For n-qubit stabilizer states the optimal sample complexity of approximate cloning is Θ(n), matching the complexity of learning.
Stabilizer bootstrapping: A recipe for efficient agnostic tomography and magic estimation
3 Pith papers cite this work. Polarity classification is still indexing.
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Polynomial-time algorithms for the Polynomial Freiman-Ruzsa theorem and equivalent formulations over F_2^n, based on an optimized quadratic Goldreich-Levin procedure.
A reduction from weak agnostic learning of class C to efficient tomography of states with bounded l1-extent w.r.t. C, with a concrete algorithm for stabilizer states running in poly(n, (ξ/ε)^log(ξ/ε)) time.
citing papers explorer
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Cloning is as Hard as Learning for Stabilizer States
For n-qubit stabilizer states the optimal sample complexity of approximate cloning is Θ(n), matching the complexity of learning.
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An algorithmic Polynomial Freiman-Ruzsa theorem
Polynomial-time algorithms for the Polynomial Freiman-Ruzsa theorem and equivalent formulations over F_2^n, based on an optimized quadratic Goldreich-Levin procedure.
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Tomography of quantum states with bounded extent
A reduction from weak agnostic learning of class C to efficient tomography of states with bounded l1-extent w.r.t. C, with a concrete algorithm for stabilizer states running in poly(n, (ξ/ε)^log(ξ/ε)) time.