5 papers
Cloning is as Hard as Learning for Stabilizer States
Nikhil Bansal, Matthias C. Caro, Gaurav Mahajan
The impossibility of simultaneously cloning non-orthogonal states lies at the foundations of quantum theory. Even when allowing for approximation errors, cloning an arbitrary unkno…
Certifying and learning local quantum Hamiltonians
Andreas Bluhm, Matthias C. Caro, Francisco Escudero Gutiérrez +4
In this work, we study the problems of certifying and learning quantum -local Hamiltonians, for a constant . Our main contributions are as follows: - Certification of Hamilto…
A PAC-Bayesian approach to generalization for quantum models
Pablo Rodriguez-Grasa, Matthias C. Caro, Jens Eisert +3
Generalization is a central concept in machine learning theory, yet for quantum models, it is predominantly analyzed through uniform bounds that depend on a model's overall capacit…
Interactive proofs for verifying (quantum) learning and testing
Matthias C. Caro, Jens Eisert, Marcel Hinsche +3
We consider the problem of testing and learning from data in the presence of resource constraints, such as limited memory or weak data access, which place limitations on the effici…
Learning quantum states and unitaries of bounded gate complexity
Haimeng Zhao, Laura Lewis, Ishaan Kannan +3
While quantum state tomography is notoriously hard, most states hold little interest to practically-minded tomographers. Given that states and unitaries appearing in Nature are of…