Study of energy deposition patterns in hadron calorimeter for prompt and displaced jets using convolutional neural network

Sophisticated machine learning techniques have promising potential in search for physics beyond Standard Model in Large Hadron Collider (LHC). Convolutional neural networks (CNN) can provide powerful tools for differentiating between patterns of calorimeter energy deposits by prompt particles of Standard Model and long-lived particles predicted in various models beyond the Standard Model. We demonstrate the usefulness of CNN by using a couple of physics examples from well motivated BSM scenarios predicting long-lived particles giving rise to displaced jets. Our work suggests that modern machine-learning techniques have potential to discriminate between energy deposition patterns of prompt and long-lived particles, and thus, they can be useful tools in such searches.Comment: 32 pages, 17 figures; version accepted for publication in JHE

Determining the lifetime of long-lived particles at the HL-LHC

We examine the capacity of the Large Hadron Collider to determine the mean proper lifetime of long-lived particles assuming different decay final states. We mostly concentrate on the high luminosity runs of the LHC, and therefore, develop our discussion in light of the high amount of pile-up and the various upgrades for the HL-LHC runs. We employ model-dependent and model-independent methods in order to reconstruct the proper lifetime of neutral long-lived particles decaying into displaced leptons, potentially accompanied by missing energy, as well as charged long-lived particles decaying ihnto leptons and missing energy. We also present a discussion for lifetime estimation of neutral long-lived particles decaying into displaced jets, along with the challenges in the high PU environment of HL-LHC. After a general discussion, we illustrate and discuss these methods using several new physics models. We conclude that the lifetime can indeed be reconstructed in many concrete cases. Finally, we discuss to which extent including timing information, which is an important addition in the Phase-II upgrade of CMS, can improve such an analysis.We examine the capacity of the Large Hadron Collider to determine the mean proper lifetime of long-lived particles assuming different decay final states. We mostly concentrate on the high luminosity runs of the LHC, and therefore, develop our discussion in light of the high amount of pile-up and the various upgrades for the HL-LHC runs. We employ model-dependent and model-independent methods in order to reconstruct the proper lifetime of neutral long-lived particles decaying into displaced leptons, potentially accompanied by missing energy, as well as charged long-lived particles decaying ihnto leptons and missing energy. We also present a discussion for lifetime estimation of neutral long-lived particles decaying into displaced jets, along with the challenges in the high PU environment of HL-LHC. After a general discussion, we illustrate and discuss these methods using several new physics models. We conclude that the lifetime can indeed be reconstructed in many concrete cases. Finally, we discuss to which extent including timing information, which is an important addition in the Phase-II upgrade of CMS, can improve such an analysis

Triggering long-lived particles in HL-LHC and the challenges in the first stage of the trigger system

Triggering long-lived particles at the first stage of the trigger system is very crucial in LLP searches to ensure that we do not miss them at the very beginning. The future High Luminosity runs of the Large Hardron Collider will have increased number of pile-up events per bunch crossing. There will be major upgrades in hardware, firmware and software sides, like tracking at level-1 (L1) as well as inclusion of the MIP timing detector. The L1 trigger menu will also be modified to cope with pile-up and maintain the sensitivity to physics processes. In our study we found that the usual level-1 triggers, mostly meant for triggering prompt particles, will not be very efficient for LLP searches in the 140 PU environment of HL-LHC, thus pointing to the need to include dedicated L1 triggers in the menu for LLPs. We consider the decay of the LLP into jets and develop dedicated jet triggers using the track information and if available, the regional timing information at L1 to select LLP events. We show in our work that these triggers give promising results in identifying LLP events with moderate trigger rates.Triggering long-lived particles (LLPs) at the first stage of the trigger system is very crucial in LLP searches to ensure that we do not miss them at the very beginning. The future High Luminosity runs of the Large Hadron Collider will have increased number of pile-up events per bunch crossing. There will be major upgrades in hardware, firmware and software sides, like tracking at level-1 (L1). The L1 trigger menu will also be modified to cope with pile-up and maintain the sensitivity to physics processes. In our study we found that the usual level-1 triggers, mostly meant for triggering prompt particles, will not be very efficient for LLP searches in the 140 pile-up environment of HL-LHC, thus pointing to the need to include dedicated L1 triggers in the menu for LLPs. We consider the decay of the LLP into jets and develop dedicated jet triggers using the track information at L1 to select LLP events. We show in our work that these triggers give promising results in identifying LLP events with moderate trigger rates

Determining the lifetime of long-lived particles at the LHC

We examine the capacity of the Large Hadron Collider to determine the mean proper lifetime of long-lived particles assuming different decay final states. We employ model-dependent and model-independent methods in order to reconstruct the proper lifetime of neutral long-lived particles decaying into displaced leptons or jets, potentially accompanied by missing energy, as well as charged long-lived particles decaying into leptons and missing energy. After a generic discussion, we illustrate and discuss these methods using several new physics models. We conclude that the lifetime can indeed be reconstructed in many concrete cases. Finally, we discuss to which extent including timing information can improve such an analysis

Determining the lifetime of long-lived particles at the HL-LHC

We examine the capacity of the Large Hadron Collider to determine the mean proper lifetime of long-lived particles assuming different decay final states. We mostly concentrate on the high luminosity runs of the LHC, and therefore, develop our discussion in light of the high amount of pile-up and the various upgrades for the HL-LHC runs. We employ model-dependent and model-independent methods in order to reconstruct the proper lifetime of neutral long-lived particles decaying into displaced leptons, potentially accompanied by missing energy, as well as charged long-lived particles decaying ihnto leptons and missing energy. We also present a discussion for lifetime estimation of neutral long-lived particles decaying into displaced jets, along with the challenges in the high PU environment of HL-LHC. After a general discussion, we illustrate and discuss these methods using several new physics models. We conclude that the lifetime can indeed be reconstructed in many concrete cases. Finally, we discuss to which extent including timing information, which is an important addition in the Phase-II upgrade of CMS, can improve such an analysis

Current status of the light neutralino thermal dark matter in the phenomenological MSSM

International audienceIn a previous publication, we studied the parameter space of the phenomenological Minimal Supersymmetric Standard Model (pMSSM) with a light neutralino thermal dark matter ($M_{\tilde{\chi}_1^0} \leq M_h/2$) and observed that the recent results from the dark matter and collider experiments put strong constraints on this scenario. In this work, we present in detail the arguments behind the robustness of this result against scanning over the large number of parameters in pMSSM. The Run-3 of LHC will be crucial in probing the surviving regions of the parameter space. We further investigate the impact of light staus on our parameter space and also provide benchmarks which can be interesting for Run-3 of LHC. We analyse these benchmarks at the LHC using the machine learning framework of \texttt{XGBOOST}. Finally, we also discuss the effect of non-standard cosmology on the parameter space

Is the light neutralino thermal dark matter in the MSSM ruled out?

We explore the parameter space of the phenomenological Minimal Supersymmetric Standard Model (pMSSM) with a light neutralino thermal dark matter ($m_{\tilde{\chi}_1^0} \leq m_h/2$) for both positive and negative values of the higgsino mass parameter ($\mu$) that is consistent with current collider and astrophysical constraints. Our investigation shows that the recent experimental results from the LHC as well as from direct detection searches for dark matter by the LUX-ZEPLIN collaboration basically rule out the $\mu>0$ scenario while only allowing a very narrow region with light electroweakinos in the $\mu<0$ scenario. These are well within the reach of the Run-3 of LHC and dedicated efforts to probe this region should be pursued