Speaker
Description
How well do we know the inner structure of protons? The answer depends not only on the precision of experimental measurements and theoretical predictions but, as was pointed out recently, on the procedure of sampling of the allowed PDF solutions over the multidimensional parameter space. With large data samples, phenomenological PDF fits are at a risk of the big-data paradox, which takes over the law of large numbers and implies that more experimental data do not automatically raise the accuracy of PDFs. Close attention to the data quality and sampling of possible PDF solutions is as essential, as well as the distinction between aleatory and epistemic uncertainties. I will summarize efforts in the CTEQ-TEA group to understand and reduce all such PDF uncertainties and provide independent methods to validate PDF uncertainty estimates in precision EW measurements.
