Related papers: Class Imbalance Techniques for High Energy Physics
We introduce a novel technique designed to look for signatures of new physics in vector boson fusion processes at the TeV scale. This functions by measuring the polarization of the vector bosons to determine the relative longitudinal to…
Class-imbalance is a common problem in machine learning practice. Typical Imbalanced Learning (IL) methods balance the data via intuitive class-wise resampling or reweighting. However, previous studies suggest that beyond class-imbalance,…
High contrast matter-wave interferometry is essential in various fundamental quantum mechanical experiments as well as for technical applications. Thereby, contrast and sensitivity are typically reduced by decoherence and dephasing effects.…
There are many real-world classification problems wherein the issue of data imbalance (the case when a data set contains substantially more samples for one/many classes than the rest) is unavoidable. While under-sampling the problematic…
Higgs boson is a fundamental particle, and the classification of Higgs signals is a well-known problem in high energy physics. The identification of the Higgs signal is a challenging task because its signal has a resemblance to the…
The existence of scale invariant physics would lead to new phenomena in particle physics that could be detected at the LHC. In this paper we exploit the effects of these unparticles in $WW \to WW$ scattering. From the requirement of…
Class imbalance poses a significant challenge in classification tasks, where traditional approaches often lead to biased models and unreliable predictions. Undersampling and oversampling techniques have been commonly employed to address…
We analyse some features of WW scattering processes at LHC. The severe cancellations between fusion diagrams and the other contributions evidence the necessity of complete calculations for studying the high WW invariant mass region and…
The polarization of a top-quark can be sensitive to new physics beyond the standard model. We propose a novel method to measure top-quark polarization, based on the charged lepton energy fraction in top-quark decay, and illustrate the…
We review in this paper the research status on testing the completeness of Quantum mechanics in High Energy Physics, especially on the Bell Inequalities. We briefly introduce the basic idea of Einstein, Podolsky, and Rosen paradox and the…
Most state-of-the-art computer vision models heavily depend on data. However, many datasets exhibit extreme class imbalance which has been shown to negatively impact model performance. Among the training-time and data-generation solutions…
A precise measurement of the Higgs boson couplings to bottom and top quarks is of paramount importance during the upcoming LHC runs. We present a comprehensive analysis for the Higgs production process in association with a…
Despite extensive research spanning several decades, class imbalance is still considered a profound difficulty for both machine learning and deep learning models. While data oversampling is the foremost technique to address this issue,…
The application of quantum information methods to high energy physics has recently been gaining traction. In particular, reconstructing density matrices and measuring entanglement have been investigated for top quark decays and Higgs…
Strong WW scattering at the LHC is discussed as a manifestation of electroweak symmetry breaking in the absence of a light Higgs boson. The general framework of the Higgs mechanism -- with or without a Higgs boson -- is reviewed, and…
A selection of unfolding methods commonly used in High Energy Physics is compared. The methods discussed here are: bin-by-bin correction factors, matrix inversion, template fit, Tikhonov regularisation and two examples of iterative methods.…
Vector boson scatterings are fundamental processes to shed light on the nature of the electroweak symmetry breaking mechanism. Deviations from the Standard Model predictions on the corresponding observables can be interpreted in terms of…
The standard model taken with a momentum space cut-off may be viewed as an effective low energy theory. The structure of it and its known parameters can give us hints for relations between these parameters. In the present investigation the…
We experimentally demonstrate a method to control the relative amount of quantum and classical energy correlations between two photons from a pair emitted by spontaneous parametric downconversion. Decoherence in the energy basis is achieved…
The vast majority of real world classification problems are imbalanced, meaning there are far fewer data from the class of interest (the positive class) than from other classes. We propose two machine learning algorithms to handle highly…