arXiv subjects

Akanksha Bhardwaj

Publications and source records attributed to Akanksha Bhardwaj.

18 recordsLinked to original sources

arXiv2024

Foundations of automatic feature extraction at LHC--point clouds and graphs

Deep learning algorithms will play a key role in the upcoming runs of the Large Hadron Collider (LHC), helping bolster various fronts ranging from fast and accurate detector simulations to physics analysis probing possible deviations from the Standard Model. The game-changing feature of these new algorithms is the ability to extract relevant information from high-dimensional input spaces, often regarded as "replacing the expert" in designing physics-intuitive variables. While this may seem true at first glance, it is far from reality. Existing research shows that physics-inspired feature extractors have many advantages beyond improving the qualitative understanding of the extracted features. In this review, we systematically explore automatic feature extraction from a phenomenological viewpoint and the motivation for physics-inspired architectures. We also discuss how prior knowledge from physics results in the naturalness of the point cloud representation and discuss graph-based applications to LHC phenomenology.

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arXiv2024

Equivariant, Safe and Sensitive -- Graph Networks for New Physics

This study introduces a novel Graph Neural Network (GNN) architecture that leverages infrared and collinear (IRC) safety and equivariance to enhance the analysis of collider data for Beyond the Standard Model (BSM) discoveries. By integrating equivariance in the rapidity-azimuth plane with IRC-safe principles, our model significantly reduces computational overhead while ensuring theoretical consistency in identifying BSM scenarios amidst Quantum Chromodynamics backgrounds. The proposed GNN architecture demonstrates superior performance in tagging semi-visible jets, highlighting its potential as a robust tool for advancing BSM search strategies at high-energy colliders.

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arXiv2024

Non-linear gauge-Higgs CP violation

A critical element of the LHC physics program is the search for an additional source of CP violation. This is largely unexplored in the context of non-linear Higgs physics, which is naturally described in Higgs Effective Field Theory (HEFT). Relevant new higher-dimensional operators modify the production rate and branching ratios of the Higgs boson, de-correlating different Higgs multiplicities. In this work, we consider single Higgs and Higgs pair production via weak boson fusion from the perspective of gauge-Higgs CP violation through the lens of Higgs non-linearity. This generalizes existing rate-based searches and analyses by the ATLAS and CMS experiments. Particular focus is given to the phenomenological differences in the expected BSM sensitivity pattern when comparing HEFT constraints with Standard Model Effective Field Theory (SMEFT) limits.

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arXiv2023

Non-linear top-Higgs CP violation

Searches for additional sources of CP violation at the Large Hadron Collider are a central part of the Higgs physics programme beyond the Standard Model. Studies employing so-called signed observables that track CP violation through purpose-built asymmetries bolster efforts based on Higgs boson rate analyses under clear assumptions. A possibility, which is so far unexplored at the LHC, is a significant non-linear realisation of CP-violation, which is naturally described in non-linear Higgs Effective Field Theory (HEFT). We perform an analysis of the HL-LHC potential to constrain such interactions considering a large range of single and double Higgs production processes, including differential information where this is statistically and theoretically possible. A particular emphasis of our work is distinguishing expected correlations in the Standard Model Effective Field Theory from those attainable in HEFT.

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arXiv2023

On the BSM reach of four top production at the LHC

Many scenarios of beyond the Standard Model (BSM) physics give rise to new top-philic interactions that can be probed at proton machines such as the Large Hadron Collider through a variety of production and decay modes. On the one hand, this will enable a detailed determination of the BSM model's parameters when a discovery is made and additional sensitivity in non-dominant production modes can be achieved. On the other hand, the naive narrow width approximation in dominant production modes such as gluon fusion might be inadequate for some BSM parameter regions due to interference effects, effectively making less dominant production modes more relevant in such instances. In this work, we consider both these questions in the context of four top quark final states at the LHC. Firstly, we show that the SM potential can be enhanced through the application of targeted Graph Neural Network techniques that exploit data correlations beyond cut-and-count approaches. Secondly, we show that destructive interference effects that can degrade BSM sensitivity of top-philic states from gluon fusion are largely avoided by turning to four top final states. This achieves considerable exclusion potential for, e.g., the two Higgs doublet model. This further motivates four top final states as sensitive tools for BSM discovery in the near future of the LHC.

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arXiv2022

Quartic Gauge-Higgs couplings: Constraints and Future Directions

Constraints on quartic interactions of the Higgs boson with gauge bosons have been obtained by the experimental LHC collaborations focussing on the so-called $κ$ framework of flat rescalings of SM-like interactions in weak boson fusion (WBF) Higgs pair production. While such approaches are admissible to obtain a qualitative picture of consistency with the SM when the statistical yield is low, once more statistics become available a more theoretically consistent framework of limit setting is desirable. Reviewing the constraints provided at the Large Hadron Collider, we first show that these limits are robust when considered in a leading order context. Turning to radiative corrections, we demonstrate the limitations of this approach in the SM, and by adopting Higgs effective field theory techniques, we clarify the sensitivity from single Higgs measurements to rescalings of quartic Higgs-gauge couplings. We then discuss avenues for sensitivity improvements of WBF analyses employing Graph Neural Networks to combat the large contributing backgrounds.

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arXiv2022

Implications of the muon anomalous magnetic moment for the LHC and MUonE

We consider the anomalous magnetic moment of the muon $a_μ$, which shows a significant deviation from the Standard Model expectation given the recent measurements at Fermilab and BNL. We focus on Standard Model Effective Field Theory (SMEFT) with the aim to identify avenues for the upcoming LHC runs and future experiments such as MUonE. To this end, we include radiative effects to $a_μ$ in SMEFT to connect the muon anomaly to potentially interesting searches at the LHC, specifically Higgs decays into muon pairs and such decays with resolved photons. Our investigation shows that similar to results for concrete UV extensions of the Standard Model, the Fermilab/BNL result can indicate strong coupling within the EFT framework and $a_μ$ is increasingly sensitive to a single operator direction for high scale UV completions. In such cases, there is some complementarity between expected future experimental improvements, yet with considerable statistical challenges to match the precision provided by the recent $a_μ$ measurement.

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arXiv2022

Discovery prospects of a vectorlike top partner decaying to a singlet boson

The possibility of a vectorlike top partner decaying to a new colourless weak-singlet scalar or pseudoscalar has attracted some attention in the literature. We investigate the production of a weak-singlet charge-$2/3$ $T$ quark that can decay to a spinless boson ($Φ$) and a top quark at the LHC. Earlier, in 2203.13753, we have shown that in a large part of the parameter space, the $T\to tΦ$ and the loop-induced $Φ\to gg$ decays become the dominant decay modes for these particles. Here, we investigate the discovery prospects of the $T$ quark in this region through the above decays. In particular, we focus on the $pp\to TT\to (tΦ)(tΦ)\to (t(gg))\,(t(gg))$ channel. Separating this signal from the huge Standard Model background is a challenging task, forcing us to employ a multivariate machine-learning technique. We find that the above channel can be a discovery channel of the top partner in the large part of the parameter space where the above decay chain dominates. Our analysis is largely model-independent, and hence our results would be useful in a broad class of new physics models.

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arXiv2022

Roadmap to explore vectorlike quarks decaying to a new scalar or pseudoscalar

The current experimental data allow for a sub-TeV colourless weak-singlet scalar or pseudoscalar. If such a singlet field is present together with TeV-range vectorlike top and bottom partners, there is a possibility that the heavy quarks decay dominantly to the singlet state and a third-generation quark, and the singlet state decays to quark and boson pairs. Such a possibility may arise in various models but it has not been explored experimentally, especially in the context of vectorlike-quark searches. We consider some minimal models, covering the possible weak representations of the top and bottom partners, that can be mapped to many well-motivated ultraviolet-complete theories. We chart out the possible interesting and unexplored signatures of the exotic decay of vectorlike quarks and identify benchmark points representing different signal topologies for the high luminosity LHC. We perform a general scan of the parameter space with the relevant direct search bounds and find that large regions, which do not require any fine-tuning, remain open for the unexplored channels. We also perform a simple projection study in the cleanest channel and indicate how other new but experimentally challenging channels can be used to probe more regions of the parameter space.

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arXiv2022

IRC-safe Graph Autoencoder for unsupervised anomaly detection

Anomaly detection through employing machine learning techniques has emerged as a novel powerful tool in the search for new physics beyond the Standard Model. Historically similar to the development of jet observables, theoretical consistency has not always assumed a central role in the fast development of algorithms and neural network architectures. In this work, we construct an infrared and collinear safe autoencoder based on graph neural networks by employing energy-weighted message passing. We demonstrate that whilst this approach has theoretically favourable properties, it also exhibits formidable sensitivity to non-QCD structures.

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arXiv2022

Machine-enhanced CP-asymmetries in the Higgs sector

Improving the sensitivity to CP-violation in the Higgs sector is one of the pillars of the precision Higgs programme at the Large Hadron Collider. We present a simple method that allows CP-sensitive observables to be directly constructed from the output of neural networks. We show that these observables have improved sensitivity to CP-violating effects in the production and decay of the Higgs boson, when compared to the use of traditional angular observables alone. The kinematic correlations identified by the neural networks can be used to design new analyses based on angular observables, with a similar improvement in sensitivity.

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arXiv2022

Improved Constraints on Effective Top Quark Interactions using Edge Convolution Networks

We explore the potential of Graph Neural Networks (GNNs) to improve the performance of high-dimensional effective field theory parameter fits to collider data beyond traditional rectangular cut-based differential distribution analyses. In this study, we focus on a SMEFT analysis of $pp \to t\bar t$ production, including top decays, where the linear effective field deformation is parametrised by thirteen independent Wilson coefficients. The application of GNNs allows us to condense the multidimensional phase space information available for the discrimination of BSM effects from the SM expectation by considering all available final state correlations directly. The number of contributing new physics couplings very quickly leads to statistical limitations when the GNN output is directly employed as an EFT discrimination tool. However, a selection based on minimising the SM contribution enhances the fit's sensitivity when reflected as a (non-rectangular) selection on the inclusive data samples that are typically employed when looking for non-resonant deviations from the SM by means of differential distributions.

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arXiv2021

Anomaly detection with Convolutional Graph Neural Networks

We devise an autoencoder based strategy to facilitate anomaly detection for boosted jets, employing Graph Neural Networks (GNNs) to do so. To overcome known limitations of GNN autoencoders, we design a symmetric decoder capable of simultaneously reconstructing edge features and node features. Focusing on latent space based discriminators, we find that such setups provide a promising avenue to isolate new physics and competing SM signatures from sensitivity-limiting QCD jet contributions. We demonstrate the flexibility and broad applicability of this approach using examples of $W$ bosons, top quarks, and exotic hadronically-decaying exotic scalar bosons.

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arXiv2020

Invisible Higgs search through Vector Boson Fusion: A deep learning approach

Vector boson fusion proposed initially as an alternative channel for finding heavy Higgs has now established itself as a crucial search scheme to probe different properties of the Higgs boson or for new physics. We explore the merit of deep-learning entirely from the low-level calorimeter data in the search for invisibly decaying Higgs. Such an effort supersedes decades-old faith in the remarkable event kinematics and radiation pattern as a signature to the absence of any color exchange between incoming partons in the vector boson fusion mechanism. We investigate among different neural network architectures, considering both low-level and high-level input variables as a detailed comparative analysis. To have a consistent comparison with existing techniques, we closely follow a recent experimental study of CMS search on invisible Higgs with 36 fb$^{-1}$ data. We find that sophisticated deep-learning techniques have the impressive capability to improve the bound on invisible branching ratio by a factor of three, utilizing the same amount of data. Without relying on any exclusive event reconstruction, this novel technique can provide the most stringent bounds on the invisible branching ratio of the SM-like Higgs boson. Such an outcome has the ability to constraint many different BSM models severely.

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arXiv2020

Boosted jet techniques for a supersymmetric scenario with gravitino LSP

Search for compressed supersymmetry at multi-TeV scale, in the presence of a light gravitino dark matter, can get sizable uplift while looking into the associated fat-jets with missing transverse momenta as a signature of the boson produced in the decay process of much heavier next-to-lightest sparticle. We focus on the hadronic decay of the ensuing Higgs and/or $Z$ boson giving rise to at least two fat-jets and $\slashed{E}_T$ in the final state. We perform a detailed background study adopting a multivariate analysis using a boosted decision tree to provide a robust investigation to explore the discovery potential for such signal at 14 TeV LHC considering different benchmark points satisfying all the theoretical and experimental constraints. This channel provides the best discovery prospects with most of the benchmarks discoverable within an integrated luminosity of $\mathcal{L}=200$ fb$^{-1}$. Kinematic observables are investigated in order to distinguish between compressed and uncompressed spectra having similar event yields.

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arXiv2020

Looking for Minimal Inverse Seesaw scenarios at the LHC with Jet Substructure Techniques

Simple extensions of the Standard Model (SM) with additional Right Handed Neutrinos (RHNs) can elegantly explain the existence of small neutrino masses and their flavor mixings. Collider searches for sterile neutrinos are being actively pursued currently. Heavy RHNs may dominantly decay into $W^\pm l^\pm$ after being produced at the LHC. In this paper, we consider collider signatures of heavy pseudo-Dirac neutrinos in the context of inverse seesaw scenario, with a sizable mixing with the SM neutrinos under two different flavor structures, viz., Flavor Diagonal (FD) and Flavor Non-Diagonal (FND) scenarios. For the latter scenario we use a general parametrization for the model parameters by introducing an arbitrary orthogonal matrix and nonzero Dirac and Majorana phases. We then perform a parameter scan to identify allowed parameter regions which satisfy all experimental constraints. As an alternative channel to the traditional trilepton signature, we propose the opposite-sign di-lepton signature in the final state, in association with a fat jet from the hadronic decay of the boosted $W^\pm$ . We specifically consider a fat jet topology and explore the required enhancements from exploiting the characteristics of the jet substructure techniques. We perform a comprehensive collider analysis to demonstrate the effectiveness of this channel in both of the scenarios, significantly enhancing the bounds on the RHN mass and mixing angles at the 13 TeV LHC. Interestingly the FND scenario can reach up to a 5- $σ$ limit under the presence of the general parametrization at the high luminosity LHC.

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arXiv2019

Probing the inert doublet model using jet substructure with a multivariate analysis

We explore the challenging but phenomenologically interesting hierarchical mass spectrum of the Inert Doublet Model where relatively light dark matter along with much heavier scalar states can fully satisfy the constraints on the relic abundance and also fulfill other theoretical as well as collider and astrophysical bounds. To probe this region of parameter space at the LHC, we propose a signal process that combines up to two large radius boosted jets along with substantial missing transverse momentum. Aided by our intuitive signal selection, we capture a hybrid process where the di-fatjet signal is significantly enhanced by the mono-fatjet contribution with minimal effects on the SM di-fatjet background. Substantiated by the sizable mass difference between the scalars, these boosted jets, originally produced from the hadronic decay of massive vector bosons, still carry the inherent footprint of their root. These features implanted inside the jet substructure can provide additional handles to deal with a large background involving QCD jets. We adopt a multivariate analysis using boosted decision tree to provide a robust mechanism to explore the hierarchical scenario, which would bring almost the entire available parameter space well within reach of the 14 TeV LHC runs with high luminosity.

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arXiv2019

Exploring CP phase in $τ$-lepton Yukawa coupling in Higgs decays at the LHC

We study the prospect of determining the CP violating phase in $τ$-lepton Yukawa coupling at the Large Hadron Collider (LHC). While the current run is already exploring the production of a pair of the third generation $τ$ leptons from Higgs decay, these measurements are not sensitive enough to constrain the CP violating phase. In this paper, several CP odd observables are proposed and analyzed utilizing the dominant channels with the semi-invisible hadronic decay of $τ$. Several asymmetries corresponding to the T odd momentum correlations are also studied and their sensitivities to the CP violating phase in tau-lepton Yukawa couplings are estimated at 13 TeV LHC with 1000 ${fb}^{-1}$ of integrated luminosity. We also present a novel way to reconstruct $τ$ momentum at the LHC utilizing the information of impact parameter. Finally, we obtain that the asymmetries can be as large as 35$\%$ for a case of maximal CP violation in the $τ$ Yukawa couplings.

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