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：我们不采用图灵机时间来度量NP搜索，而是将见证恢复重新解释为信息获取过程：隐藏的见证是唯一的不确定性来源，而识别需要通过香农意义上的速率受限访问接口充分降低这种不确定性。为使这一观点具体化，我们分析了一个极端情形——psocid模型，其中见证仅能通过相等探针$[π= w^\star]$在均匀无结构先验下访问。每个探针最多揭示$O(N/2^N)$比特互信息，因此多项式数量探针累计仅能获得$o(1)$比特总信息量。根据法诺不等式，可靠恢复需要$Ω(N)$比特信息，这形成了恢复所需信息与接口可获取信息之间的根本性不匹配。psocid设定隔离了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除性杠杆作用，从而揭示了指数搜索复杂度的内在信息论根源。