A recent CMS search for a new resonance decaying to eμ in the mass range 110 GeV to 160 GeV finds an excess of events at 146 GeV. We interpret the search results in the context of the type-III ...two-Higgs-doublet-model. We find that the excess is moderately constrained by low-energy lepton-flavor-violation constraints, in particular the μ→eγ decay. We also find the bounds from CMS search can be superior to the low-energy constraints for the scalar mass between 110 GeV and 150 GeV, suggesting the importance of this mass range for future searches.
One burden of high energy physics data analysis is uncertainty within the measurement, both systematically and statistically. Even with sophisticated neural network techniques that are used to assist ...in high energy physics measurements, the resulting measurement may suffer from both types of uncertainties. Fortunately, most types of systematic uncertainties are based on knowledge from information such as theoretical assumptions, for which the range and behaviour are known. It has been proposed to mitigate such systematic uncertainties by using a new type of neural network called adversarial neural network (ANN) that would make the discriminator less sensitive to these uncertainties, but this has not yet been demonstrated in a real-life LHC analysis. This work investigates ANNs using as a benchmark the search for the production of four top quarks, an extremely rare physics process at the LHC and one of the important processes that can prove or disprove the Standard Model. The search for four top quarks in some cases is sensitive to large systematic uncertainties. The expected cross section upper limit for four top quark production is calculated using traditional neural networks and adversarial neural networks based on simulated proton-proton collisions within the Compact Muon Solenoid detector within Large Hadron Collider, and are compared to existing results. The improvement and further considerations to the search for rare processes at the LHC will be discussed.
In Particle Data Analysis laboratory activity, aimed at undergraduate and high school students, the student is tasked with classifying collision events which contain two muons decaying from J/ψ ...meson. The activity provides 2000 collision events from the CMS detector, selected by CMS outreach community. However, classifying 2000 collision events by hand can be a tedious task for any human, so a smaller subset of collision events are usually used in the activity to save time. We built a machine learning classifier which mimic the student's classification based on a subset of collision events handed to the student, using some information from data in corresponding collision event. The information used in this system is parts of muon trajectory, extracted from files suited for CMS event viewer on the internet, as well as the four-momentum of both muons, available from the same source. With this system, students can input a subset of graded events into the system, and the system will be able to illustrate the results if the student worked on all 2000 collision events using his/her logic. Users can download the code from our repository and follow easy instructions to replicate this activity.
Physics analysis at the Compact Muon Solenoid requires both the production of simulated events and processing of the data collected by the experiment. Since the end of the LHC Run-I in 2012, CMS has ...produced over 20 billion simulated events, from 75 thousand processing requests organised in one hundred different campaigns. These campaigns emulate different configurations of collision events, the detector, and LHC running conditions. In the same time span, sixteen data processing campaigns have taken place to reconstruct different portions of the Run-I and Run-II data with ever improving algorithms and calibrations. The scale and complexity of the events simulation and processing, and the requirement that multiple campaigns must proceed in parallel, demand that a comprehensive, frequently updated and easily accessible monitoring be made available. The monitoring must serve both the analysts, who want to know which and when datasets will become available, and the central production teams in charge of submitting, prioritizing, and running the requests across the distributed computing infrastructure. The Production Monitoring Platform (pMp) web-based service, has been developed in 2015 to address those needs. It aggregates information from multiple services used to define, organize, and run the processing requests. Information is updated hourly using a dedicated elastic database and the monitoring provides multiple configurable views to assess the status of single datasets as well as entire production campaigns. This contribution will describe the pMp development, the evolution of its functionalities, and one and half year of operational experience.
Recently, the CMS Collaboration performed a search on a new resonance decaying to \(e^\pm\mu^\mp\) in the mass range of 110 GeV to 160 GeV. The search also hints a possible excess at 146 GeV with a ...\(3.8\sigma~(2.8\sigma)\) of local (global) significance. Motivated by that, we try to interpret the results in the context of the type-III two-Higgs-doublet-model. We find that the excess is only moderately constrained by low-energy lepton-flavor-violation processes, in particular the \(\mu\to e \gamma\) decay. We also compare the CMS bounds across the entire search region against constraints of \(\mu\to e\gamma\) and \(\mu\to e\) conversion in nuclei. Our finding indicates that the collider bounds can be superior to those of low-energy processes for the scalar mass between \(110 \text{ GeV}\) and \(150 \text{ GeV}\), suggesting the importance of this mass range for future searches.
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