We derive lower and upper bounds on the identification capacity of inverse Gaussian channels, a fundamental model for molecular communications in fluid environments. The analysis considers deterministic encoding schemes under a peak time constraint and characterizes the asymptotic growth of codebook sizes. A central result reveals that, under a mild regularity condition on the noise, i.e., the stochastic first arrival time of an information-carrying molecule propagating via diffusion and drift to the receiver, the identification capacity exhibits super-exponential growth in the codeword length, $n,$ i.e., $\sim 2^{(n \log n)R},$ where $R$ is the coding rate.

翻译：我们推导了逆高斯信道（流体环境中分子通信的基本模型）的辨识容量的下界与上界。分析考虑了峰值时间约束下的确定性编码方案，并刻画了码本大小的渐近增长。核心结果表明，在噪声的温和正则性条件下（即携信息分子通过扩散与漂移传播至接收器的随机首次到达时间），辨识容量在码字长度 $n$ 上呈超指数增长，即 $\sim 2^{(n \log n)R}$，其中 $R$ 为编码速率。