Effects of Data Uncertainty on Triple Probe Measurements

Triple Langmuir probes are frequently employed to infer electron temperatures and number densities in plasmas that evolve too rapidly for voltage-swept diagnostics. In this work, a physics-based numerical model is used to simulate triple probe current collection in equilibrium plasmas and a Monte Carlo approach is applied to quantify how uncertainty in measured probe currents propagates into inferred plasma properties. The results show that, when the assumptions of standard triple probe theory are satisfied, random uncertainty in the collected currents propagates in a largely proportional and statistically well-behaved manner into both electron temperature and number density, with no strong evidence of nonlinear amplification. At elevated electron temperatures, violations of the ion saturation current assumption introduce systematic bias in the inferred number density that is distinct from stochastic measurement uncertainty. These findings demonstrate that while triple probe inference is robust to random measurement uncertainty under ideal conditions, its accuracy remains strongly dependent on the validity of the underlying physical assumptions.