Disentangling Boosted Higgs Boson Production Modes with Machine Learning

Higgs Bosons produced via gluon-gluon fusion (ggF) with large transverse momentum ($p_T$) are sensitive probes of physics beyond the Standard Model. However, high $p_T$ Higgs Boson production is contaminated by a diversity of production modes other than ggF: vector boson fusion, production of a Higgs boson in association with a vector boson, and production of a Higgs boson with a top-quark pair. Combining jet substructure and event information with modern machine learning, we demonstrate the ability to focus on particular production modes. These tools hold great discovery potential for boosted Higgs bosons produced via ggF and may also provide additional information about the Higgs Boson sector of the Standard Model in extreme phase space regions for other production modes as well.Comment: 17 pages, 9 figure

Exploring the Universality of Hadronic Jet Classification

The modeling of jet substructure significantly differs between Parton Shower Monte Carlo (PSMC) programs. Despite this, we observe that machine learning classifiers trained on different PSMCs learn nearly the same function. This means that when these classifiers are applied to the same PSMC for testing, they result in nearly the same performance. This classifier universality indicates that a machine learning model trained on one simulation and tested on another simulation (or data) will likely be optimal. Our observations are based on detailed studies of shallow and deep neural networks applied to simulated Lorentz boosted Higgs jet tagging at the LHC.Comment: 25 pages, 7 figures, 7 table

Liquid biopsy genotyping in lung cancer: ready for clinical utility?

Liquid biopsy is a blood test that detects evidence of cancer cells or tumor DNA in the circulation. Despite complicated collection methods and the requirement for technique-dependent platforms, it has generated substantial interest due, in part, to its potential to detect driver oncogenes such as epidermal growth factor receptor (EGFR) mutants in lung cancer. This technology is advancing rapidly and is being incorporated into numerous EGFR tyrosine kinase inhibitor (EGFR-TKI) development programs. It appears ready for integration into clinical care. Recent studies have demonstrated that biological fluids such as saliva and urine can also be used for detecting EGFR mutant DNA through application other user-friendly techniques. This review focuses on the clinical application of liquid biopsies to lung cancer genotyping, including EGFR and other targets of genotype-directed therapy and compares multiple platforms used for liquid biopsy

Sensitivity Reach on the Heavy Neutral Leptons and τ\tau-Neutrino Mixing ∣UτN∣2|U_{\tau N}|^2 at the HL-LHC

The model of heavy neutral leptons (HNLs) is one of the well-motivated models beyond the standard model (BSM) from both theoretical and phenomenological point of views. It is an indispensable ingredient to explain the puzzle of tiny neutrino masses and the origin of the matter-antimatter asymmetry in our Universe, based on the models in which the simplest Type-I seesaw mechanism can be embedded. The HNL with a mass up to the electroweak scale is an attractive scenario which can be readily tested in present or near-future experiments including the LHC. In this work, we study the decay rates of HNLs and find the sensitive parameter space of the mixing angles between the active neutrinos and HNLs. Since the mixing between $\nu_{\tau}$ and HNL is not well established in literature compared with those of $\nu_e$ and $\nu_{\mu}$ for the HNL of mass in the electroweak scale, we focus on the channel $pp\rightarrow W^{\pm(\ast)} + X\rightarrow \tau^{\pm} N + X$ to search for HNLs at the LHC 14 TeV. The targeted signature consists of three prompt charged leptons, which include at least two tau leptons. After the signal-background analysis, we further set sensitivity bounds on the mixing $|U_{\tau N}|^2$ with $M_N$ at High-Luminosity LHC (HL-LHC). We predict the testable bounds from HL-LHC can be stronger than the previous LEP constraints and Electroweak Precision Data (EWPD), especially for $M_N \lesssim$ 50 GeV can reach down to $|U_{\tau N}|^2 \approx 2\times 10^{-6}$.Comment: Published versio