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A. Zaborenko

Publications and source records attributed to A. Zaborenko.

9 recordsLinked to original sources

Geometric algebra as the input language of collider foundation models

A hard hadron-collider event is represented here as a single geometric object: the kinematics and object-type labels of all reconstructed final-state particles in one multivector $\evMV$, one $\Cl(1,3)\otimes\Vflav$ slot per object, whose higher grades the algebra generates from the measured four-momenta --- rather than as a list of four-momenta with label fields attached. The setting is geometric algebra, whose grade decomposition organises essentially every observable in current use: invariants at grade zero, four-momenta at grade one, decay-plane bivectors at grade two, oriented three-volumes at grade three, the CP-odd pseudoscalar at grade four. The high-level invariants, the low-level recipe and the equivariant-network inputs are recovered as projections onto specific grades. A per-grade dictionary of $32$ classical observables and an inventory of the symmetries acting on $\evMV$ are provided. Theorem settles which Lorentz invariants the higher grades unlock: none beyond $\{p_i\!\cdot\!p_j,\,m_i^2\}$, the CP-odd sign of the pseudoscalar being the one genuine channel. The representation is intended as a uniform input layer for foundation models of collider physics, and the realisations demonstrated here occupy two rungs of a ladder: the higher grades are formed inside the network from the per-object slots, or selected grade-two and grade-three objects are supplied at the input layer. It is demonstrated on the resonance-topology separation of $pp\!\to\!tWb$ with a Lorentz-equivariant multivector transformer of L-GATr type. An ablation over eight input representations separates what supplying algebraic content explicitly can and cannot buy: content reconstructible from the measured momenta unlocks no new invariant, by the theorem, whereas a fixed reference blade encoding the beam plane carries structure the momenta do not contain.

hep-ph

A Methodology for Developing Foundational Transformer Models in Collider Physics Analysis

We present a methodology for training foundational transformer models capable of processing collider data with diverse kinematic signatures. Our universal foundation model is designed for simultaneous analysis of all processes involving from one to four top-quarks production with their corresponding background processes. The approach employs multi-task pre-training on combined datasets of simulated events, enabling the model to capture the full spectrum of interaction physics while extracting universal patterns across different final states prior to task-specific fine-tuning. This unified architecture eliminates the need for separate analysis frameworks for different final signatures and specific tasks. The transformer-based pre-training strategy explicitly preserves unique interaction patterns through adaptive attention mechanisms while establishing cross-process correlations. We plan to demonstrate how this architecture maintains sensitivity to rare high-multiplicity topologies (3t and 4t) without compromising performance on conventional channels ($t\bar{t}$, $tX$, $t\bar{t}H$), effectively bridging the gap between disparate analysis paradigms in collider physics.

hep-ph

Applying Normalizing Flows for spin correlations reconstruction in associated top-quark pair and dark matter production

We apply a unified machine-learning framework based on Normalizing Flows (NFs) for the event-by-event reconstruction of invisible momenta and the subsequent evaluation of spin-sensitive observables in top-quark pair and dark-matter (DM) associated production processes. Building on recent studies in single-top + DM topologies, we extend the research to $t\bar{t}$ + DM final states. Inputs to our networks combine low-level four-momenta and missing transverse energy with high-level kinematic and angular variables. We compare a baseline multilayer perceptron (MLP) regressor, an autoregressive flow, and the conditional $ν$-Flows model -- trained to learn the full conditional density. In these final states all the models perform well and demonstrate high reconstruction quality in independent regions split by $m_{t\bar{t}}$ for validation purposes. We highlight the potential of this approach to be extended to three- and four-top-quark production.

hep-ph

Manifestations of Dark Matter in processes with three and four Top-Quarks

This study explores possible manifestations of Dark Matter (DM) in processes involving multiple top quarks at the LHC. We analyze both the associated production of scalar and pseudoscalar DM Mediators with up to four top quarks, as well as their resonant production in top-rich final states, within a simplified model framework. Cross sections were calculated using the CompHEP and MadGraph packages with benchmark parameters recommended by the LHC Dark Matter Working Group. A detailed comparison of differential cross sections for key kinematic observables in three- and four-top-quark production demonstrates pronounced deviations from Standard Model predictions. The results highlight the limited feasibility of associated production channels, while resonant DM Mediator production offers realistic discovery prospects. Overall, the analysis underscores the potential of multi-top-quark final states as sensitive probes of Dark Matter at current and future collider experiments.

hep-ph

Reconstruction of angular correlations in the associated top quark and the dark matter mediator production

For the process of single top quark production within the "simplified model" with a scalar dark matter mediator, a new variable based on angular correlations was presented, for the proper reconstruction of which it is necessary to separate the contributions of two undetectable particles: the neutrino and the mediator. In this work, various machine learning approaches for reconstructing the momenta of these particles are analyzed. A comparison is made between the results obtained using a multilayer perceptron and the Normalizing Flows architectures. The neural networks based on Normalizing Flows, presented in this work, demonstrate a high quality of reconstruction of the target variable and can be used for collider data analysis.

hep-ph

Separation of left-handed and anomalous right-handed vector operators contributions into the Wtb vertex for single and double resonant top quark production processes using a neural network

The paper describes the application of deep neural networks for the searchdeviations from the Standard Model predictions at the Wtb vertex in the processes of single and double resonant top quark production with identical final state tWb. Monte-Carlo events preliminary classified by first level neural network as corresponding to single or double resonant top quark production are analyzed by two second level neural networks if there is a possible contribution of the anomalous right-handed vector operator into Wtb vertex or events are corresponded to the Standard Model. The second level neural networks are different for single and double resonant classes. The classes depend differently on anomalous contribution and such splitting leads to better sensitivity. The developed statistical model is used to set constraints on the anomalous right-handed vector operator at the Wtb vertex in different regions of phase space. It is demonstrated that the proposed method allows to increase the efficiency of a search for the anomalous contributions to the Wtb vertex.

hep-ph

Application of Kolmogorov-Arnold Networks in high energy physics

Kolmogorov-Arnold Networks represent a recent advancement in machine learning, with the potential to outperform traditional perceptron-based neural networks across various domains as well as provide more interpretability with the use of symbolic formulas and pruning. This study explores the application of KANs to specific tasks in high-energy physics. We evaluate the performance of KANs in distinguishing multijet processes in proton-proton collisions and in reconstructing missing transverse momentum in events involving dark matter.

hep-ph

Angular correlations in associated top-quark and dark matter production at Large Hadron Collider

In the paper, we consider the processes of single top-quark production in association with dark matter particles through the t-channel in simplified models with scalar and pseudoscalar mediators. Within the framework of these models, we analyze the angular correlations that arise in the top quark production process in association with dark matter, comparing them with the production of a top quark in the Standard Model. We consider angular correlations of kinematic variables, which define admissible regions in momentum space and can be used experimentally to distinguish between the fraction of the total momentum carried away by the scalar or pseudoscalar mediator. We demonstrate that scalar mediator significantly changes the rest frame of the well-known angular correlation observable and changes the distributions. In this case, this variable provides clear separation between the SM and DM contribution and can be used to increase the sensitivity of future DM analyses.

hep-ph

Search for dark matter mediator in the production of three and four top quarks

In the context of simplified models of dark matter, the contributions of a scalar mediator to top quark production processes are considered. Tree-level and one-loop contributions of the mediator's decay into a top-antitop quark pair in two-, three-, and four-top quarks production processes are calculated. A significant contribution from diagrams involving the dark matter mediator is demonstrated in the total cross section for three- and four-top quark production processes, taking into account current experimental limits on model parameters. The perspective of searching for dark matter mediators in the processes under consideration is determined by the ability to reconstruct the final state with modern collider detectors and the experimental sensitivity that has already been achieved for such rare events.

hep-ph