Neural network-based approach to phase space integration
- Physics, Computer Science
A Neural Network algorithm optimized to perform Monte Carlo methods to integrate and sample probability distributions on multi-dimensional phase spaces, including situations with non-trivial features such as sharp resonances and soft/collinear enhancements.
Exploring phase space with Neural Importance Sampling
- PhysicsSciPost Physics
An importance sampling technique capable of overcoming typical deficiencies of existing approaches by incorporating neural networks is proposed, which guarantees full phase space coverage and the exact reproduction of the desired target distribution, in this case given by the squared transition matrix element.
Event generation with normalizing flows
- Physics, Computer SciencePhysical Review D
A novel integrator based on normalizing flows which can be used to improve the unweighting efficiency of Monte-Carlo event generators for collider physics simulations and generates the correct result even if the underlying neural networks are not optimally trained.
Direct numerical evaluation of multi-loop integrals without contour deformation
- MathematicsThe European Physical Journal C
We propose a method for computing numerically integrals defined via $$i \epsilon $$ i ϵ deformations acting on single-pole singularities. We achieve this without an explicit analytic contour…
Quantum chromodynamics : simulation in Monte Carlo event generators
This thesis contains the work of two recent developments in the Herwig general purpose event generator. Firstly, the results from an new implementation of the KrkNLO method in the Herwig event…
45 Computing for Perturbative QCD
One of the main challenges facing the particle-physics community to date is the interpretation of LHC measurements on the basis of accurate and robust theoretical predictions. The discovery of a…
A ug 2 00 0 Generating QCD-antennas
An extension of the SARGE-algorithm of  is introduced, which includes the incoming momenta in the kinematical pole structure of the density with which the momenta are generated. The algorithm is…
Automating the P OWHEG method in S HERPA
A new implementation of the POWHEG method  into the Monte-Carlo event generator SHERPA  is presented, focusing on processes with a simple colour structure. Results for a variety of processes,…
Monte Carlo simulations for BSM physics and precision Higgs physics at the LHC
Monte Carlo event generators are indispensable tools for the interpretation of data taken at particle collider experiments like the Large Hadron Collider (LHC), the most powerful particle collider…
SHOWING 1-2 OF 2 REFERENCES
- 27 (1978) 192, and Cornell preprint CLNS- 80/447