Congratulations to Angira Rastogi, Willem Verbeke, and David Walter who won the 2022 CMS Ph.D. Thesis Award!
The CMS Collaboration recognizes annually the outstanding achievements of young scientists through this award and highlights the exceptional contributions made by doctoral researchers in advancing the field of high-energy physics.
The 32 nominees for this award had to defend their theses between November 1st, 2021 and October 31st, 2022. Theses covering various aspects of CMS-related work, including physics analysis, simulation, computing, detector development, and engineering, were eligible for nomination. Then the CMS Thesis Award Committee, consisting of 30 scientists, evaluated the theses based on their content, originality, and the clarity of writing.
«The award-winning theses are exemplary in that they provide models of high-quality scientific and technological research and writing for new students engaging in research with CMS. At the same time, they are a lasting value for all CMS collaborators, as they provide accessible but in-depth documentation of a diversified set of CMS-related research methods (physics analysis, simulation, computing, detector development, engineering, etc.) throughout the lifetime of the experiment.»- Marta Felcini, chair of the CMS PhD Thesis Award Committee.
The winners of the CMS Ph.D. Thesis Award receive a Thesis Award Certificate, a Gift Voucher and travel expenses coverage so they can present their thesis results at an international conference, They are also given the opportunity to present their thesis work during a plenary session of CMS Week, and they are provided with a CMS Endorsement for Publication in Springer Theses.
Time to learn more about the three winners and their exceptional theses!
In my thesis, I have tried to address many open questions of the Standard Model (SM) of Particle Physics, by finding signatures of new physics scenarios through their coupling to leptons. Leptons have a very clear and distinct footprint in the CMS detector, which facilitates probing these new theories at higher precision in great depths, from very high particle masses to very low couplings. I have particularly focused on designing an inclusive multi lepton analysis for beyond-the-SM (BSM) searches, which puts the tau leptons also on an equal footing with the lighter flavors. Tau leptons undergo weak decays due to finite lifetime, and can decay to hadrons in addition to the leptons. So, this makes the background estimation as well as signal selection a very challenging task. But, I made use of the novel machine learning techniques to look at a brand new portal of BSM physics scenarios producing tau leptons in the final state, for the first time by LHC experiments, such as the vector-like tau leptons.
When the CMS Pixel tracker was upgraded in 2017 to improve the overall track reconstruction and also extend the tracking volume of charged particles in the forward region, I implemented the new geometry in the fast simulation framework of the CMS. I then modified the track reconstruction algorithm to benefit from the enhanced geometry which enabled the collaboration to produce a larger grid of BSM physics simulation in a faster way, with less consumption of computing resources, yet not compromising on the physics aspect.
For now, I have switched gears to the high-luminosity LHC (HL-LHC) ATLAS detector upgrades, focusing on the data acquisition from the silicon pixel modules via the means of optical communication. I hope to apply my expertise on the tau leptons very soon in the ATLAS experiment as well, broadening the paradigm of new physics searches."
My thesis describes several searches for physics processes that were undiscovered at the time of writing. The searches target diverse physics, but are experimentally closely related in the sense that they all use LHC collisions that result in multiple charged leptons. Charged leptons give extraordinarily clean experimental signals, therefore being an ideal probe in many particle physics analyses.
The earliest result described in the thesis is the first search for sterile neutrinos at the LHC that targets collision events with three leptons. It allowed us to search for these elusive particles in previously uncharted parameter space.
Second is a search for single top quark production in association with a Z boson (tZq), an extremely rare SM process with an extraordinary sensitivity to new physics. Being about 50 times more rare than Higgs boson production in the current LHC collisions, tZq production remained undiscovered prior to the work presented in my thesis. The use of a machine learning based lepton identification algorithm and a total redesign of the analysis strategy compared to earlier results allowed for the first unambiguous discovery of tZq production.
Lastly, a search for Supersymmetry, one of the most popular extensions of the standard model, is presented. In this search parametric neural networks are used to separate signal and background events. Such neural networks are able to search for particles with several unknown properties, vastly increasing the reach of the presented search over earlier results. This is the first time parametric neural networks are used in such a search, opening the door for improved searches for all kinds of undiscovered physics in the future.
In my work I studied a process that is considered rare and was observed only in 2018. The simultaneous production of a top quark and a Z boson, the top quark is the heaviest known fundamental particle, while the Z boson is the third heaviest. In first approximation, the process has only electroweak interactions and offers unique features, such as sensitivity to the very small b quark content in the proton, the coupling of the top quark to the b quark via the W boson, and at the same time the coupling of the top quark to the Z boson. For the first time I made differential measurements of the process and studied its properties, for example related to the top quark spin. I compared my results with different theory predictions. I also obtained the most precise determination for the production probability of this process.
In a second project, I developed a new method using Z bosons to measure the luminosity, which is an essential input to every analysis in CMS. For the first time I made a complete uncertainty assessment of this alternative approach. It shows competitive results and the unique features could help reduce the luminosity uncertainty in the future. In particular for the upcoming HL-LHC which has more challenging data-taking conditions.