pith. sign in

arxiv: 1103.0480 · v2 · pith:NID4ZH7Hnew · submitted 2011-03-02 · 🪐 quant-ph

Quantum learning algorithms for quantum measurements

Alessandro Bisio , Giacomo Mauro D'Ariano , Paolo Perinotti , Michal Sedlak This is my paper
classification 🪐 quant-ph
keywords quantumlearningmeasurementsalgorithmalgorithmscaseexamplesoptimal
0
0 comments X
read the original abstract

We study quantum learning algorithms for quantum measurements. The optimal learning algorithm is derived for arbitrary von Neumann measurements in the case of training with one or two examples. The analysis of the case of three examples reveals that, differently from the learning of unitary gates, the optimal algorithm for learning of quantum measurements cannot be parallelized, and requires quantum memories for the storage of information.

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Quantum Advantage in Storage and Retrieval of Isometry Channels

    quant-ph 2025-07 unverdicted novelty 7.0

    Quantum strategy stores isometry channels with n = Θ(1/√ε) queries for error ε, quadratic improvement over classical n = Θ(ε^{-1}).