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We propose a method to organize experimental data from particle collision experiments in a general format which can enable a simple visualisation and effective classification of collision data using machine learning techniques. The method…
Robotic blimps, as lighter-than-air (LTA) aerial systems, offer long endurance and inherently safe operation but remain highly susceptible to wind disturbances. Building on recent advances in moving mass actuation, this paper addresses the…
The performance of missing transverse momentum reconstruction algorithms is presented using 8 TeV pp collision data collected with the CMS detector, corresponding to an integrated luminosity of $12.2 \pm 0.5$ $\mathrm{fb^{-1}}$. The scale…
Radiation damage significantly impacts the performance of silicon tracking detectors in Large Hadron Collider (LHC) experiments such as ATLAS and CMS, with signal reduction being the most critical effect. Adjusting sensor bias voltage and…
Studies of heavy-ion collisions at the LHC will benefit from an array of qualitatively new probes not readily available at lower collision energies. These include fully formed jets at ET > 50 GeV, Z0's and abundantly produced heavy flavors.…
Hadron production and their suppression in Pb+Pb collisions at LHC at a center-of-mass energy of s_NN = 2.76 TeV are studied within a multiphase transport (AMPT) model whose initial conditions are obtained from the recently updated HIJING…
We discuss different physics cases, mainly of the ALICE TPC, such as pile-up, jets in pp and PbPb, Bottonium and Charmonium spectroscopy, and there corresponding demands on the ALICE High Level Trigger (HLT) System. We show that compression…
Attention-based transformer models have become increasingly prevalent in collider analysis, offering enhanced performance for tasks such as jet tagging. However, they are computationally intensive and require substantial data for training.…
The collective phenomena are observed not only in heavy ion collisions, but also in the proton-nucleus and in high-multiplicity $pp$ collisions. The latest results from this area obtained in ATLAS are presented. In $p$+Pb collisions the…
Motivated by the expectation that new physics may manifest itself in the form of very heavy new particles, most of the operation time of the LHC is devoted to $pp$ collisions at the highest achievable energies and collision rates. The large…
In ultra-relativistic heavy-ion collisions at $\sqrt{s_{NN}}$ = 5.5 TeV at the ALICE experiment at the LHC, interactions between the high-$p_{T}$ partons and the hot, dense medium produced in the collisions, are expected to lead to jet…
Central lead-lead collisions at the LHC energies may pose a particular challenge for jet identification as multiple jets are produced per each collision event. We simulate the jet evolution in central Pb-Pb events at $\sqrt{s_{\rm NN}} =…
Large transverse momentum jets provide unique tools to study dense QCD matter in high-energy heavy-ion collisions. Results from RHIC on suppression of high transverse momentum particles in Au+Au collisions indicate a significant energy loss…
A novel combination of established data analysis techniques for reconstructing all charged-particle tracks in high energy collisions is proposed. It uses all information available in a collision event while keeping competing choices open as…
We show that the recently observed suppression of the yield ratio of deuteron to proton and of helium-3 to proton in p+p collisions compared to those in p+Pb or Pb+Pb collisions by the ALICE Collaboration at the Large Hadron Collider (LHC)…
High energy physics (HEP) experiments at the LHC generate data at a rate of $\mathcal{O}(10)$ Terabits per second. This data rate is expected to exponentially increase as experiments will be upgraded in the future to achieve higher…
Hadron collisions at the LHC offer a unique opportunity to study strong interactions. The exciting data collected by the four RHIC experiments suggest that in heavy-ion collisions at sqrt(s_NN) = 200 GeV, an equilibrated, strongly-coupled…
The generation of collider data using machine learning has emerged as a prominent research topic in particle physics due to the increasing computational challenges associated with traditional Monte Carlo simulation methods, particularly for…
We address the important problem of generalizing robotic rearrangement to clutter without any explicit object models. We first generate over 650K cluttered scenes - orders of magnitude more than prior work - in diverse everyday…
We investigate how a Generative Adversarial Network could be used to generate a list of particle four-momenta from LHC proton collisions, allowing one to define a generative model that could abstract from the irregularities of typical…