Computational hardness of estimating quantum entropies via binary entropy bounds
Yupan Liu

TL;DR
This paper proves the computational hardness of estimating quantum $ ext{R}^{ ext{R}}_{ ext{Renyi}}$ and Tsallis entropies for various orders, establishing BQP-completeness for certain rank-restricted problems.
Contribution
It introduces new reductions based on inequalities relating binary entropies of different orders, extending hardness results to all positive orders and the infinity case.
Findings
Rank-2 variants of entropy estimation are BQP-hard for all positive orders and infinity.
Low-rank entropy estimation problems are BQP-complete for all orders in specified ranges.
New inequalities between binary entropies underpin the reductions and hardness proofs.
Abstract
We investigate the computational hardness of estimating the quantum -R\'enyi entropy and the quantum -Tsallis entropy , both of which converge to the von Neumann entropy as the order approaches . The promise problems Quantum -R\'enyi Entropy Approximation (R\'enyiQEA) and Quantum -Tsallis Entropy Approximation (TsallisQEA) ask whether or , is at least or at most , where is typically a positive constant. Previous hardness results cover only the von Neumann entropy (order ) and some cases of the quantum -Tsallis entropy, while existing approaches do not readily extend to other orders. We establish that for all…
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