The Learnability of Quantum States
E1002078
"The Learnability of Quantum States" is a research paper by Scott Aaronson that investigates under what conditions quantum states can be efficiently learned or approximated from measurement data within the framework of computational learning theory.
All labels observed (1)
| Label | Occurrences |
|---|---|
| The Learnability of Quantum States canonical | 1 |
Statements (45)
| Predicate | Object |
|---|---|
| instanceOf |
research paper
ⓘ
scientific publication ⓘ |
| analyzes |
learnability of mixed quantum states
ⓘ
learnability of pure quantum states ⓘ number of measurements needed to learn a quantum state ⓘ tradeoff between accuracy and number of measurements ⓘ |
| assumes |
ability to perform measurements on quantum states
ⓘ
access to copies of an unknown quantum state ⓘ |
| author | Scott Aaronson NERFINISHED ⓘ |
| contributesTo |
complexity-theoretic limits on quantum information extraction
ⓘ
foundations of quantum machine learning ⓘ theory of quantum state learning ⓘ understanding of quantum tomography efficiency ⓘ |
| field |
computational learning theory
ⓘ
quantum computing ⓘ quantum information theory ⓘ |
| focusesOn |
approximating quantum states from measurement outcomes
ⓘ
conditions under which quantum states can be efficiently learned ⓘ learning quantum states with limited measurements ⓘ |
| hasAuthorAffiliation | Massachusetts Institute of Technology NERFINISHED ⓘ |
| hasDiscipline |
physics
ⓘ
theoretical computer science ⓘ |
| hasFormat | academic article ⓘ |
| hasKeyConcept |
approximation of high-dimensional quantum states
ⓘ
efficient learnability ⓘ generalization from measurement data ⓘ measurement complexity ⓘ |
| language | English ⓘ |
| proposes |
bounds on sample complexity for learning quantum states
ⓘ
formal definitions of learning quantum states ⓘ |
| relatedTo |
classical learnability theory
ⓘ
quantum algorithms ⓘ quantum communication complexity ⓘ quantum information compression ⓘ quantum machine learning ⓘ |
| topic |
PAC learning
ⓘ
computational complexity of learning ⓘ efficient approximation of quantum states ⓘ information-theoretic limits ⓘ learnability of quantum states ⓘ measurement data ⓘ quantum state tomography ⓘ sample complexity ⓘ |
| usesFramework |
Probably Approximately Correct learning
NERFINISHED
ⓘ
computational learning theory ⓘ |
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.