Spectral upper bound for the torsion function of symmetric stable processes

We prove a spectral upper bound for the torsion function of symmetric stable processes that holds for convex domains in ${\mathbb{R}}^d$. Our bound is explicit and captures the correct order of growth in $d$, improving upon the existing results of Giorgi and Smits (2010) and Biswas and L\H{o}rinczi (2019). Along the way, we make progress towards a torsion analogue of Chen and Song’s (2005) two-sided eigenvalue estimates for subordinate Brownian motion.