70 citations · 242 across the 10 of their papers we have counts for
6 papers · 1 filter
Improved Neural Network Monte Carlo Simulation
I-Kai Chen, Matthew D. Klimek, Maxim Perelstein
The algorithm for Monte Carlo simulation of parton-level events based on an Artificial Neural Network (ANN) proposed in arXiv:1810.11509 is used to perform a simulation of $H\to 4\…
The Time Substructure of Jets and Boosted Object Tagging
Matthew D. Klimek
We initiate the study of the time substructure of jets, motivated by the fact that the next generation of detectors at particle colliders will resolve the time scale over which jet…
Neural Network-Based Approach to Phase Space Integration
Matthew D. Klimek, Maxim Perelstein
Monte Carlo methods are widely used in particle physics to integrate and sample probability distributions (differential cross sections or decay rates) on multi-dimensional phase sp…
Multi-Dimensional Phase Space Methods for Mass Measurements and Decay Topology Determination
Baris Altunkaynak, Can Kilic, Matthew D. Klimek
Collider events with multi-stage cascade decays fill out the kinematically allowed region in phase space with a density that is enhanced at the boundary. The boundary encodes all a…
Ordered Kinematic Endpoints for 5-body Cascade Decays
Matthew D. Klimek
We present expressions for the kinematic endpoints of 5-body cascade decay chains proceeding through all possible combinations of 2-body and 3-body decays, with one stable invisibl…
Signatures of Top Flavored Dark Matter
Can Kilic, Matthew D. Klimek, Jiang-Hao Yu
We study the experimental signatures of top flavored dark matter (top FDM) in direct detection searches and at the LHC. We show that for a dark matter mass above 200 GeV, top FDM c…