skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.


Title: Model selection and signal extraction using Gaussian Process regression
A bstract We present a novel computational approach for extracting localized signals from smooth background distributions. We focus on datasets that can be naturally presented as binned integer counts, demonstrating our procedure on the CERN open dataset with the Higgs boson signature, from the ATLAS collaboration at the Large Hadron Collider. Our approach is based on Gaussian Process (GP) regression — a powerful and flexible machine learning technique which has allowed us to model the background without specifying its functional form explicitly and separately measure the background and signal contributions in a robust and reproducible manner. Unlike functional fits, our GP-regression-based approach does not need to be constantly updated as more data becomes available. We discuss how to select the GP kernel type, considering trade-offs between kernel complexity and its ability to capture the features of the background distribution. We show that our GP framework can be used to detect the Higgs boson resonance in the data with more statistical significance than a polynomial fit specifically tailored to the dataset. Finally, we use Markov Chain Monte Carlo (MCMC) sampling to confirm the statistical significance of the extracted Higgs signature.  more » « less
Award ID(s):
2209460
PAR ID:
10401727
Author(s) / Creator(s):
; ; ;
Date Published:
Journal Name:
Journal of High Energy Physics
Volume:
2023
Issue:
2
ISSN:
1029-8479
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. null (Ed.)
    A bstract A search is presented for the production of the Standard Model Higgs boson in association with a high-energy photon. With a focus on the vector-boson fusion process and the dominant Higgs boson decay into b -quark pairs, the search benefits from a large reduction of multijet background compared to more inclusive searches. Results are reported from the analysis of 132 fb − 1 of pp collision data at $$ \sqrt{s} $$ s = 13 TeV collected with the ATLAS detector at the LHC. The measured Higgs boson signal yield in this final-state signature is 1 . 3 ± 1 . 0 times the Standard Model prediction. The observed significance of the Higgs boson signal above the background is 1 . 3 standard deviations, compared to an expected significance of 1 . 0 standard deviations. 
    more » « less
  2. Abstract The possibility in supersymmetric scenarios that the dark matter candidate is a Higgsino-like neutralino means that its production can be associated with Higgs bosons. Taking advantage of this fact, we propose a LHC search strategy for gluinos with $$\tau $$ τ leptons in the final state, coming from the decay of a Higgs boson. We consider the strong production of a pair of gluinos, one of which decays into the Higgsino plus jets while the other decays into the bino plus jets. In turn, this bino decays into the Higgsino plus a Higgs boson which finally decays into a $$\tau $$ τ -lepton pair. Therefore, the experimental signature under study consists of 4 jets, 2 $$\tau $$ τ leptons, and a large amount of missing transverse energy. This work represents a proof of principle of a search that is sensitive to a spectrum such that the gluino does not directly decay to the dark matter candidate but to an intermediate electroweakino that then produces Higgs bosons in its subsequent decay. Our cut-based search strategy allows us to reach, for a LHC center-of-mass energy of 14 TeV and a total integrated luminosity of 1 ab $$^{-1}$$ - 1 , significances of up to 2 standard deviations, considering systematic uncertainties in the SM background of 30%. The projections for 3 ab $$^{-1}$$ - 1 are encouraging, with significances at the evidence level, which in more optimistic experimental scenarios could exceed 4 standard deviations. 
    more » « less
  3. Labeled data can be expensive to acquire in several application domains, including medical imaging, robotics, computer vision and wireless networks to list a few. To efficiently train machine learning models under such high labeling costs, active learning (AL) judiciously selects the most informative data instances to label on-the-fly. This active sampling process can benefit from a statistical function model, that is typically captured by a Gaussian process (GP) with well-documented merits especially in the regression task. While most GP-based AL approaches rely on a single kernel function, the present contribution advocates an ensemble of GP (EGP) models with weights adapted to the labeled data collected incrementally. Building on this novel EGP model, a suite of acquisition functions emerges based on the uncertainty and disagreement rules. An adaptively weighted ensemble of EGP-based acquisition functions is advocated to further robustify performance. Extensive tests on synthetic and real datasets in the regression task showcase the merits of the proposed EGP-based approaches with respect to the single GP-based AL alternatives. 
    more » « less
  4. A bstract A search is presented for a heavy W′ boson resonance decaying to a B or T vector-like quark and a t or a b quark, respectively. The analysis is performed using proton-proton collisions collected with the CMS detector at the LHC. The data correspond to an integrated luminosity of 138 fb − 1 at a center-of-mass energy of 13 TeV. Both decay channels result in a signature with a t quark, a Higgs or Z boson, and a b quark, each produced with a significant Lorentz boost. The all-hadronic decays of the Higgs or Z boson and of the t quark are selected using jet substructure techniques to reduce standard model backgrounds, resulting in a distinct three-jet W′ boson decay signature. No significant deviation in data with respect to the standard model background prediction is observed. Upper limits are set at 95% confidence level on the product of the W′ boson cross section and the final state branching fraction. A W′ boson with a mass below 3.1 TeV is excluded, given the benchmark model assumption of democratic branching fractions. In addition, limits are set based on generalizations of these assumptions. These are the most sensitive limits to date for this final state. 
    more » « less
  5. null (Ed.)
    A bstract A search for standard model Higgs bosons (H) produced with transverse momentum ( p T ) greater than 450 GeV and decaying to bottom quark-antiquark pairs ( $$ \mathrm{b}\overline{\mathrm{b}} $$ b b ¯ ) is performed using proton-proton collision data collected by the CMS experiment at the LHC at $$ \sqrt{s} $$ s = 13 TeV. The data sample corresponds to an integrated luminosity of 137 fb − 1 . The search is inclusive in the Higgs boson production mode. Highly Lorentz-boosted Higgs bosons decaying to $$ \mathrm{b}\overline{\mathrm{b}} $$ b b ¯ are reconstructed as single large-radius jets, and are identified using jet substructure and a dedicated b tagging technique based on a deep neural network. The method is validated with Z → $$ \mathrm{b}\overline{\mathrm{b}} $$ b b ¯ decays. For a Higgs boson mass of 125 GeV, an excess of events above the background assuming no Higgs boson production is observed with a local significance of 2.5 standard deviations ( σ ), while the expectation is 0.7. The corresponding signal strength and local significance with respect to the standard model expectation are μ H = 3 . 7 ± 1 . 2(stat) $$ {}_{-0.7}^{+0.8} $$ − 0.7 + 0.8 (syst) $$ {}_{-0.5}^{+0.8} $$ − 0.5 + 0.8 (theo) and 1 . 9 σ . Additionally, an unfolded differential cross section as a function of Higgs boson p T for the gluon fusion production mode is presented, assuming the other production modes occur at the expected rates. 
    more » « less