# Neural network generated parametrizations of deeply virtual Compton form factors

@article{Kumeriki2011NeuralNG, title={Neural network generated parametrizations of deeply virtual Compton form factors}, author={Kre{\vs}imir Kumeri{\vc}ki and Dieter M{\"u}ller and Andreas Sch{\"a}fer}, journal={Journal of High Energy Physics}, year={2011}, volume={2011}, pages={1-17} }

We have generated a parametrization of the Compton form factor (CFF) $ \mathcal{H} $ based on data from deeply virtual Compton scattering (DVCS) using neural networks. This approach offers an essentially model-independent fitting procedure, which provides realistic uncertainties. Furthermore, it facilitates propagation of uncertainties from experimental data to CFFs. We assumed dominance of the CFF $ \mathcal{H} $ and used HERMES data on DVCS off unpolarized protons. We predict the beam charge…

## 31 Citations

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### On extraction of twist-two Compton form factors from DVCS observables through harmonic analysis

- PhysicsJournal of High Energy Physics
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Abstract
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Generalized Parton Distributions (GPDs) encode the correlations between longitudinal momentum and transverse position of partons inside hadrons and can give access to a picture of the nucleon…

## References

SHOWING 1-10 OF 43 REFERENCES

### Neural network parameterizations of electromagnetic nucleon form-factors

- Computer Science
- 2010

The electromagnetic nucleon form-factors data are studied with artificial feed forward neural networks and the Bayesian approach for the neural networks is adapted for χ2 error-like function and applied to the data analysis.

### Neural network parametrization of deep inelastic structure functions

- Computer Science
- 2002

We construct a parametrization of deep-inelastic structure functions which retains information on experimental errors and correlations, and which does not introduce any theoretical bias while…

### A fitter code for Deep Virtual Compton Scattering and Generalized Parton Distributions

- Physics
- 2008

We have developed a fitting code based on the leading-twist handbag Deep Virtual Compton Scattering (DVCS) amplitude in order to extract Generalized Parton Distribution (GPD) information from DVCS…

### Unbiased determination of the proton structure function F 2 p with faithful uncertainty estimation

- Computer Science
- 2005

We construct a parametrization of the deep-inelastic structure function of the proton F2(x,Q2) based on all available experimental information from charged lepton deep-inelastic scattering…

### Extraction of the Compton form factor H from deeply virtual Compton scattering measurements at Jefferson Lab

- Physics
- 2009

In the framework of generalized parton distributions, we study the helicity-dependent and independent cross sections measured in Hall A and the beam spin asymmetries measured in Hall B at Jefferson…

### Generalized Parton Distributions from Deeply Virtual Compton Scattering at HERMES

- Physics
- 2009

The HERMES Collaboration has recently published a set of (correlated) beam charge, beam spin and target spin asymmetries for the Deeply Virtual Compton Scattering (DVCS) process. This reaction allows…

### Deeply Virtual Compton Scattering

- Physics
- 1997

We study in QCD the physics of deeply virtual Compton scattering (DVCS){emdash}the virtual Compton process in the large s and small t kinematic region. We show that DVCS can probe a new type of {ital…

### The neural network approach to parton distribution functions

- Computer Science, Physics
- 2006

This work presents in detail the approach to parametrize experimental data, based on a combination of Monte Carlo methods and neural networks, applied to the parametrization of parton distributions.

### Extraction of the Compton Form Factor H from DVCS measurements at Jefferson Lab

- Physics
- 2009

In the framework of Generalised Parton Distributions, we study the helicitydependent and independent cross sections measured in Hall A and the beam spin asymmetries measured in Hall B at Jefferson…