Periodic Reporting for period 1 - LHCTOPVLQ (Direct and indirect searches for new physics in events with top quarks using LHC proton-proton collisions at the CMS detector)
Periodo di rendicontazione: 2017-11-01 al 2019-10-31
The standard model (SM) of particle physics is currently the state of the art in describing the behaviour of particles at the most elementary (i.e. fundamental) level. It is a successful theory that can make very precise predictions in many areas of physics, but it has known limitations and is only an approximate and incomplete description of the physics of the Universe.
Many theories exist for the fundamental nature of physics beyond the SM (BSM), but none are significantly favoured by existing experimental evidence. The discovery of a new particle, or significant deviations in the behaviour of particles from the predictions of the SM, would revolutionise our understanding of nature, and set the research agenda for the coming decades.
The top quark is the heaviest elementary particle in the SM, a fact that may be connected to the theory of physics beyond the SM — particularly that of the Higgs mechanism of electroweak symmetry breaking, which is responsible for the existence of elementary particle mass. In this project, we look for signs of physics beyond the SM predictions in events with top quarks using LHC proton-proton collisions at the CMS detector. A general analysis framework to search for new particles in the CMS data, signalled by an excess of events with properties consistent with new particles and not the predicted background events from the well-known SM particle production processes, is developed. The search for a new particle related to the top quark (a top quark partner), a common prediction of new theories, is conducted as an example application.
The strategy of directly searching for new particles is complemented by an indirect but model-independent search for new physics interacting with top quarks, by looking for deviations from SM predictions in precision measurements of the behaviour of the top quark. In order to enable these and similar searches to continue at the future High Luminosity LHC, we study the performance of the upgraded trigger for events with top quarks, including optimisation of reconstruction algorithms and working points.
Many theories exist for the fundamental nature of physics beyond the SM (BSM), but none are significantly favoured by existing experimental evidence. The discovery of a new particle, or significant deviations in the behaviour of particles from the predictions of the SM, would revolutionise our understanding of nature, and set the research agenda for the coming decades.
The top quark is the heaviest elementary particle in the SM, a fact that may be connected to the theory of physics beyond the SM — particularly that of the Higgs mechanism of electroweak symmetry breaking, which is responsible for the existence of elementary particle mass. In this project, we look for signs of physics beyond the SM predictions in events with top quarks using LHC proton-proton collisions at the CMS detector. A general analysis framework to search for new particles in the CMS data, signalled by an excess of events with properties consistent with new particles and not the predicted background events from the well-known SM particle production processes, is developed. The search for a new particle related to the top quark (a top quark partner), a common prediction of new theories, is conducted as an example application.
The strategy of directly searching for new particles is complemented by an indirect but model-independent search for new physics interacting with top quarks, by looking for deviations from SM predictions in precision measurements of the behaviour of the top quark. In order to enable these and similar searches to continue at the future High Luminosity LHC, we study the performance of the upgraded trigger for events with top quarks, including optimisation of reconstruction algorithms and working points.
"At the beginning of the project, I started a collaboration with groups from Purdue University, DESY, and Istanbul Technical University on precision top quark physics, measuring the complete set of top quark-antiquark spin correlation and polarisation variables encoded in the ""spin density matrix"" for top quark-antiquark production. My contributions in the first year of the project were mostly to the unfolding (the key statistical tool used in the analysis), including developing a new method to give unbiased regularisation and improved resolution. In the second year I focussed on the EFT interpretation (where deviations from SM predictions are parameterised in terms of different BSM contributions) and making the full results publicly available via HEPData and a Rivet routine, allowing easy access for theorists to make future interpretations in the context of new models. Preliminary results were made public in a CMS Physics Analysis Summary public document in December 2018, which I presented at the Moriond EWK conference in March 2019. The final results were published in PRD in October 2019, and presented both in a talk and as a poster at the TOP2019 conference in September 2019. I also gave talks on the analysis at the NExT seminar meeting in May 2018, and in the CMS UK meeting in July 2019.
I also collaborated with the University of Bristol particle physics group on direct searches for new physics. My initial focus was on the analysis framework, and I joined the new Faster Analysis Software Taskforce (F.A.S.T.) with the objective of developing a faster, more flexible analysis framework based on data frames (commonly used in industry, but not yet in particle physics). The framework is intended for use across several UK search analyses, and an initial demonstrator analysis replicating an earlier analysis searching for top quark partners was completed in the first year of the project. In the second year, we refined the framework to a more generalised approach, to suit the needs of many analyses in CMS as well as other experiments searching for new particles such as LUX-ZEPLIN. In each year, we presented the results at the annual CHEP conference (CHEP 2018 and CHEP 2019), followed by publication in EPJ Web of Conferences. We also ran several successful tutorial sessions for the framework, both at CERN and in the UK, including a session I organised at RAL.
As part of the project I engaged closely with the RAL outreach and public engagement activities, including European Researchers' Night, where I gave tours and an explanation of the work of the RAL particle physics department to members of the general public, and the annual Masterclass, where I co-led sessions on the hunt for the Higgs boson for sixth-form students. In each year of the project, I supervised an undergraduate summer student in an eight-week project, in each case building on my work connected to the CMS detector upgrade aspect of the project. Last year (2018), we made studies to optimise the primary vertex finding algorithm in the context of the eventual FPGA implementation. This summer (2019), I supervised a student in a project investigating the use of neural networks at the software trigger level, in this case for primary vertex finding and event reconstruction."
I also collaborated with the University of Bristol particle physics group on direct searches for new physics. My initial focus was on the analysis framework, and I joined the new Faster Analysis Software Taskforce (F.A.S.T.) with the objective of developing a faster, more flexible analysis framework based on data frames (commonly used in industry, but not yet in particle physics). The framework is intended for use across several UK search analyses, and an initial demonstrator analysis replicating an earlier analysis searching for top quark partners was completed in the first year of the project. In the second year, we refined the framework to a more generalised approach, to suit the needs of many analyses in CMS as well as other experiments searching for new particles such as LUX-ZEPLIN. In each year, we presented the results at the annual CHEP conference (CHEP 2018 and CHEP 2019), followed by publication in EPJ Web of Conferences. We also ran several successful tutorial sessions for the framework, both at CERN and in the UK, including a session I organised at RAL.
As part of the project I engaged closely with the RAL outreach and public engagement activities, including European Researchers' Night, where I gave tours and an explanation of the work of the RAL particle physics department to members of the general public, and the annual Masterclass, where I co-led sessions on the hunt for the Higgs boson for sixth-form students. In each year of the project, I supervised an undergraduate summer student in an eight-week project, in each case building on my work connected to the CMS detector upgrade aspect of the project. Last year (2018), we made studies to optimise the primary vertex finding algorithm in the context of the eventual FPGA implementation. This summer (2019), I supervised a student in a project investigating the use of neural networks at the software trigger level, in this case for primary vertex finding and event reconstruction."
The results of this project significantly improved the experimental measurements of the spin density matrix for top quark pair production at the LHC, bringing the experimental understanding of the top quark to an unprecedented level. This led to the strongest direct constraints to date on coupling strengths parameterising the contributions from physics beyond the SM (BSM) to top quark pair productions, including anomalous top quark chromoelectric and chromomagnetic dipole moments.
The analysis framework developed by F.A.S.T. during the course of the project is now being used in analyses in CMS as well as other experiments such as LUX-ZEPLIN, building on the evolving technologies from the Scikit-HEP and IRIS-HEP projects as well as industry-standard libraries such as Pandas and Matplotlib.
The analysis framework developed by F.A.S.T. during the course of the project is now being used in analyses in CMS as well as other experiments such as LUX-ZEPLIN, building on the evolving technologies from the Scikit-HEP and IRIS-HEP projects as well as industry-standard libraries such as Pandas and Matplotlib.