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arXiv:1701.02398 · Science China Physics Mechanics and Astronomy

Sharp continuity bounds for entropy and conditional entropy

ZhiHua Chen, Zhihao Ma, Ismail Nikoufar, Shao-Ming Fei

Published Nov 24, 2016• 19 citations
arXivHTMLPDF
DOI
10.1007/s11433-016-0367-x

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We prove the sharp uniform continuity bound for quantum conditional entropy. If two bipartite states are at trace distance at most δδδ and d=dim⁡Ad=\dim Ad=dimA, the optimal dimension-only modulus of continuity is h2(δ)+δlog⁡(d2−1)h_2(δ)+δ\log(d^2-1)h2​(δ)+δlog(d2−1) up to δ=1−d−2δ=1-d^{-2}δ=1−d−2 and 2log⁡d2\log d2logd thereafter, where h2h_2h2​ denotes the binary entropy. When dim⁡B≥d\dim B\ge ddimB≥d, this bound is tight for every δ∈[0,1]δ\in[0,1]δ∈[0,1]. The key proof idea was developed with the assistance of ChatGPT 5.6 Sol, building on and adapting the tight classical proof of Alhejji \& Smith [IEEE ISIT (2020)], which follows a conceptually different approach.
We determine the sharp modulus of continuity, in trace distance, of the optimized Petz and sandwiched Rényi conditional entropies for every order α∈[12,1)α\in[\frac12,1)α∈[21​,1). If two bipartite states are within trace distance δδδ, then both conditional entropies differ by at most 11−αlog⁡[(1−ε)α+(D−1)1−αεα]\frac{1}{1-α} \log[(1-\varepsilon)^α +(D-1)^{1-α}\varepsilon^α]1−α1​log[(1−ε)α+(D−1)1−αεα], where ε:=min⁡{δ,1−1/D}\varepsilon := \min\{δ,1-1/D\}ε:=min{δ,1−1/D} and DDD is the effective dimension, given by the dimension of the first subsystem times the largest possible Schmidt rank. For every distance constraint δ∈[0,1]δ\in[0,1]δ∈[0,1], the bound is attained by an isotropic pair with a maximally entangled anchor. Taking α↑1α\uparrow1α↑1 recovers the recent sharp continuity bound of quantum conditional entropy by Berta et al. [arXiv:2607.24687]. The proof linearizes the relevant concave Rényi functional at a comparison point dictated by the isotropic equality family. Schmidt-rank domination extends the equality geometry to an arbitrary anchor state, after which trace-distance duality and a noncommutative calibration estimate control the perturbation and anchor term without weakening the sharp constant. The latter estimate requires matrix analysis and is assisted by ChatGPT 5.6 Sol.