pdfsense: Parton distribution function sensitivity experiments
In liminal: Multivariate Data Visualization with Tours and Embeddings

Description Usage Format Details Source References

Data from Wang et al., 2018 to compare embedding approaches to a tour path.

pdfsense

An object of class data.frame with 2808 rows and 62 columns.

Data were obtained from CT14HERA2 parton distribution function fits as used in Laa et al., 2018. There are 28 directions in the parameter space of parton distribution function fit, each point in the variables labelled X1-X56 indicate moving +- 1 standard devation from the 'best' (maximum likelihood estimate) fit of the function. Each observation has all predictions of the corresponding measurement from an experiment.

(see table 3 in that paper for more explicit details).

The remaining columns are:

InFit: A flag indicating whether an observation entered the fit of CT14HERA2 parton distribution function
Type: First number of ID
ID: contains the identifier of experiment, 1XX/2XX/5XX correpsonds to Deep Inelastic Scattering (DIS) / Vector Boson Production (VBP) / Strong Interaction (JET). Every ID points to an experimental paper.
pt: the per experiment observational id
x,mu: the kinematics of a parton. x is the parton momentum fraction, and mu is the factorisation scale.

http://www.physics.smu.edu/botingw/PDFsense_web_histlogy/

Wang, B.-T., Hobbs, T. J., Doyle, S., Gao, J., Hou, T.-J., Nadolsky, P. M., & Olness, F. I. (2018). PDFSense: Mapping the sensitivity of hadronic experiments to nucleon structure. Retrieved from https://arxiv.org/abs/1808.07470

Cook, D., Laa, U., & Valencia, G. (2018). Dynamical projections for the visualization of PDFSense data. The European Physical Journal C, 78(9), 742. doi: 10.1140/epjc/s10052-018-6205-2

liminal documentation built on May 28, 2021, 9:06 a.m.