An efficient threshold and noise extraction algorithm suitable for FPGAs

A silicon pixel detector's threshold and noise are typically characterized by recording the detection efficiency as a function of the signal size. This data follows a characteristic S-curve and can be mathematically described by a Gauss error function. The common way to extract threshold and noise is a fit of the error function to the data, thus requires solving a nonlinear optimization problem. In this talk, we present a novel method which allows the determination of threshold and noise in a purely analytical way suitable for an FPGA implementation.