activity
20092021
most citedNeural Network-Based Approach to Phase Space Integration

70 citations · 242 across the 10 of their papers we have counts for

collaborators

10 papers

math.CA2021

A new entire factorial function

Matthew D. Klimek

We introduce a new factorial function which agrees with the usual Euler gamma function at both the positive integers and at all half-integers, but which is also entire. We describe…

hep-ph2020★ 44 cited

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\…

hep-ph2019★ 3 cited

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…

hep-ph2018★ 70 cited

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…

hep-ph2016★ 11 cited

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…

hep-ph2016★ 2 cited

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…