Determining the form of the Higgs potential is one of the most exciting challenges of modern particle physics. Higgs pair production directly probes the Higgs self-coupling and should be observed in the near future at the High-Luminosity LHC. We explore how to improve the sensitivity to physics beyond the Standard Model through per-event kinematics for di-Higgs events. In particular, we employ machine learning through simulation-based inference to estimate per-event likelihood ratios and gauge potential sensitivity gains from including this kinematic information. In terms of the Standard Model Effective Field Theory, we find that adding a limited number of observables can help to remove degeneracies in Wilson coefficient likelihoods and significantly improve the experimental sensitivity.

United States

Radha Mastandrea

Benjamin Nachman

Germany

Tilman Plehn

Constraining the Higgs potential with neural simulation-based inference for di-Higgs production

In this work, we consider the case of a strongly coupled dark/hidden sector, which extends the Standard Model (SM) by adding an additional non-Abelian gauge group. These extensions generally contain matter fields, much like the SM quarks, and gauge fields similar to the SM gluons. We focus on the exploration of such sectors where the dark particles are produced at the LHC through a portal and undergo rapid hadronization within the dark sector before decaying back, at least in part and potentially with sizeable lifetimes, to SM particles, giving a range of possibly spectacular signatures such as emerging or semi-visible jets. Other, non-QCD-like scenarios leading to soft unclustered energy patterns or glueballs are also discussed. After a review of the theory, existing benchmarks and constraints, this work addresses how to build consistent benchmarks from the underlying physical parameters and present new developments for the pythia Hidden Valley module, along with jet substructure studies. Finally, a series of improved search strategies is presented in order to pave the way for a better exploration of the dark showers at the LHC.

France

Guillaume Albouy

Canada

Jared Barron

Taiwan

Hugues Beauchesne

Elias Bernreuther

United Kingdom

Marcella Bona

Switzerland

Cesare Cazzaniga

Cari Cesarotti

Timothy Cohen

Annapaola Cosa

David Curtin

Zeynep Demiragli

Sweden

Caterina Doglioni

Alison Elliot

Karri DiPetrillo

Florian Eble

Carlos Erice

Chad Freer

Aran Garcia-Bellido

Caleb Gemmell

Marie-Hélène Genest

Italy

Giovanni Cortona

CERN

Giuliano Gustavino

Nicoline Hemme

Tova Holmes

South Africa

Deepak Kar

Simon Knapen

Austria

Suchita Kulkarni

Luca Lavezzo

Belgium

Steven Lowette

Benedikt Maier

Seán Mee

Stephen Mrenna

India

Harikrishnan Nair

Jeremi Niedziela

Christos Papageorgakis

Nukulsinh Parmar

Christoph Paus

Kevin Pedro

Ana Peixoto

Alexx Perloff

Christiane Scherb

Pedro Schwaller

Jessie Shelton

Akanksha Singh

Sukanya Sinha

Torbjörn Sjöstrand

Aris Spourdalakis

Daniel Stolarski

Matthew Strassler

Netherlands

Andrii Usachov

Carlos Sierra

Christopher Verhaaren

Long Wang

Theory, phenomenology, and experimental avenues for dark showers: a Snowmass 2021 report

Confining dark sectors with pseudo-conformal dynamics produce SUEPs, or Soft Unclustered Energy Patterns, at colliders: isotropic dark hadrons with soft and democratic energies. We target the experimental nightmare scenario, SUEPs in exotic Higgs decays, where all dark hadrons decay promptly to SM hadrons. First, we identify three promising observables: the charged particle multiplicity, the event ring isotropy, and the matrix of geometric distances between charged tracks. Their patterns can be exploited through a cut-and-count search, supervised machine learning, or an unsupervised autoencoder. We find that the HL-LHC will probe exotic Higgs branching ratios at the per-cent level, even without a detailed knowledge of the signal features. Our techniques can be applied to other SUEP searches, especially the unsupervised strategy, which is independent of overly specific model assumptions and the corresponding precision simulations.

Gregor Kasieczka

Unsupervised hadronic SUEP at the LHC

We provide a comprehensive global analysis of Run II top measurements at the LHC in terms of dimension-6 operators. A distinctive feature of the top sector as compared to the Higgs-electroweak sector is the large number of four-quark operators. We discuss in detail how they can be tested and how quadratic terms lead to a stable limit on each individual Wilson coefficient. Predictions for all observables are computed at NLO in QCD. Our SFitter analysis framework features a detailed error treatment, including correlations between uncertainties.

Ilaria Brivio

Sebastian Bruggisser

Fabio Maltoni

Rhea Moutafis

Eleni Vryonidou

Susanne Westhoff

China

Cen Zhang

O new physics, where art thou? A global search in the top sector

Simplified template cross sections define a framework for the measurement and dissemination of kinematic information in Higgs measurements. We benchmark the currently proposed setup in an analysis of dimension-6 effective field theory operators for W H production. Calculating the Fisher information allows us to quantify the sensitivity of this framework to new physics and study its dependence on phase space. New machine- learning techniques let us compare the simplified template cross section framework to the full, high-dimensional kinematic information. We show that the way in which we truncate the effective theory has a sizable impact on the definition of the optimal simplified template cross sections.

Johann Brehmer

Sally Dawson

Samuel Homiller

Felix Kling

Benchmarking simplified template cross sections in W H production

Dark matter scenarios with spin-0 mediators in the <math><mi>s</mi></math> channel have be tested in well-established processes with missing energy, such as top-pair- and mono-jet-associated production. We suggest electroweak single top production in association with a dark matter pair as an alternative channel. Based on a realistic analysis for the LHC at 13 TeV, we demonstrate how to efficiently discriminate between the signal and standard model background using event kinematics. With <math><mrow><mn>300</mn><mtext> </mtext><mtext> </mtext><msup><mrow><mi>fb</mi></mrow><mrow><mo>−</mo><mn>1</mn></mrow></msup></mrow></math> <math><mrow><mo>(</mo><mn>3</mn><mtext> </mtext><mtext> </mtext><msup><mrow><mi>ab</mi></mrow><mrow><mo>−</mo><mn>1</mn></mrow></msup><mo>)</mo></mrow></math> of data, on-shell scalar mediators with a coupling strength <math><msubsup><mi>g</mi><mi>S</mi><mi>t</mi></msubsup><mo>=</mo><mn>1</mn></math> to top quarks can be probed up to masses of 180(360) GeV. Single-top-associated dark matter production should thus be included as an independent search channel in the LHC dark matter program.

Jennifer M. Thompson

Dark matter from electroweak single top production

The measurement of triple Higgs coupling is a key benchmark for the Large Hadron Collider (LHC) and future colliders. It directly probes the Higgs potential and its fundamental properties in connection to new physics beyond the Standard Model. There exist two phase space regions with an enhanced sensitivity to the Higgs self-coupling, the Higgs pair production threshold, and an intermediate top pair threshold. We show how the invariant mass distribution of the Higgs pair offers a systematic way to extract the Higgs self-coupling, focusing on the leading channel <math><mrow><mi>p</mi><mi>p</mi><mo>→</mo><mi>h</mi><mi>h</mi><mo>+</mo><mi>X</mi><mo>→</mo><mi>b</mi><mover><mrow><mi>b</mi></mrow><mrow><mo>¯</mo></mrow></mover><mi>γ</mi><mi>γ</mi><mo>+</mo><mi>X</mi></mrow></math>. We utilize new features of the signal events at higher energies and estimate the potential of a high-energy upgrade of the LHC and a future hadron collider with realistic simulations. We find that the high-energy upgrade of the LHC to 27 TeV would reach a <math><mrow><mn>5</mn><mi>σ</mi></mrow></math> observation with an integrated luminosity of <math><mrow><mn>2.5</mn><mtext> </mtext><mtext> </mtext><msup><mrow><mi>ab</mi></mrow><mrow><mo>−</mo><mn>1</mn></mrow></msup></mrow></math>. It would have the potential to reach 15% (30%) accuracy at the 68% (95%) confidence level to determine the Standard Model (SM) Higgs boson self-coupling. A future 100 TeV collider could improve the self-coupling measurement to better than 5% (10%) at the 68% (95%) confidence level.

Dorival Gonçalves

Tao Han

Japan

Michihisa Takeuchi

Higgs boson pair production at future hadron colliders: From kinematics to dynamics

Measuring the <math><mi>C</mi><mi>P</mi></math> symmetry in the Higgs sector is one of the key tasks of the LHC and a crucial ingredient for precision studies, for example in the language of effective Lagrangians. We systematically analyze which LHC signatures offer dedicated <math><mi>C</mi><mi>P</mi></math> measurements in the Higgs-gauge sector and discuss the nature of the information they provide. Based on the Fisher information measure, we compare the maximal reach for <math><mi>C</mi><mi>P</mi></math>-violating effects in weak boson fusion, associated <math><mi>Z</mi><mi>H</mi></math> production, and Higgs decays into four leptons. We find a subtle balance between more theory-independent approaches and more powerful analysis channels, indicating that rigorous evidence for <math><mi>C</mi><mi>P</mi></math> violation in the Higgs-gauge sector will likely require a multistep process.

Tim M. P. Tait

Better Higgs-<math><mrow><mi>C</mi><mi>P</mi></mrow></math> tests through information geometry

Machine learning based on convolutional neural networks can be used to study jet images from the LHC. Top tagging in fat jets offers a well-defined framework to establish our DeepTop approach and compare its performance to QCD-based top taggers. We first optimize a network architecture to identify top quarks in Monte Carlo simulations of the Standard Model production channel. Using standard fat jets we then compare its performance to a multivariate QCD-based top tagger. We find that both approaches lead to comparable performance, establishing convolutional networks as a promising new approach for multivariate hypothesis-based top tagging.

Michael Russell

Torben Schell

Deep-learning top taggers or the end of QCD?

The effective Lagrangian expansion provides a framework to study effects of new physics at the electroweak scale. To make full use of LHC data in constraining higher-dimensional operators we need to include both the Higgs and the electroweak gauge sector in our study. We first present an analysis of the relevant di-boson production LHC results to update constraints on triple gauge boson couplings. Our bounds are several times stronger than those obtained from LEP data. Next, we show how in combination with Higgs measurements the triple gauge vertices lead to a significant improvement in the entire set of operators, including operators describing Higgs couplings.