Related papers: B-tagging and searches for new physics beyond the …
Methods for anomaly detection of new physics processes are often limited to low-dimensional spaces due to the difficulty of learning high-dimensional probability densities. Particularly at the constituent level, incorporating desirable…
This paper presents a new tool to perform various steps in jet tagger development in an efficient and comprehensive way. A common data structure is used for training, as well as for performance evaluation in data. The introduction of this…
Two machine learning techniques for jet measurements at the LHCb experiment are presented: a regression-based method for jet-energy calibration and a deep neural network algorithm for jet flavour tagging, distinguishing between $b$-quark,…
Recent jet and jet substructure measurements at the LHC, and of machine-learning-based tagging techniques are presented using proton-proton collision data collected by the ATLAS and CMS experiments at CERN's Large Hadron Collider. These…
A jet algorithm based on the k-means clustering procedure is proposed which can be used for the invariant-mass reconstruction of heavy states decaying to hadronic jets. The proposed algorithm was tested by reconstructing E+ E- to ttbar to 6…
The flavor dependence of jet quenching is a powerful handle to discriminate between models of parton energy loss in heavy-ion collisions. We demonstrate the capacity of CMS to identify jets initiated by bottom quarks using displaced…
We describe a method to obtain point and dispersion estimates for the energies of jets arising from b quarks produced in proton-proton collisions at an energy of $\sqrt{s} =$ 13 TeV at the CERN LHC. The algorithm is trained on a large…
Neutrino experiments study the least understood of the Standard Model particles by observing their direct interactions with matter or searching for ultra-rare signals. The study of neutrinos typically requires overcoming large backgrounds,…
Stochastic process discovery is concerned with deriving a model capable of reproducing the stochastic character of observed executions of a given process, stored in a log. This leads to an optimisation problem in which the model's parameter…
Jet radiation patterns are indispensable for the purpose of discriminating partons' with different quantum numbers. However, they are also vulnerable to various contaminations from the underlying event, pileup, and radiation of adjacent…
We study the performance of the Particle Transformer (ParT) for jet flavor tagging using ILD full simulation events (1M jets) as well as fast simulation samples (10M and 1M jets). We perform 3-category ($b/c/d$), 6-category ($b/c/d/u/s/g$),…
Using techniques borrowed from statistical physics and neural networks, we determine the parameters, associated with a scoring function, that are chosen optimally to ensure complete success in threading tests in a training set of proteins.…
Jet substructure tools have proven useful in a number of high-energy particle-physics studies. A particular case is the discrimination, or tagging, between a boosted jet originated from an electroweak boson (signal), and a standard QCD…
Accurate modeling of astrophysical jets is critical for understanding accretion systems and their impact on the interstellar medium. While astronomical observations can validate models, they have limitations. Controlled laboratory…
This document introduces basics in data preparation, feature selection and learning basics for high energy physics tasks. The emphasis is on feature selection by principal component analysis, information gain and significance measures for…
The performance of taggers for hadronically decaying top quarks and $W$ bosons in $pp$ collisions at $\sqrt{s}$ = 13 TeV recorded by the ATLAS experiment at the Large Hadron Collider is presented. A set of techniques based on jet shape…
We present the current status and Monte Carlo study based performance estimates of b-jet tagging using ALICE, as obtained using both impact parameter as well as secondary vertex methods. We also address the prospects of the identification…
We present a new technique for tagging heavy-flavor jets with p_T > 500 GeV called "mu_x tagging." Current track-based methods of b-jet tagging lose efficiency and experience a large rise in fake rate in the boosted regime. Using muons from…
The rejection of forward jets originating from additional proton--proton interactions (pile-up) is crucial for a variety of physics analyses at the LHC, including Standard Model measurements and searches for physics beyond the Standard…
Machine learning has become an essential tool in jet physics. Due to their complex, high-dimensional nature, jets can be explored holistically by neural networks in ways that are not possible manually. However, innovations in all areas of…