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Amit Chakraborty

Amit Chakraborty appears in the imported research catalog. Authorship, coauthor and topic links are available while profile ownership is still unclaimed.

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hep-phhep-exMachine Learningeess.SYSystems and ControlArtificial Intelligencemath.OCeess.ASmath.NANumerical AnalysisSound

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Published work

25 published item(s)

preprint2026arXiv

Bangla-WhisperDiar: Fine-Tuning Whisper and PyAnnote for Bangla Long-Form Speech Recognition and Speaker Diarization

Automatic Speech Recognition (ASR) and speaker diarization in Bangla remain challenging due to long form recordings, diverse acoustic conditions, and significant speaker variability. This work addresses these two core tasks in Bangla spoken language understanding by developing robust systems for long form ASR and speaker diarization. For ASR (Problem 1), we fine tune the tugstugi bengaliai regional asr whisper medium model on a custom-curated dataset of approximately 15,000 chunked and aligned Bangla audio segments, employing full weight training with extensive data augmentation including noise injection, reverb simulation, echo, clipping distortion, and pitch/time perturbation. For speaker diarization (Problem 2), we fine-tune the pyannote/segmentation-3.0 model using PyTorch Lightning on the competition annotated diarization dataset, swapping the fine-tuned segmentation backbone into the pyannote/speaker-diarization-community-1 pipeline while retaining the pretrained speaker embedding and clustering components. Our ASR system achieves a Word Error Rate (WER) of 0.2441, while our diarization system achieves a Diarization Error Rate (DER) of 0.2392, both evaluated on the test set, demonstrating notable improvements over the respective pretrained baselines. We describe our complete pipeline, including data preprocessing, text normalization, audio augmentation, training strategies, inference optimization, and post-processing for both tasks.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

Search for Quadruplet Scalars using Boosted Decision Trees at the LHC

Beyond the Standard Model scenarios introduce additional scalar and fermion multiplets, which influence neutrino mass generation mechanisms and yield distinctive collider signatures. This work focuses on a particular scenario involving a fermion quintuplet and a scalar quadruplet. The study examines the production and decay of the scalar quadruplet components at the Large Hadron Collider (LHC), emphasizing how their decay patterns, fermiophobic versus fermiophilic, depend on mass differences and Yukawa couplings with the fermion multiplets. This study provides an overview of possible signals at the LHC, along with a detailed collider analysis focused on final states containing at least four leptons and two jets, in which the masses of the scalars and fermions are reconstructed successfully. Standard Model backgrounds are also incorporated in the study, with multivariate techniques leveraged via Boosted Decision Trees. Results indicate discovery potential for scalar masses around 600-700 GeV and exclusion sensitivity extending beyond 1 TeV, highlighting the promising experimental signatures of the model and its role in probing new physics at colliders.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Demystifying the Data Need of ML-surrogates for CFD Simulations

Computational fluid dynamics (CFD) simulations, a critical tool in various engineering applications, often require significant time and compute power to predict flow properties. The high computational cost associated with CFD simulations significantly restricts the scope of design space exploration and limits their use in planning and operational control. To address this issue, machine learning (ML) based surrogate models have been proposed as a computationally efficient tool to accelerate CFD simulations. However, a lack of clarity about CFD data requirements often challenges the widespread adoption of ML-based surrogates among design engineers and CFD practitioners. In this work, we propose an ML-based surrogate model to predict the temperature distribution inside the cabin of a passenger vehicle under various operating conditions and use it to demonstrate the trade-off between prediction performance and training dataset size. Our results show that the prediction accuracy is high and stable even when the training size is gradually reduced from 2000 to 200. The ML-based surrogates also reduce the compute time from ~30 minutes to around ~9 milliseconds. Moreover, even when only 50 CFD simulations are used for training, the temperature trend (e.g., locations of hot/cold regions) predicted by the ML-surrogate matches quite well with the results from CFD simulations.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

EMVLight: A Decentralized Reinforcement Learning Framework for Efficient Passage of Emergency Vehicles

Emergency vehicles (EMVs) play a crucial role in responding to time-critical events such as medical emergencies and fire outbreaks in an urban area. The less time EMVs spend traveling through the traffic, the more likely it would help save people's lives and reduce property loss. To reduce the travel time of EMVs, prior work has used route optimization based on historical traffic-flow data and traffic signal pre-emption based on the optimal route. However, traffic signal pre-emption dynamically changes the traffic flow which, in turn, modifies the optimal route of an EMV. In addition, traffic signal pre-emption practices usually lead to significant disturbances in traffic flow and subsequently increase the travel time for non-EMVs. In this paper, we propose EMVLight, a decentralized reinforcement learning (RL) framework for simultaneous dynamic routing and traffic signal control. EMVLight extends Dijkstra's algorithm to efficiently update the optimal route for the EMVs in real time as it travels through the traffic network. The decentralized RL agents learn network-level cooperative traffic signal phase strategies that not only reduce EMV travel time but also reduce the average travel time of non-EMVs in the network. This benefit has been demonstrated through comprehensive experiments with synthetic and real-world maps. These experiments show that EMVLight outperforms benchmark transportation engineering techniques and existing RL-based signal control methods.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

On Using Hamiltonian Monte Carlo Sampling for Reinforcement Learning Problems in High-dimension

Value function based reinforcement learning (RL) algorithms, for example, $Q$-learning, learn optimal policies from datasets of actions, rewards, and state transitions. However, when the underlying state transition dynamics are stochastic and evolve on a high-dimensional space, generating independent and identically distributed (IID) data samples for creating these datasets poses a significant challenge due to the intractability of the associated normalizing integral. In these scenarios, Hamiltonian Monte Carlo (HMC) sampling offers a computationally tractable way to generate data for training RL algorithms. In this paper, we introduce a framework, called \textit{Hamiltonian $Q$-Learning}, that demonstrates, both theoretically and empirically, that $Q$ values can be learned from a dataset generated by HMC samples of actions, rewards, and state transitions. Furthermore, to exploit the underlying low-rank structure of the $Q$ function, Hamiltonian $Q$-Learning uses a matrix completion algorithm for reconstructing the updated $Q$ function from $Q$ value updates over a much smaller subset of state-action pairs. Thus, by providing an efficient way to apply $Q$-learning in stochastic, high-dimensional settings, the proposed approach broadens the scope of RL algorithms for real-world applications.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Revisiting Jet Clustering Algorithms for New Higgs Boson Searches in Hadronic Final States

We assess the performance of different jet-clustering algorithms, in the presence of different resolution parameters and reconstruction procedures, in resolving fully hadronic final states emerging from the chain decay of the discovered Higgs boson into pairs of new identical Higgs states, the latter in turn decaying into bottom-antibottom quark pairs. We show that, at the Large Hadron Collider (LHC), both the efficiency of selecting the multi-jet final state and the ability to reconstruct from it the masses of the Higgs bosons (potentially) present in an event sample depend strongly on the choice of acceptance cuts, jet-clustering algorithm as well as its settings. Hence, we indicate the optimal choice of the latter for the purpose of establishing such a benchmark Beyond the SM (BSM) signal.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Dissipative SymODEN: Encoding Hamiltonian Dynamics with Dissipation and Control into Deep Learning

In this work, we introduce Dissipative SymODEN, a deep learning architecture which can infer the dynamics of a physical system with dissipation from observed state trajectories. To improve prediction accuracy while reducing network size, Dissipative SymODEN encodes the port-Hamiltonian dynamics with energy dissipation and external input into the design of its computation graph and learns the dynamics in a structured way. The learned model, by revealing key aspects of the system, such as the inertia, dissipation, and potential energy, paves the way for energy-based controllers.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Interpretable Deep Learning for Two-Prong Jet Classification with Jet Spectra

Classification of jets with deep learning has gained significant attention in recent times. However, the performance of deep neural networks is often achieved at the cost of interpretability. Here we propose an interpretable network trained on the jet spectrum $S_{2}(R)$ which is a two-point correlation function of the jet constituents. The spectrum can be derived from a functional Taylor series of an arbitrary jet classifier function of energy flows. An interpretable network can be obtained by truncating the series. The intermediate feature of the network is an infrared and collinear safe C-correlator which allows us to estimate the importance of a $S_{2}(R)$ deposit at an angular scale R in the classification. The performance of the architecture is comparable to that of a convolutional neural network (CNN) trained on jet images, although the number of inputs and complexity of architecture is significantly simpler than the CNN classifier. We consider two examples: one is the classification of two-prong jets which differ in color charge of the mother particle, and the other is a comparison between Pythia 8 and Herwig 7 generated jets.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Neural Network-based Top Tagger with Two-Point Energy Correlations and Geometry of Soft Emissions

Deep neural networks trained on jet images have been successful in classifying different kinds of jets. In this paper, we identify the crucial physics features that could reproduce the classification performance of the convolutional neural network in the top jet vs. QCD jet classification. We design a neural network that considers two types of substructural features: two-point energy correlations, and the IRC unsafe counting variables of a morphological analysis of jet images. The new set of IRC unsafe variables can be described by Minkowski functionals from integral geometry. To integrate these features into a single framework, we reintroduce two-point energy correlations in terms of a graph neural network and provide the other features to the network afterward. The network shows a comparable classification performance to the convolutional neural network. Since both networks are using IRC unsafe features at some level, the results based on simulations are often dependent on the event generator choice. We compare the classification results of Pythia 8 and Herwig 7, and a simple reweighting on the distribution of IRC unsafe features reduces the difference between the results from the two simulations.

0 citations0 reviewsNo code linkedOpen access
preprint2016arXiv

Chasing New Physics in Stacks of Soft Tracks

In this letter we introduce a new variable $ξ$, namely the number of tracks associated with the primary vertex, which are not parts of reconstructed objects such as jets/isolated leptons etc. We demonstrate its usefulness in the context of new physics searches in the channel monojet$+$missing transverse momentum (MET). In models such as in compressed supersymmetry, events are often characterized by a rather large number of soft partons from the cascade decays, none of which result in reconstructed objects. We find that $ξ$, binned in $p_T$, can discriminate these new physics events from events due to $Z+\text{jets}$, that is, the main background in the channel monojet+ MET. The information contained in soft tracks is largely uncorrelated with traditional variables such as the effective mass, MET, $p_T$ of the jet, etc. and, therefore, can be combined with these to increase the discovery potential by more than $200\%$ (depending on the spectra, of course). In fact, we find that simple cuts on $ξ(p_T)$ along with cuts on MET, and the effective mass outperforms sophisticated optimized MultiVariate Analyses using all conventional variables. One can model the background distribution of $ξ(p_T)$ in an entirely data-driven way, and make these robust against pile-up by identifying the primary vertex.

0 citations0 reviewsNo code linkedOpen access
preprint2016arXiv

Diphoton resonance at 750 GeV in the broken MRSSM

Non-observation of superpartners of the Standard Model particles at the early runs of the LHC provide strong motivation for an $R$-symmetric minimal supersymmetric Standard Model, or MRSSM. This model also comes with a pair of extra scalars which couple only to superpartners at the tree level. We demonstrate that in the limit when the $U(1)_R$ symmetry is broken, one of these scalars develops all the properties necessary to explain the 750 GeV diphoton resonance recently observed at the LHC, as well as the non-observation of associated signals in other channels. Some confirmatory tests in the upcoming LHC runs are proposed.

0 citations0 reviewsNo code linkedOpen access
preprint2016arXiv

Probing $(g-2)_μ$ at the LHC in the paradigm of R-parity violating MSSM

The measurement of the anomalous magnetic moment of the muon exhibits a long standing discrepancy compared to the Standard model prediction. In this paper, we concentrate on this issue in the framework of $R$-parity violating Minimal supersymmetric standard model. Such a scenario provides substantial contribution to the anomalous magnetic moment of the muon while satisfying constraints from low energy experimental observables as well as neutrino mass. In addition, we point out that the implication of such operators satisfying muon $g-2$ are immense from the perspective of the LHC experiment, leading to a spectacular four muon final state. We propose an analysis in this particular channel which might help to settle the debate of R-parity violation as a probable explanation for $(g-2)_μ$.

0 citations0 reviewsNo code linkedOpen access
preprint2016arXiv

Radion Candidate for the LHC Diphoton Resonance

The recent observation of a modest excess in diphoton final states at the LHC, by both the ATLAS and CMS Collaborations, has sparked off the expected race among theorists to find the right explanation for this proto-resonance, assuming that the signal will survive and not prove to be yet another statistical fluctuation. We carry out a general analysis of this `signal' in the case of a scalar which couples only to pairs of gluons (for production) and photons (for diphoton decay modes), and establish that an explanation of the observed resonance, taken together with the null results of new physics searches in all the other channels, requires a scalar with rather exotic behaviour. We then demonstrate that a fairly simple-minded extension of the minimal Randall-Sundrum model can yield a radion candidate which might reproduce this exotic behaviour.

0 citations0 reviewsNo code linkedOpen access
preprint2016arXiv

Status of the 98 - 125 GeV Higgs scenario with updated LHC-8 data

In the context of minimal supersymmetric standard model (MSSM), we discuss the possibility of the lightest Higgs boson with mass $M_h = 98 $ GeV to be consistent with the $2.3σ$ excess observed at the LEP in the decay mode $e^+e^- \to Zh$, with $h \to b {\bar b}$. In the same region of the MSSM parameter space, the heavier Higgs boson $(H)$ with mass $M_H \sim 125 $ GeV is required to be consistent with the latest data on Higgs coupling measurements at the end of 7 + 8 TeV LHC run with $25{\rm fb}^{-1}$ of data. While scanning the MSSM parameter space, we impose constraints coming from flavour physics, relic density of the cold dark matter as well as direct dark matter searches. We study the possibility of observing this light Higgs boson in vector boson fusion process and associated production with $W/Z$ boson at the high luminosity $(3000~{\rm fb}^{-1})$ run of the 14 TeV LHC. Our analysis shows that this scenario can hardly be ruled out even at the high luminosity run of the LHC. However, the precise measurement of the Higgs signal strength ratios can play a major role to distinguish this scenario from the canonical MSSM one.

0 citations0 reviewsNo code linkedOpen access
preprint2016arXiv

Study of MSSM heavy Higgs bosons decaying into charginos and neutralinos

A multitude of searches have already been performed by the ATLAS and CMS collaborations at the LHC to probe the heavy Higgses of the Minimal Supersymmetric Standard Model (MSSM) through their decay to the Standard Model particles. In this paper, we study the decay of the MSSM heavy Higgses into neutralino and chargino pairs and estimate the maximum possible branching ratios for these `ino' modes being consistent with the present LHC data. After performing a random scan of the relevant electroweakino parameters, we impose the SM 125 GeV Higgs constraints, low energy flavour data as well as current bounds on heavy Higgses from the LHC run-I and run-II data. The present limits on the electroweakino masses and couplings are also considered in our analysis. We choose a few representative benchmark points satisfying all the above-mentioned constraints, and then perform a detailed collider simulation, including fast detector effects, and analyze all the potential SM backgrounds in order to estimate the discovery reach of these heavy Higgses at the LHC. We restrict ourselves within the leptonic cascade decay modes of these heavy Higgses and study the mono-X + MET (X=W,Z) and trilepton + MET signatures in the context of high luminosity run of the 14 TeV LHC.

0 citations0 reviewsNo code linkedOpen access
preprint2015arXiv

Alternating direction method of multipliers for regularized multiclass support vector machines

The support vector machine (SVM) was originally designed for binary classifications. A lot of effort has been put to generalize the binary SVM to multiclass SVM (MSVM) which are more complex problems. Initially, MSVMs were solved by considering their dual formulations which are quadratic programs and can be solved by standard second-order methods. However, the duals of MSVMs with regularizers are usually more difficult to formulate and computationally very expensive to solve. This paper focuses on several regularized MSVMs and extends the alternating direction method of multiplier (ADMM) to these MSVMs. Using a splitting technique, all considered MSVMs are written as two-block convex programs, for which the ADMM has global convergence guarantees. Numerical experiments on synthetic and real data demonstrate the high efficiency and accuracy of our algorithms.

0 citations0 reviewsNo code linkedOpen access
preprint2015arXiv

Probing the NMSSM via Higgs boson signatures from stop cascade decays at the LHC

Higgs signatures from the cascade decays of light stops are an interesting possibility in the next to minimal supersymmetric standard model (NMSSM). We investigate the potential reach of the light stop mass at the 13 TeV run of the LHC by means of five NMSSM benchmark points where this signature is dominant. These benchmark points are compatible with current Higgs coupling measurements, LHC constraints, dark matter relic density and direct detection constraints. We consider single and di-lepton search strategies, as well as the jet-substructure technique to reconstruct the Higgs bosons. We find that one can probe stop masses up to 1.2 TeV with 300 $\rm fb^{-1}$ luminosity via the di-lepton channel, while with the jet-substructure method, stop masses up to 1 TeV can be probed with 300 $\rm fb^{-1}$ luminosity. We also investigate the possibility of the appearance of multiple Higgs peaks over the background in the fat-jet mass distribution, and conclude that such a possibility is viable only at the high luminosity run of 13 TeV LHC.

0 citations0 reviewsNo code linkedOpen access
preprint2015arXiv

Proximal gradient method for huberized support vector machine

The Support Vector Machine (SVM) has been used in a wide variety of classification problems. The original SVM uses the hinge loss function, which is non-differentiable and makes the problem difficult to solve in particular for regularized SVMs, such as with $\ell_1$-regularization. This paper considers the Huberized SVM (HSVM), which uses a differentiable approximation of the hinge loss function. We first explore the use of the Proximal Gradient (PG) method to solving binary-class HSVM (B-HSVM) and then generalize it to multi-class HSVM (M-HSVM). Under strong convexity assumptions, we show that our algorithm converges linearly. In addition, we give a finite convergence result about the support of the solution, based on which we further accelerate the algorithm by a two-stage method. We present extensive numerical experiments on both synthetic and real datasets which demonstrate the superiority of our methods over some state-of-the-art methods for both binary- and multi-class SVMs.

0 citations0 reviewsNo code linkedOpen access
preprint2015arXiv

Status of MSSM Higgs Sector using Global Analysis and Direct Search Bounds, and Future Prospects at the HL-LHC

In this paper, we search for the regions of the phenomenological minimal supersymmetric standard model (pMSSM) parameter space where one can expect to have moderate Higgs mixing angle ($α$) with relatively light (up to 600 GeV) additional Higgses after satisfying the current LHC data. We perform a global fit analysis using most updated data (till December 2014) from the LHC and Tevatron experiments. The constraints coming from the precision measurements of the rare b-decays $B_s \to μ^+ μ^-$ and $b\to s γ$ are also considered. We find that low $M_{A}$ $(\lesssim 350)$ and high $\tanβ$ $(\gtrsim 25)$ regions are disfavored by the combined effect of the global analysis and flavour data. However, regions with Higgs mixing angle $α\sim$ 0.1 - 0.8 are still allowed by the current data. We then study the existing direct search bounds on the heavy scalar/pseudoscalar ($\rm H/A$) and charged Higgs boson ($\rm H^\pm$) masses and branchings at the LHC. It has been found that regions with low to moderate values of $\tanβ$ with light additional Higgses (mass $\le$ 600 GeV) are unconstrained by the data, while the regions with $\tanβ>$ 20 are excluded considering the direct search bounds by the LHC-8 data. The possibility to probe the region with $\tanβ$ $\le$ 20 at the high luminosity run of LHC are also discussed, giving special attention to the $\rm H \to hh$, $\rm H/{A} \to t \bar t$ and $\rm H/{A} \to τ^{+}τ^{-}$ decay modes.

0 citations0 reviewsNo code linkedOpen access
preprint2014arXiv

HIPAD - A Hybrid Interior-Point Alternating Direction algorithm for knowledge-based SVM and feature selection

We consider classification tasks in the regime of scarce labeled training data in high dimensional feature space, where specific expert knowledge is also available. We propose a new hybrid optimization algorithm that solves the elastic-net support vector machine (SVM) through an alternating direction method of multipliers in the first phase, followed by an interior-point method for the classical SVM in the second phase. Both SVM formulations are adapted to knowledge incorporation. Our proposed algorithm addresses the challenges of automatic feature selection, high optimization accuracy, and algorithmic flexibility for taking advantage of prior knowledge. We demonstrate the effectiveness and efficiency of our algorithm and compare it with existing methods on a collection of synthetic and real-world data.

0 citations0 reviewsNo code linkedOpen access
preprint2014arXiv

Study of Baryonic R-Parity Violating MSSM Using Jet Substructure Technique at the 14 TeV LHC

We study the discovery reach of the gluino ($\widetilde{g}$) and the lightest stop squark ($\widetilde{t}_1$) with baryonic R-parity violation (UDD type) in the context of Minimal Supersymmetric Standard Model (MSSM) at the 14 TeV run of the LHC. We consider the gluino pair production process followed by its decay to a top quark and a real or virtual stop squark. The top quark produced from the decay of the gluino can have sufficient transverse momentum to appear as a single fat jet. We apply the jet substructure technique to tag such a hadronically decaying boosted top quark and find that gluino mass up to 1.65 TeV can be discovered whereas exclusion limit extends up to 1.9 TeV at the 14 TeV LHC with 300 $\rm fb^{-1}$ luminosity. We also briefly discuss the discovery prospect of the boosted stop squark which may be identified as a narrow resonance in the jet mass distribution.

0 citations0 reviewsNo code linkedOpen access
preprint2014arXiv

The 125 GeV Higgs signal at the LHC in the CP Violating MSSM

The ATLAS and CMS collaborations have observed independently at the Large Hadron Collider (LHC) a new Higgs-like particle with a mass $M_h \sim$ 125 GeV and properties similar to that predicted by the Standard Model (SM). Although the measurements indicate that this Higgs-like boson is compatible with the SM hypothesis, however due to large uncertainties in some of the Higgs detection channels, one still has the possibility of testing this object as being a candidate for some Beyond the SM (BSM) physics scenarios, for example, the Minimal Supersymmetric Standard Model (MSSM), in the CP-conserving version (CPC-MSSM). In this paper, we evaluate the modifications of these CPC-MSSM results when CP-violating (CPV) phases are turned on explicitly, leading to the CP-violating MSSM (CPV-MSSM). We investigate the role of the CPV phases in (some of) the soft Supersymmetry (SUSY) terms on both the mass of the lightest Higgs boson $h_1$, and the rates for the processes $gg \rightarrow h_1 \rightarrow γγ$, $gg \rightarrow h_1 \rightarrow ZZ^*\rightarrow 4l$, $gg \rightarrow h_1 \rightarrow WW^*\rightarrow l νl ν$, $pp \rightarrow V h_1 \rightarrow V b\bar b$ and $pp \rightarrow V h_1 \rightarrow V τ^+τ^-$, ($V \equiv W^\pm, Z$) at the LHC, considering the impact of the flavor constraints as well as the constraints coming from the Electric Dipole Moment (EDM) measurements. We find that the imaginary part of the top and bottom Yukawa couplings can take very small but non-zero values even after satisfying the recent updates from LHC. Our study shows that the CPV-MSSM provides an equally potential solution (like its CP-conserving (CPC) counterpart) to the recent LHC Higgs data. Improvement in different Higgs coupling measurements is necessary in order to test the possibility of probing the small dependence on these CPV phases in the Higgs sector of the MSSM.

0 citations0 reviewsNo code linkedOpen access
preprint2013arXiv

Implications of 98 GeV and 125 GeV Higgs scenario in non-decoupling SUSY with updated ATLAS, CMS and PLANCK data

We discuss both MSSM and NMSSM scenarios in which the lightest Higgs boson with $m_h=98$~GeV is consistent with the small excess ($\sim 2.3 σ$) observed at the LEP in $e^+ e^-\rightarrow Zh$, with $h \rightarrow b {\bar b}$ process and the heavier Higgs boson of mass close to 125~GeV as the observed candidate of the SM Higgs like particle at the LHC. We show the allowed regions in the non-decoupling Higgs zone of MSSM parameter space which are consistent with several low energy constraints coming from heavy flavour physics, latest experimental data on Higgs signals and lower limit on superparticle masses from 7~TeV and 8~TeV LHC run. We also implement the constraints from the relic density of the cold dark matter as obtained from the recent PLANCK data. Additionally, we discuss the possibility of observing the light Higgs boson of mass 98~GeV at the 14~TeV LHC run via $pp \rightarrow V h$, with $h \rightarrow b \bar b$ using the technique of jet substructure. Our analysis shows that at 14~TeV LHC run with 300 ${\rm fb}^{-1}$ luminosity the signal efficiency of such a light Higgs boson is at most 2.5$σ$. Finally, we make a comment on the prospect of proposed $e^+ e^-$ ILC to discover/exclude this light Higgs boson.

0 citations0 reviewsNo code linkedOpen access
preprint2013arXiv

Stop and sbottom search using dileptonic $M_{T2}$ variable and boosted top technique at the LHC

The ATLAS and CMS experiments at the CERN LHC have collected about 20 $fb^{-1}$ of data each at the end of their 8 TeV run, and ruled out a huge swath of parameter space in the context of Minimally Supersymmetric Standard Model(MSSM). Limits on masses of the gluino ($\tilde{g}$) and the squarks of the first two generations($\tilde{q}$) have been pushed to the TeV range. Light third generation squarks namely stop and sbottom of sub-TeV masses, on the other hand, are still allowed by their direct search limits. Interestingly, the discovery of a Standard Model(SM) higgs boson like particle with a mass of $\sim$ 125 GeV favours a light third generation which is also motivated by naturalness arguments. Decays of stop and sbottom quarks can in general produce a number of distinct final states which necessitate different search strategies in the collider experiments. In this paper we, on the other hand, propose a general search strategy to look for third generation squarks in the final state which contains a top quark in the sample along with two additional hard leptons and substantial missing transverse momentum. We illustrate that a search strategy using the dileptonic $M_{T2}$, the effective mass $m_{eff}$ and jet substructure to reconstruct the hadronic top quark can be very effective to reduce the SM backgrounds. With the proposed search strategy, we estimate that the third generation squarks with masses up to about 800 GeV can be probed at the 14 TeV LHC with a 100 $fb^{-1}$ data set. We also interpret our results in two simplified scenarios where we consider the stop (sbottom) pair production followed by their subsequent decay to a top quark and the second lightest neutralino (lightest chargino). In this case also we find that stop (sbottom) mass up to 1 TeV (0.9 TeV) can be discovered at the 14 TeV LHC with 100 $fb^{-1}$ integrated luminosity.

0 citations0 reviewsNo code linkedOpen access
preprint2012arXiv

Using Jet Substructure at the LHC to Search for the Light Higgs Bosons of the CP-Violating MSSM

The CP-violating version of the Minimal Supersymmetric Standard Model (MSSM) is an example of a model where experimental data do not preclude the presence of light Higgs bosons in the range around 10 -- 110 GeV. Such light Higgs bosons, decaying almost wholly to b-bbar pairs, may be copiously produced at the LHC, but would remain inaccessible to conventional Higgs searches because of intractable QCD backgrounds. We demonstrate that a significant number of these light Higgs bosons would be boosted strongly enough for the pair of daughter $b$-jet pairs to appear as a single `fat' jet with substructure. Tagging such jets could extend the discovery potential at the LHC into the hitherto-inaccessible region for light Higgs bosons.

0 citations0 reviewsNo code linkedOpen access