TY - JOUR
T1 - Universal algorithms for quantum data learning
AU - Fanizza, Marco
AU - Skotiniotis, Michalis
AU - Calsamiglia, John
AU - Muñoz-Tapia, Ramon
AU - Sentís, Gael
N1 - Funding Information:
We acknowledge financial support from the Spanish Agencia Estatal de Investigación, Grant No. PID2019-107609GB-I00 and Catalan Government for the project QuantumCAT 001-P-001644, co-financed by the European Regional Development Fund (FEDER). JC also acknowledges support from ICREA Academia award.
Publisher Copyright:
Copyright © 2022 EPLA.
PY - 2022/10
Y1 - 2022/10
N2 - Operating quantum sensors and quantum computers would make data in the form of quantum states available for purely quantum processing, opening new avenues for studying physical processes and certifying quantum technologies. In this Perspective, we review a line of works dealing with measurements that reveal structural properties of quantum datasets given in the form of product states. These algorithms are universal, meaning that their performances do not depend on the reference frame in which the dataset is provided. Requiring the universality property implies a characterization of optimal measurements via group representation theory.
AB - Operating quantum sensors and quantum computers would make data in the form of quantum states available for purely quantum processing, opening new avenues for studying physical processes and certifying quantum technologies. In this Perspective, we review a line of works dealing with measurements that reveal structural properties of quantum datasets given in the form of product states. These algorithms are universal, meaning that their performances do not depend on the reference frame in which the dataset is provided. Requiring the universality property implies a characterization of optimal measurements via group representation theory.
UR - http://www.scopus.com/inward/record.url?scp=85141954473&partnerID=8YFLogxK
U2 - 10.1209/0295-5075/ac9c29
DO - 10.1209/0295-5075/ac9c29
M3 - Article
AN - SCOPUS:85141954473
SN - 0295-5075
VL - 140
JO - EPL
JF - EPL
IS - 2
M1 - 28001
ER -