发表机构
International Centre for Theory of Quantum Technologies, University of Gdańsk（格但斯克大学量子技术理论国际中心）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究在不完美CNOT模型中探究制备、相互作用角度和场无序对环境记录的影响，揭示对齐参数与条件分支几何决定记录的非单调响应，并证明Z基仍最优，为稳健量子达尔文主义记录提供碎片大小指导。
AI 中文摘要
量子达尔文主义通过冗余的环境记录来解释客观信息。早期工作已表明，不完美的记录可以被放大，且环境自演化可以增强或抑制其形成。我们研究了在不完美CNOT模型中，制备、相互作用角度和场无序如何共同作用，该模型具有随机高斯耦合和纯的、无相互作用的环境量子比特。我们发现，在没有场的情况下，单一的对齐参数$\Lambda$决定了条件态可区分性对制备和相互作用角度的依赖。增加相互作用的不完美性或局部场强可以改善或抑制记录。我们通过条件分支分离的几何学来解释这种非单调响应。对于本文考虑的纯初始环境，$Z$基对于Holevo信息仍然是最优的，因此场辅助记录不需要改变被记录的系统可观测量。在均方根强度相等的情况下，比较均匀局部场强与高斯分布场强，显示了无序如何拓宽有益和有害的场效应。碎片信息的精确表达式和最多24个环境量子比特的数值模拟，量化了高平均信息与跨碎片及有限观测窗口内可靠记录之间的区别。这些结果将局部信息获取的几何学与稳健记录所需的碎片大小联系起来。分支可区分性分析本身仅需要每个环境量子比特的条件演化，并可推广到其他保持系统指针基的相互作用。
英文摘要
Quantum Darwinism explains objective information through redundant environmental records. Earlier work established that imperfect records can be amplified and that environment self-evolution can enhance or suppress their formation. We investigate how preparation, interaction angle, and field disorder combine in an imperfect-CNOT model with random Gaussian couplings and pure, noninteracting environment qubits. We find that, without fields, a single alignment parameter $Λ$ determines the preparation and interaction-angle dependence of conditional-state distinguishability. Increasing interaction imperfection or local field strength can improve or suppress recording. We explain this nonmonotonic response through the geometry of conditional branch separation. For the pure initial environments considered here, the $Z$ basis remains optimal for Holevo information, so field-assisted recording requires no change of the recorded system observable. Comparing uniform local field strengths with Gaussian-distributed strengths at equal root-mean-square strength shows how disorder broadens both beneficial and detrimental field effects. Exact expressions for fragment information and numerical simulations with up to 24 environment qubits quantify the distinction between high mean information and reliable records across fragments and throughout a finite observation window. These results connect the geometry of local information acquisition to the fragment sizes needed for robust recording. The branch-distinguishability analysis itself requires only the conditional evolution of each environment qubit and extends to other interactions that preserve a system pointer basis.
Comments20 pages including references, 9 figures; plus 10 pages of Supplemental Material with 7 figures
