Speaker
Description
A new method to approximate Euclidean correlation functions by exponential sums is introduces. The truncated Hankel correlator (THC) method builds a Hankel matrix from the full correlator data available and truncates the eigenspectrum of said Hankel matrix. It proceeds by applying the Prony generalised eigenvalue method to the thus obtained low-rank approximation. A large number of algebraic correlator analysis methods including (block) Prony (and equivalently (block) Lanczos) and the generalised eigenvalue problem (GEVP) can be reproduced as sub-optimal special cases of the THC method. Moreover, the THC method is robust against noise and requires comparably little human oversight. When applied to symmetric data, the obtained energy spectrum is guaranteed to be symmetric up to machine precision. It goes without saying that the signal-to-noise problem has not been solved.
| Parallel Session (for talks only) | Algorithms and artificial intelligence |
|---|
