Speaker
Description
The problem of reconstructing spectral densities from noisy Euclidean-time Monte-Carlo data provides a valuable test-bed for investigating real-time and inclusive observables, and sign problems more broadly. In this talk, I will discuss the causal bootstrap, a new method for spectral reconstructions that unifies several approaches, including analyticity-based methods (Nevanlinna-Pick interpolation, moment problems), convex programming methodologies, and generalizes linear reconstruction methods, such as the commonly used Hansen, Lupo, and Tantalo (HLT) method. The causal bootstrap uses tools originally developed for the conformal bootstrap in order to provide rigorous bounds on smeared spectral functions while enforcing the positivity of the underlying spectral density, and is directly applicable to noisy Monte-Carlo data. I will discuss the methods and their relations, as well as initial results on applying the causal bootstrap to semi-inclusive tau decay on RBC-UKQCD domain wall fermion ensembles.