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Computational hardness of estimating quantum entropies via binary entropy bounds

Yupan Liu

TL;DR

This work analyzes the computational hardness of estimating quantum entropies of generalized Rényi and Tsallis forms, ${\rm S}^{\tt R}_{\alpha}(\rho)$ and ${\rm S}^{\tt T}_q(\rho)$, framing the task as promise problems with a constant gap. It introduces rank-2 reductions that connect quantum entropies of rank-2 mixtures to binary entropies, and proves that Rank2RényiQEA$_{\alpha}$ and Rank2TsallisQEA$_q$ are ${\sf BQP}$-hard for all positive orders, with ${\sf BQP}$-completeness for LowRank variants when the rank is polynomial. The paper also establishes order-zero results in the ${\sf NQP}$ class and develops a suite of new inequalities relating binary entropies across orders, which are of independent interest. By combining these hardness results with existing rank-dependent quantum-query algorithms, the authors obtain comprehensive hardness landscapes: ${\sf BQP}$-hardness for all $\alpha>0$ and $q>0$, with ${\sf BQP}$-completeness for relevant low-rank regimes and for Tsallis entropy with $q>1$. These findings illuminate fundamental limits on efficiently estimating quantum entropies and provide a new framework for reductions via entropy-order inequalities, with potential implications for quantum cryptography and information-processing tasks that rely on entropy estimation.

Abstract

We investigate the computational hardness of estimating the quantum $α$-Rényi entropy ${\rm S}^{\tt R}_α(ρ) = \frac{\ln {\rm Tr}(ρ^α)}{1-α}$ and the quantum $q$-Tsallis entropy ${\rm S}^{\tt T}_q(ρ) = \frac{1-{\rm Tr}(ρ^q)}{q-1}$, both converging to the von Neumann entropy as the order approaches $1$. The promise problems Quantum $α$-Rényi Entropy Approximation (RényiQEA$_α$) and Quantum $q$-Tsallis Entropy Approximation (TsallisQEA$_q$) ask whether $ {\rm S}^ {\tt R}_α(ρ)$ or ${\rm S}^{\tt T}_q(ρ)$, respectively, is at least $τ_{\tt Y}$ or at most $τ_{\tt N}$, where $τ_{\tt Y} - τ_{\tt N}$ is typically a positive constant. Previous hardness results cover only the von Neumann entropy (order $1$) and some cases of the quantum $q$-Tsallis entropy, while existing approaches do not readily extend to other orders. We establish that for all positive real orders, the rank-$2$ variants Rank2RényiQEA$_α$ and Rank2TsallisQEA$_q$ are ${\sf BQP}$-hard. Combined with prior (rank-dependent) quantum query algorithms in Wang, Guan, Liu, Zhang, and Ying (TIT 2024), Wang, Zhang, and Li (TIT 2024), and Liu and Wang (SODA 2025), our results imply: - For all real orders $α> 0$ and $0 < q \leq 1$, LowRankRényiQEA$_α$ and LowRankTsallisQEA$_q$ are ${\sf BQP}$-complete, where both are restricted versions of RényiQEA$_α$ and TsallisQEA$_q$ with $ρ$ of polynomial rank. - For all real order $q>1$, TsallisQEA$_q$ is ${\sf BQP}$-complete. Our hardness results stem from reductions based on new inequalities relating the $α$-Rényi or $q$-Tsallis binary entropies of different orders, where the reductions differ substantially from previous approaches, and the inequalities are also of independent interest.

Computational hardness of estimating quantum entropies via binary entropy bounds

TL;DR

This work analyzes the computational hardness of estimating quantum entropies of generalized Rényi and Tsallis forms, and , framing the task as promise problems with a constant gap. It introduces rank-2 reductions that connect quantum entropies of rank-2 mixtures to binary entropies, and proves that Rank2RényiQEA and Rank2TsallisQEA are -hard for all positive orders, with -completeness for LowRank variants when the rank is polynomial. The paper also establishes order-zero results in the class and develops a suite of new inequalities relating binary entropies across orders, which are of independent interest. By combining these hardness results with existing rank-dependent quantum-query algorithms, the authors obtain comprehensive hardness landscapes: -hardness for all and , with -completeness for relevant low-rank regimes and for Tsallis entropy with . These findings illuminate fundamental limits on efficiently estimating quantum entropies and provide a new framework for reductions via entropy-order inequalities, with potential implications for quantum cryptography and information-processing tasks that rely on entropy estimation.

Abstract

We investigate the computational hardness of estimating the quantum -Rényi entropy and the quantum -Tsallis entropy , both converging to the von Neumann entropy as the order approaches . The promise problems Quantum -Rényi Entropy Approximation (RényiQEA) and Quantum -Tsallis Entropy Approximation (TsallisQEA) ask whether or , respectively, 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 positive real orders, the rank- variants Rank2RényiQEA and Rank2TsallisQEA are -hard. Combined with prior (rank-dependent) quantum query algorithms in Wang, Guan, Liu, Zhang, and Ying (TIT 2024), Wang, Zhang, and Li (TIT 2024), and Liu and Wang (SODA 2025), our results imply: - For all real orders and , LowRankRényiQEA and LowRankTsallisQEA are -complete, where both are restricted versions of RényiQEA and TsallisQEA with of polynomial rank. - For all real order , TsallisQEA is -complete. Our hardness results stem from reductions based on new inequalities relating the -Rényi or -Tsallis binary entropies of different orders, where the reductions differ substantially from previous approaches, and the inequalities are also of independent interest.
Paper Structure (31 sections, 33 theorems, 109 equations, 3 tables)

This paper contains 31 sections, 33 theorems, 109 equations, 3 tables.

Key Result

theorem 1.1

The following statements hold:

Theorems & Definitions (58)

  • theorem 1.1: Computational hardness of estimating quantum entropies, informal version of \ref{['thm:comp-hardness-Renyi', 'thm:comp-hardness-Tsallis']}
  • corollary 1
  • corollary 2
  • theorem 1.2: Informal version of \ref{['thm:order-zero-NQPcomplete']}
  • definition 2.1: Binary entropies
  • lemma 1: Tsallis binary entropy lower bound, adapted from LW25
  • lemma 2: Monotonicity of Rényi binary entropy, adapted from BS93
  • proposition 2.2: Binary min-entropy lower bound
  • definition 2.3: Quantum entropies
  • definition 2.4: Quantum $q$-Tsallis Entropy Approximation, , adapted from LW25
  • ...and 48 more