Rather than measuring NP search in terms of Turing-machine time, we reinterpret witness recovery as an information-acquisition process: the hidden witness is the sole source of uncertainty, and identification requires sufficient reduction of this uncertainty through a rate-limited access interface in the sense of Shannon. To make this perspective explicit, we analyze an extreme regime, the \emph{psocid model}, in which the witness is accessible only via equality probes $[π= w^\star]$ under a uniform, structureless prior. Each probe reveals at most $O(N/2^N)$ bits of mutual information, so polynomially many probes accumulate only $o(1)$ total information. By Fano's inequality, reliable recovery requires $Ω(N)$ bits, creating a fundamental mismatch between the information required for recovery and that obtainable through the interface. The psocid setting isolates a fully symmetric search regime in which no intermediate computation yields global eliminative leverage, thereby exposing an intrinsic informational origin of exponential search complexity.

翻译：不将NP搜索置于图灵机时间框架下度量，我们重新将见证恢复解读为信息获取过程：隐藏见证是唯一的不确定性来源，而识别要求通过香农意义上的速率受限访问接口充分降低此不确定性。为明确阐述这一视角，我们分析了一个极端情形——即"psocid模型"，在该模型中，见证仅能通过相等性试探$[π= w^\star]$在均匀无结构先验下访问。每次试探至多揭示$O(N/2^N)$比特互信息，因此多项式次试探累积的总信息量仅为$o(1)$。根据Fano不等式，可靠恢复需要$Ω(N)$比特，这导致恢复所需信息与接口所能获取信息之间存在根本性失衡。psocid设定隔离出一个完全对称的搜索机制，其中任何中间计算都无法产生全局消解杠杆，从而暴露出指数搜索复杂性的内禀信息论起源。