| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 1845592 | Nuclear Physics B - Proceedings Supplements | 2012 | 5 Pages |
Abstract
We describe a method, based on neural networks, of revealing Compton form factors in the deeply virtual region. We compare this approach to standard least-squares model fitting both for a simplified toy case and for HERMES data.
Related Topics
Physical Sciences and Engineering
Physics and Astronomy
Nuclear and High Energy Physics
