Finding Wombling Boundaries in LHC Data with Voronoi and Delaunay Tessellations
arXiv:2006.06582 · doi:10.1007/JHEP12(2020)137
Abstract
We address the problem of finding a wombling boundary in point data generated by a general Poisson point process, a specific example of which is an LHC event sample distributed in the phase space of a final state signature, with the wombling boundary created by some new physics. We discuss the use of Voronoi and Delaunay tessellations of the point data for estimating the local gradients and investigate methods for sharpening the boundaries by reducing the statistical noise. The outcome from traditional wombling algorithms is a set of boundary cell candidates with relatively large gradients, whose spatial properties must then be scrutinized in order to construct the boundary and evaluate its significance. Here we propose an alternative approach where we simultaneously form and evaluate the significance of all possible boundaries in terms of the total gradient flux. We illustrate our method with several toy examples of both straight and curved boundaries with varying amounts of signal present in the data.
arXiv comment54 pages. New figure 13 and appendix A added. Conclusions unchanged. Matches published version
References in corpus (45)
- FastJet user manual
- A Supersymmetry Primer
- Simplified Models for LHC New Physics Searches
- Anomaly Detection with Density Estimation
- Classification without labels: Learning from mixed samples in high energy physics
- Searching for New Physics with Deep Autoencoders
- Anomaly Detection for Resonant New Physics with Machine Learning
- Extending the Bump Hunt with Machine Learning
- A generic anti-QCD jet tagger
- QCD or What?
- Novelty Detection Meets Collider Physics
- Adversarially-trained autoencoders for robust unsupervised new physics searches
- Machine and Deep Learning Applications in Particle Physics
- Guiding New Physics Searches with Unsupervised Learning
- Variational Autoencoders for New Physics Mining at the Large Hadron Collider
- Uncovering latent jet substructure
- Global Search for New Physics with 2.0/fb at CDF
- A robust anomaly finder based on autoencoders
- Model-Independent and Quasi-Model-Independent Search for New Physics at CDF
- Search for New Physics in e mu X Data at D0 Using Sleuth: A Quasi-Model-Independent Search Strategy for New Physics
- A general search for new phenomena in ep scattering at HERA
- A Quasi-Model-Independent Search for New Physics at Large Transverse Momentum
- Algebraic Singularity Method for Mass Measurements with Missing Energy
- A Quasi-Model-Independent Search for New High p_T Physics at DZero
- Supersymmetric particle mass measurement with invariant mass correlations
- Machine Learning in High Energy Physics Community White Paper
- Distribution of Cell Area in Bounded Poisson Voronoi Tessellations with Application to Secure Local Connectivity
- Improved mass measurement using the boundary of many-body phase space
- Detecting kinematic boundary surfaces in phase space: particle mass measurements in SUSY-like events
- Using sorted invariant mass variables to evade combinatorial ambiguities in cascade decays
- Nonparametric semisupervised classification for signal detection in high energy physics
- Identifying Phase Space Boundaries with Voronoi Tessellations
- Enhancing the discovery prospects for SUSY-like decays with a forgotten kinematic variable
- Measuring the W-Boson mass at a hadron collider: a study of phase-space singularity methods
- Singularity Variables for Missing Energy Event Kinematics
- Multi-Dimensional Phase Space Methods for Mass Measurements and Decay Topology Determination
- Voronoi binning: Optimal adaptive tessellations of multi-dimensional data
- Singular ways to search for the Higgs boson
- Systematic Analysis of High Energy Collider Data
- Kinematic Focus Point Method for Particle Mass Measurements in Missing Energy Events
- Model-Independent Global Search for New High-pT Physics at CDF
- Discoveries far from the Lamppost with Matrix Elements and Ranking
- Discovering New Physics with Voronoi Tessellations
- Systematic Analysis of Frontier Energy Collider Data
- Statistical Challenges with Massive Data Sets in Particle Physics