inclusiveAI: A machine learning representation of the $F_2$ structure function over all charted $Q^2$ and $x$ range

Understand

Structure function data provide insight into the nucleon quark distribution.

• They are relatively straightforward to extract from the world's vast, and growing, amount of inclusive lepto-production data.
• In turn, structure functions can be used to model the physical processes needed for planning and optimizing future experiments.
• In this paper a machine learning algorithm capable of predicting, using a unique set of parameters, the $F_2$ structure function, for four-momentum transfer $0.055 \leq Q^2 \leq 800.0$ GeV$^2$ and for Bjorken $x$ from $2.8 \times 10^{-5}$ to the pion threshold is presented.