Quantum Purity Amplification for Arbitrary Eigenstates and Multiple Outputs
Zhaoyi Li, Elias Theil, Aram W. Harrow, and Isaac Chuang

TL;DR
This paper introduces a comprehensive solution for quantum purity amplification (QPA), enabling high-fidelity eigenstate copying from mixed states across arbitrary dimensions and spectra, with detailed performance laws and sample complexity bounds.
Contribution
It provides the first dimension-uniform sample complexity bounds for optimal QPA and develops a generalized Young diagram theory for nonasymptotic analysis.
Findings
Optimal QPA performance characterized across output regimes.
Input copies scale as O(m/(ff D_{k, ext{min}}^2)) for constant spectral gap.
Dimension-uniform guarantees established for QPA with tight sample complexity bounds.
Abstract
Quantum purity amplification (QPA) is the task of coherently transforming copies of a mixed state into high-fidelity copies of a chosen eigenstate. We solve QPA in the general setting of input copies, output copies, arbitrary target eigenstates, arbitrary local dimension , and generic input spectra. We characterize the optimal channel and derive its all-site and one-site performance laws across output regimes. For the asymptotic analysis, we use a path-graph parametrization to show that, when the target eigenvalue has a constant spectral gap , achieving all-site error requires a number of input copies independent of and scaling as . When approaches a constant, the performance exhibits phase-like regimes, which we characterize explicitly. For the nonasymptotic analysis, we develop a theory…
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