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Colloidal heat engines are paradigmatic models to understand the conversionof heat into work in a noisy environment - a domain where biological andsynthetic nano/micro machines function. While the operation of these enginesacross thermal baths is well-understood, how they function across baths withnoise statistics that is non-Gaussian and also lacks memory, the simplestdeparture from equilibrium, remains unclear. Here we quantified the performanceof a colloidal Stirling engine operating between an engineered\textit{memoryless} non-Gaussian bath and a Gaussian one. In the quasistaticlimit, the non-Gaussian engine functioned like an equilibrium one as predictedby theory. On increasing the operating speed, due to the nature of noisestatistics, the onset of irreversibility for the non-Gaussian engine precededits thermal counterpart and thus shifted the operating speed at which power ismaximum. The performance of nano/micro machines can be tuned by altering onlythe nature of reservoir noise statistics.

Tuning the performance of a micrometer-sized Stirling engine through reservoir engineering