%A V Buzek
%X We consider a finite number, N, of qubits that encode a pure single qubit state SU(2) covariantly. Given the N-qubit state has already been measured optimally to estimate the single-qubit state, we analyse the maximum information obtainable by a second, and subsequent observers ignorant of important details of the previous measurements. We quantify the information acquired by each observer as a function of N and of the number of independent observers that in succession have independently measured the same ensemble of qubits before him.
%B Physica Scripta
%V T140
%P 014059
%U http://iopscience.iop.org/1402-4896/2010/T140/014059?fromSearchPage=true
%R 10.1088/0031-8949/2010/T140/014059