Probabilistic Circuit Model

In this poster, we present our recent exploration of the novel probabilistic circuit model (PCM). Compared to dynamic circuits (i.e., circuits with mid-circuit measurements), probabilistic circuits (i.e., circuits containing stochastic applications of gates) suggest a way to model non-deterministic circuit behavior without the need for mid-circuit measurements. This poster first demonstrates how the PCM can reduce midcircuit measurements of dynamic circuits. By static analysis of quantum constant propagation (QCP), we replace mid-circuit measurements with probabilistic circuit snippets. This replacement can significantly reduce runtime overhead for dynamic circuits because mid-circuit measurements heavily burden quantum hardware due to the need for signal analysis and the integration of a classical feedback loop. Then, this poster establishes the equivalence between the dynamic circuits and the PCM regarding their expressive power. This finding implies the potential use of probabilistic gates in designing quantum algorithms. Finally, this poster takes errors of a depolarizing channel as an example to showcase the ability of probabilistic circuits to model nondeterministic behaviors in circuits. With PCM, the behavior of stochastic errors in circuits can be concisely visualized and modeled by probabilistic gates.