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Constraining Effective Field Theories with Machine Learning.

Johann Brehmer¹, Kyle Cranmer¹, Gilles Louppe²

¹New York University, New York 10003, New York, USA.

Physical Review Letters

|September 29, 2018

Summary

New analysis techniques for the Large Hadron Collider (LHC) extract more information from simulations. These methods significantly improve constraints on effective field theories and dimension-six operators, enhancing LHC legacy constraints.

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Area of Science:

High Energy Physics
Computational Physics
Particle Physics

Background:

Effective field theories (EFTs) are crucial for describing particle physics beyond the Standard Model.
The Large Hadron Collider (LHC) provides vast datasets for testing these theories.
Current analysis methods face limitations in extracting maximum information from complex simulations.

Purpose of the Study:

To develop novel, powerful analysis techniques for constraining EFTs at the LHC.
To enhance the precision of physics measurements by leveraging advanced computational methods.
To improve the sensitivity to new physics phenomena through more robust data analysis.

Main Methods:

Utilizing the inherent structure of particle physics processes to extract additional information from Monte Carlo simulations.
Training neural network models to estimate the likelihood ratio for EFT parameter inference.
Developing scalable methods applicable to processes with numerous observables and theory parameters.

Main Results:

The new techniques successfully extract extra information from Monte Carlo simulations.
Neural network models trained on this information provide accurate likelihood ratio estimations.
The methods demonstrate scalability to complex processes and rapid evaluation times (microseconds).

Conclusions:

The presented analysis techniques significantly strengthen bounds on dimension-six operators compared to existing methods.
These advancements hold substantial potential for improving the precision of LHC legacy constraints.
The methods offer a powerful new tool for EFT exploration at the LHC.