12 research outputs found
Edge Detecting New Physics the Voronoi Way
We point out that interesting features in high energy physics data can be
determined from properties of Voronoi tessellations of the relevant phase
space. For illustration, we focus on the detection of kinematic "edges" in two
dimensions, which may signal physics beyond the standard model. After deriving
some useful geometric results for Voronoi tessellations on perfect grids, we
propose several algorithms for tagging the Voronoi cells in the vicinity of
kinematic edges in real data. We show that the efficiency is improved by the
addition of a few Voronoi relaxation steps via Lloyd's method. By preserving
the maximum spatial resolution of the data, Voronoi methods can be a valuable
addition to the data analysis toolkit at the LHC.Comment: 6 pages, 7 figure
Resolving Combinatorial Ambiguities in Dilepton Event Topologies with Constrained Variables
We advocate the use of on-shell constrained variables in order to
mitigate the combinatorial problem in SUSY-like events with two invisible
particles at the LHC. We show that in comparison to other approaches in the
literature, the constrained variables provide superior ansatze for the
unmeasured invisible momenta and therefore can be usefully applied to
discriminate combinatorial ambiguities. We illustrate our procedure with the
example of dilepton events. We critically review the existing
methods based on the Cambridge variable and MAOS-reconstruction of
invisible momenta, and show that their algorithm can be simplified without loss
of sensitivity, due to a perfect correlation between events with complex
solutions for the invisible momenta and events exhibiting a kinematic endpoint
violation. Then we demonstrate that the efficiency for selecting the correct
partition is further improved by utilizing the variables instead.
Finally, we also consider the general case when the underlying mass spectrum is
unknown, and no kinematic endpoint information is available
Enhancing the discovery prospects for SUSY-like decays with a forgotten kinematic variable
The lack of a new physics signal thus far at the Large Hadron Collider
motivates us to consider how to look for challenging final states, with large
Standard Model backgrounds and subtle kinematic features, such as cascade
decays with compressed spectra. Adopting a benchmark SUSY-like decay topology
with a four-body final state proceeding through a sequence of two-body decays
via intermediate resonances, we focus our attention on the kinematic variable
which previously has been used to parameterize the boundary of the
allowed four-body phase space. We highlight the advantages of using
as a discovery variable, and present an analysis suggesting that
the pairing of with another invariant mass variable leads to a
significant improvement over more conventional variable choices and techniques.Comment: 20 pages, 13 figures. v2: matches published versio
Identifying Phase Space Boundaries with Voronoi Tessellations
Determining the masses of new physics particles appearing in decay chains is
an important and longstanding problem in high energy phenomenology. Recently it
has been shown that these mass measurements can be improved by utilizing the
boundary of the allowed region in the fully differentiable phase space in its
full dimensionality. Here we show that the practical challenge of identifying
this boundary can be solved using techniques based on the geometric properties
of the cells resulting from Voronoi tessellations of the relevant data. The
robust detection of such phase space boundaries in the data could also be used
to corroborate a new physics discovery based on a cut-and-count analysis.Comment: 48 pages, 23 figures, Journal-submitted versio
Discoveries far from the lamppost with matrix elements and ranking
The prevalence of null results in searches for new physics at the LHC motivates the effort to make these searches as model-independent as possible. We describe procedures for adapting the Matrix Element Method for situations where the signal hypothesis is not known a priori. We also present general and intuitive approaches for performing analyses and presenting results, which involve the flattening of background distributions using likelihood information. The first flattening method involves ranking events by background matrix element, the second involves quantile binning with respect to likelihood (and other) variables, and the third method involves reweighting histograms by the inverse of the background distribution
Detecting kinematic boundary surfaces in phase space: particle mass measurements in SUSY-like events
Abstract We critically examine the classic endpoint method for particle mass determination, focusing on difficult corners of parameter space, where some of the measurements are not independent, while others are adversely affected by the experimental resolution. In such scenarios, mass differences can be measured relatively well, but the overall mass scale remains poorly constrained. Using the example of the standard SUSY decay chain q ˜ → χ ˜ 2 0 → ℓ ˜ → χ ˜ 1 0 , we demonstrate that sensitivity to the remaining mass scale parameter can be recovered by measuring the two-dimensional kinematical boundary in the relevant three-dimensional phase space of invariant masses squared. We develop an algorithm for detecting this boundary, which uses the geometric properties of the Voronoi tessellation of the data, and in particular, the relative standard deviation (RSD) of the volumes of the neighbors for each Voronoi cell in the tessellation. We propose a new observable, Σ ¯ , which is the average RSD per unit area, calculated over the hypothesized boundary. We show that the location of the Σ ¯ maximum correlates very well with the true values of the new particle masses. Our approach represents the natural extension of the one-dimensional kinematic endpoint method to the relevant three dimensions of invariant mass phase space
Detecting kinematic boundary surfaces in phase space and particle mass measurements in SUSY-like events
We critically examine the classic endpoint method for particle mass determination, focusing on difficult corners of parameter space, where some of the measurements are not independent, while others are adversely affected by the experimental resolution. In such scenarios, mass differences can be measured relatively well, but the overall mass scale remains poorly constrained. Using the example of the standard SUSY decay chain , we demonstrate that sensitivity to the remaining mass scale parameter can be recovered by measuring the two-dimensional kinematical boundary in the relevant three-dimensional phase space of invariant masses squared. We develop an algorithm for detecting this boundary, which uses the geometric properties of the Voronoi tessellation of the data, and in particular, the relative standard deviation (RSD) of the volumes of the neighbors for each Voronoi cell in the tessellation. We propose a new observable, , which is the average RSD per unit area, calculated over the hypothesized boundary. We show that the location of the maximum correlates very well with the true values of the new particle masses. Our approach represents the natural extension of the one-dimensional kinematic endpoint method to the relevant three dimensions of invariant mass phase space.We critically examine the classic endpoint method for particle mass determination, focusing on difficult corners of parameter space, where some of the measurements are not independent, while others are adversely affected by the experimental resolution. In such scenarios, mass differences can be measured relatively well, but the overall mass scale remains poorly constrained. Using the example of the standard SUSY decay chain , we demonstrate that sensitivity to the remaining mass scale parameter can be recovered by measuring the two-dimensional kinematical boundary in the relevant three-dimensional phase space of invariant masses squared. We develop an algorithm for detecting this boundary, which uses the geometric properties of the Voronoi tessellation of the data, and in particular, the relative standard deviation (RSD) of the volumes of the neighbors for each Voronoi cell in the tessellation. We propose a new observable, , which is the average RSD per unit area, calculated over the hypothesized boundary. We show that the location of the maximum correlates very well with the true values of the new particle masses. Our approach represents the natural extension of the one-dimensional kinematic endpoint method to the relevant three dimensions of invariant mass phase space.We critically examine the classic endpoint method for particle mass determination, focusing on difficult corners of parameter space, where some of the measurements are not independent, while others are adversely affected by the experimental resolution. In such scenarios, mass differences can be measured relatively well, but the overall mass scale remains poorly constrained. Using the example of the standard SUSY decay chain , we demonstrate that sensitivity to the remaining mass scale parameter can be recovered by measuring the two-dimensional kinematical boundary in the relevant three-dimensional phase space of invariant masses squared. We develop an algorithm for detecting this boundary, which uses the geometric properties of the Voronoi tessellation of the data, and in particular, the relative standard deviation (RSD) of the volumes of the neighbors for each Voronoi cell in the tessellation. We propose a new observable, , which is the average RSD per unit area, calculated over the hypothesized boundary. We show that the location of the maximum correlates very well with the true values of the new particle masses. Our approach represents the natural extension of the one-dimensional kinematic endpoint method to the relevant three dimensions of invariant mass phase space