Tag: CMS

  • CMS tunes in searches for new physics

    CMS tunes in searches for new physics

    CMS tunes in searches for new physics The CERN LHC has produced proton-proton collisions at an unprecedented center of mass energy of 13 TeV since 2015, providing an excellent opportunity to search for new phenomena in regions that were previously inaccessible to collider experiments. While the standard model (SM) of particle physics is well established

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  • CMS weighs in for the top quark

    CMS weighs in for the top quark

    CMS weighs in for the top quark The top quark has a special position in the zoo of elementary particles, being the heaviest as well as one of the rarest fundamental particles ever sighted. With a mass of about 173 GeV, it has 40 times the mass of its partner, the bottom quark and is

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  • CMS weighs in for the top quark

    CMS weighs in for the top quark

    CMS weighs in for the top quark The top quark has a special position in the zoo of elementary particles, being the heaviest as well as one of the rarest fundamental particles ever sighted. With a mass of about 173 GeV, it has 40 times the mass of its partner, the bottom quark and is

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  • Exploring new ways to see the Higgs boson

    Exploring new ways to see the Higgs boson

    Exploring new ways to see the Higgs boson The ATLAS and CMS collaborations presented their latest results on new signatures for detecting the Higgs boson at CERN’s Large Hadron Collider. These include searches for rare transformations of the Higgs boson into a Z boson – which is a carrier of one of the fundamental forces

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  • New physics opportunities with heavy-ion collisions at the LHC

    New physics opportunities with heavy-ion collisions at the LHC

    New physics opportunities with heavy-ion collisions at the LHC The LHC is the latest scientific tool in a long line of increasingly sophisticated machines built over the last 70 years to study the inner workings of our Universe and the laws governing its microscopic structure and evolution. Decades-long experimental and theoretical efforts have given rise

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  • Artificial neural networks shed light on rare SM processes.

    Artificial neural networks shed light on rare SM processes.

    Artificial neural networks shed light on rare SM processes. In a new paper released last month, the ATLAS Collaboration reported the observation of a single top quark produced in association with a Z boson (tZq) using the full Run-2 dataset, thereby confirming earlier results by ATLAS and CMS using smaller datasets. As reported in an

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  • Towards high-precision luminosity for CMS in Run 3 and beyond

    Towards high-precision luminosity for CMS in Run 3 and beyond

    Towards high-precision luminosity for CMS in Run 3 and beyond Luminosity is a key parameter for any collider-based high energy physics experiment as it links the interaction rates observed in an experiment to the cross sections of physics processes. Therefore, it is a key ingredient to most major analyses performed at an experiment and the

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  • Heterogeneous computing efforts for high-energy physics experiments

    Heterogeneous computing efforts for high-energy physics experiments

    Heterogeneous computing efforts for high-energy physics experiments Substantial improvements to the current experiments at the LHC are underway, and new experiments are being proposed or discussed at future energy-frontier accelerators to answer fundamental questions in particle physics. At future hadron colliders, complex silicon vertex trackers (3D and 4D) and highly granular calorimeters must operate in

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  • ATLAS and CMS joint bootcamp for analysis preservation

    ATLAS and CMS joint bootcamp for analysis preservation

    ATLAS and CMS joint bootcamp for analysis preservation Last month, 30 young graduate students and postdocs gathered at CERN to attend the first joint ATLAS+CMS analysis preservation bootcamp, organised by Sam Meehan, Clemens Lange, Lukas Heinrich (CERN), and Savannah Thais (Princeton). Over the course of three days, the workshop participants learnt through hands-on tutorials and

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  • Deep Neural Networks for particle reconstruction in high-granularity calorimeters

    Deep Neural Networks for particle reconstruction in high-granularity calorimeters

    Deep Neural Networks for particle reconstruction in high-granularity calorimeters Precision measurements in high energy physics as well as an increasing amount of searches for new phenomena rely on a precise reconstruction of the event that caused a particular signature in the detector. Particle flow algorithms [1, 2, 3, 4] aim to identify individual particles before

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