We perform a comprehensive analysis of a charged parent freeze-in dark matter model, focusing on scenarios where the Universe reheats to a temperature comparable to or lower than the mass scales of the theory. In such configurations, dark matter production is Boltzmann-suppressed, allowing for stronger couplings between dark matter and the Standard Model thermal bath while still reproducing the observed relic abundance. We emphasize the non-trivial interplay between the reheating temperature, the mediator and dark matter masses and the coupling strength. We show that tracking the number density evolution of both dark matter and the mediator is essential to obtain reliable predictions, including unexpected behaviors such as the mediator non-equilibration due to fast decays. Lastly, we explore the phenomenological implications of this scenario, updating constraints from LHC searches and lepton flavour-violating decays and highlighting the complementarity of these searches in probing the cosmologically viable parameter space.

In recent years, significant progress has been made in the development of automated tools that match the parameters of new physics models and the appropriate low-energy Effective Field Theories. This work introduces an extensible, hybrid tool, OperatorToC++, that combines the strengths of Mathematica and C++ to facilitate the next steps beyond the matching. OperatorToC++ efficiently tackles the complexities within the analytical matched expressions such as intricate loop-functions and lengthy sums and products involving tensor objects. It then translates and bundles the results into C++ classes and functions which provide a convenient platform for further numerical analyses. Finally, it offers the possibility of calling the compiled Wilson coefficient methods as Python functions, thus enabling to link them with the vast Python library ecosystem for High Energy Physics workflows.

We present the complete one-loop matching of the Minimal Supersymmetric Standard Model (MSSM) onto the Standard Model Effective Field Theory (SMEFT), considering the most general case for the MSSM with conserved R-parity, which has 124 free parameters. The matching is performed with the Matchete package, which integrates out all superpartners at once with non-degenerate masses, while also retaining the most general flavor structure. Our results include all correlations among the different SMEFT Wilson coefficients that are governed by supersymmetry and thus provide a basis for future systematic and global studies of the MSSM parameter space employing EFT methods. A detailed discussion is provided on the treatment of the Higgs sector and electroweak symmetry breaking, along with the reduction of redundant operators in the EFT Lagrangian to the Warsaw basis. Furthermore, we validate against existing results in the literature and present a minimal phenomenological example. As an alternative low-energy scenario, we also provide the complete one-loop matching of the MSSM onto the two-Higgs-doublet-model EFT, where the second Higgs doublet is retained in the infrared spectrum. Extensive auxiliary material, including the code utilized for the matching, is available on GitHub ( https://github.com/BSM-EFT/MSSM-to-SMEFT ).

This report, summarising work achieved in the context of the LHC Dark Matter Working Group, investigates the phenomenology of t-channel dark matter models, spanning minimal setups with a single dark matter candidate and mediator to more complex constructions closer to UV-complete models. For each considered class of models, we examine collider, cosmological and astrophysical implications. In addition, we explore scenarios with either promptly decaying or long-lived particles, as well as featuring diverse dark matter production mechanisms in the early universe. By providing a unified analysis framework, numerical tools and guidelines, this work aims to support future experimental and theoretical efforts in exploring t-channel dark matter models at colliders and in cosmology.

This report, summarising work achieved in the context of the LHC Dark Matter Working Group, investigates the phenomenology of $t$-channel dark matter models, spanning minimal setups with a single dark matter candidate and mediator to more complex constructions closer to UV-complete models. For each considered class of models, we examine collider, cosmological and astrophysical implications. In addition, we explore scenarios with either promptly decaying or long-lived particles, as well as featuring diverse dark matter production mechanisms in the early universe. By providing a unified analysis framework, numerical tools and guidelines, this work aims to support future experimental and theoretical efforts in exploring $t$-channel dark matter models at colliders and in cosmology.

Data from particle physics experiments are unique and are often the result of a very large investment of resources. Given the potential scientific impact of these data, which goes far beyond the immediate priorities of the experimental collaborations that obtain them, it is imperative that the collaborations and the wider particle physics community publish and preserve sufficient information to ensure that this impact can be realised, now and into the future. The information to be published and preserved includes the algorithms, statistical information, simulations and the recorded data. This publication and preservation requires significant resources, and should be a strategic priority with commensurate planning and resource allocation from the earliest stages of future facilities and experiments.

We develop a machine learning method for mapping data originating from both Standard Model processes and various theories beyond the Standard Model into a unified representation (latent) space while conserving information about the relationship between the underlying theories. We apply our method to three examples of new physics at the LHC of increasing complexity, showing that models can be clustered according to their LHC phenomenology: different models are mapped to distinct regions in latent space, while indistinguishable models are mapped to the same region. This opens interesting new avenues on several fronts, such as model discrimination, selection of representative benchmark scenarios, and identifying gaps in the coverage of model space.

Conversion-driven freeze-out is an appealing mechanism to explain the observed relic density while naturally accommodating the null results from direct and indirect detection due to a very weak dark matter coupling. Interestingly, the scenario predicts long-lived particles decaying into dark matter with lifetimes favorably coinciding with the range that can be resolved at the LHC. However, the small mass splitting between the long-lived particle and dark matter renders the visible decay products soft, thus challenging current search strategies. We consider four different classes of searches covering the entire range of lifetimes: heavy stable charge particles, disappearing tracks, displaced vertices, and missing energy searches. We discuss the applicability of these searches to conversion-driven freeze-out and derive current constraints highlighting their complementarity. For the displaced vertex search, we demonstrate how a slight modification of the current analysis significantly improves its sensitivity to the scenario. Published by the American Physical Society 2024

We present a new way to interpret Top Standard Model measurements going beyond the SMEFT framework. Instead of the usual paradigm in Top EFT, where the main effects come from tails in momenta distributions, we propose an interpretation in terms of new physics which only shows up at loop-level. The effects of these new states, which can be lighter than required within the SMEFT, appear as distinctive structures at high momenta, but may be suppressed at the tails of distributions. As an illustration of this phenomena, we present the explicit case of a UV model with a $\mathcal{Z}_2$ symmetry, including a Dark Matter candidate and a top-partner. This simple UV model reproduces the main features of this class of signatures, particularly a momentum-dependent form factor with more structure than the SMEFT. As the new states can be lighter than in SMEFT, we explore the interplay between the reinterpretation of direct searches for colored states and Dark Matter, and Top measurements made by ATLAS and CMS in the differential $t \bar t$ final state. We also compare our method with what one would expect using the SMEFT reinterpretation, finding that using the full loop information provides a better discriminating power.

SModelS is a public tool for fast reinterpretation of LHC searches for new physics based on a large database of simplified model results. While previous versions were limited to models with a Z2-type symmetry, such as R-parity conserving supersymmetry, version 3 can now handle arbitrary signal topologies. To this end, the tool was fully restructured and now relies on a graph-based description of simplified model topologies. In this work, we present the main conceptual changes and novel features of SModelS v3, together with the inclusion of new experimental searches for resonant production of spin-1 and spin-0 mediators with decays to quarks or to dark matter. Applying these results to a model containing two mediators, we discuss the interplay of resonance and missing energy searches, and the model's coverage by the currently available simplified model results.

Electroweak-inos, superpartners of the electroweak gauge and Higgs bosons, play a special role in supersymmetric theories. Their intricate mixing into chargino and neutralino mass eigenstates leads to a rich phenomenology, which makes it difficult to derive generic limits from LHC data. In this paper, we present a global analysis of LHC constraints for promptly decaying electroweak-inos in the context of the minimal supersymmetric standard model, exploiting the SModelS software package. Combining up to 16 ATLAS and CMS searches for which electroweak-ino efficiency maps are available in SModelS, we study which combinations maximise the sensitivity in different regions of the parameter space, how fluctuations in the data in individual analyses influence the global likelihood, and what is the resulting exclusion power of the combination compared to the analysis-by-analysis approach.

With the increasing usage of machine-learning in high-energy physics analyses, the publication of the trained models in a reusable form has become a crucial question for analysis preservation and reuse. The complexity of these models creates practical issues for both reporting them accurately and for ensuring the stability of their behaviours in different environments and over extended timescales. In this note we discuss the current state of affairs, highlighting specific practical issues and focusing on the most promising technical and strategic approaches to ensure trustworthy analysis-preservation. This material originated from discussions in the LHC Reinterpretation Forum and the 2023 PhysTeV workshop at Les Houches.

We present version 2.3 of SModelS, a public tool for the fast reinterpretation of LHC searches for new physics on the basis of simplified-model results. The main new features are a database update with the latest available experimental results for full Run 2 luminosity, comprising in particular a large variety of electroweak-ino searches, and the ability to combine likelihoods from different analyses. This enables statistically more rigorous constraints and opens the way for global likelihood analyses for LHC searches. The physics impact is demonstrated for the electroweak-ino sector of the minimal supersymmetric standard model.

Input SLHA and SModelS output (.smodels and .py) files from the paper "SModelS v2.3: enabling global likelihood analyses". The dataset comprises 18544 electroweak-ino scan points and can be used to reproduce all the plots presented in the paper. ewino_slha.tar.gz : input SLHA files including mass spectra, decay tables and cross sections ewino_smodels_v23_combSRs.tar.gz : SModelS v2.3 output with combineSRs=True and combineAnas = ATLAS-SUSY-2018-41,CMS-SUS-21-002 (primary v2.3 results used in section 4, Figs. 2-6) ewino_smodels_v23_bestSR.tar.gz : SModelS v2.3 output with combineSRs=False and combineAnas = ATLAS-SUSY-2018-41,CMS-SUS-21-002 (used only in Fig. 2) ewino_smodels_v21.tar.gz : SModelS v2.1 output with combineSRs=False (used only in Fig. 2) Changes w.r.t. version 1: removed 13 SLHA input files, which had wrong neutralino2 decays due to a bug in softsusy 4.1.11; recomputed smodels_v23_combSRs results with sigmacut=1e-3 fb. See comments on https://scipost.org/submissions/2306.17676v2/ for details.

We make the case for the systematic, reliable preservation of event-wise data, derived data products, and executable analysis code. This preservation enables the analyses' long-term future reuse, in order to maximise the scientific impact of publicly funded particle-physics experiments. We cover the needs of both the experimental and theoretical particle physics communities, and outline the goals and benefits that are uniquely enabled by analysis recasting and reinterpretation. We also discuss technical challenges and infrastructure needs, as well as sociological challenges and changes, and give summary recommendations to the particle-physics community.

The measured branching fractions of $B$-mesons into leptonic final states derived by the LHCb collaboration hint towards the breakdown of lepton flavour universality. In this work we take at face value the so-called $R_{D^{(*)}}$ observables that are defined as the ratios of neutral $B$-meson charged-current decays into a charged $D$-meson, a charged lepton and a neutrino final state in the tau and muon channels. A well-studied and simple solution to this charged current anomaly is to introduce a scalar leptoquark $S_1$ that couples to the second and third generation of fermions. We investigate how $S_1$ can also serve as a mediator between the Standard Model and a dark sector. We study this scenario in detail and estimate the constraints arising from collider searches for leptoquarks, collider searches for missing energy signals, direct detection experiments and the dark matter relic abundance. We stress that the production of a pair of leptoquarks that decays into different final states (i.e. the commonly called mixed channels) provides critical information for identifying the underlying dynamics, and we exemplify this by studying the $t \tau b \nu$ and the resonant $S_1$ plus missing energy channels. We find that direct detection data provides non-negligible constraints on the leptoquark coupling to the dark sector, which in turn affects the relic abundance. We also show that the correct relic abundance can not only arise via standard freeze-out, but also through conversion-driven freeze-out. We illustrate the rich phenomenology of the model with a few selected benchmark points, providing a broad stroke of the interesting connection between lepton flavour violation and dark matter.

A bstract We present version 2 of SM odel S, a program package for the fast reinterpretation of LHC searches for new physics on the basis of simplified model results. The major novelty of the SM odel S v2 series is an extended topology description with a flexible number of particle attributes, such as spin, charge, decay width, etc. This enables, in particular, the treatment of a wide range of signatures with long-lived particles. Moreover, constraints from prompt and long-lived searches can be evaluated simultaneously in the same run. The current database includes results from searches for heavy stable charged particles, disappearing tracks, displaced jets and displaced leptons, in addition to a large number of prompt searches. The capabilities of the program are demonstrated by two physics applications: constraints on long-lived charged scalars in the scotogenic model, and constraints on the electroweak-ino sector in the Minimal Supersymmetric Standard Model.

Abstract We present a novel algorithm to identify potential dispersed signals of new physics in the slew of published LHC results. It employs a random walk algorithm to introduce sets of new particles, dubbed “proto-models”, which are tested against simplified-model results from ATLAS and CMS (exploiting the SModelS software framework). A combinatorial algorithm identifies the set of analyses and/or signal regions that maximally violates the SM hypothesis, while remaining compatible with the entirety of LHC constraints in our database. Demonstrating our method by running over the experimental results in the SModelS database, we find as currently best-performing proto-model a top partner, a light-flavor quark partner, and a lightest neutral new particle with masses of the order of 1.2 TeV, 700 GeV and 160 GeV, respectively. The corresponding global p-value for the SM hypothesis is p global ≈ 0.19; by construction no look-elsewhere effect applies.

SModelS is an automatized tool enabling the fast interpretation of simplified model results from the LHC within any model of new physics respecting a $\mathbb{Z}_2$ symmetry. In this contribution, we report on two important updates of SModelS during 2020: the extension of the SModelS' database with 13 ATLAS and 10 CMS analyses, including 5 ATLAS and 1 CMS analyses at full Run~2 luminosity, and the ability to use full likelihoods now provided by ATLAS in the form of pyhf JSON files. Moreover, we briefly explain how to use SModelS and give an overview of ongoing developments.