Resampling Algorithms for High Energy Physics Simulations
arXiv:1912.02436 · doi:10.1140/epjc/s10052-020-08500-y
Abstract
We demonstrate that the method of interleaved resampling in the context of parton showers can tremendously improve the statistical convergence of weighted parton shower evolution algorithms. We illustrate this by several examples showing significant statistical improvement.
arXiv comment7 pages, 3 figures
References in corpus (20)
- A critical appraisal of NLO+PS matching methods
- General-purpose event generators for LHC physics
- Matrix-Element Corrections to Parton Shower Algorithms
- Sequential Monte Carlo smoothing for general state space hidden Markov models
- Automated Parton-Shower Variations in Pythia 8
- Reweighting QCD matrix-element and parton-shower calculations
- Subleading Nc improved Parton Showers
- Triple collinear emissions in parton showers
- Leading-color fully differential two-loop soft corrections to QCD dipole showers
- A framework for second-order parton showers
- A general theory of particle filters in hidden Markov models and some applications
- Parton branching at amplitude level
- Parton shower evolution with subleading color
- Reweighting Parton Showers
- Color matrix element corrections for parton showers
- Fooling Around with the Sudakov Veto Algorithm
- Summing Large-N Towers in Colour Flow Evolution
- Path storage in the particle filter
- (MC)**3 -- a Multi-Channel Markov Chain Monte Carlo algorithm for phase-space sampling
- ExSample -- A Library for Sampling Sudakov-Type Distributions
Cited by in corpus (4)
- Challenges in Monte Carlo event generator software for High-Luminosity LHC
- The role of colour flows in matrix element computations and Monte Carlo simulations
- Rings and strings: a basis for understanding subleading colour and QCD coherence beyond the two-jet limit
- Towards Colour Flow Evolution at Two Loops