30 citations · 76 across the 10 of their papers we have counts for
10 papers
Quantum Edge Detection
Santiago Llorens, Walther González, Gael Sentís +3
This paper introduces quantum edge detection, aimed at locating boundaries of quantum domains where all particles share the same pure state. Focusing on the 1D scenario of a string…
Quantum multi-anomaly detection
Santiago Llorens, Gael Sentís, Ramon Muñoz-Tapia
A source assumed to prepare a specified reference state sometimes prepares an anomalous one. We address the task of identifying these anomalous states in a series of preparatio…
Characterizing generalized axisymmetric quantum states in systems
Marcel Seelbach Benkner, Jens Siewert, Otfried Gühne +1
We introduce a family of highly symmetric bipartite quantum states in arbitrary dimensions. It consists of all states that are invariant under local phase rotations and local cycli…
Online identification of symmetric pure states
Gael Sentís, Esteban Martínez-Vargas, Ramon Muñoz-Tapia
We consider online strategies for discriminating between symmetric pure states with zero error when copies of the states are provided. Optimized online strategies involve local…
Unsupervised classification of quantum data
Gael Sentís, Alex Monràs, Ramon Muñoz-Tapia +2
We introduce the problem of unsupervised classification of quantum data, namely, of systems whose quantum states are unknown. We derive the optimal single-shot protocol for the bin…
Experimentally detecting a quantum change point via Bayesian inference
Shang Yu, Chang-Jiang Huang, Jian-Shun Tang +15
Detecting a change point is a crucial task in statistics that has been recently extended to the quantum realm. A source state generator that emits a series of single photons in a d…
Quantitative bound entanglement in two-qutrit states
Gael Sentís, Christopher Eltschka, Jens Siewert
Among the many facets of quantum correlations, bound entanglement has remained one the most enigmatic phenomena, despite the fact that it was discovered in the early days of quantu…
Programmable discrimination with an error margin
G. Sentís, E. Bagan, J. Calsamiglia +1
The problem of optimally discriminating between two completely unknown qubit states is generalized by allowing an error margin. It is visualized as a device---the programmable disc…
Robust optimal quantum learning without quantum memory
G. Sentís, J. Calsamiglia, R. Munoz-Tapia +1
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 learning without quantum memory
G. Sentís, J. Calsamiglia, R. Munoz-Tapia +1
A quantum learning machine for binary classification of qubit states that does not require quantum memory is introduced and shown to perform with the very same error rate as the op…