arXiv subjects

Ahmed Hammad

Publications and source records attributed to Ahmed Hammad.

6 recordsLinked to original sources

arXiv2026

Hunting the Unseen: Deep Learning Analysis for Semi-Visible Jet Tagging

Semi-Visible Jets (SVJs) constitute a distinctive collider signature of strongly interacting dark sectors, embedding Dark Matter candidates, wherein jets contain both visible Standard Model objects and invisible dark hadrons, giving rise to correlated jet activity and missing transverse momentum. In this work, we investigate SVJs produced through a heavy Z' mediator and perform an study over a representative set of benchmark scenarios spanning different mediator masses and dark sector parameters in the context of so-called Hidden Valley Models. To characterise the signal, we combine global event kinematics with jet substructure observables, including the primary Lund Jet Plane (LJP), the two-point energy correlation, angularity, and charged hadron multiplicity. These representations are used to train five Deep Learning classifiers for SVJ vs standard jet discrimination: a Vision Transformer operating on LJP images, a JetLOV network based on a hierarchical clustering tree, a Multi-Layer Perceptron using high level observables, and two multimodal networks that combine the image-based or hierarchical representations of the radiation pattern with the high jet-level observables. This enables a direct combination of global kinematics, radiation patterns, and jet clustering structure. We find that global kinematic observables outperform the LJP and hierarchical jet representations, with the latter providing stronger discrimination than LJP images. Combining these complementary representations with global kinematics yields the best overall performance. More broadly, this study shows that unlocking the full discovery potential of SVJs would benefit from going beyond global kinematics to exploit the rich information encoded in their internal structure, providing a benchmark for future searches at the Large Hadron Collider.

hep-ph↗

arXiv2026

Language-Guided Hypotheses Generation for Sparse SMEFT Analyses

Global fits of the Standard Model Effective Field Theory are challenged by the large number of operators, while any given database constrains only a small subset. Selecting relevant operator hypotheses therefore requires theoretical insight into operator correlations and the sensitivity of observables. We present llm4smeft, an open source framework that addresses this problem by combining a language model, fine-tuned on the SMEFT literature, with retrieval augmented generation based on quantitative summaries of SMEFiT package global fits. Given a set of observables, the framework proposes candidate relevant operators together with their corresponding Fisher information, while retrieval ensures that model outputs are grounded in existing fit results whenever available. The framework runs in an interactive mode in which accepted hypotheses are stored in a growing knowledge base. We publicly release the llm4smeft package together with the fine-tuned language model, in which the entire framework runs locally, requiring neither internet access nor paid cloud services.

hep-ph↗

arXiv2026

Articulating Assumptions in AI-Generated Scientific Analyses through Task Decomposition

Scientific results produced by LLM generated analysis code must be understandable and reproducible. However, uncertainty can arise at different stages of the process, both in the original natural language specification and in the generated implementation. As a result, even executable code may not provide a clear understanding of which quantities are being computed or which assumptions determine the final results. To address this challenge, we introduce quantity grounded semantic differencing, a multi-agent framework for analyzing and comparing scientific programs generated by LLMs. The framework assigns code generation, execution, tracing, and validation to separate agents, allowing it to reconstruct how key output quantities are produced and to identify differences between the intended analysis and the implemented code. We also introduce a module that inspects ambiguities in the initial user instruction and suggests alternative rewrites before code generation. Its modular design enables application to different scientific domains by replacing domain specific resources while preserving the same workflow. We validate the framework on representative collider physics analyses. The results demonstrate that the modular task decomposition enhances both transparency and reliability relative to the previous single prompt approach, while enabling substantially smaller models to execute the complete workflow.

cs.SE↗

arXiv2026

Predicting Three Generations of Fermions: Discovery Prospects of the Bilepton Model

We study the production of pairs of doubly-charged bileptons and assess their discovery potential in light of the integrated luminosities available at the High-Luminosity LHC. The production rates are governed primarily by the bilepton mass, $(m_Y)$, and the mass of the exotic heavy quarks, $(m_D)$. We consider two complementary production channels: (i) direct bilepton pair production and (ii) bilepton production mediated through heavy-quark decays. Notably, the latter typically yields significantly enhanced cross sections and gives rise to distinctive LHC signatures, even when the bileptons are produced off-shell. The two mechanisms therefore probe complementary regions of parameter space, with direct production being predominantly sensitive to $m_Y$, while the heavy-quark-mediated channel depends mainly on $m_D$. Owing to the essentially background-free signature of four energetic leptons at the LHC, we show that Run-2 data allow a discovery only for $m_D \lesssim 1\,\mathrm{TeV}$, whereas the HL-LHC can achieve a $5\sigma$ discovery up to $m_D \lesssim 2.5\,\mathrm{TeV}$ (nearly independently of $m_Y$) and/or for $m_Y \lesssim 2\,\mathrm{TeV}$ (even if $D$ is heavy).

hep-ph↗

arXiv2019

Searching for long-lived particles beyond the Standard Model at the Large Hadron Collider

Particles beyond the Standard Model (SM) can generically have lifetimes that are long compared to SM particles at the weak scale. When produced at experiments such as the Large Hadron Collider (LHC) at CERN, these long-lived particles (LLPs) can decay far from the interaction vertex of the primary proton-proton collision. Such LLP signatures are distinct from those of promptly decaying particles that are targeted by the majority of searches for new physics at the LHC, often requiring customized techniques to identify, for example, significantly displaced decay vertices, tracks with atypical properties, and short track segments. Given their non-standard nature, a comprehensive overview of LLP signatures at the LHC is beneficial to ensure that possible avenues of the discovery of new physics are not overlooked. Here we report on the joint work of a community of theorists and experimentalists with the ATLAS, CMS, and LHCb experiments --- as well as those working on dedicated experiments such as MoEDAL, milliQan, MATHUSLA, CODEX-b, and FASER --- to survey the current state of LLP searches at the LHC, and to chart a path for the development of LLP searches into the future, both in the upcoming Run 3 and at the High-Luminosity LHC. The work is organized around the current and future potential capabilities of LHC experiments to generally discover new LLPs, and takes a signature-based approach to surveying classes of models that give rise to LLPs rather than emphasizing any particular theory motivation. We develop a set of simplified models; assess the coverage of current searches; document known, often unexpected backgrounds; explore the capabilities of proposed detector upgrades; provide recommendations for the presentation of search results; and look towards the newest frontiers, namely high-multiplicity "dark showers", highlighting opportunities for expanding the LHC reach for these signals.

hep-ex↗

arXiv2016

Large BR(h -> tau mu) in Supersymmetric Models

We analyze the Lepton Flavor Violating (LFV) Higgs decay h -> tau mu in three supersymmetric models: Minimal Supersymmetric Standard Model (MSSM), Supersymmetric Seesaw Model (SSM), and Supersymmetric B-L model with Inverse Seesaw (BLSSM-IS). We show that in generic MSSM, with non-universal slepton masses and/or trilinear couplings, it is not possible to enhance BR(h -> tau mu) without violating the experimental bound on the BR(tau -> mu gamma). In SSM, where flavor mixing is radiatively generated, the LFV process mu -> e gamma strictly constrains the parameter space and the maximum value of BR(h -> tau mu) is of order 10^-10, which is extremely smaller than the recent results reported by the CMS and ATLAS experiments. In BLSSM-IS, with universal soft SUSY breaking terms at the grand unified scale, we emphasize that the measured values of BR(h -> tau mu) can be accommodated in a wide region of parameter space without violating LFV constraints. Thus, confirming the LFV Higgs decay results will be a clear signal of BLSSM-IS type of models. Finally, the signal of h -> tau mu in the BLSSM-IS at the LHC, which has a tiny background, is analyzed.

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